This PDF file contains the front matter associated with SPIE Proceedings Volume 12591, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

With the development of society, single-view crowd counting can no longer meet the existing social needs, in order to solve the existing problems, multi-view crowd counting emerged. The multi-view crowd counting is suitable for situations where a single view cannot cover the entire scene. In the rail transit industry, multi-view crowd counting can be used to count passengers on the platform, organize driving activity more scientifically and rationally, improve driving efficiency. In this paper, we propose a multi-view branch-shared crowd counting model for subway platforms, which uses a single branch to extract features and select scales for multi-perspective views. Compared with the existing multi-branch model, the structure of a single branch is more concise, and the feature redundancy is reduced. Considering the relationship between pixels, this paper introduces a combination of the local consistency loss function and Euclidean loss function. The performance of this model is tested on two public datasets (PETS2009 and CityStreet), and better results are obtained compared with the existing five methods.

Considering the subway, private cars, and cycling, the Personal Mobility Carbon Credits Trading scheme is explored in a super network with homogeneous travelers to discuss the impact on travel mode split rate and system carbon emissions. The Personal Mobility Carbon Credits Trading scheme includes the travel route choice behavior and the dynamic credits price evolution, which affect each other. The former is modeled in a super network. The Dial-MSA algorithm is used for flow distribution, and the results are fed back to the dynamic credits price evolution model. Accordingly, the result of dynamic credits price evolution, in turn, affects travel cost and finally governs the result of traffic flow allocation. The results show that the system will reach a stable state in a finite time range. The convergent equilibrium price has nothing to do with the initial price but is related to the number of total credits and the credits allocation scheme. Compared with the equivalent distribution scheme, proportional distribution is more equitable.

In order to study the influence of the off gap caused by the track camber on the dynamic response of CRTS Ⅱ slab ballast=less track, a vehicle track coupling dynamic model of CRH II was established by using the finite element analysis software ABAQUS. The influence of different off-gap amplitudes on vehicle acceleration, wheel rail vertical force, track structure acceleration and displacement, wheel load reduction rate and derailment coefficient are analyzed. The results show that when the amplitude of the upper arch of the off-gap is greater than 4mm, the vertical acceleration of the vehicle and the maximum wheel rail force change obviously; the influence of the off-gap amplitude on the vibration acceleration of the track plate is obviously greater than that of the rail, but the displacement of both has obvious following property, which is about 0.6 mm; when the off-gap amplitude is 10mm, the wheel load reduction rate exceeds the limit value. The dynamic response of wheel-rail system under different off-gap working conditions can provide a basis for the maintenance of the upper arch under the slab and ensure the traffic safety.

Auxiliary Power unit Systems (APS) are widely used in civil aircraft to provide air and power. APS is an air-breathing power system, and its intake system at the front end of the system cycle has a very important impact on the overall performance. Through the geometric modeling of the APS intake system, three-dimensional fluid simulation calculations are carried out to study the influence of the inlet door angle on the intake aerodynamic performance. As the angle of inlet door increases, whether on the ground or in the air, the average total pressure at the outlet of the inlet duct increases, the total pressure loss decreases, the ram recovery coefficient becomes larger, and the intake aerodynamic performance is better, which is beneficial to the APS system performance. This phenomenon is more obvious in air conditions.

In order to better adjust to the construction of expressways, this paper analyzes the characteristics of expressways in Yunnan Province and the reasons for the over-budget of some expressways during the 13th Five-Year Plan period. Based on the principle of risk classification, the probability of occurrence and loss caused by the super probability are taken as the important basis of risk classification, and the product of the two is taken as the risk classification factor. The actual operation also adopts the ranking of the occurrence probability of over-budget event and the loss caused by the previous event through the list rating and takes corresponding control measures according to different risk levels, so as to provide reference for the management and control of over-budget risk of engineering construction.

To improve the reliability of the traction drive system of the CR200J EMU, its structural characteristics and logical relationship were analyzed, and a reliability model of the traction drive system was established. The degree of reliability is used as the evaluation index, and the reliability of each subsystem of the traction drive system is allocated. The allocation process is described in detail. The results show that in the early stage of EMU operation, it is of great significance to calculate the reliability of EMUs through the correct reliability model and reasonable reliability distribution method, which is of great importance for the use of EMUs and the formulation of maintenance plans.

In order to strengthen the management of the safe use of large-scale equipment in automobile maintenance enterprises, a comprehensive evaluation index system was established for the safe use of spray paint booths in automobile maintenance enterprises, and the weights of indicators at all levels were determined by the analytic hierarchy process. Combined with the results of two consecutive random inspections on the safe use of spray paint booths in maintenance companies in a certain area, a fuzzy comprehensive evaluation of the safe use status of car spray booths in auto repair companies was carried out, and finally the quantitative score of management and technology categories was 83.54 and 69.52. The resulting overall score was 76.53. The research shows that the evaluation index system, evaluation method and results can actually reflect the safe use status of spray paint booths of automobile maintenance enterprises in a specific area. The quantitative assessment results will provide targeted guidance for strengthening the safety management of the auto maintenance industry.

Based on a gasoline engine bench, DLPI particles were collected at the front and rear ends of the GPF at a rotational speed of 2100r/min and a load of 75%. The collected particles were scanned with a transmission electron microscope and analyzed for their microscopic morphology. The results show that the basic particles of particles are almost spherical, and GPF has no obvious effect on the micro morphology of particles. The particles collected in the first to fourth stages of DLPI are less affected by GPF, and the particles collected in the fifth to eighth stages are more affected by GPF. The aggregation degree of the basic particles of level 1 to level 8 particles tends to rise first, then fall and then rise from level one to level eight, which may be due to the relatively tight structure of small particles and the relatively loose structure of large particles.

Reduction of the minimum operation interval is one of the key means to solve the shortage of the line operation capacity and improve ride comfort of urban rail transit. For headway of large passenger flow stations that restricts the reduction of the minimum operation interval, it is difficult to reduce the long dwell time. If change the station wiring or station location, it is faced with such problems as high cost of transformation, long period of transformation and great difficulty of transformation. Therefore, this paper aims at target reduction of headway, adjustment and implement accurately and easily for CBTC system of urban rail transit and proposes two target reduction of headway methods based on the analyses of relevant train operation profile. Two methods can not only be realized through ATS function operation, but also control the adjustment measures in small line section. The simulation results show that both methods can effectively reduce the headway. Compared with the method two, the method one has better headway reduction effect, less impact on the running time between stations and can increase the flexible adjustment space for operation management.

Information release of railway emergencies is an important way for the public to enjoy the right to know about railway emergencies and win their understanding, sympathy, trust and support. Firstly, the principles that should be followed in the release of railway emergency information are summarized. On this basis, the evaluation index system of railway emergency information release is established for the first time from six dimensions of timeliness, authority, diversity, authenticity and humanity, rationality of strategy and interactivity. Linear programming model can quickly and effectively calculate the index weight and can make full use of effective data to obtain reasonable and satisfactory results. Finally, an example is used to evaluate the index system, in order to provide some reference for the guidance and management of railway emergency information release.

In order to monitor and warn the leakage fault of air control valves in train braking system, rapid analysis of fault characteristics is the key premise. The relay valve used in train braking system was taken as an example in this paper. Its working principle and physical structure were clarified, and the leakage fault was divided into internal leakage and external leakage based on the airflow direction. The simulation model of relay valve was established, and the internal and external leakage faults were simulated by using the model-based fault injection method. The influence laws of leakage faults on the output pressure and balance state of the relay valve were analyzed, and it was found that the relay valve had a dynamic balance position besides the tri-state position. Finally, the leakage simulation bench test was carried out, and the test results show that the relay valve model could correctly analyze the leakage fault characteristics, and the output pressure could be used as the fault characteristic to warn leakage faults. The method proposed in this paper provides an effective way to analyze the fault characteristics of braking system and can be used to obtain fault data for fault diagnosis.

Urban rail transit passenger flow distribution has a very important reference value for urban rail transit operation and management. Most of the current research focuses on static passenger flow distribution, and there are few studies on passenger flow allocation considering dynamic passenger flow demand changes. Therefore, this paper focuses on considering dynamic passenger flow. The problem of passenger flow distribution under the change of passenger flow demand. This paper first analyzes the time and space distribution characteristics of passenger travel demand, uses the 4-parameter Logistic function to fit the cumulative passenger flow curve segmentally, deduces the calculation formula of passenger flow demand at each station in any time period, and divides passenger travel into smooth state and the generalized travel cost of passengers is calculated based on the congestion state, combined with the logit passenger flow distribution model, the travel cost is dynamically revised and a solution algorithm is designed to achieve dynamic passenger flow distribution. Finally, the feasibility and effectiveness of the model and algorithm are analyzed and verified by constructing the urban rail transit network, and the passenger flow distribution under the dynamic passenger flow demand is realized.

The coordinated development of urban agglomerations has become a national key development strategy, and the realization of this strategy must be supported by an efficient and scientific transportation system. The analysis of the spatiotemporal characteristics of intercity travel in urban agglomerations is the basic support for the study of intercity transportation policies, planning and construction, and operation management. Based on massive mobile phone signaling data, this paper extracts the intercity travel data of the Beijing-Tianjin-Hebei urban agglomeration, and reveals the spatiotemporal characteristics of intercity travel from different perspectives. The results of the study show that there are two distinct peak periods for intercity travel during holidays. Holidays can be divided into three categories according to time characteristics: holidays with traditional customs such as family reunion (such as Spring Festival, Mid-Autumn Festival), long holidays (such as National Day, Labor Day), and short holidays (such as Ching Ming Festival, Dragon Boat Festival). During the first peak travel period of holidays, from the inside to the outside of the Beijing-Tianjin-Hebei urban agglomeration, the spatial distribution of the inflow and outflow of intercity travel shows highest outflow-higher outflow-highest inflowhigher inflow- basically flat inflow and outflow space structure. The second type of holidays (Labor Day, National Day) in this hierarchical structure is the most obvious. The research results of this paper provide a scientific reference for the planning of the intercity transportation system of urban agglomerations during holidays.

In urban bus planning and bus schedule design, reasonably determining the time control points of bus route and compiling points schedule can effectively improve the service level of bus system. According to the six principles of time control points setting, considering the influence of POI factors near the station on time control points selection, this paper establishes the average number of bus boarding, standard deviation rate of bus headway, standard deviation rate of running time between stations, importance of POI around the station and station dispersion index, proposes the technical process of scheme preference, and designs a comprehensive evaluation function for time control points selection. Thus, the control point scheme selection is carried out. In the study, the proposed time control points selection method was applied to the bus route 700 in Xi'an, taking the APTS data and POI data of the bus route for one week as an example, and the study showed that the method can be applied to the actual bus operation management, which can provide scientific decision-making basis for urban bus planning and design.

In this paper, a distributed cruise control strategy for trains in virtual coupled is proposed. This control strategy is designed by integrating adaptive control with cooperative control to deal with the formation problem for trains with uncertainties, based on multi-agent system theory. External disturbance can be estimated by a distributed observer while parameter uncertainties can be adaptively estimated. Potential function is designed to ensure that state constraints, namely the restrict of the distances between the neighboring trains in the virtually coupled train formation, won’t be violated. This distributed control method enables all trains to track the desired trajectory without collision, whether the train can directly receive the reference information. Numerical examples are discussed to demonstrate the effectiveness of the proposed control method.

In the design process of the air-conditioning system of the existing EMUs, teams from different fields work together through the design of text, which is prone to problems such as ambiguity in natural language understanding and unclear data traceability. Therefore, proposing the Model-Based Systems Engineering (MBSE) method to model the air conditioning system architecture of the EMU in the early design stage and taking the ventilation function of the air-conditioning system of the EMU as an example, using the Arcadia method to model the functional architecture of the system through four levels of operational analysis, system analysis, logical architecture analysis, and physical architecture analysis. The results show that the method can realize the retrospective verification between data, improve the reusability of the model, and improve the efficiency of the EMU's functional architecture design of the air conditioning system.

Spacecraft will suffer some degree of vibration and shock when transported by road, it will bring the security and stability risks to the spacecraft’s internal structure. In this paper, based on the study of the vibration and shock sources of spacecraft’s road transportation, the vibration characteristics of road transportation at the launch site are analyzed, and a road transportation monitoring system is designed and developed by using virtual instrument technology. By collecting acceleration signals during transportation and using FFT technology to process and analyze signals, the system realizes real-time monitoring of the vibration of the spacecraft transportation process. Now the system is built and put into use to meet the measurement requirements and has great significance for ensuring the safety of spacecraft during transportation.

Traffic accidents caused by wrong stepping on the accelerator when braking due to the driver's fault or the driver's error in busy work are not uncommon. In order to avoid such traffic accidents, a more accurate and effective control system is designed to prevent accidentally stepping on the accelerator when braking. The system takes the gear position of the vehicle gearbox, driving speed, engine speed and the distance between the vehicle and the front and rear obstacles as the discrimination threshold of accidentally stepping on the accelerator, the vehicle electronic controller ECU performs signal discrimination and processing, controls the throttle opening of the engine, reduces the vehicle power, and starts the braking system, so as to reduce the vehicle speed until it stops.

In order to study the effect of adverse weather on driver vision in cold urban areas, Firstly, the mechanism of the effect of adverse weather conditions such as rainfall, snowfall, and fog on drivers' vision was analyzed; secondly, the effect of different vehicle speeds and illumination levels on drivers' visual adaptation time under adverse weather conditions was analyzed by extracting drivers' reaction times at different vehicle speeds and target contrast levels with different illumination levels (E); finally, regression fitting was carried out on the average driver reaction times and ambient illumination data to analyze their Finally, the mean driver reaction time and the ambient illumination data were fitted to the regression to analyze their correlation. The study shows that bad weather has a significant impact on ambient illumination, visibility, and driver vision. The incidence of bad weather leads to a sharp decrease in road visibility and illumination, and as road illumination decreases, driver reaction time increases, which is likely to cause traffic accidents.

In order to effectively utilize braking torque to recover braking energy and ensure braking strength and stability, a control strategy that meets the requirements of ECE regulation on braking force distribution for front and rear axle vehicles was proposed for the composite electromechanical braking system composed of electric braking and conventional friction braking. The whole vehicle model of electric vehicle was established by ADVISOR, and the NEDC cycle was used to simulate the electric vehicle. The results show that the strategy can improve the driving range of electric vehicles under typical urban conditions.

The continued outbreak of the novel coronavirus pneumonia (COVID-19) has had a huge impact on people's lives. In the context of the ongoing epidemic and the limited distribution capacity due to the multi-regional epidemic closure, it has become an urgent reality to minimize the damage caused to people's daily lives under the epidemic and other emergencies, and to implement safe, fair and economical dispatch of emergency supplies for the epidemic area. The problem. Based on this, a mixed integer linear programming model is constructed to maximize the fairness and minimize the transportation cost of emergency material dispatch.

Based on the vehicle plane motion model, an integrated control strategy of Active Front Steering (AFS) and Direct Yaw Control (DYC) based on Multi-Input Multi-Output (MIMO) structure is proposed. Based on the hierarchical structure of chassis integrated control system, the integrated controller based on phase plane theory and the integrated controller based on MIMO structure are built respectively. The designed integrated controller is verified by simulation under different driving conditions. The results show that the proposed integrated control strategy based on multi-input multi-output structure has better control effect under different working conditions, effectively ensures the vehicle state to follow the desired value, and thus significantly improves the handling stability of the vehicle.

In order to grasp the pattern of passenger flow changes at the initial opening of new urban rail transit TOD stations and to address the problem of irregular fluctuations in passenger flow at new stations and the absence of historical data, this paper proposes a method for predicting passenger flow in and out of new urban rail transit stations based on the TOD mode division. Firstly, through the analysis of the classification method of traditional TOD stations and the classification index of TOD stations, the TOD characteristic similarity urban rail stations are classified based on the hierarchical clustering algorithm. Secondly, according to the station classification results, a method is proposed to construct a historical database of passenger flow in and out of new stations. Then, by optimizing the parameters of the differential integrated moving average autoregressive model, a short-time prediction method for passenger flow in and out of new stations of urban rail TOD is proposed. Finally, the model is tested with the actual passenger flow data of the urban rail line network. The results show that the prediction errors of incoming and outgoing passenger flows are 2.59% and 7.67%, respectively, indicating that the prediction method is effective and can be applied to the pre-construction planning of new TOD stations. The prediction results can provide a reference for the urban rail traffic organization.

The inventory control problem is a classic intelligent decision-making scenario. A good inventory policy can greatly improve the efficiency of supply chain and enhance the competitiveness of enterprises. This paper introduces an algorithm to compute the (R, s, S) policy parameters for a two-echelon warehouse non-stationary stochastic lot-sizing problem with backorder. The two-echelon warehouse system refers to a system where the warehouses are divided into business-oriented and customer-oriented two tiers, which are widely used in the real world but poorly studied in the literature. The businessoriented warehouse supplies both the business partners and the customer-oriented warehouse while the customer's demands are met only by the latter. The heuristic combines a backward stochastic dynamic programming and a greedy relaxation of the problem. A technique is proposed to convert customer-oriented sales into the replenishment demands for the businessoriented warehouse. The (R, s, S) policy parameters are then computed for product sales of the customer-oriented warehouse and total demand of the business-oriented warehouse. Moreover, we speed up the procedure by applying a convexity property and some techniques to avoid recomputation, which extends its adoptability to large-scale problems. The results show that the computational efforts remain acceptable as the problems’ sizes increase. Sensitivity analysis shows that the performance is less affected by parameter settings, which represents the stability of the algorithm.

As cruise ships call at many ports and passengers come from all over the world, it is very easy to carry viruses on cruise ships. Under the control of the epidemic situation on board, the solid waste generated by them should be scientifically treated to prevent the spread of infectious diseases such as COVID-19 pneumonia. Therefore, Reasonable selection of waste disposal ports and formulation of unloading plans are directly related to the resumption of cruise operations. This study considers the cost and risk of waste disposal, uses robust optimization to deal with waste volume, increases the scenarios of port service interruption due to epidemics and other reasons, and proposes a variety of emergency strategies. Finally, the relevant strategies are selected according to the decision-maker's preference for cost and risk; by solving the relevant examples, the optimal choice of the cruise ship waste disposal port under the epidemic situation is given, which verifies the validity and feasibility of the model. The research helps to improve the management of cruise waste during the post-epidemic period and has practical value and guiding significance for the normal operation and development of the global cruise market.

A reasonable signal timing scheme can improve the traffic capacity of intersections. In order to solve the traffic congestion problem at the intersection of Gongyuan road and Daqiao road in Xuzhou City during the morning rush hour, this paper combines the road field survey data, uses Webster formula to optimize the signal timing scheme of intersections, uses VISSIM software to simulate, compares the average delay before and after optimization, and explains the optimized signal timing, The peak congestion at the intersection can be improved.

Due to the large number of passengers served by the metro, with its extensive served area, as well as the interconnection of different stations within the metro system, there is a high possibility that a large number of city residents' trips will be delayed or forced to be canceled and cause economic losses, once a safety accident occurs in the subway system. An easy-to-practice and highly flexible evaluation framework are proposed to explore the identification of vulnerable nodes in a weighted metro network, considering network connectivity and node traffic. The degree distribution of the passenger flow weighted network obeys the power law distribution. The relationship between node connectivity, node passenger flow, and key players in the network are also discussed. We simulated network node failures under four scenarios to assess the impact of node failures on network accessibility and the number of passengers served. The network is robust when the nodes fail randomly; the network is vulnerable to deliberate attacks based on topological node characteristics. The strategies that have the most significant impact on site traffic are node weight-based attack and node weighted-degree-based attack, with the weighted-degree-based attack being more disruptive to network connectivity and the best performing strategy in aggregate. Furthermore, we have identified the top 10 nodes in the Shenzhen Metro network that are more influential to passengers and disruptive to the network structure, which could provide a reference for metro emergency management.

Compared with simpler road sections such as the direction and speed of traffic flow, the intersection will produce a series of changes in speed density and direction due to the influence of vehicle steering and traffic signal control equipment, which will have a more serious impact on road traffic. . The delay is an important indicator to judge the operation efficiency and service quality of an intersection. In order to reduce the average delay at the intersection of Ren min Avenue and Haidian Wuxi Road in Haikou City, this paper uses manual observation to collect delay-related data, and conducts VISSIM road simulation according to actual road conditions to obtain the average delay data under ideal conditions. The variable method optimizes the signal accessories of each entrance, and designs the left-turn waiting area according to the actual situation, which effectively reduces the average delay at the intersection, and provides a reference and idea for the optimization of road intersections in Haikou City.

The asymmetry of freight information between supply and demand leads to the existence of partially unutilized or inadequate and inefficient transport capacity in the railway transport network. With the rapid information propagating, the demand selection between the Origin-Destination (OD) supply chain has changed, which causes dramatic shifts in traffic over time and space. This change will also spread with the railway networks and eventually form an Unstable Freight (USF) which seriously impacts the planning and operation organization of railway transportation. This study constructs the dynamic USF networks first, then identifies the key stations and extracts the connectivity and stability of the network by using a complex topology network tool. A simulation model is established to capture the diffusion phenomenon and identify the propagation mechanism. Taking China's chemical freight as a case, the results identified the key stations and ODs that led to the imbalance of freight supply and demand and determined the diffusion characteristics of unstable freight. The data show that the chemicals USF network lacks self-regulation (with a high propagation rate γ =0.77) and recovery ability (low recovery rate β =0.42) in China compared with the average ( γ =0.5767 and β =0.5756). These provide technical support for predicting the change in railway freight demand and rational allocation of transportation resources and give a decision-making basis for government departments to balance the market, reduce logistics costs and protect the environment.

To study the influencing factors of the implementation effect of the expressway directional lanes, and also to analyze the importance of different influencing factors on the implementation effect of the directional lanes, this paper explores the degree of influence of four influencing factors, namely, the number of lanes, the length of the interweaving area, the traffic volume and the proportion of exit flow by using the VISSIM, and constructs the mathematical relationship between multiple influencing factors and the proportion of average speed improvement by using the multivariate nonlinear regression The model was used as an example to analyze the section of Fuxingmen Bridge on the West Second Ring Road in Beijing. The results show that the number of lanes, the length of the interweaving area, the traffic volume and the exit flow ratio all have significant effects on the implementation of the expressway directional lanes, and the exit flow ratio is the most important influencing factor, followed by the traffic volume, the number of lanes and the length of the interweaving area. The results of the study provide a theoretical basis for further research on the setting of expressway directional lanes.

With the continuous development of rural construction, the rural standard of living has been significantly improved in recent years. The length of rural roads and the number of vehicles continued to increase. However, due to the lack of necessary lighting guidance equipment at night in countryside, in the recent years, there have been many traffic accidents at night, causing huge losses. The problems of night traffic safety in countryside have also become increasingly serious. Favorable economic development and construction need a stable social order and environment as guarantee. Especially for rural night driving, there are many contradictory problems in its development. In addition, there is not much research on this direction. Therefore, optimizing the night driving safety in countryside is of great significance for promoting the stand of rural economic development and social order. This paper takes rural night driving as the research object, by combining with the current rural road infrastructure planning and construction and the relationship between safety and existing energy and resources. The paper analyzes the practical problems of driving at night in rural areas of China, through the research and put forward the optimization measures of night driving safety in countryside.

In recent years, the carbon emissions in the transport sector have been maintained at annual growth rate over 5%, making it one of the major sources of Greenhouse Gas (GHG) emissions in China. In the background of low-carbon transformation, the "carbon peaking and carbon neutrality" target has put forward higher requirements for energy saving and carbon reduction in the transport sector. Heavy-duty trucks are a major energy consumer in the transport sector and are a key area for carbon neutrality. With the theory of human-machine-environment system engineering, this research figures out the factors affecting the energy consumption of vehicles. Based on the dynamic data of Heavy-duty trucks Global Positioning System (GPS), the research uses big data processing and statistical analysis to estimate the CO2 emissions of heavy-duty trucks over 12 tons in China and puts forward relevant policy suggestions for the development of energy-saving and carbon-reduction in the road freight industry. This paper provides theoretical support and reference for the green transformation of China's transportation industry.

As the initial condition of evaporative combustion, the jet atomization formed by the swirl nozzle has the characteristics of large distribution space and small atomization particle size, so it is very important to study the jet atomization of the swirl nozzle. Previously, most scholars used the interface tracking method to study the primary breakage of the rotating conical liquid film, but there were few studies on the secondary breakage of the liquid film. This paper aims to use the cross-scale VTD model, comprehensively consider the actual situation of multi-scale and multi-phase flow coupling in the atomization process and discuss the changing characteristics of the conical liquid film during the crushing process in combination with different jet parameters. The smaller the viscosity of the liquid, the better the atomization effect, the smaller the primary crushing area and the more severe the secondary crushing; the axial velocity has a great influence on the surface wave structure, with the increase of the axial velocity, the surface wavelength also increases; the jet velocity. The impact on the distribution of the crushing area is small, but it has a greater impact on the severity of the secondary crushing.

This paper analyzes the adaptability of the line slope after the failure of the EMU and conducts a simulation calculation for the traction and braking capabilities of the CR400AF EMU. Combined with the test results of a long-slope line of a high-speed railway, a comparative analysis is carried out, and the restrictive conditions for the operation of the long-slope line are put forward. The relevant conclusions can provide reference for the railway bureau to organize on-site rescue of EMUs and formulate relevant emergency plans.

The port throughput is a barometer of the world economic development and the basic premise for the competent government departments to formulate macroeconomic and industrial development policies. In order to screen out the factors that affect the port throughput more accurately and clarify the action time of each factor, this study determines the VAR model, which is famous for its medium and long-term prediction accuracy, as the main application model for analysis, and expounds the relevant theory of the model. Then, it introduces the steps of establishing the model and the evaluation indicators of the model, and then demonstrates the method in combination with the coal throughput of Chinese ports. This study selects the annual data of the port coal throughput, the added value of the third industry, the total import and export investment and other indicators from 1980 to 2020, and finally concludes that the port coal throughput of China has a strong correlation with the total import and export investment and the number of people, and the port coal throughput has a positive impact on itself and reaches the maximum in the second phase, The impact of total import and export investment on Port coal throughput is negative after reaching the maximum in phase II, and the impact of population on Port coal throughput is negative after reaching the maximum in phase III.

Rain and snow are typical disastrous weather on highway in winter. It is a common meteorological phenomenon that rain and snow are accompanied by wind. So, the compound condition of wind, rain and snow or other adverse weather must be considered in order to study the impact of adverse weather on driving safety. Heavy duty trucks have become one of the most popular choices for high-speed logistics in recent years because there is massive demand for cold chain logistics in the transportation market and heavy-duty trucks have lower fuel cost. However, due to the high center of gravity and large windward area, it is easier for heavy duty trucks to sideslip in the above-mentioned weather condition, which seriously affects driving safety and reduces logistics benefits. This paper studies the critical speed of truck on highway, aiming at the natural objective phenomena that rain and snow are often accompanied by wind in winter. Based on Trucksim simulation software and a certain domestic highway, this paper establishes the vehicle dynamic simulation model, and takes the maximum lateral offset of vehicle as the criterion to calculate the critical speed under the compound condition of wind, rain and snow, which provides a reliable basis for taking precautions against accidents and is of great significance in ensuring road safety in adverse weather.

Offshore structure heavy lifts, such as drilling platforms, large port machinery, etc., are currently mostly transported by semi-submersible ships over long distances. Due to the effect of the marine environment, the heavy structures carried by ships need to be securely fastened to the carrying ships. The rolling of structures caused by the movement of ships during transportation is an important factor affecting their lashing and reinforcement. At this stage, there are two commonly used inertial force calculation methods. The paper simulates and calculates the motion and load response of the ship during the navigation process based on the joint distribution frequency of the significant wave height and period of two typical waves in the sea area. During the numerical simulation of sailing, the roll response of the ship under different waves is calculated. In order to reduce the roll amplitude, it is recommended that the ship keep the top wave or the inclined top wave within 40° of the unilateral wave direction from 180° to 140° when sailing in the middle and high latitude harsh sea areas. Expanded to 60° range from 180° to 120°.

Traffic volume prediction is the basis of road network planning and project feasibility studies, where total expressway traffic generation prediction is one of the cornerstones. Based on the big data of expressway network toll collection and related socio-economic indicators in Guangdong Province from 2015 to 2018, the correlation between the traffic generation (attraction) of expressways and socio-economic indicators was analyzed based on multiple linear regression, and a prediction model on fitting function for total expressway traffic generation in Guangdong Province was established. Finally, a real case study was used to test and verify our study.

In view of the problems of many parameters, complex network and too much memory occupied by the current target detection algorithm based on convolutional neural network in the edge computing equipment, a video based lightweight convolutional neural network YOLOv5-MN3 for Abandoned Objects in Freeway is proposed. Firstly, we reduce the network parameters and the amount of computation by changing the backbone network architecture and replacing the standard convolution with the deep separable convolution. Secondly, the paper enhances the feature extraction ability of neural network by integrating attention mechanism and improves the recall and accuracy of model detection. Finally, through knowledge distillation to further compress the model, we completed the design of lightweight network. The experimental results showed that the average accuracy of YOLOv5-MN3 network can reach 88.2%, which is 38.68% smaller than the original network. Therefore, the network met the requirements of edge computing device deployment.

In the world aviation market, business jets are in the high end of civil aircraft, with the characteristics of high degree of customization and high technical requirements. The most prominent features of business jets are the high degree of customer customization and good comfort. Based on the overall cabin parameters of an airline aircraft, this paper proposes the cabin layout form to meet customer needs and excavates the potential of the aircraft modify to business jet, enlarges the advantages, reduces the disadvantages, provides guidance for business jet design, and provides a reference for the improvement and modification of subsequent aircraft.

Because of the advantages of high capacity and fast speed, suburban railway is regarded as an ideal way to achieve fast commuting between downtown area and its surrounding satellite cities. In the actual operation of suburban railway, trains generally use a mixture mode of "fast & slow train" to meet different travel needs, but this mode will inevitably lead to the occurrence of overtaking phenomenon between trains. Even in a same trains operating plan, there are still multiple different overtaking plans. And different overtaking plans will have different effects on line passing capacity. In order to find the overtaking plan that can maximize line passing capacity, this paper proposes a method for optimizing the passing capacity of suburban railway based on UIC406 method. And a real suburban railway line is used for simulation and verification. The optimization results show that on the simulated railway line and with the train operating plan we used in simulation, allowing trains to overtake can save 23.4% of the time consumed by the trains passing through the line compared to not allowing trains to overtake. And the bottleneck that affects the further reduction of the time consumption is mainly in the "first departure section" of each station.

In order to cope with all kinds of emergencies on the freeway and improve the emergency response capability of the freeway system, the emergency response capability of the freeway road network is quantitatively assessed. Based on the system resilience theory, a freeway emergency response capability assessment index system is constructed from three aspects: resistance capability, adaptive capability and recovery and optimization capability. The concept of cloud model is introduced, and the traditional hierarchical analysis scalar theory is modified to show the randomness, fuzziness and dispersion of the evaluation system with three numerical characteristics of expectation, entropy and super entropy, so as to determine the relative weight of each index and the cloud numerical characteristics of risk value; finally, the cloud model is used to quantify the randomness and fuzziness of each index, generate the cloud map of each risk evaluation level, and obtain the overall evaluation results. The results show that the overall emergency response capability score is 91.646, which is in the good level and should focus on strengthening the road network recovery and optimization capability and adaptive capability construction to improve the comprehensive resilience of the road network. This method can be used to quantitatively assess the emergency response capability of the freeway network and provide a scientific basis for the improvement of the emergency management capability of the road network system.

The safety evaluation in the stage of acceptance inspection is the last safety inspection before highway operation, which is of great practical significance to minimize the traffic safety risk during the operation period. Collector-distributed first-grade highway mainly plays the role of collecting and evacuating traffic. It has the characteristics of many intersections and mixed traffic. Its traffic characteristics are complex, so traffic accidents occur frequently. Taking the safety evaluation of Leicheng connecting line of Donglei highway as an example, this paper analyzes and evaluates the main factors affecting the operation traffic safety of the collector-distributed first-grade highway, such as sight distance, clearance of highway, median divider opening, piers and abutments of upper-span bridges, speed limit scheme, and puts forward corresponding improvement suggestions, in order to reduce the accident rate during highway operation and ensure the safety and smoothness of highway traffic.

In order to improve the driving safety of the high-altitude highway tunnel entrance section, the physiological changes of drivers passing through the tunnel entrance section under a hypoxic environment were studied. Build a low-oxygen environment and conduct real vehicle tests to collect test data such as illumination, vehicle speed, and heart rate. The single factor analysis method was used to test the significant differences in the data, to analyze the influence of the illumination and speed on the heart rate growth rate at the entrance of the tunnel, and to establish a relationship model between the illumination, and speed and heart rate growth rate. The results show that: the sharp change of illumination intensity at the entrance of the tunnel causes the heart rate growth rate to increase significantly, and the heart rate growth rate fluctuates gently after the illumination becomes stable; the vehicle speed and heart rate growth rate before and after the tunnel entrance are significantly different. When the vehicle speed decreases, the growth rate of heart rate gradually increases; the growth rate of heart rate reaches a peak value of 35.83% within 50m of the tunnel opening; the low oxygen environment leads to a higher growth rate of the driver’s heart rate, which is not conducive to driving safety. The research results can provide a certain reference for traffic safety control at the entrance of high-altitude highway tunnels.

In order to identify the traffic state of urban expressway more accurately, a traffic state recognition model based on K-means clustering algorithm and AdaBoost integrated with multiple decision stump classifiers (AdaBoost-DS) is proposed. Taking the traffic flow, velocity and occupancy as the basic parameters, combined with the existing research results, the expressway traffic state is divided into four categories, and the K-means clustering algorithm is used to classify the traffic state; then, the classified traffic flow data are used to train the AdaBoost-DS model. The example verification and comparative analysis of the measured data of urban expressway show that the method in this paper is effective and feasible, and its recognition accuracy is 93.2%, which is 7.6% higher than that of BPNN.

In order to investigate the ability of China's state-owned airlines route network in resisting network cascading failure, using load-capacity cascading failure model combined with the method of using TOPSIS-entropy weight comprehensive evaluation method to define the initial load, simulate the network cascading failure process, and study the invulnerability of each airline’s route network and found that: 1). MU airlines have strong cascading invulnerability, CZ is the second and CA airline have the weakest cascading invulnerability, and all of them are more dependent on the headquarters nodes. 2). The more significant the network small-world characteristics and the degree of heterogeneous distribution, the weaker the network cascading invulnerability and the lower the network line cost.

In the development of highway, the trend of its network is gradually presented, and there are also some structural problems. Based on the geographic information data and vehicle toll data of the national highway network, this paper realized the construction of the national highway network topology model with a high efficiency algorithm and realized the traffic flow distribution based on the Dijkstra shortest path algorithm. It provided new thoughts to solve the problem of national expressway cost allocation.

To study the driving behaviors of drivers at the entrance section of high-altitude highway tunnels, the data related to drivers' heart rate and longitudinal acceleration of vehicles were obtained through real vehicle tests. To study the driving behavior at the entrance section of high-altitude highway tunnels, the data related to the driver's heart rate and vehicle longitudinal acceleration were obtained through real vehicle tests. Then, the acceleration standard deviation algorithm was used to calculate the standard deviation values of longitudinal acceleration in the entrance section of the high-altitude tunnel, the normal tunnel section, and the highway section, and to compare and analyze them. The results show that when driving in a high-altitude highway tunnel driving environment, in the tunnel entrance section, the longitudinal acceleration changes significantly with the HR, which shows a deceleration behavior when approaching the tunnel entrance and speeding up behavior after entering the tunnel; secondly, from the longitudinal acceleration standard deviation comparison, it can be seen that the longitudinal acceleration standard deviation is the largest in the high-altitude tunnel entrance section, then in the ordinary tunnel section, while the highway section longitudinal The acceleration standard deviation is the smallest, which indicates that the driver's operation of the vehicle is higher than other road sections when passing through the high-altitude entrance section.

Fleet assignment problem is a combinatorial optimization problem with multiple objectives and constraints. This paper established a mathematical model of the fleet assignment problem for diverse optimization objectives of the problem. The objectives are to find the minimum number of aircraft needed to operate the network and assign the optimal fleet to each flight leg in order to maximize the total profit. LINDO software was utilized to run the programming and obtain the optimal solution. This paper also demonstrated a calculation example by assuming a new-established airline in the U.S. with its hub and spoke network being analyzed. The algorithm is proved to be feasible and effective when examining in Sabre software, which is not available in domestic Chinese market. The methodology is not only conducive to the safe and punctual operation of flights, but also guides airlines to optimize the utilization of the fleet and effectively reduce the operation and maintenance costs. It is practical to airline schedulers and will promote the development of system and software in Chinese market.

Energy is important for country economy and industry development. Maritime shipping is one of the major transportation methods for energy. About 80% energy transportation pass through the maritime corridors, of which the importance of security and stability is extremely vital. This article analyses the development of maritime energy transportation corridor system by shipping operational data from Automatic Identification System (AIS). The risks and challenges faced by China's maritime energy transportation corridors are discussed through the "Human-Material-Environment" system engineering theory and PESTEL model. In the end, this article puts forward suggestions to alleviate China energy transportation corridor dependency.

The highway accessibility of scenic spots has a profound impact on the formulation of regional tourism development strategies. Based on GIS technology, this study constructs an accessibility evaluation model through the accessibility index and the isochron of scenic spots to analyze the highway accessibility of A-level scenic spots in Nanning, Guangxi, China. The results show that: (1) The overall accessibility of the scenic spots is good, showing a decreasing trend from city center to edge, and the average time is 59.45 minutes from the origin of tourist to the scenic spots. (2) The highway accessibility of scenic spots is affected by the density of the road network and the level of the road, that is, the denser the road network and the higher the road level, the higher the accessibility of scenic spots, and vice versa.

Accurate perception of lane lines position and lane width is a key factor in driver assistance systems. At the same time, night driving is an important driving scene. Therefore, this paper proposes a night-time lane lines positioning method based on camera and LiDAR fusion. The lane lines are detected in the image by using computer vision, and the road surface equation is established based on the deep fusion of image and point cloud data. Combining these two aspects, the position of the lane lines in the 3D space can be solved. According to the positioning results, the distance between the vehicle and the lane lines and the lane width can be obtained. After testing the actual collected data sets, the method can achieve 99% accuracy after testing, and the maximum error is within 3%. The proposed method integrates the image and point cloud information, completes the road surface point cloud and uses the road surface as the limiting condition of lane lines positioning to make the positioning result more accurate. The method can bring positive effect to traffic scene perception under night driving.

In order to monitor the driving behaviors of vehicles on urban roads and give early warning of dangers, the control system needs to identify the behaviors of vehicles in a short time and guide the future driving trend. Based on the machine learning method, the vehicle behavior characteristics are extracted. The vehicle behavior prediction model based on high-precision trajectory data is established to recognize and predict the vehicle lane changing and car following behaviors. The research uses the binary logistic regression method to analyze the traffic parameters between vehicles, analyzes the traffic information such as vehicle speed, vehicle head angle, relative position, and the relative speed with surrounding vehicles, and obtains the influencing factors of vehicle behaviors. This study establishes a vehicle behaviors prediction model based on BP neural network model. The results show that 12 factors are strongly correlated with vehicle behavior. The behavior prediction model can accurately predict the left-right lane change and car following behavior of vehicles, and the comprehensive prediction accuracy of the model can reach 93.9%. The research provides a theoretical and data basis for intelligent transportation development and urban road traffic management.

Under the plateau environment, the experiment was based on a GDI gasoline engine bench, and the collected particles were observed by high-resolution transmission electron microscope. The micro morphology and microstructure parameter changes of particles were analyzed under the working conditions of rotating speed of 1500r/min and load of 25%, 50%, 75% and 100%, respectively. The results showed that the basic carbon particles of GDI gasoline vehicle exhaust particles were of a quasi-circular core shell amorphous structure. The basic carbon particle diameter and carbon crystal length of GDI gasoline vehicle exhaust particulates are unimodal. Different loads do not affect the peak particle size, but only the size distribution proportion of microcrystals.

With the rapid development of e-commerce, the demand for urban freight has grown rapidly. However, the space for improving the transportation capacity of urban road infrastructure is limited, while the urban rail transit network has redundant capacity during peak periods. Under this background, this paper proposes a subway passenger and freight co-transportation mode based on collinear separation, that is, freight trains and passenger trains can be transported on the same line and staggered. Specifically, under the premise of ensuring no passengers are stranded, the dynamic loading and unloading process of cargo demand on the platform under the condition of first come, first service is embedded, as well as the interactive relationship between dynamic passenger flow and passenger trains, such that a mathematical optimization model is proposed with the optimization objective of minimizing the delay of cargo demand. Taking Beijing Yizhuang Line as an example, a set of numerical experiments are designed. The experimental results show that the co-transportation mode of passengers and freight can be completed simultaneously by using the capacity of urban rail transit lines, and the service level of passenger transportation and the timeliness of freight transportation can be ensured. It provides theoretical support for the improvement of the overall benefit of the urban logistics system.

In this paper, through simulation and analysis technology, a rolling stock running in China's Ha Da line in low temperature -40 ℃ conditions, rubber parts, hydraulic damper stiffness and damping changes, as well as a system of spring and two system of spring freezing and freezing at the same time when the fault, the vehicle in different speeds, the old and new two tread state, the study of the vehicle system of snaking motion stability, operational safety and smooth operation, to obtain the vehicle dynamics of the low temperature state performance change law, the study shows that a system of spring and two system of spring freezing and freezing at the same time when the fault has a very serious impact on the vehicle dynamics performance.

The yaw damper for high-speed trains is one of the key suspension components, which plays a vital role in ensuring the vehicle's running stability. In this paper, the modeling process and damping characteristics of the oil unidirectional yaw damper are deeply studied, and the nonlinear dynamic model of the yaw damper is established. The comparison results of simulation and bench test show that the nonlinear dynamic model can accurately simulate the static and dynamic characteristics of the yaw damper. By changing the static damping characteristic curve of the yaw damper, the law of influence on the dynamic parameters is analyzed. The results show that simply increasing the unloading force will significantly increase the dynamic damping, and the dynamic stiffness will also increase significantly when the excitation frequency is greater than 4 Hz. And simply increasing the unloading speed reduces both the dynamic damping and the dynamic stiffness.

After comparing and analyzing the advantages and disadvantages of various parametric modeling methods, the Partial Least Squares (PLS) method is used to establish a manufacturing cost estimation model based on the overall engine parameters for a civil high bypass ratio turbofan engine, to estimate the manufacturing cost in support of value engineering and to conduct a trade-off analysis of product performance, weight, and cost design options.

The role played by human defence projects in modern high-tech local warfare is becoming increasingly important, and conference rooms are commonly used by personnel in wartime. Therefore, it is important to explore scientific and feasible optimisation measures to address the current problem of excessive CO₂ concentration in the internal environment of human defence projects. This paper simulates and verifies the optimisation effect by means of Airpak software simulation, i.e. by changing the parameters such as the aspect ratio of the conference room, the position of the ventilation openings, the air supply angle and the air supply speed.

With the development of heavy-duty trains in the direction of heavier loads and a more extended number of groups, the longitudinal impact force has become the reason that restricts its development, and it will also affect the safety of train operation. Researchers proposed Electronically Controlled Pneumatic (ECP) and Segmented Electro-Pneumatic (SEP) braking systems to reduce the longitudinal impact force, but their differences are not apparent. In this paper, based on SIMPACK, AMESim and Simulink, the train dynamics model, pneumatic braking model and braking control module are established, and a comprehensive computing model is constructed, which analyzes the braking performance of ECP and SEP. The results show no significant difference in performance indicators such as braking distance and brake cylinder pressure between ECP and SEP braking. In addition, the differences in the working mechanism of ECP braking and SEP braking are discussed in detail, which will provide a reference for optimizing the electronically controlled braking system.

Warehousing as an important link in the logistics process, the application of intelligent warehousing, to ensure the accuracy of data and transmission speed of goods in all aspects of warehousing, so that warehouse managers can accurately grasp the effective data of the operation in real time, the inventory control to a reasonable interval. In this paper, through the analysis of RFID technology in A wisdom warehouse application status, from facilities and equipment to software system research, through the analysis of its application effect, found that A wisdom warehouse RFID technology application mode has a strong replicability, and in the field of wisdom warehousing has a good demonstration role, has a good promotion value. It provides a good practice case for other warehousing enterprises in building a wise warehousing system, reducing operating costs, improving operational efficiency and enhancing their refined and wise warehousing management.

For the minimum value problem, an adaptive parameter adjustment method is proposed, so that the ship can quickly leave the local minimum value. According to the special provisions of the "Rules" for narrow channel waters, the risk evaluation index is introduced to the repulsion force field. Adjusting the ship through the magnitude of the repulsive force in different directions, and with corresponding thresholds set to prevent emergencies, the ship is guided to take further avoidance measures so that the planned ship avoidance measures are more in line with the requirements of international maritime collision avoidance regulations.

Taking the S700K type rutting machine commonly used in high-speed rail as an example, a new method of turnout fault prediction based on the improved GM (1,1) model is proposed in view of the problems of "fault repair" and "timed repair" of traditional railway electricity. In order to improve the prediction accuracy of the model, the sliding average method and multi-step prediction are introduced to improve the traditional GM (1,1) model. Algorithm simulation comparison and verification of turnout action current data shows that the prediction accuracy of the improved GM (1,1) model is better. taking the 2DQJ characteristics of the field S700K turning machine as an example, the effectiveness and accuracy of the improved GM (1,1) model in the prediction of turnout fault are verified.

In view of the mixed use of the straight right lane and the bus lane at the level signalized intersection of urban roads, the influence on the intersection after the establishment of the bus lane is analyzed with the saturation as the judgment index. Taking the intersection of Jiangsu Road and Zangdaxi road in Lhasa City as an example, this paper quantitatively analyzes the optimized HCM saturation flow rate model based on the actual observation data and the stop line method based on the signal phase based on the actual observation data to calculate the capacity of the intersection respectively, and then compares the saturation of the actual flow observed in the field and the flow without bus lane simulated by VISSIM. It is considered that the establishment of bus lane at the right straight lane will reduce the traffic capacity of the intersection by about 2% - 5%, which can be ignored in the actual situation, but it is not recommended to mix the right straight lane and bus lane in comprehensive consideration of administrative costs.

With the goal of improving the "Three-basic" construction of expressway enterprise safety management foundation, grassroots ability and basic skills, a simulation model of hazard warning drill was constructed through the KYT activity process of status investigation, hazard factor identification, countermeasure formulation and unified training. Intercept the expressway service area as the research object to carry out 3D, conducted simulation analysis on the evacuation of people in the expressway service area under emergency conditions, and compared the status of employees who have received KYT and those who have not received KYT. It verified the positive effect of expressway enterprise’s hazard warning drill in ensuring expressway safety, promotes the transformation of expressway enterprise employees from "passive management" to "self-management" state, and provides good experience for expressway operating enterprises.

Snowfall affects driving safety by causing changes in roadway surface that results in traffic accidents. Road friction is directly related to the amount of snow and the intensity of melt events on the road surface. Moreover, passing vehicles compresses the snow, sometimes even to ice, which impairs driving safety more seriously. Based on the fact that friction coefficient of road surface on different conditions such as the above-mentioned, this paper provides a method for calculating a safe speed limit in snowy days, taking into consideration the road parameters, visibility, and snow coverage and compression intensity. A Co-Simulation of CarSim&Simulink is established to simulate driving conditions on a snowy road, with stopping-sight distance model and sideslip model introduced. Taking braking distance and lateral offset as evaluation criteria, this paper analyzes the simulation results to verify the reliability of the proposed calculating method, and offers speed limit strategies for safe driving on highways in snowy days.

With the rapid development of private vehicles in recent years in China, the traditional bus priority control strategy can’t play a great role in easing heavy traffic anymore. To design a suitable bus priority control scheme to optimize the passing of buses at intersections, while coordinating other traffic movements at the same time, is very significant for urban traffic operation. This paper establishes a bus priority decision model and proposes a decision factor to judge the priority phases that can be calculated from the influence analysis of cars and buses according to delay, queue length and bus arrival rates and other indexes. In addition, a special parameter, named bus response level, is proposed to rank the bus priority applications from different phases. Then the actuated bus priority control process is designed in detail. Some simulation models based on Cellular Automata (CA) theory, such as lane changing model and improved VDR model, traffic elements size and intersection rules are adopted to describe the running behaviors of mixed traffic under this actuated signal control process. The simulation results show that the average delay of buses is obviously lower than that of cars. It means some obvious improvements can be achieved.

The material procurement management of rail transit engineering projects has a certain degree of planning, but the process is extensive, the procurement cost is high, and the information sharing between the supply and demand sides is low, and the ability to adapt to random needs is insufficient. will affect the progress of the project. In order to enhance the adaptability of the Rail Transit Engineering Project Management Center (EPMC) to the random demand of project material procurement, taking into account the individual interests of the project department and the overall interests of the project management center, based on the JIT strategy, to improve the confidence of the order meeting the random demand as well as the full load rate of transport vehicles, a multi-objective optimization model is established, an adaptive genetic algorithm is designed, and a case study is carried out. The results show that: under the new management mode, the fitness function value of the processed final order, the confidence of meeting the random demand and the transport vehicle have increased by 0.066, 0.087, 0,131 respectively, and the average daily operating cost of the EPMC project departments was reduced by RMB 559,147 and the procurement cycle of engineering materials was shortened by 1 day.

To improve the driving safety of high-altitude highway tunnel entrance sections in a fog environment, the physiological changes of drivers during driving in the tunnel entrance section were studied. Firstly, the hypoxia environment was constructed, and the real vehicle test was carried out under different foggy conditions, and the test data such as vehicle speed and heart rate were collected. Secondly, the single factor analysis method was used to test the significant difference in the data, analyze the influence law of tunnel entrance velocity on heart rate. Finally, establish the relationship model between velocity and heart rate. The results show that with the increase in fog concentration, the vehicle speed decreases, and the heart rate increases. The vehicle speed in the dense fog environment was significantly lower than that in the other three fog environments. The heart rate in the dense fog environment was significantly higher than that in the other three fog environments, and the maximum heart rate in the four environments all appeared within the range of 50 m from the tunnel entrance to the tunnel entrance. The relationship model showed that there was a strong correlation between speed and heart rate, and excessive speed would lead to increased heart rate and enhanced physiological discomfort for drivers. The existence of a low oxygen environment leads to a higher heart rate in drivers, which is not conducive to driving safety.

In response to the increasing demand for urban low-altitude Unmanned Aerial Vehicle (UAV) operation, this paper comprehensively considers the constraints of urban area traffic demand, airspace environment and UAV performance, with the goal of minimizing network nodes and maximizing coverage demand points, this paper proposes an urban low-altitude UAV route network construction method. First, the network node generation model and the route network construction model are established; secondly, the improved greedy algorithm is used to generate network nodes; then, k-Nearest Neighbor(K-NN) and Prim's algorithm are combined to construct the UAV route network. Finally, simulation verification is carried out based on the demand data of logistics business in Shanghai and the low-altitude operating environment, and the performance of the constructed route network is analyzed by using the complex network-related indicators. The results show that the urban low-altitude UAV route network construction method proposed in this paper can realize the construction of trunk and branch route networks at the same time, and the trunk route network realizes full network connectivity. In addition, the network nodes can be set according to the UAV mission requirements to achieve flexible planning of the route network.

In order to adapt to the needs of double steering axle vehicle steering wheel transverse side slip detection, through experimental research, the key technical parameters of the automobile side slip tester of double steering axle were determined, namely, dynamic value error of ±4%, value repeatability of ±0.1m/km, zero error of ±0.2m/km; the value drift should be controlled within ±0.2m/km; the data acquisition frequency of side slip should be less than 100Hz. The drift of the indicated value should be controlled within the range of ±0.2m/km; the data collection frequency of the side-slip amount should be not less than 100Hz. The technical transformation of the double-plate linkage side sliding table, the double-steering axis side sliding table using the "fast return" method, when the first steering axis through the side sliding table slide, the slide plate back to the initial zero position of the time should not be greater than 300ms. In the case of the "twice positioned" double steering axis side slides, when the first steering axis passes through the side slides, the side slip display should be zeroed within 300ms. The results of the study unify and standardize the technical parameters of the double steering axis side sliding table.

The subway itself has the advantages of high speed, large traffic volume, little interference from other traffic modes, and not easy to be affected by the weather. It has become the choice of travel mode for more and more residents. The subway line construction based on hot travel can better meet the requirements of fast, comfortable, less transfer and no congestion for tourists. At the same time, it can greatly reduce the traffic pressure such as traffic and parking in scenic spots, which is conducive to energy conservation and emission reduction. Therefore, good hot metro line planning has practical significance for urban development. The introduction of large and small routing schemes in this paper can, on the one hand, alleviate the problem of high train load rate and poor passenger comfort in crowded sections, on the other hand, reduce the waste of transport capacity in small sections of passenger flow, and save resources and enterprise transport costs. This paper first introduces the research background and significance of large and small routes, as well as the research status at home and abroad, then analyzes the factors that affect the setting of large and small routes, establishes the constraints of the model, and finally takes the train full load rate, departure frequency, minimum departure frequency, the number of short route stations as the constraints, and takes the train running distance and the total waiting time of passengers as the objective function. The linear weighting method, genetic algorithm and MATLAB software are used to solve two objective equations, the operating range of small routes and the departure frequency of trains with large and small routes. Finally, the feasibility of the model in real life is verified by taking the hot travel line of Chengdu Metro Line 1 as an example.

Urban intersections, especially grade crossings, are bottlenecks of city road, as well as the locations with more traffic accidents. The characteristics of traffic conflict are large sample and easy observation. Traffic conflict is used to evaluate the intersection safety. For the two-phase signalized intersection, the main type of intersection conflict is the conflict between turn left and opposite direct. In order to evaluate the influence of turn-left and opposite direct traffic volume on signalized intersection, a Vissim simulation experiment was made for imitating the traffic flow condition on a two-phase signalized intersection. We achieved the trajectory data by changing the traffic volume. Based on traffic conflict technique, a generalized linear traffic conflict prediction model was established, and then the prediction traffic conflict was used to evaluate the signalized intersection safety level. By analyzing the conflict of Sidaokou, a two-phase signalized intersection in Haidian District, Beijing, we found that this model can effectively provide the prediction traffic conflict to evaluate intersection safety status.

For the design and control method of tandem intersection, a new control strategy and design scheme is proposed to realize pedestrian crossing at the pre-signal. Compared with the conventional tandem intersection design, the signal control for right-turning vehicles at the pre-signal is increased and the right-turning lane in the sorting area is retained. The cumulative arrival and departure curves are used to describe the spatial and temporal operating states of vehicles at the pre-signal area and analyze their delays. The results show that the delay error is within 10% compared with the simulation software, and the fit is good.

Real time identification of the running state of the track circuit of urban rail vehicles is of great significance to the safe operation of trains. In this paper, a SVM based method for identifying the running state of urban rail vehicle track circuit is proposed. According to the real-time monitoring data of each sensor of the track circuit of the urban rail vehicle, the method of collective empirical mode decomposition is used to extract the features of the voltage signal. Finally, the running state of the track circuit is divided into three states: normal, mild failure and failure.

To improve the line operation adaptability of high-speed trains, a Model Predictive Control (MPC) method based on anti-yaw damper is proposed to realize the stability control of vehicle hunting motion based on the real-time adjustment of the damping value of the shock absorbers. A simplified dynamic model with seven degrees of freedom in the lateral direction of the whole vehicle is established, including the traverse, yaw and roll degrees of freedom of the vehicle body, the traverse and yaw degrees of freedom of the bogie, and the linear wheel-rail contact relationship is considered. Based on Model Predictive Control (MPC) theory, the active yaw damper is designed, the objective function and constraint conditions are established, and the optimal damping coefficient is solved. The effect of the stability control of vehicle hunting motion is analyzed. The results show that compared with the passive suspension, the MPC active yaw damper can effectively suppress the primary hunting motion of the vehicle, but the restraint effect on the second hunting motion of the vehicle is not obvious.

Lane-change is a common and dangerous condition in the process of vehicle driving. Especially in the multi-vehicle environment, the relative safety between lane-change vehicles and surrounding vehicles is very important. In this paper, a lane-change trajectory planning method based on quintic polynomial is proposed by considering the trajectory prediction results of surrounding vehicles. Firstly, by fusing the driving state of the vehicle, the lane-change trajectory cluster is obtained by using the quintic polynomial programming method, and the stability boundary of the trajectory cluster is obtained according to the three-degree-of-freedom dynamics model of the vehicle. Then, in order to get a relative in trajectory cluster environment vehicle safety of lane-change trajectory, we assume that the information data of surrounding vehicles is available, according to different location of the vehicle, to establish a different objective function, to evaluate different lane-change trajectory of the vehicle relative security, according to the objective function to solve trajectory optimal solution in the cluster. Finally, the co-simulation based on MatLab and CarSim verifies the reliability of the proposed lane-change trajectory planning method.

In terms of traffic travel, vehicles are developing towards the direction of intelligence. The research on V2X has improved the intelligent level of vehicles. This paper mainly studies the typical green wave vehicle scene in V2X. First, the vehicle information data is obtained, then a vehicle speed guidance model based on the green wave vehicle scene is proposed, and PID controller is set to track the speed. The vehicle speed guidance model proposed in this paper can guide the vehicles to pass through the intersection without stopping and improve the travel efficiency.

For a long time, the operation efficiency of highways in Sichuan plateau mountainous areas has been low, and overtaking accidents occur frequently. In addition, many places are limited by natural conditions and unable to build the two-way four-lane highway. Hence, this paper proposes a new scheme to transform and expand the two-lane road into a 2+1 alternate lane. We used VISSIM software, combined with the actual traffic characteristics of the Sichuan mountainous area, and integrated with the driving behavior features to conduct a simulation analysis on the geometric parameter design, setting influencing factors and applicability of 2+1 alternate highway. It not only fills the domestic research gap but also provides theoretical support for building a safe and efficient mountain traffic system. The study found: This scheme optimizes the service level while improving the operation efficiency. When the proportion of trucks exceeds 20%, prohibiting trucks from passing through overtaking lanes shows relatively higher service levels. 2+1 alternate highways in mountainous areas have significantly better service levels than other options when the overtaking lane length is set to 550-900m, and the speed limit in the single lane is 50-100km/h.

A multi-body kinematic modeling method is proposed and simulated for the trajectory deflection of the rear axle of the trailer during the right turn of A-Double Vehicles. Firstly, based on the kinematic theory of the multi-body system, a kinematic model of the vehicle double-track is established and the overall equations of motion of the vehicle right turn are derived. Secondly, MATLAB software was used to calculate and simulate the trajectory of each wheel during the right turn of the vehicle. Finally, the influence of vehicle wheelbase and trailer wheelbase on the offset of trailer rear wheel trajectory was compared and analyzed. The results show that the appropriate reduction of the trailer wheelbase can effectively reduce the offset of the trajectory of the rear wheels of the trailer during the right turn of the A-Double Vehicles and improve the driving safety of the vehicle.

Virtual Coupling railway technology allows trains to conduct dynamic formation and reconciliation according to the actual passenger transport needs. The trains within the formation operate at small intervals close to the length of mechanical hooks, realizing local ultra-high density driving and collaborative control. In order to ensure that the train can also operate safely when the location and speed information is missing, this paper proposes to predict the train track and perceive the future train operation state in advance to realize the safe operation. Firstly, the existing urban rail train braking model is analyzed, and the highly accurate train braking model is identified by the improved Particle Swarm (PSO) algorithm; then after analyzing Long Short-Term Memory (LSTM) and Unscented Kalman Filter (UKF) respectively, the Virtual Coupling train track prediction algorithm based on LSTM and UKF is proposed. Finally, the actual operation data construction environment, simulation prediction and verification. The simulation experiment results show that: compared with the simple LSTM trajectory prediction, the formation train trajectory prediction model based on LSTM-UKF can further reduce the prediction error and instability, which is conducive to the safe operation of the virtual formation train.

With the development in recent years, bike-sharing projects have gradually become mature and have a huge market scale. Accurate pricing and appropriate launching strategies are essential for the bike-sharing platforms to gain a foothold in the market. This article considers the pricing and the lunching strategies in the centralized model and the decentralized model, respectively. The manufacturer, as the game leader, first sets the wholesale price, then the platform, as the game follower, decides the rental price to the user every time they use bike sharing and the quantity of launching bike sharing. Furthermore, with the centralized supply chain as a benchmark, the pricing and launching strategies of the proposed model are analyzed. The results show that bike sharing rental price, wholesale price, quantity, and profit of supply chain system are positively correlated with market demand, and negatively correlated with price sensitivity. The efficiency of the decentralized supply chain system is relatively low due to the double marginalization effect. Finally, we design a revenue sharing contract to coordinate the supply chain and promote a win-win situation in the supply chain.

As the urban parking problem is becoming more and more serious, shared parking has attracted widespread attention. But the uncertainty factor in the shared parking process hinders its development. The core of the research is "whether the platform can match the demanders to the berths within the acceptable time". Based on the data of Beijing, a MNL model of shared parking user's choice behavior under the condition of "the platform can't match the berth in time" is built. It is found that the factors leading to users' withdrawal mainly lie in three aspects: parking habits, willingness and awareness of shared parking, and characteristics of shared berths. Finally, some suggestions are put forward.

This work proposes a method that quickly selects suitable rescue resources to participate in rescue activities under limited professional rescue equipment in the South China Sea. Specifically, the developed scheme relies on the analytic hierarchy process to establish a rescue equipment selection model and determine the weight coefficient of the index, which is further modified utilizing an entropy weight coefficient method. The importance of each index for the rescue equipment selection process is obtained by comparing the size of the combined weight value. Then, the analytic hierarchy process and the weighted scoring decision method are used to optimize the rescue equipment and compare the sorting results. The sorting results are verified through actual South China Sea rescue cases, revealing that the ranking results are consistent with the actual dispatch plan and demonstrating that the proposed method is scientific and feasible for selecting marine salvage equipment.

With the continuous development of modern information technology and the improvement of people's demand for logistics under the new crown epidemic, the development of smart logistics has been promoted. In order to study the important factors and development level of the development of smart logistics, this paper constructs an evaluation index system for the development of smart logistics according to the development status of smart logistics, and uses the entropy method to study the important factors affecting the development of smart logistics, and measured the development level of smart logistics in China from 2012 to 2021. Finally, according to the research results, some suggestions for the development of smart logistics are put forward.

In order to avoid collision accidents and solve the problem that direct sailing ships cannot accurately determine when they are in an urgent situation when ships meet, this paper collates the previous research on the method of the latest steering point, and based on the quaternion ship field, improves the model of the latest steering point of ships in open waters to make it conform to the restricted waters. According to the international rules for preventing collision at sea, on the premise of considering only turning to avoid collision, an urgent situation model is established through the geometric principle of ship motion, and finally a mathematical model of the latest steering point of a ship in the restricted waters is derived. The effectiveness of this method is verified by simulation data.

With the development of economy and the gradual improvement of material living standards, people's demand for nutritious and fresh products such as fresh, dairy products, fruits and vegetables is also increasing. Under the influence of the COVID-19, people put forward higher requirements for the distribution timeliness and radiation radius of cold chain logistics enterprises. Based on the existing research, this paper conducts an optimization study on the location selection of the distribution center of cold chain logistics for large-scale enterprises with self-operated operation mode. Moreover, a location model based on cluster analysis is proposed. The clustering results are corrected by gravity center method. Secondly, the optimization model of cycle picking is used to consider transportation cost, cooling cost, time constraint and so on. A better distribution center node is selected from the alternative points. Finally, the validity of the model is verified by case analysis.

The 15th to 44th span of a high-speed interchange main line bridge is a 30×15 m reinforced concrete frame bridge. After reinforcement for many times, the frame bridge still has many defects such as damage, exposed reinforcement and cracking, It is necessary to demolish them and build new bridges on both sides at the same time. Considering the convenience of the construction of the new bridge, it is proposed to demolish the longitudinal beams on the left and right sides of the old bridge first. The nearest clear distance between the new bridge pile foundation and the old bridge is about 1.4 m. The impact drilling construction technology is proposed. The impact drilling adopts the hammer with a weight of 5 t and an impact time of 5 ms. In order to understand the influence of impact drilling construction on the demolition of longitudinal beams on both sides of adjacent frame bridge, the finite element software was used to establish a part of the separated common node model of frame bridge, and the mechanical response of adjacent frame bridge under the impact of impact drilling construction was numerically simulated. The results show that: the maximum vertical displacement of the frame pier column is 0.955 mm, and the lateral and longitudinal horizontal displacement outside the bridge deck are 0.068 mm and 1.63 mm respectively. The stress of the frame bridge structure does not reach its ultimate failure value. Using the impact drilling technology construction, considering the need for multiple impacts in the process of impact drilling, it will cause the settlement value of the adjacent frame bridge and the transverse horizontal displacement of the bridge deck is large, which causes the structure to bear greater safety risks. It is recommended to build a new bridge after all the frame bridges are demolished.

Airport passenger throughput is the main production index to measure the operation status of civil aviation airport. The prediction of airport passenger throughput is of great significance to the development, function and management of airports, as well as to the promotion of high-quality and appropriate functional planning of airports. This paper chooses Jinan Yaoqiang International Airport as the research object. Firstly, the econometric method and trend extrapolation method were used to empirically analyze the passenger throughput data of Jinan Airport from 2009 to 2018. Because the two prediction models are different in emphasis, the Euclidean distance combination method based on the two methods is used to establish the model and make the prediction. Finally, the error degree of the three methods is compared and analyzed. According to the data analysis, the prediction results of the combined prediction model are obviously better than those of the above two prediction models, which can effectively reduce the error and improve the prediction accuracy.

In order to verify whether the pre-built finished product distribution and delivery logistics system of cigarette industry enterprises can meet the use requirements and the feasibility of AGV system in the distribution and delivery logistics system, computer software is used for modeling and simulation analysis. In demo3D software, Automatic Storage and Retrieval System (AS/RS), Conveyor System, AGV System and Route, Platform, Transport vehicle and other logistics equipment and subsystems were built to form an organic whole of cigarette finished product delivery logistics system. (1) Through simulation verification, the daily (working hours:10 hours) delivery capacity of the finished product distribution and delivery system of the cigarette industrial enterprise reached 3119 pallets (319.9 pallets / hour), which was higher than the system delivery demand of 895 pallets (89.5 pallets / hour) and could meet the daily delivery requirements. (2) After the completion of the system construction, in experiment, the delivery capacity reaches 101.2 pallets / hour, which is higher than the system construction demand of 89.5 pallets / hour. The minimum time for pallet handling is 2.433 minutes, the maximum is 103.467 minutes, and the median is 18.367 minutes. With the AGV subsystem as the core, the logistics system for the delivery of finished cigarette products for distribution is feasible, and the system capacity can meet the use demand.

This paper mainly takes the international logistics park as an example to analyze the planning method and layout design of the international logistics node. First, it summarizes the planning methods of logistics parks at home and abroad and points out the applicability of different methods. Secondly, systematically expounds the planning and layout methods of international logistics parks from the aspects of market analysis, strategic positioning, functional design, layout design and business plan. More importantly, by analyzing the layout design model, this paper further studies the layout design method of the logistics park and optimizes the layout of international logistics parks and nodes.

Based on the three-dimensional model of an external mixing fan-shaped air atomization nozzle, the atomization characteristics of the nozzle are analyzed. According to the nozzle, three kinds of orifice combination models are established, and the most basic model is simulated to verify the validity of the simulation model. The atomization characteristics of this type of air atomizing nozzle under different inlet pressure conditions are studied by CFD method. The effects of nozzle structure and inlet pressure on spray angle, droplet size, and the change of droplet size on different mixing sections are analyzed. The results shows that with the increase of inlet pressure, the distance required to reach the minimum droplet size is shortened, the expansion of the spray angle is mainly controlled by the airflow of the fan-shaped control holes, and the auxiliary atomization holes enhance the droplet refinement effect.

The distributed permutation flowshop scheduling problem (DPFSP) has become a research hotspot. In order to maximize total profit, two improved NEH algorithms are proposed to solve the DPFSP with rejection cost, tardiness penalty and release time. The basic NEH heuristic consists of two parts: generating initial job sequence and assigning jobs. This paper optimizes the NEH heuristic in these two parts. Two priority rules are proposed for generating initial job sequences. Two heuristics are proposed for assigning jobs according to the increment of tardiness penalty and increment of profit, respectively. In order to verify the performance of the proposed algorithms, they are compared with similar algorithms in the literature. The results validate the superiority of the proposed two prioritization rules and two heuristics.

With the continuous development of navigation business, the number of ships navigating at sea has increased greatly, and the congestion of waterways is also increasing, which brings the risk of ship collision is also increasing day by day. For this phenomenon this paper proposes an effective solution, this paper takes the ship navigation in the sea near Luoyuan Bay as the research object, first processes the AIS data of the ship, and then uses ArcGIS software to superimpose the AIS data on the nautical chart onto the nautical chart to reproduce the marine traffic situation, and then screens the traffic-intensive area of the navigation area and evaluates the navigation safety risk in the sea area, finally finds a navigation method that can effectively reduce the risk of ship collision. Using the recommended navigation method for navigation guidance can effectively reduce risk accidents and improve navigation safety.

China's leading vehicle-infrastructure cooperative autonomous driving technology route is the inevitable choice for the development of automatic driving technology in the future. The vehicle-infrastructure cooperative autonomous driving formed through "People-Vehicle-Infrastructure-Network-Map-Measurement -Operation" will better realize the integration of safety management and application services through the China scheme of vehicle-infrastructure cooperative autonomous driving. Firstly, the fusion of traffic situation awareness and vehicle end awareness under autonomous driving classification and taxonomy of intelligent road infrastructures is described. Secondly, the scenario and industrial chain in the industrial development are analyzed, and the system architecture of vehicle-infrastructure cooperative autopilot is proposed. Finally, it discusses the current roadside fusion perception technology, automatic driving technology, data compliance and other key technologies, providing reference for the industrial development and key technology research and development of the future vehicle-infrastructure cooperative autonomous driving scheme in China.

Food is a necessity of people's life, with its unique characteristics and irreplaceability. Due to the sudden, unpredictable and destructive nature of the epidemic, countries need to take particularly strict epidemic prevention measures to manage and control the epidemic in areas with severe development of the epidemic, which affects the trans-regional transportation of food and other agricultural products, and makes food supply become mainly local supply and become a limited resource. Through the integration of food supply chain in response to the outbreak of COVID-19, the service efficiency and cost can be improved, so that the community residents affected by the disaster can get high-quality food more quickly.

Computer technology in 19th-century project construction has been integrated into supply chain management, digital supply chain management is officially normalized in the 21st century, and Glodon BIM software has become a new type of practical supply chain management software. Traditional handwriting and Excel software supply chain records can no longer meet today's multiple types of diversified construction supply materials. Numerous scholars were studying BIM and supply chains, but the biggest difference in context is that this research is dedicated to addressing the supply chain model of some of the rough construction sites in China, with the aim of incorporating digital supply chain optimization management. The thesis takes a case study approach to research overall, using a housing construction project in a central Chinese city as an example to complete a digital simulation of the materials supply chain management for a construction project. This study reveals three new advantages of digital supply chain management for housing construction projects, namely efficient data collection and processes, organized records and fast search. The study shows that the application of Glodon BIM software is able to exploit these three new highlights and improve the speed and accuracy of supply chain management.

The turnover speed of the port is the key to the efficiency of railway and shipping joint transportation of large-scale coal energy enterprises. In view of the situation that the high stock of coal port leads to the difficulty of railway unloading, a ship scheduling optimization model considering the priority of ship queuing is constructed. The model takes into account the characteristics of ships entering and leaving the port, tidal characteristics, and the matching characteristics of berths and ships. Genetic algorithm is designed to solve the optimization model with the optimization objective of reducing the storage and increasing the efficiency of the port. The optimal ship scheduling scheme and ship berth matching scheme are given. The example analysis shows that compared with the traditional manual scheduling scheme based on the priority of ship queuing, the model can realize the rapid reduction of port inventory and improve the ship scheduling efficiency while considering the priority of ship queuing, which verifies the effectiveness of the model.

To evaluate the environmental benefits and operating efficiency of exit lanes for left-turn intersections, a signal optimization model considering emissions and delays is proposed. Considering the three pollutants of CO, HC, and NOx in cars and buses exhaust, VISSIM simulation software is used to obtain second-by-second data of vehicles. The data is used to calculate the second-by-second Vehicle Specific Power and to calibrate the two types of emission factors for each lane group. Cycle length, main-signal and pre-signal control are regarded as constraints, and minimum emissions and delays are regarded as optimization goals. The bi-objective optimization for exit lanes for left-turn intersections is transformed into a single-objective optimization problem through the linear weighted sum method, and the genetic algorithm is used to solve the optimal signal timing scheme. The results show that, compared with conventional intersections, the design of EFL intersections can not only improve operation efficiency, but also reduce emissions. The optimal signal timing scheme for exit lanes for left-turn intersection can reduce the delay by 6.27% and the total emissions by 7.47%; At the same time, when the proportion of left-turn traffic is 35%~40%, the signal optimization model proposed in this paper has the best optimization performance. Effective in relieving traffic pressure and has good environmental benefits.

Unlike traditional railway vehicles, the particularity of tram right of way determines the multiple and diversity of its accident forms. Based on the analysis of accident data at home and abroad, this paper determines the three road right management modes with the highest accident rate. On this basis, three collision scenarios are designed between a three-module 100% low-floor tram and various types of passenger vehicles. In this paper, we innovatively use PC-Crash crash simulation combined with SPSS quantitative analysis to study the accident characteristics of tram and passenger vehicle collisions under disparate right of way. The results show that the occupant's living space is smaller in 45° side impact under the semi-independent right of way. Under the mixed right of way, when the tram is used as a rear-end vehicle, the collision interface force is more intense. At the same collision speed, the displacement of the vehicle body and the invasion of the living space will be larger under the mixed right of way. Finally, based on the simulation results and causal analysis method, an accurate and highly flexible accident cause analysis framework is formed. From the aspects of single influence and comprehensive influence, the factors affecting the safety of tram operation under diverse road right management modes are analyzed, and tailored suggestions are given to improve the safety of the track system.

The rapid development of new energy vehicles and ride-hailing has injected many new uncertainties into the change of private car ownership. Reasonable and accurate prediction of the development trend of car ownership is helpful for the state to formulate relevant policies and measures. Based on private car ownership in China from 2000 to 2021, statistical data, considering the traditional and non-traditional factors selection such as per capita GDP, residents' consumption level, a total of 12 factors, using Principal Component Analysis (PCA) dimensionality reduction processing, establishing the principal component and the Logistic regression model between private car ownership. Finally, the prediction results of PCA-Logistic regression model were compared with the results obtained by using the cubic exponential smoothing method. The research results showed that the introduction of new factors such as ride-hailing and new energy vehicles, Using PCA-Logistic regression model can improve the prediction accuracy to a certain extent.

The study of multimodal transport path optimization considering carbon policy is of great theoretical and practical significance in the situation of high-quality development. By establishing a multi-objective multimodal transportation path optimization base model considering transportation cost, time cost and carbon emission cost, and a model considering three carbon policies: mandatory carbon emission, carbon tax and carbon trading, and designing an improved simulated annealing genetic algorithm to analyze the cases to compare the multimodal transportation solutions and costs under different carbon policies. The results show that: 1) the improved simulated annealing genetic algorithm can achieve the lowest cost and lowest carbon emission than the traditional genetic algorithm in terms of time search and effect search and can obtain more appropriate transportation solutions for intermodal transport operators. 2) The comparison of carbon policies by example shows that the mandatory carbon emission policy has a strong constraint effect, while the carbon tax and carbon trading have relatively loose constraints. 3) The choice of different carbon policies can achieve the goal of controlling carbon emissions and reducing total costs. The model and algorithm proposed in this paper can provide a theoretical basis for administrative departments and logistics service providers to optimize transportation solutions.

In recent years, online sales of clothing have grown rapidly, return events and return rates have put forward higher standards for the reverse logistics of returns. First of all, this paper sorts out the three traditional logistics modes of clothing e-commerce returns and exchanges. In view of the disadvantages of the existing models, from the perspective of reverse green logistics, a new logistics mode for clothing e-commerce returns and exchanges that integrates outsourcing third-party and joint venture models is proposed. Secondly, build an evaluation index system, take H clothing e-commerce enterprise as an example, use the entropy weight method to calculate the weight, and use the TOPSIS method to analyze the four logistics modes of clothing e-commerce return and exchange goods, so as to help H enterprise choose the optimal mode.

It is of great practical significance to analyze the passenger route decision of Urban Rail Transit under the condition of operation interruption. On the basis of defining the research scope of urban rail transit emergencies, based on AFC data, a recognition method for the spatiotemporal impact scope of rail passenger flow under emergencies is proposed. Taking the passengers affected by emergencies as the research object, this paper explores the components of generalized travel cost of passenger travel path, and builds a generalized travel cost function. Using the path search algorithm matching with the urban rail transit system, the probability of passengers choosing the path is calculated by logit model, so as to better predict the travel path of passengers. Combined with the operation interruption data of Chongqing rail transit, a new train timetable is formulated to calculate the number of passenger flow affected by emergencies. The travel path of the affected passengers is re planned, and the passenger flow is redistributed, so as to ensure the travel of passengers to the maximum extent and reduce the impact of emergencies. It has a certain reference value for emergency management of Urban Rail Transit under emergencies.

At present, the visual-based lane detection algorithm can be divided into feature-based algorithm and model-based algorithm. Each of them has its own advantages and disadvantages in performance. This paper studies these two algorithms and proposes a feature-model fusion method. Firstly, the image is preprocessed by region of interest division, image gray scaling, filtering and denoising, binarization, edge feature extraction and image masking. Then the lane line is fitted based on the linear model. In terms of model parameter solving methods, the advantages and disadvantages of the feature segment extraction based on K-means clustering algorithm and the least square method fitting model are compared, and the experimental verification is carried out. The results show that the extracting feature line segment by K-means clustering method has certain requirements on the results of image processing, and a certain amount of information needs to be retained before the line segment parameters can be obtained by clustering. The least square method is easy to be disturbed by noise and has poor fitting effect on dashed lane lines. In this paper, the combination of the two methods is adopted, that is, the K-means clustering algorithm is used to extract the feature points of lane lines, and then the least square method is used to fit them, which will have a better fitting effect.

With the development and commercialization of smart transportation, the road safety of intelligent connected vehicle has attracted much attention. The test and evaluation report are the solid evidence for verifying the safety of ICV. At present, the digital twin test plays an important role for ICV with low-cost and high efficiency, which has become a research hot pot. However, one of challenge of digital twin test is the consistency between the simulation and real-world. In this paper, a solution of digital twins is put forward to reduce the gap of the consistency. Firstly, the digital twin test platform is built, with the construction of automatic digital twin system. Then, a site test is built with a set of evaluation metrics. Finally, the solution is executed under three typical working conditions, and the result shows that the closed-loop simulation test of digital twin simulation platform is feasible, and the consistency is highly achieved. The research and platform provide pattern for the implementation of ICV digital twin test.

Autonomous driving vehicle will come reality more and more possible along with prosperity of relevant technologies. However, autonomous driving vehicles and artificial driving vehicles will coexist for a long time until full connected and autonomous traffic environment achieved. To modeling lane-changing decision of autonomous driving vehicles, which can be regard as non-cooperative static game under complete information, we establish the game theory-based lane-changing model with combined driving style (GLCD model). Then we conduct a series of simulation experiments to evaluate indicators of the GLCD model, which include the number of lane-changing, the number of accidents, the number of vehicles passes and, the average passing time, compared with the cellular automata model, also compared with the general game theory-based lane-changing model. Results show that the developed model (GLCD model) can improve the efficiency of vehicle driving and ensure stability on the road under the premise of ensuring safety. Furthermore, this model can provide a feasible vehicle lane-change decision in a mixed traffic flow environment in the future.

Ship track prediction is an important embodiment of ship intellectualization. Aiming at the problems of slow convergence speed and falling into local minimum of standard particle swarm optimization BP network algorithm, an improved PSO-BP neural network algorithm is proposed. The learning rate in BP network changes with the cosine of weight in PSO algorithm. At the same time, PSO algorithm based on sine function change and adaptive change of learning factor is used to optimize the inertia weight. For the original AIS data, layda criterion and cubic spline interpolation were used to remove the outliers and repair the missing values of AIS data. Experimental verification with AIS data after processing shows that the improved PSO-BP algorithm improves the prediction accuracy, the prediction accuracy of latitude and longitude increases by 15.3% and 17.2% respectively, while reducing the possibility of falling into the local minimum and improving the convergence speed.

With the improvement of scientific and technological level and the popularization of the 5G network, the distribution mode of "delivery vehicle + drone" has gradually become a new effective distribution method. In order to solve the distribution path optimization problem of the "distribution vehicle + drone" mode of emergency materials under emergencies; In this paper, aiming at the shortest delivery time of "vehicle + drone", by combining the K-Means algorithm, genetic algorithm, and Floyd algorithm, a K-Means optimization genetic algorithm is proposed to solve the model; It is compared and discussed with the individual distribution of vehicles and the joint distribution under the limitation of increased vehicle load; finally, the feasibility of the model and algorithm is verified by numerical example simulation. The experimental results show that the proposed K-Means-based optimal genetic algorithm greatly improves the distribution efficiency of emergency materials in the process and results of the route solution for the "distribution vehicle + drone" distribution mode, compared with the vehicle alone distribution. The path optimization problem provides a scientific basis for decision-making, The actual path that can get the maximum benefit under the balance between the optimal distribution point demand and the maximum load of the vehicle has important research value.

In recent years, tourism in Western Sichuan has just started, coupled with the impact of its own geographical characteristics, the travel research to adapt to the plateau area is still blank. When tourists travel, because there are many scenic spots, the scenic spots that they visit most in a limited time need to plan the path in advance. The current navigation software can only optimize the path between single points, It cannot realize how to choose an optimal path between multiple scenic spots. In view of the above problems, this paper combines the symbolic method of geospatial data provided by AreGIS software, realizes the path optimization problem between multiple scenic spots through ant colony algorithm, and forms a new western Sichuan tourism destination with air travel as the main line and multiple traffic linkage; Ease the inconvenience caused by long and rugged mountain roads in Western Sichuan tourism and improve travel efficiency.

Due to the large number of motor vehicles in urban road networks, serious traffic congestion and high proportion of road carbon emissions, failure to take effective measures to manage travel demand will result in waste of road resources and environmental pollution. Considering the complex variability of the actual road network and the heterogeneous characteristics of road travelers, this paper proposes a dynamic traffic network allocation model in the context of carbon trading. The model is a dual dynamic day-by-day model, which considers both the dynamic changes of road network traffic and the dynamic adjustment and changes of carbon quota consumption rate. After 600 days of dynamic evolution, the road network reaches the system optimal state while achieving user equilibrium. Meanwhile, the carbon emission reduction on the road transport network before and after the implementation of carbon trading scheme is compared and analyzed, and the overall carbon emission is reduced by 9.23%. This provides a scientific theoretical basis and a feasible solution for the carbon trading scheme in urban transportation demand management and guiding low-carbon travel.

Aiming at the problems such as the lack of consideration of space and other factors in the traditional key intersection identification model and the lack of objectivity in the weight distribution of intersection evaluation indicators in the urban traffic road network, an improved CRITIC (Criteria Importance Though Intercrieria Correlation)-independent weight method based on fusion is proposed. The improved TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method. Aiming at the defects of the CRITIC method, the Theil index and the grey correlation degree are introduced to improve the CRITIC method; the independent weight method is used to eliminate the collinearity between the evaluation indexes and assign the weights of the evaluation indexes; in order to overcome the defects of using Euclidean distance as the distance measurement in TOPSIS , the weighted Mahalanobis distance is introduced to replace the Euclidean distance, and the key intersection identification is realized according to the closeness. The simulation results show that compared with the traditional key intersection identification model, the model proposed in this study can identify key intersections more accurately and comprehensively, which fully verifies the validity and accuracy of the model proposed in this study.

The speed tracking control system of maglev trains has the characteristics of complexity, instability, and multiple disturbances. The traditional speed tracking control algorithm has low tracking accuracy, large tracking errors and easy external interference, so it will increase train energy consumption and reduce passengers’ riding comfort. In order to improve the deficiencies in the existing control algorithms, the disturbance rejection PID (DR-PID) algorithm based on fuzzy control (F-DR-PID) is proposed. The DR-PID controller increases the anti-disturbance capability and tracking accuracy of the control system, and the fuzzy control algorithm adjusts the three weights of the DR-PID in real time. To verify the effectiveness of the F-DR-PID control algorithm, this paper is compared and analyzed with PID, F-PID and DR-PID control algorithms under the same experimental conditions. The results show that the F-DR-PID control algorithm has better tracking accuracy and passengers’ riding comfort and reduces train energy consumption and parking error.

Bridge influence lines play an important role in damage identification and condition assessment research. The existing research on influence lines mostly focus on highway bridges. In contrast, rail vehicles have a large number of axles and fast running speeds, which increases the difficulty of influence lines acquisition and extraction. At first a high-accuracy extraction method for the influence lines of track bridges based on regularization is firstly established; following that, the bridge response data is obtained by the finite element model and the validity of the extraction method of the influence lines is verified. On this basis, the influence of equipment parameters such as (sampling frequency, sampling accuracy) on the results is studied. The results show that the influence line calculation method based on regularization can be well applied to the identification and extraction of influence lines of track bridges. In order to ensure the extraction accuracy of the influence lines, the sampling frequency of strain and deflection is not lower than 25Hz, and the deflection and strain sampling accuracy is higher than 0.05mm and 1με , respectively.

The study of short-term passenger flow of rail transit is based on the passenger flow data, usually taking the station as the smallest unit and can only grasp the passenger flow law between stations macroscopically. In order to study the microscopic passenger flow law in different scenes within the station, it is necessary to obtain the passenger flow sequence of the corresponding scene. Therefore, we propose an end-to-end refined short-term passenger flow identification model based on computer vision named PAX-Detect. The structure of the model are as follows: 1). Take pictures of the scene in the station and manually mark the passenger's head; 2). Using annotated datasets to train the YOLOv5 algorithm and pruning optimization;3). YOLOv5 and Deep SORT algorithm are used to detect and track passengers in the video, and the statistical results of the number of passengers are output in real-time. The experiment is carried out on the video data of the escalator entrance of a subway station in Beijing. The experimental results show that the accuracy of the real-time statistical algorithm for passenger numbers reaches 99.4% in the test scenario. The proposed model can identify the microscopic passenger flow in the scene of the rail transit station in real-time and has a certain application prospect.

Due to the different purposes of passenger travel, the passenger flow has high instability in time. When designing the train diagram, it should not only meet the needs of passenger travel, but also highlight the carrying capacity during peak hours and holidays. Through the analysis of the temporal and spatial distribution characteristics of passenger flow and the characteristics of train diagram, the paper describes the balance scientifically. Through the study of the existing literature and the characteristics of passenger flow, this paper mainly establishes the equilibrium index system from three aspects: train, station and passenger flow matching degree. The fuzzy comprehensive evaluation method is selected to calculate the equilibrium value of the train diagram and evaluate its equilibrium.

With the continuous acceleration of China's new urbanization process and the implementation of the rural revitalization strategy, the links and exchanges between urban and rural areas are increasingly close and extensive, and the integrated development of urban and rural road passenger transport has become an inevitable trend. As the core link connecting urban and rural development and serving residents' travel, urban and rural public transport is an important support for the integrated development of urban and rural economy and society and is the key to rural revitalization and development. Based on the analysis of the influencing factors of urban and rural public transport evaluation, the evaluation index system of urban and rural public transport integration is constructed from four aspects: urban and rural public transport infrastructure, transport service, management level, and the guarantee of social and economic development for the development of urban and rural public transport integration. The TOPSIS evaluation model is used to determine the weight value of the indexes, and the dimensionless treatment of the indexes. The evaluation indexes are calculated and analyzed.

Short-term passenger flow forecasting plays an important role in better traffic management and organization. Emerging deep learning models offer a great way to improve short-term forecast accuracy. However, a large number of existing forecasting models are very complex in their model structure because they combine various neural network layers to improve the accuracy of the models. Therefore, it is necessary to reduce the complexity of the models while ensuring their accuracy. Finally, we propose a Graph-GAN model based on deep learning with a simple structure and high prediction accuracy to predict short-term passenger flows in urban rail networks. Graph-GAN consists of two main components: (1) a graph convolutional network (GCN) for extracting topological information of the metro network; and (2) a generative adversarial network (GAN) for predicting passenger flow, where the generator and discriminator in the GAN consist of only simple fully connected neural networks. Graph-GAN was tested on real Beijing subway datasets in 2016 and 2018. The prediction performance of Graph-GAN is compared with several state-of-the-art models to illustrate the superiority of the model.

In order to investigate the traffic dynamics in Runyang Bridge, we conduct some microscopic simulations by SUMO. Two different cases are considered, including case one in which the traffic flow rates are changed, and case two in which the accident occurs, and one lane is temporarily closed. The time series of many parameters, including velocities, occupancies and delays are presented and discussed. By the comparisons between different lanes, we find all the recovery time of three lanes in case one is much longer than that in case two. The differences between three lanes are mainly determined by the default rules of lane-changing models in SUMO. All these results can help to better control the traffic flow on this bridge.

The analysis of factors influencing the severity of road traffic accidents based on accident data is the basis for developing traffic safety countermeasures. To study the factors influencing the severity of motor vehicle road traffic accidents, 2,187 accident cases with different severity levels were analyzed and a binary logistics regression model was established. A total of 14 independent variables, including weather, time, road characteristics, temperature, humidity, air pressure, and wind speed, were selected as the dependent variables for the analysis, and the results showed that time, road characteristics, and temperature all had significant effects on the severity of the accident consequences, while humidity and the presence of stop signs near the accident site had no significant effects on the severity of the accident. Based on this, suggestions for measures to reduce the severity of road traffic accidents were made.

The comprehensive transportation hub of Dalian North Railway Station is located in the square on the north side of Dalian North High-speed Railway Station. The foundation pit support design adopts Lizheng deep foundation pit support software, and a typical cross-section diagram of the support system is obtained. In order to verify and optimize the design scheme, the finite element numerical simulation method is used to carry out a detailed analysis of each construction condition of the foundation pit support, and the numerical simulation results are compared with the actual monitoring results on site. The conclusion shows that the finite element numerical simulation can directly reflect the lateral displacement of the foundation pit support and the ground settlement around the foundation pit under various construction conditions, which can verify and supplement the design scheme of the deep foundation pit support software.

The number and scale of highway tunnels in Xinjiang are growing day by day, but the newly built emergency resources are far below the national average. Once a traffic accident occurs in multiple highway tunnels, the resources provided by the emergency resource points may not be able to meet the emergency resource needs of all accident points at the same time, resulting in further loss of life and property. Through the research on the priority of traffic accident rescue in multiple highway tunnels, a multi-objective planning model for emergency resource scheduling of highway tunnels is established, which aims at the shortest delay time of resource scheduling and the highest satisfaction of emergency resources. The priority coefficient is introduced into the mathematical model, and the optimal solution of the mathematical model is found using LINGO software, so as to obtain the optimal emergency resource scheduling scheme. The results show that the model can solve the emergency resource scheduling problem. It does not provide reference for emergency decision makers.

Maritime Autonomous Surface Ships are increasingly becoming a topic of discussion due to the continuous improvement of ship’s intelligence levels. To meet the safety and economic requirements in a ship’s route design, a multi-objective intelligent hybrid algorithm based on the genetic algorithm and the greedy algorithm was proposed in this work. The marine environment model was gridded to a dynamic and static no-voyage zone. The initial continuous and random routes were generated by the greedy algorithm. The objective function, designed according to the multi-objective and multi-constraint, was solved by the genetic algorithm to generate the optimal route and corresponding speed distribution. The experimental results show that this method can ensure the safety of the ship and flexibly meet the needs of different decision-makers.

An enhanced ant colony method for omnidirectional mobile vehicle path planning is presented in this paper. The enhanced ant colony algorithm seeks a suitable path that connects the starting and ending sites of the environment while avoiding hazards. The path planning issue, which has been improved to take into consideration the properties of the omnidirectional mobile vehicle, is solved using the ant colony algorithm. Additionally, in the updated approach, the path search is greatly aided by the non-uniform distribution of the initial pheromone and the selection technique with the direction. In order to avoid repetitive searches and reduce the effect of the ant population on the algorithm's performance, the coverage and updating strategy of pheromone is introduced. Furthermore, segmentation and pheromone evaporation coefficient adjustments may be beneficial in achieving a compromise between convergence speed and search capability. This paper's strong mathematical derivation theoretically supports the improved ant colony algorithm, and some numerical simulations are also given to show the effectiveness of the theoretical findings.

Urban metro is developing in the direction of the network. With the increasing scale, dealing with the sudden accident of the metro network has brought significant challenges to the relevant departments. When the metro is disrupted, it is necessary to evacuate the passengers. Emergency bus bridging is an essential means to evacuate the passengers. Notably, the core of efficient emergency bus bridging strategy is how to plan the location of the emergency bus reserve bases. Hence, this paper aims to establish the site selection model based on the vulnerability of the complex metro network, and rationally lay out the source of the emergency bridging bus in the case of sudden disruption of the complex metro network. Firstly, the space L topology model of the metro network is established, and the performance indicators of the network are analyzed by grey relational analysis (GRA), to identify the key stations. Secondly, we use a reverse covering location model to optimize the bridging response delay time and the number of reserved buses. Taking Tianjin metro network as a case study scenario, the research results of this paper are compared with those of other scholars. By comparison, the location results are better in coverage, bridging response delay time and the number of reserved buses. Therefore, the research method of this paper provides new ideas and new methods for the location of the emergency bridge bus reserve base.

An in-depth and comprehensive study of the spatial spillover effects of transportation infrastructure will help to better understand the factors of uneven development among different regions in China, so that it can play a better role in the process of China's urbanization. Using multiple indicator data of 30 provinces in China from 2001 to 2019, and by constructing a spatial econometric model, this paper empirically measures the spatial spillover effect of China's transportation infrastructure (highway, railways) on regional urbanization development. The study found that the spatial spillover effect of transportation infrastructure on urbanization is very significant, and the roles of different types of transportation infrastructure in the process of urbanization in China are different. The construction of highways and railways will directly promote regional urbanization. At the same time, because of its network and external characteristics, the impact of transportation infrastructure construction on the urbanization of surrounding areas is also worth considering.

Jiangsu is located in the core of the Yangtze River Delta, with the dense water network and developed shipping. At the same time, the number of bridges crossing the waterway is increasing, and the risk of collision between ships and bridges is increasing. Therefore, this project carries out the development and research of the intelligent bridge-ship collision avoidance system. We intend to effectively prevent the occurrence of collision accidents through developing the water level monitoring system, over-height warning system and yaw warning system. This is good for bridge safety and ship safety.

As the core part of intelligent transportation system, traffic flow prediction is vulnerable to the influence of original signal noise, modal aliasing and other factors, and most of the current traffic flow prediction models cannot take into account the various characteristics of traffic flow, so their stability is poor. In order to improve the accuracy and stability of short-term traffic flow prediction, a combined prediction model based on graph attention network, variational modal decomposition and lightweight gradient elevator is proposed. First, the model uses the mutual information entropy algorithm to process the spatial correlation of road segments and filters out the historical data of the road segments with the highest spatial correlation with the target road segments. The spatial structure between the filtered data and the road segments is used as the input of the graph attention network to obtain the spatial features contained in the data. At the same time, the filtered data is decomposed by variational mode, the arrangement entropy of each component is calculated, the validity of the component is verified, the invalid component is de noised and decomposed again, and the spatial features obtained before are combined with the effective component to form a new time series. Finally, each new time series is input into the LightGBM prediction model as an input, and the predicted values of all new series are superimposed to form the final short-term traffic flow prediction result. The pems04 data set was used as experimental data for verification. The results show that compared with the comparison model, the MAE of GAT-VMD-LightGBM prediction model is reduced by 47.07% and RMSE is reduced by 52.5%, which can prove that the prediction performance of this model is better.

In view of the complex constraints of ships choosing entry and exit channels, which are likely to cause ship congestion and low entry efficiency, the support vector machine algorithm is used to establish a classification model suitable for ship navigation channels to realize decision-making management and control of ships choosing entry and exit channels. By deleting the missing values and irrelevant features of AIS data, eight related factors related to ship size and sailing state were selected as input variables of support vector machine, and a two-classification model of waterway based on SVM was established. Using precision and recall as indicators to evaluate model performance and comparing the results of three machine learning classification algorithms: random forest, logistic regression, and support vector machine, it is found that the support vector machine model has the highest accuracy, reaching 92%, and the AUC is 94. %. The research results show that the ships navigable in the two channels have obvious differences, and the SVM model can better select the seaworthy channel.

Virtual coupling is an innovative train control mode, which enables trains to track at very small headway and significantly improve the transport capacity. However, such small headways are challenges to safety and control system. To ensure the safe operation of virtual coupling and reduce the risk of collision accidents, this research proposed a refined virtual coupling train safe distance model and an improved consensus control algorithm. Firstly, the virtual coupling emergency braking process is analyzed while considering the processing of information transferring and on-board equipment handling in the scene. A refined safe distance model with higher safety is proposed based on the analysis. Secondly, an improved multi-agent information consensus distance control algorithm for virtual coupling is proposed. The improvement makes the algorithm consider both the convergence speed and coupling stability effectively, is adaptive for various virtual coupling scenes. Thirdly, real train data and rail line data are imported, and train dynamic model is established to verify the convergence ability and adaptability of the proposed algorithm by simulation.

Differing acceleration, inclination and deflection angles of the car body during the race bring different visual impact and physical experience to the driver. Unlike ordinary car driving, race car driving requires humans to have stronger physical fitness to control a high-speed racing car and resist the stress on the body during high-speed motion. Fortunately, modern technology can resist the pressure of part of the driver's body. However, in earlier racing cars, there was no complex mechanical assistance, and the driver also needed to master better body balance to assist the stability of the body. However, as technology has improved, the driving experience of racing cars has changed from that of early racing cars in history. As autonomous driving plays an increasingly important role in our lives today and into the future, this research explores the relationships between human drivers and their vehicles as they are mediated through advancing technologies. What kind of experience will human beings lose by assisting human driving with advanced technology? How will human engagement in the driving of racing cars develop after borrowing automated intelligent technology in the future?

In the era of rapid development of intelligent transport construction, predicting traffic flow is a crucial aspect of managing and operating contemporary transportation networks. However, traffic prediction tasks have complex spatio-temporal connections. On the one hand, the temporal characteristics of different time scales affect the accurate prediction of traffic flows, and on the other hand, the potential spatial relationships between road traffic cannot be reasonably expressed by the current predefined graph structure. In order to anticipate traffic flow, this article suggests a model (Dynamic attention and Multi gated time convolution Network) based on dynamic attention and multiple gated temporal convolution. The model introduces a multi-gated time convolution layer to extract temporal features of different time ranges and extracts potential spatial relationships between traffic nodes through a multi-headed dynamic attention mechanism to dynamically acquire spatio-temporal variations. Unlike existing models, the model does not require a priori road knowledge of the traffic map, but instead adjusts the inter-node relationships through multi-head dynamic attention. At the same time, the convolution kernel's size is expanded by the model and the gating output of the temporal convolution on top of the original temporal gating to improve the accurate prediction of different temporal pattern tasks. The model forecasts greater properly than the contrasted baseline methodologies, according to analytical outcomes.

With the rapid development of the city, urban rail transit has also entered the fast lane of development. Many scholars have studied the deformation of foundation pit excavation without adjacent bridge piles. However, with more and more engineering construction adjacent to viaduct piles, the foundation pit engineering is also developing in the direction of 'deep, large, near, difficult and dangerous'. It is becoming more and more important to study the deformation law of foundation pit adjacent to bridge piles. As a powerful analysis tool, finite element software has been widely used in practical engineering. This paper takes a practical project in Jinan as the background and compares the numerical simulation with the measured data to verify the reliability of the numerical simulation. It is found that the difference between the surface settlement affected by the surrounding bridge pile and the maximum cumulative settlement value without the influence of the bridge pile can reach three times, which also reflects the existence of the bridge pile to a certain extent on the surface settlement. Under the influence of no bridge pile, the lateral deformation 'peak point' of the retaining structure is obvious, while the bridge pile exists on the side of the active zone, which will have a great influence on the deformation of the retaining structure, mainly in the excavation direction. The deformation is uniform, and the 'peak point' becomes not obvious. Due to the existence of bridge piles in the active area, it has a great influence on the deformation of the retaining structure, which greatly weakens the original 'peak point', and it can be seen that the retaining effect of the bridge pile is very obvious. By comparing with the finite element software, it is found that the difference between the simulation results and the measured data is small, which has a strong reference and can provide reference for similar engineering design and evaluation.

In order to solve the problems of ship demurrage and berth resource waste caused by ship traffic organization and berth allocation methods in some two-way navigation ports, this paper integrates and optimizes ship traffic organization and berth allocation in two-way navigation ports, specifically considering ships attributes, berth status, port navigation rules and ship traffic conditions, a mixed integer linear programming model is established, and a diploid genetic algorithm is designed to solve the model. Finally, an example is used to test the model and algorithm. The results show that the proposed model and algorithm can provide a feasible plan for ship entry and exit organization and berth allocation under the condition of ensuring safety, and effectively improve the efficiency of ship entry and exit.

The development of intelligent transportation is of great significance to improving the effectiveness and safety of traffic. A new two-lane lattice hydrodynamics model (LHM) is proposed by simultaneously considering the effects of lane-changing and mixed traffic of connected and non-connected vehicles (CNVs). Using linear analysis, the stability conditions are derived, which indicates that lane-changing has a positive impact on traffic stability. In addition, the numerical simulation results provide support for theoretical analysis and confirm the correctness.

In this paper, a fully automatic algorithm to detect rebar in reinforced concrete from Ground Penetrating Radar (GPR) data is developed and validated. GPR is a widely used electromagnetic test method in bridge engineering, which is efficient, non-destructive, and sensitive to the dielectric difference. The exact rebar locations can be known from the surveyed GPR data of bridge decks manually, which is time-consuming. Therefore, an automatic, accurate and robust algorithm is necessary to engineering applications. The automatic algorithm proposed in the paper is a pattern recognition method. First, a template of a rebar hyperbola in a GRP image is selected; second, a rebar is detected from the local minimum points in the map of Sum of Square Difference (SSD); third, an output file is created and saved, including the geographical location of each detect rebar. Finally, the proposed method is validated from field tests in a reinforced concrete bridge, and the detection accuracy is 91.1%, which is very promising.