In response to the inadequacy of timing control methods in adapting to the random changes in traffic flow at intersections and the neglect of the impact of intelligent connected new energy vehicles (ICNEVs), we investigate the effectiveness of a full induction control logic for intersections considering ICNEVs. Firstly, vehicle headway and queue detectors are deployed at each approach of the intersection to monitor real-time traffic conditions. Subsequently, a full induction control logic and corresponding parameters are established based on the clearance and queue status of vehicles at the intersection. The study then considers the influence of different permeability of ICNEVs on the full induction control logic. Finally, a comparison is made among the current state scheme, timed optimization, and full induction control schemes using VISSIM traffic simulation software. Additionally, the study further analyzes the effects of intersection full induction control under different permeability of ICNEVs, thereby validating the effectiveness of the research.
The calibration of driving behavior parameters in the traffic simulation model for pavement formed by different aggregate mixtures is of crucial significance in ensuring the effectiveness of traffic simulation evaluation results for various asphalt pavement. This study first examines different aggregate asphalt mixtures as asphalt pavement materials through experiments. Subsequently, using queue length as the evaluation indicator, a sensitivity analysis is conducted based on VISSIM traffic simulation software to identify the set of sensitive parameter set data among the driving behavior parameters for asphalt pavement under study. The study then uses the traffic simulation model to determine the value of the driving behavior parameter set that result in the smallest error rate between simulated queue length and measured queue length on asphalt pavement. This completes the calibration of driving behavior parameters for the studied asphalt pavement in the traffic simulation model. Finally, the proposed method is validated through real-world case studies. This study proposes a feasible parameter calibration method for traffic simulation scenarios of asphalt pavement formed by different gradations of asphalt mixtures. At the same time, it establishes the foundation for optimizing and controlling intersection signals for corresponding asphalt pavement.
With the rapid development of China's economy, the development speed and scale of transportation engineering have also expanded rapidly. But the problem of environmental pollution problems have also gradually emerged, and the use of environmental protection materials has become an inevitable trend of green transportation development. This paper puts forward the traffic optimization method at five-way intersection based on green building materials and signal processing. Firstly, the green and environment protection hot-melt reflective marking paint and color asphalt concrete pavement materials are used to construct the travel space of motor vehicles, non-motor vehicles and pedestrians at five-way intersection. Then, on this basis, the phase design method based on clipping method and the corresponding signal timing method are proposed to optimize the traffic flow travel time at five-way intersection. Finally, the evaluation and analysis is done by the VISSIM traffic simulation software, the results show that this method based on green building materials effectively defines the travel space of five-way intersection. On this premise, the traffic efficiency is further improved through signal processing optimization technology, which effectively reduces the number of conflict point at the five-way intersection and provides a basis for the research on the optimal control of deformed intersections based on green building materials and signal processing.
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