Paper
22 December 2022 Automated scenario generation and iterative regression testing method for autonomous driving systems
Jianli Duan, Rui Wang, Shulian Zhao, Mengxia Hu, Hua Chen, Chuzhao Li, Hao Wu, Pengfei Bai, Yi Wang, Keqiang Li
Author Affiliations +
Proceedings Volume 12460, International Conference on Smart Transportation and City Engineering (STCE 2022); 124603A (2022) https://doi.org/10.1117/12.2657984
Event: International Conference on Smart Transportation and City Engineering (STCE 2022), 2022, Chongqing, China
Abstract
In this paper, we propose a new automatic test and evaluation method that can be used for autonomous driving systems in virtual simulation test. Aiming at the problems that the existing automated test method cannot guarantee coverage and validity of the test scenarios, and evaluation lacks the consideration of the complete development life cycle of the systems, we firstly introduce a new scenarios generation method that can generate scenarios with higher overall effectivity on the premise of ensuring coverage. Then, an integrated test platform is constructed, in which the components can be automatically invoked by test scripts. Finally, the automated iterative regression testing is used to ensure the effectiveness of the whole development and test process. The application and verification of a level three (L3) Traffic Jam Pilot (TJP) system is carried out on the above-stated method. The result shows that the proposed method can effectively detect system defects and significantly improve test efficiency.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jianli Duan, Rui Wang, Shulian Zhao, Mengxia Hu, Hua Chen, Chuzhao Li, Hao Wu, Pengfei Bai, Yi Wang, and Keqiang Li "Automated scenario generation and iterative regression testing method for autonomous driving systems", Proc. SPIE 12460, International Conference on Smart Transportation and City Engineering (STCE 2022), 124603A (22 December 2022); https://doi.org/10.1117/12.2657984
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KEYWORDS
Testing and analysis

Data acquisition

Roads

Data modeling

Monte Carlo methods

Sensors

Systems modeling

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