Research on the framework of automatic evaluation system for test results of high-level automated driving system

Shenyan Li; Jie Zheng; Xiong Hu; Wei Liao; Xuecong Ding

doi:10.1117/12.2690018

7 September 2023 Research on the framework of automatic evaluation system for test results of high-level automated driving system

Shenyan Li, Jie Zheng, Xiong Hu, Wei Liao, Xuecong Ding

Author Affiliations +

Proceedings Volume 12790, Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023); 127900U (2023) https://doi.org/10.1117/12.2690018
Event: 8th International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023), 2023, Hangzhou, China

Abstract

With the gradual realization of high-level automatic driving vehicles, the previous testing and evaluation methods for Advanced Driver Assistance Systems(ADAS) functions are gradually unable to meet the requirements for testing and evaluation of high-level ADS. In order to effectively test and evaluate the auto drive system, a system framework is proposed, which consists of a hardware system for data acquisition and pre-processing and a software system for data slicing, identification and evaluation. The system is a modular framework, which can be used to build system adaptability for different test requirements of hardware-in-loop, vehicle-in-loop and open road test. The core of the system is firstly to extract Region of Interesting(ROI) data segment from real-time test data stream based on Responsibility-Sensitive Safety(RSS) model, secondly perform scenario recognition and classification processing on this data segment，thirdly index the corresponding evaluation criteria from the scene knowledge base to evaluate each operating parameter in this data segment, Finally, a comprehensive evaluation is conducted by weighting the three levels of "operating parameters", "scenario" and "performance" separately. This study proposes a novel and feasible technical framework for the efficient automated evaluation of high-level autonomous driving systems, which can serve as a reference for related subsequent research.

Citation Download Citation

Shenyan Li, Jie Zheng, Xiong Hu, Wei Liao, and Xuecong Ding "Research on the framework of automatic evaluation system for test results of high-level automated driving system", Proc. SPIE 12790, Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023), 127900U (7 September 2023); https://doi.org/10.1117/12.2690018

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KEYWORDS

Advanced distributed simulations

Data modeling

Data transmission

Safety

Data processing

Autonomous driving

Performance modeling

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