With the advancement in automatic driving technology, testing methods-such as road test for conventional automatic is difficult to verify the safety and reliability of automatic driving vehicles. Virtual testing method has become an important mean due to the technical superiority of test efficiency and time consumption. This paper selects a highway traffic accident from China In-Depth Accident Study (CIDAS) database and analyzes the accident cause. Builds the traffic accident scenario in virtual simulation software-CarMaker, including actual road environment information, ego vehicle, and other traffic participants maneuver and so on; then take a hardware-in-the-loop(HIL) testing, and the ACC and AEB control system based on radar simulator is used to test the ability of the ADAS system of respond to traffic accident scenario. Testing result shows that the ADAS system can reduce the likelihood of collision in some way. Testing process verifies the feasibility of virtual test that verify the functionality of the ADAS system, which will provide an method to large-scale virtual simulation test for AD and study test scenario.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Virtual Validation Method for Automated Driving Vehicles Based on Traffic Accident


    Contributors:
    Zhang, Shan (author) / Shi, Juan (author) / Guo, Kuiyuan (author) / Wang, Yu (author)

    Conference:

    20th COTA International Conference of Transportation Professionals ; 2020 ; Xi’an, China (Conference Cancelled)


    Published in:

    CICTP 2020 ; 365-375


    Publication date :

    2020-08-12




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Virtual Validation Method for Automated Driving Vehicles Based on Traffic Accident

    Zhang, Shan / Shi, Juan / Guo, Kuiyuan et al. | TIBKAT | 2020


    Near-future traffic evaluation based navigation for automated driving vehicles

    Lin, Kuen-Wey / Li, Yih-Lang / Hashimoto, Masanori | IEEE | 2017


    Virtual Traffic Simulator for Connected and Automated Vehicles

    Chang, ChenFang / Wu, Hai / Zhao, Junfeng | SAE Technical Papers | 2019


    Near-Future Traffic Evaluation Based Navigation for Automated Driving Vehicles

    Lin, Kuen-Wey / Li, Yih-Lang / Hashimoto, Masanori | British Library Conference Proceedings | 2017


    Virtual Traffic Simulator for Connected and Automated Vehicles

    Zhao, Junfeng / Wu, Hai / Chang, ChenFang | British Library Conference Proceedings | 2019