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    Combining Reachability Analysis and Importance Sampling for Accelerated Evaluation of Highway Automated Vehicles at Pedestrian Crossing

    Source: ASME Letters in Dynamic Systems and Control:;2021:;volume( 001 ):;issue: 001::page 011017-1
    Author:
    Wang, Xinpeng
    ,
    Peng, Huei
    ,
    Zhao, Ding
    DOI: 10.1115/1.4046610
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Highly automated vehicles (HAVs) must be rigorously evaluated before they are deployed on public roads. An accelerated evaluation framework was proposed in the literature to test HAVs more efficiently. However, running such a test is challenging due to the fact that some of the generated test cases may be not feasible or realistic. This paper proposes an improved accelerated evaluation framework that combines importance sampling with reachability analysis, so that the feasibility of all test cases are guaranteed, and the risk levels of cases are controlled. The performance of the proposed framework is studied using the unprotected pedestrian crossing scenario. A total od 2689 pedestrian–vehicle interaction events are extracted from open-source video data, and a truncated Gaussian mixture model (TGMM) is developed to describe the pedestrian–vehicle interaction. Simulation results show that the proposed method achieves unbiased crash rate estimation in an accelerated fashion while achieving the aforementioned benefits for test case generation (feasible and at controlled risk level).
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      Combining Reachability Analysis and Importance Sampling for Accelerated Evaluation of Highway Automated Vehicles at Pedestrian Crossing

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4275914
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    contributor authorWang, Xinpeng
    contributor authorPeng, Huei
    contributor authorZhao, Ding
    date accessioned2022-02-04T23:00:57Z
    date available2022-02-04T23:00:57Z
    date copyright1/1/2021 12:00:00 AM
    date issued2021
    identifier issn2689-6117
    identifier otheraldsc_1_1_011017.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4275914
    description abstractHighly automated vehicles (HAVs) must be rigorously evaluated before they are deployed on public roads. An accelerated evaluation framework was proposed in the literature to test HAVs more efficiently. However, running such a test is challenging due to the fact that some of the generated test cases may be not feasible or realistic. This paper proposes an improved accelerated evaluation framework that combines importance sampling with reachability analysis, so that the feasibility of all test cases are guaranteed, and the risk levels of cases are controlled. The performance of the proposed framework is studied using the unprotected pedestrian crossing scenario. A total od 2689 pedestrian–vehicle interaction events are extracted from open-source video data, and a truncated Gaussian mixture model (TGMM) is developed to describe the pedestrian–vehicle interaction. Simulation results show that the proposed method achieves unbiased crash rate estimation in an accelerated fashion while achieving the aforementioned benefits for test case generation (feasible and at controlled risk level).
    publisherThe American Society of Mechanical Engineers (ASME)
    titleCombining Reachability Analysis and Importance Sampling for Accelerated Evaluation of Highway Automated Vehicles at Pedestrian Crossing
    typeJournal Paper
    journal volume1
    journal issue1
    journal titleASME Letters in Dynamic Systems and Control
    identifier doi10.1115/1.4046610
    journal fristpage011017-1
    journal lastpage011017-7
    page7
    treeASME Letters in Dynamic Systems and Control:;2021:;volume( 001 ):;issue: 001
    contenttypeFulltext
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