汽车工程

汽车工程 ›› 2022, Vol. 44 ›› Issue (11): 1636-1646.doi: 10.19562/j.chinasae.qcgc.2022.11.002

所属专题： 智能网联汽车技术专题-感知&HMI&测评2022年

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基于行车安全场理论的预期功能安全场景风险评估

陈浩1,2,王红3,李维汉1,2,白先旭1,2(),陈炯4,李楚照3,5,石琴1,2,孙骏1,2   

  1. 1.合肥工业大学，安徽省智慧交通车路协同工程研究中心，合肥 　230009
    2.合肥工业大学汽车与交通工程学院，车辆工程系自适应结构与智能系统实验室，合肥 　230009
    3.清华大学车辆与运载学院，北京 　100084
    4.上海蔚来汽车有限公司，上海 　201804
    5.中国汽车工程研究院股份有限公司汽车噪声振动和安全技术国家重点实验室，重庆 　401122
  • 收稿日期:2022-05-06 修回日期:2022-06-16 出版日期:2022-11-25 发布日期:2022-11-19
  • 通讯作者: 白先旭 E-mail:bai@hfut.edu.cn
  • 基金资助:
    安徽省新能源汽车暨智能网联汽车创新工程项目(JZ2021AFKJ00002)

Risk Assessment of Safety of the Intended Functionality Scenes Based on Driving Safety Field Theory

Hao Chen1,2,Hong Wang3,Weihan Li1,2,Xianxu Bai1,2(),Jiong Chen4,Chuzhao Li3,5,Qin Shi1,2,Jun Sun1,2   

  1. 1.Hefei University of Technology，Engineering Research Center for Intelligent Transportation and Cooperative Vehicle-Infrastructure of Anhui Province，Hefei 　230009
    2.Department of Vehicle Engineering，Hefei University of Technology，Laboratory for Adaptive Structures and Intelligent Systems （LASIS），Hefei 　230009
    3.School of Vehicle and Mobility，Tsinghua University，Beijing 　100084
    4.NIO Co. ，Ltd. ，Shanghai 　201804
    5.State Key Laboratory of Vehicle NVH and Safety Technology，China Automotive Engineering Research Institute Company，Ltd. ，Chongqing 　401122
  • Received:2022-05-06 Revised:2022-06-16 Online:2022-11-25 Published:2022-11-19
  • Contact: Xianxu Bai E-mail:bai@hfut.edu.cn

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摘要：

面向自动驾驶车辆预期功能安全（SOTIF）场景的不同测试标定要求和侧重，本文提出了一种基于行车安全场（DSF）理论的SOTIF场景风险评估方法。首先，利用DSF对场景的各层元素进行风险量化，从而实现风险的集成计算。通过分析SOTIF场景的定义与架构和DSF模型的参数，证明该模型满足SOTIF场景的风险评估要求。接着将所提方法应用于3类车辆运行场景的划分中，分别是已知安全、已知不安全和未知安全/不安全。为实现场景的划分，将DSF理论中不同的驾驶状态与SOTIF中车辆的运行场景进行匹配。最后，进行了封闭场地和开放道路的测试。一方面将相对驾驶安全系数指标RDSI与碰撞时间TTC指标作对比，验证了RDSI可更准确、敏感地评估行车风险。另一方面，证明了所提方法可有效地实现场景划分。

关键词: 预期功能安全, 场景, 风险评估, 行车安全场, 参数标定

Abstract:

Facing different test calibration requirements and emphases of the safety of the intended functionality （SOTIF） scene for autonomous vehicles （AVs）， a risk assessment method of SOTIF scene based on driving safety field （DSF） theory is proposed in this paper. Firstly， DSF is utilized to conduct risk quantification on each layer of scene elements， and hence to achieve integrated risk calculation. The definition， architecture of SOTIF scene， and the parameters of DSF model are analyzed to prove that DSF model meets the risk assessment requirements of SOTIF scene. Then， the method proposed is applied to divide the vehicle operation scenes into three types： known safe， known unsafe and unknown safe/unsafe. For realizing scene division， different driving states in DSF theory are matched with the operational scenes of vehicles in SOTIF. Finally， closed field tests and road tests are carried out. On one hand， the relative driving safety indicator （RDSI） is compared with time-to-collision （TTC） to verify that RDSI can more accurately and sensitively assess the driving risk. On the other hand， it is proved that the method proposed can effectively fulfill scene division.

Key words: SOTIF, scenes, risk assessment, driving safety field, parameter calibration