基于行车安全场理论的预期功能安全场景风险评估  

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

作　　者：陈浩[1,2] 王红 李维汉[1,2] 白先旭[1,2] 陈炯 李楚照[3,5] 石琴 孙骏 Chen Hao;Wang Hong;Li Weihan;Bai Xianxu;Chen Jiong;Li Chuzhao;Shi Qin;Sun Jun(Hefei University of Technology,Engineering Research Center for Intelligent Transportation and Cooperative Vehicle-Infrastructure of Anhui Province,Hefei 230009;Department of Vehicle Engineering,Hefei University of Technology,Laboratory for Adaptive Structures and Intelligent Systems(LASIS),Hefei 230009;School of Vehicle and Mobility,Tsinghua University,Beijing 100084;NIO Co.,Ltd.,Shanghai 201804;State Key Laboratory of Vehicle NVH and Safety Technology,China Automotive Engineering Research Institute Company,Ltd.,Chongqing 401122)

机构地区：[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

出　　处：《汽车工程》2022年第11期1636-1646,共11页Automotive Engineering

基　　金：安徽省新能源汽车暨智能网联汽车创新工程项目(JZ2021AFKJ00002)资助。

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。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.

关 键 词：预期功能安全 场景 风险评估 行车安全场 参数标定 

分 类 号：U463.6[机械工程—车辆工程]