智能网联汽车预期功能安全风险评估3σ接受准则

doi:10.3901/JME.2024.10.182

机械工程学报 ›› 2024, Vol. 60 ›› Issue (10): 182-191.doi: 10.3901/JME.2024.10.182

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智能网联汽车预期功能安全风险评估3σ接受准则

白先旭^1,2,3, 潘宇翔^1,2,3, 陈浩^1,2,3, 李维汉^1,2,3, 石琴^1,2

1. 合肥工业大学自动驾驶汽车安全技术安徽省重点实验室合肥 230009;
2. 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;
3. 合肥工业大学车辆工程系合肥 230009

收稿日期:2023-10-08 修回日期:2024-03-01 出版日期:2024-05-20 发布日期:2024-07-24
作者简介:白先旭(通信作者),男,1984年出生,博士,教授,博士研究生导师。主要研究方向为运载系统动力学与控制、智能网联汽车。
E-mail:bai@hut.edu.cn
潘宇翔,男,2000年出生。主要研究方向为智能网联汽车。
E-mail:2023171596@mail.hfut.edu.cn
基金资助:
合肥市自然科学基金(202350)和中央高校基本科研业务费专项资金(JZ2023YQTD0073)资助项目。

Three-σ Acceptance Criteria of Risk Assessment of Safety of the Intended Functionality of Intelligent Connected Vehicles

BAI Xianxu^1,2,3, PAN Yuxiang^1,2,3, CHEN Hao^1,2,3, LI Weihan^1,2,3, SHI Qin^1,2

1. Key Laboratory for Automated Vehicle Safety Technology of Anhui Province, Hefei University of Technology, Hefei 230009;
2. Engineering Research Center for Intelligent Transportation and Cooperative Vehicle-infrastructure of Anhui Province, Hefei University of Technology, Hefei 230009;
3. Department of Vehicle Engineering, Hefei University of Technology, Hefei 230009

Received:2023-10-08 Revised:2024-03-01 Online:2024-05-20 Published:2024-07-24

摘要/Abstract

摘要： 预期功能安全(Safety of the Intended functionality, SOTIF)问题是智能网联汽车商业化推广的最大难题之一。在对智能网联汽车进行SOTIF分析的过程中，建立合适的风险接受准则能为危害识别和风险评估提供更准确的判别标准，有助于降低开发成本、提高整车的SOTIF信心度和开发效率。为建立合适的风险接受准则，对自然驾驶数据中部分驾驶人交通特性关键参数进行提取以验证驾驶人行为的“极值特性”和参数的正态分布，并分析建立安全接受准则需要遵循的三类基本原则。在结合6标准差(6sigma, 6σ)理论在工科领域中的实际应用的基础上，提出将6σ理论用于建立SOTIF风险评估的3σ接受准则，并基于该接受准则重新定义行车安全场(Driving safety field, DSF)中驾驶安全系数(Driving safety index, DSI)标准值的计算方法。利用TrafficNet数据库计算不同基础场景下的DSI的标准值(DSI^*)，量化基础场景下的SOTIF风险接受准则。研究结果完善智能网联汽车的SOTIF评价体系，有利于从源头提升智能网联汽车安全水平，对避免无止境地推高累积测试里程具有指导意义。

关键词: 智能网联汽车, 预期功能安全, 风险评估, 驾驶安全系数, 接受准则

Abstract: Safety of the intended functionality(SOTIF) is one of the biggest challenges in the commercialization of intelligent connected vehicles. In the process of conducting SOTIF analysis on intelligent connected vehicles, establishing appropriate risk acceptance criteria can provide more accurate evaluation criteria for hazard identification and risk assessment, and help reduce development costs, improve the SOTIF confidence and development efficiency of the entire vehicle. In order to establish appropriate risk acceptance criteria, some key parameters of driver traffic characteristics in natural driving data are extracted to validate the “extreme value characteristics” of driver behavior and the normal distribution of parameters. Three basic principles that need to be followed in establishing safety acceptance criteria are analyzed. Based on the practical application of the six standard deviation (6sigma, 6σ) theory in the field of engineering, it is proposed to use the 6σ theory to establish the 3σ acceptance criteria for SOTIF risk assessment. Based on this acceptance criteria, the calculation method of the standard value of the driving safety index(DSI) in the driving safety field(DSF) is redefined. Finally, the TrafficNet database is used to calculate the standard value of DSI(DSI^*) under different basic scenarios, quantifying the SOTIF risk acceptance criteria under the basic scenarios. The research results have improved the SOTIF evaluation system for intelligent connected vehicles. They are of significance for improving the safety level of intelligent connected vehicles fundamentally and avoiding endless accumulation of testing mileage.

Key words: intelligent connected vehicles, safety of the intended functionality, risk assessment, driving safety index, acceptance criteria

中图分类号:

U463

白先旭, 潘宇翔, 陈浩, 李维汉, 石琴. 智能网联汽车预期功能安全风险评估3σ接受准则[J]. 机械工程学报, 2024, 60(10): 182-191.

BAI Xianxu, PAN Yuxiang, CHEN Hao, LI Weihan, SHI Qin. Three-σ Acceptance Criteria of Risk Assessment of Safety of the Intended Functionality of Intelligent Connected Vehicles[J]. Journal of Mechanical Engineering, 2024, 60(10): 182-191.

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智能网联汽车预期功能安全风险评估3σ接受准则

Three-σ Acceptance Criteria of Risk Assessment of Safety of the Intended Functionality of Intelligent Connected Vehicles

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