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汽车安全与节能学报 ›› 2026, Vol. 17 ›› Issue (2): 179-187.DOI: 10.3969/j.issn.1674-8484.2026.02.003

• 汽车安全 • 上一篇    下一篇

面向组合驾驶辅助系统的安全事件评估方法与影响因素分析

张帆1(), 于峰1, 胡鑫磊1, 张子晗1, 朱煜1, 姜腾龙1, 裴天箫1, 沈金华1, 苍学俊1, 李泉2, 周青2, 王辰3   

  1. 1 上海机动车检测认证技术研究中心有限公司上海 201805, 中国
    2 清华大学 车辆与运载学院北京 100084, 中国
    3 中国汽车工程学会北京 100176, 中国
  • 收稿日期:2025-10-15 修回日期:2026-02-27 出版日期:2026-04-30 发布日期:2026-04-30
  • 作者简介:张帆(1981—),男(汉),北京,高级工程师。E-mail:fanz@smvic.com.cn
  • 基金资助:
    国家重点研发计划项目(2024YFB2505701)

Evaluation method and influencing factor analysis of safety events for combined driver assistance system

ZHANG Fan1(), YU Feng1, HU Xinlei1, ZHANG Zihan1, ZHU Yu1, JIANG Tenglong1, PEI Tianxiao1, SHEN Jinhua1, CANG Xuejun1, LI Quan2, ZHOU Qing2, WANG Chen3   

  1. 1 Shanghai Motor Vehicle Inspection, Certification & Tech Innovation Center Co., Ltd., Shanghai 201805, China
    2 School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China
    3 China Society of Automotive Engineers, Beijing 100176, China
  • Received:2025-10-15 Revised:2026-02-27 Online:2026-04-30 Published:2026-04-30

摘要:

为明确组合驾驶辅助系统(CDAS)安全边界与性能差异,解决现有评估方法工况单一、场景适配不足、多影响因素耦合机制不明等问题,构建了融合场景分级、功能解构、多维度量化的CDAS安全事件系统化评估方法体系。以4款量产车型为研究对象,在6座城市开展实车道路评估,细化定义36类子功能、10类驾驶行为与3级场景复杂度,通过数据切片提取出典型驾驶员紧急干预事件。以驾驶员紧急干预脱离率、间隔里程为指标,对场景复杂度与远程软件升级(OTA)进行对比分析。结果表明:不同子功能场景脱离率有差异, 高复杂度场景脱离率为8.97%~19.88%,显著高于低复杂度场景(< 5%);博弈场景脱离率是无博弈场景的3~7倍;OTA提升了多数子功能场景的安全性,而在路口右转、避让、分合流等复杂场景易出现性能退化。CDAS的安全表现同时受交通场景复杂度、博弈场景及OTA耦合影响。建议算法在迭代过程中建立基于场景的优先级矩阵,以均衡训练数据并避免训练的偏置效应。

关键词: 组合驾驶辅助系统(CDAS), 城区场景, 驾驶员紧急干预, 评估方法, 安全事件

Abstract:

To clarify the safety boundaries and performance differences of the combined driving assistance system (CDAS), and solve the problems of single existing evaluation condition, insufficient scenario adaptation and unclear coupling mechanism of multiple influencing factors, a systematic evaluation methodology system for CDAS safety events was constructed, which integrated scenario classification, function decomposition and multi-dimensional quantification. Four mass-produced vehicle models were taken as research objects, and real-vehicle road evaluations were carried out in six cities. 36 types of sub-functions, 10 types of driving behaviors and 3 levels of scene complexity were defined in detail, and typical driver emergency intervention events were extracted through data slicing. With the driver emergency intervention disengagement rate and interval mileage as indicators, a comparative analysis was conducted on scene complexity and over-the-air (OTA) updates. The results show that there are differences in disengagement rates among different sub-function scenarios; the disengagement rate in high-complexity scenarios is 8.97%~19.88%, which is significantly higher than that in low-complexity scenarios (<5%); the disengagement rate in game scenarios is 3~7 times that in non-game scenarios; OTA improves the safety of most sub-function scenarios, while performance degradation is prone to occur in complex scenarios such as right turns at intersections, evasion, and merging/diverging. The safety performance of CDAS is jointly affected by the coupling of traffic scene complexity, game scenarios and OTA. It is suggested that a scenario-based priority matrix should be established in the algorithm iteration process, the training data should be balanced to avoid the bias effect of training.

Key words: combined driver assistance systems (CDAS), urban scenarios, driver emergency intervention, evaluation methodology, safety events

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