十字路口乘用车与二轮车典型危险场景聚类及推演

doi:10.16265/j.cnki.issn1003-3033.2020.04.016

中国安全科学学报 ›› 2020, Vol. 30 ›› Issue (4): 100-107.doi: 10.16265/j.cnki.issn1003-3033.2020.04.016

十字路口乘用车与二轮车典型危险场景聚类及推演

周华^1,2 副研究员, 张巧玉¹, 母尧尧¹, 谭正平^1,2 讲师, 孙庆³ 讲师, 张道文^1,2 教授

1.西华大学汽车与交通学院,四川成都 610039;
2.汽车测控与安全四川省重点实验室,四川成都 610039;
3.成都技师学院汽车工程学院,四川成都 610039

收稿日期:2020-01-12 修回日期:2020-03-25 出版日期:2020-04-28 发布日期:2021-01-27
作者简介:周华(1968—),男,重庆人,副研究员,硕士,主要从事道路交通安全方面的研究。E-mail:xhqcxy@163.com。
基金资助:
中国标准化研究院场景库测试项目(192304);四川省省重点实验室开放课题项目(szjj2018-129);上海汽车工业科技发展基金资助(1828);西华大学研究生创新基金资助(ycjj2019117)。

Clustering and deduction of typical dangerous scenarios between passenger vehicles and two-wheelers at crossroads

ZHOU Hua^1.2, ZHANG Qiaoyu¹, MU Yaoyao¹, TAN Zhengping¹, SUN Qing³, ZHANG Daowen^1.2

1. School of Automobile and Transportation, Xihua University, Chengdu Sichuan 610039, China;
2. Key Laboratory of Vehicle Measurement Control and Safety of Sichuan Province, Chengdu Sichuan 610039, China;
3. School of Automotive Engineering, Chengdu Technician College, Chengdu Sichuan 610039, China

Received:2020-01-12 Revised:2020-03-25 Online:2020-04-28 Published:2021-01-27

摘要/Abstract

摘要： 为了给智能汽车研发提供有效的场景推演构建方案,统计分析国家车辆事故深度调查体系(NAIS)数据库中乘用车与二轮车发生在十字路口的事故场景数据,得到2类高占比的基础场景;选取7个场景关联变量,并就2类基础场景对应的静态特性数据进行聚类分析;建立运动学推演模型,结合5类典型危险场景的动态参数实际阈值,构建5类典型危险场景的速度-距离危险模型。结果表明:通过统计分类、聚类分析和运动学模型叠加推演方法,可得到5类符合中国道路交通情况的十字路口乘用车与二轮车典型危险场景,进而得出5个危险场景集。

关键词: 十字路口, 乘用车, 二轮车, 典型危险场景, 聚类分析, 推演

Abstract: In order to provide an effective scenario deduction and construction scheme for research and development of intelligent vehicles, statistical analysis was conducted on data of accident scenarios between passenger vehicles and two-wheelers at crossroads from National Automobile Accident In-depth Investigation System (NAIS) database, and two types of basic scenarios with high proportion were obtained. Then, seven scenario correlation variables were selected for cluster analysis on static characteristics of these two types of scenarios. Finally, a kinematics deduction model was established, and furthermore, considering actual threshold of dynamic parameters of five types of typical dangerous scenarios, speed-distance danger models of them were constructed. The results show that through methods of statistical classification, cluster analysis and kinematic model superposition deduction, five kinds of typical hazard scenes of passenger cars and two-wheeled vehicles at intersections can be obtained in conformity with traffic situation in China, and moreover five sets of dangerous scenarios are obtained.

Key words: crossroads, passenger vehicles, two-wheeler, typical dangerous scenarios, cluster analysis, deduction

中图分类号:

X951

周华, 张巧玉, 母尧尧, 谭正平, 孙庆, 张道文. 十字路口乘用车与二轮车典型危险场景聚类及推演[J]. 中国安全科学学报, 2020, 30(4): 100-107.

ZHOU Hua, ZHANG Qiaoyu, MU Yaoyao, TAN Zhengping, SUN Qing, ZHANG Daowen. Clustering and deduction of typical dangerous scenarios between passenger vehicles and two-wheelers at crossroads[J]. China Safety Science Journal, 2020, 30(4): 100-107.

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十字路口乘用车与二轮车典型危险场景聚类及推演

Clustering and deduction of typical dangerous scenarios between passenger vehicles and two-wheelers at crossroads

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