交通运输系统工程与信息 ›› 2018, Vol. 18 ›› Issue (1): 89-95.

所属专题: 车路协同与智能化技术

• 智能交通系统与信息技术 • 上一篇    下一篇

基于车联网V2P 的行人碰撞风险辨识研究

彭理群*1, 3 ,何书贤2 ,贺宜2,艾云飞3   

  1. 1. 华东交通大学 交通运输与物流学院,南昌 330013;2. 武汉理工大学 智能交通系统研究中心,武汉 430063; 3. 交通安全应急信息技术国家工程实验室,北京 100011
  • 收稿日期:2017-11-06 修回日期:2017-12-25 出版日期:2018-02-25 发布日期:2018-02-26
  • 作者简介:彭理群(1984-),男,湖北武汉人,副教授,博士.
  • 基金资助:

    国家重点研发计划/National Key R&D Program of China(2017YFC0803900);国家自然科学基金/National Natural Science Foundation of China(61703160,51775396,51605350).

Vehicle-pedestrian Collision Risk Assessment Based on Connected Vehicle V2P Communication

PENG Li-qun 1, 3 , HE Shu-xian 2, HE Yi2,AI Yun-fei3   

  1. 1. School of Transport and Logistics, East China Jiaotong University, Nanchang 330013, China; 2. Intelligent Transport Systems Research Center,Wuhan University of Technology,Wuhan 430063, China; 3. National Engineering Laboratory for Transportation Safety & Emergency Informatics, Beijing 100011, China)
  • Received:2017-11-06 Revised:2017-12-25 Online:2018-02-25 Published:2018-02-26

摘要:

为探索基于车联网V2P(Vehicle to Pedestrian)通信技术的行人碰撞风险辨识方法, 首先,在车联网环境下实时获取了目标位置、速度、运动方向等信息,并分析了典型人—车相 对运动场景中交通参与者的行为不确定性,进而提出了人—车碰撞区域随机几何模型;然后, 综合考虑了车联网系统的通信延时、定位误差、人—车相对运动不确定性等多因素的影响,建 立了人—车碰撞事故概率和冲突风险程度模型;最后,通过仿真实验分析了行车速度、通信延 时、定位精度等因素对行人碰撞风险辨识模型效果的影响,以及各因素间的相关性关系.本文 提出的方法对行人安全保护研究具有一定的参考价值,研究结果同时指出了车联网系统通信 延时与定位精度的技术要求.

关键词: 智能交通, 行人防撞, 车路协同, 车联网V2P

Abstract:

In this paper, a novel method is investigated for assessing vehicle- pedestrian collision risk in road traffic on the basis of connected vehicle V2P (Vehicle to Pedestrian) communication. First of all, a general V2P communication scenario is constructed to enable pedestrian motion being detected by approaching vehicles, explicitly along with real time obtaining the objects trajectory, velocity, orientation etc., while the typical behaviors of involved vehicles and pedestrians are analyzed, which in return, a stochastic geometric model is established for explicitly describing the pedestrian and vehicle location distribution in near crash situations. Then, vehiclepedestrian crash probability and risk evaluation model is established with comprehensively considering the V2P communication delay, positioning accuracy, uncertainty of vehicle- pedestrian relative motion. Finally, simulated Connected Vehicle test is conducted to examine the performance of pedestrian crash assessment model under the influence of connected vehicle communication delay, positioning accuracy and vehicle speed, and specially explore the relativity among these factors. The proposed method provides reference value for practical pedestrian safety application. The research results also indicate the technical requirements of Connected Vehicle system for future safety application.

Key words: intelligent transportation, pedestrian collision avoidance, cooperative vehicle infrastructure system, connected vehicle V2P communication

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