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清华大学学报(自然科学版)  2022, Vol. 62 Issue (3): 447-457    DOI: 10.16511/j.cnki.qhdxxb.2021.22.034
  机械工程 本期目录 | 过刊浏览 | 高级检索 |
车路协同环境下行车风险场模型的扩展与应用
田野1, 裴华鑫1, 晏松1, 张毅1,2,3
1. 清华大学 自动化系, 北京 100084;
2. 清华-伯克利深圳学院, 深圳 518055;
3. 江苏省现代城市交通技术创新中心, 南京 210096
Extended driving risk field model for i-VICS and its application
TIAN Ye1, PEI Huaxin1, YAN Song1, ZHANG Yi1,2,3
1. Department of Automation, Tsinghua University, Beijing 100084, China;
2. Tsinghua-Berkeley Shenzhen Institute(TBSI), Shenzhen 518055, China;
3. Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing 210096, China
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摘要 车路协同(i-VICS)环境下,行车风险场是一种评估网联自动驾驶汽车(CAVs)行驶安全性的有效手段。目前主流的行车风险场模型未考虑车辆几何特性和航向角等影响行驶安全的信息,且忽视了自车因素对行车风险的影响,在安全评估的准确性上有待进一步提升。该文提出了一种行车风险场的扩展模型,将碰撞时间(TTC)融入风险场模型,引入自车物理属性和运动状态,有效提升了模型的准确性,同时引入车辆几何特性与航向角信息,扩展了模型的适用范围。将风险场模型应用于典型交通场景,结果表明所提出的扩展模型可有效克服已有研究的不足;将扩展模型用于车辆轨迹规划问题求解,结果表明该模型可有效完成复杂场景下的车辆轨迹规划任务。
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田野
裴华鑫
晏松
张毅
关键词 系统模拟车路协同(i-VICS)网联自动驾驶汽车(CAVs)行车风险场碰撞时间(TTC)    
Abstract:In intelligent vehicle-infrastructure cooperation systems (i-VICS), the driving risk field is an effective method for evaluating the driving safety of connected and automated vehicles (CAVs). However, existing driving risk field models do not consider the geometric characteristics and heading angles of vehicles and ignore the influences of the ego vehicle, which limits the accuracy of these existing models for vehicle safety assessments. This paper describes an extended driving risk field model. This driving risk field model includes the time to collision (TTC) and adds the physical attributes and movement information of the ego vehicle, including the vehicle size and heading, into the driving risk field model which improves the safety assessment. Application of this driving risk field model to typical traffic scenarios shows that this extended model overcomes the limitations of existing models. Simulations using this model for trajectory planning demonstrate the promising performance of the extended model.
Key wordssystem simulation    intelligent vehicle-infrastructure cooperation systems (i-VICS)    connected and automated vehicles (CAVs)    driving risk field    time to collision (TTC)
收稿日期: 2021-03-05      出版日期: 2022-03-10
基金资助:张毅,教授,E-mail:zhyi@tsinghua.edu.cn
引用本文:   
田野, 裴华鑫, 晏松, 张毅. 车路协同环境下行车风险场模型的扩展与应用[J]. 清华大学学报(自然科学版), 2022, 62(3): 447-457.
TIAN Ye, PEI Huaxin, YAN Song, ZHANG Yi. Extended driving risk field model for i-VICS and its application. Journal of Tsinghua University(Science and Technology), 2022, 62(3): 447-457.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2021.22.034  或          http://jst.tsinghuajournals.com/CN/Y2022/V62/I3/447
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
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