基于轨迹预测的智能汽车行驶风险评估方法  

Intelligent Vehicle Driving Risk Assessment Method Based on Trajectory Prediction

作　　者：高翔[1] 陈龙[1] 王歆叶 熊晓夏 李祎承 陈月霞[2] Gao Xiang;Chen Long;Wang Xinye;Xiong Xiaoxia;Li Yicheng;Chen Yuexia(Institute of Automotive Engineering,Jiangsu University,Zhenjiang 212013;School of Automotive and Traffic Engineering,Jiangsu University,Zhenjiang 212013)

机构地区：[1]江苏大学汽车工程研究院,镇江212013 [2]江苏大学汽车与交通工程学院,镇江212013

出　　处：《汽车工程》2023年第4期588-597,共10页Automotive Engineering

基　　金：国家自然科学基金(52002154,52272418,U20A20333);江苏省重点研发项目(BE2020083-2,BE2021011-2)资助。

摘　　要：提出了基于预测轨迹的行车风险评估方法,首先建立了沿预测轨迹两侧具有渐变高斯截面特征的驾驶风险域DRF以表征驾驶员行为的不确定性,然后考虑车辆与周围静态、动态障碍物处于特定状态的风险后果建立环境事件成本,得到适应复杂行车场景不确定性的量化感知风险,并基于贝叶斯理论融合预测区间内的量化感知风险时间序列,实现了对于未来行车潜在碰撞风险的预测。实车轨迹和仿真实验结果表明,相比于经典TTC指标方法,基于融合未来一段时间内自车与周边环境交互信息的DRF的风险评估方法可以更快、更准确地辨识复杂交通场景的行车风险变化,为研究周边多车复杂场景下车辆碰撞风险问题提供了参考。This paper proposes a driving risk assessment method based on trajectory prediction.Firstly,a driver’s risk field(DRF)with Gaussian cross-section characteristics along both sides of the prediction trajectory is established to characterize the uncertainty of the driver’s behavior.Then,taking the risk consequences of the vehicle and the surrounding static and dynamic obstacles in specific states into consideration,the environmental event cost is established,and the quantitative perception risk that adapts to the uncertainty of complex driving scenarios is obtained.Finally,the quantitative perception risk time series in the prediction interval is then fused based on Bayesian theory to realize prediction of potential collision risks in future driving.The real vehicle trajectory and simulation results show that compared with the classic TTC index method,the risk assessment method of DRF based on the integration of interaction information between self-vehicle and surrounding environment in the future can identify the driving risk changes of complex traffic scenarios faster and more accurately,which provides a reference for the study of vehicle collision risk problems in complex scenarios with multiple surrounding vehicles.

关 键 词：智能汽车 行驶风险评估 轨迹预测 复杂行车场景 驾驶风险域 

分 类 号：U463.6[机械工程—车辆工程]