The invention relates to an expressway real-time accident risk prediction method based on a quasi-vehicle trajectory. The method comprises the following steps of: extracting the quasi-vehicle trajectory based on historical accident data; establishing a vehicle group accident risk prediction model based on the quasi-vehicle trajectory; acquiring speed data and flow data of a road section to be predicted in real time, and acquiring an accident risk prediction result based on the vehicle group accident risk prediction model; and performing coordinated control on the vehicle speed based on the accident risk prediction result. Compared with the prior art, the real-time change of the vehicle group traffic flow characteristics is associated with the accident possibility, the trajectory problem ofcollision vehicles is fully considered, detailed traffic information is applied, various traffic resources are gathered, the time-space information of the vehicles is acquired by combining the traffic data based on the speed and the traffic data based on the flow, the vehicle state is adjusted in time, accidents are prevented, and the safety of the networked automatic driving vehicles is improved.
本发明涉及一种基于准车辆轨迹的快速路实时事故风险预测方法,该方法包括以下步骤:基于历史事故数据提取准车辆轨迹;基于所述准车辆轨迹建立车群事故风险预测模型;实时获取待预测路段的速度数据和流量数据,并基于所述车群事故风险预测模型获得事故风险预测结果;基于所述事故风险预测结果对车辆速度进行协调控制。与现有技术相比,本发明将车群交通流特征的实时变化与事故可能性联系起来,充分考虑了碰撞车辆的轨迹问题,应用了详细的交通信息,汇聚了多种交通资源,结合基于速度和基于流量的交通数据来获取车辆的时空信息,及时调整车辆状态,防止事故的发生,提高网联自动驾驶汽车的安全性。
Expressway real-time accident risk prediction method based on quasi-vehicle trajectory
一种基于准车辆轨迹的快速路实时事故风险预测方法
2020-12-29
Patent
Electronic Resource
Chinese
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