基于行车风险场的交通冲突风险预警方法
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1.广东工业大学自动化学院 广州 510006; 2.广东工业大学集成电路学院 广州 510006

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U419-3

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国家自然科学基金(U22A2054)、国家自然科学基金(61971148)项目资助


Traffic conflict risk warning method based on driving risk field
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1.School of Automation, Guangdong University of Technology,Guangzhou 510006, China; 2.School of Integrated Circuit, Guangdong University of Technology,Guangzhou 510006, China

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    摘要:

    城市交叉路口是交通事故多发路段,对于智能网联汽车来说,在行驶过程中进行风险检测与碰撞预警,从而保障驾驶的安全性至关重要。本文针对有信号灯的城市交叉路口提出一种考虑信号灯约束的行车风险场模型,并基于此模型设计三级碰撞预警方法。首先针对城市交叉路口的潜在冲突风险点构建功能场景,并将信号灯的约束作用考虑进行车风险场模型。为了解决碰撞预警问题,提出以TTC为指标划分三级冲突区域,通过计算主车行驶过程中周围对应的场强值,并根据干扰车在主车周围势能场的位置来衡量主车所受碰撞风险。实验结果表明,所设计的模型能够准确对进入主车势能场范围的干扰车进行预警,预警成功率可达100%,误报率仅为3.4%,证明所提方法的可靠性和有效性。

    Abstract:

    Urban intersections are accident-prone sections. For intelligent networked vehicles, it is very important to carry out risk detection and collision warning during driving to ensure the safety of driving. This paper proposes a traffic risk field model considering traffic signal constraints for urban intersections with traffic lights, and designs a three-level collision warning method based on this model. Firstly, a functional scenario is constructed according to the potential conflict risk points of urban intersections, and the vehicle risk field model is carried out considering the constraint effect of traffic signal. In order to solve the problem of collision warning, a three-level conflict area is proposed to be divided by the index, and the collision risk of the main vehicle is measured according to the position of the potential energy field around the main vehicle by calculating the corresponding field strength around the main vehicle. The experimental results show that the designed model can accurately warn the interfering vehicles entering the potential energy field of the main vehicle, the warning success rate can reach 100%, and the false alarm rate is only 3.4%, which proves the reliability and effectiveness of the proposed method.

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薛先斌,谭北海,余荣,钟武昌.基于行车风险场的交通冲突风险预警方法[J].电子测量技术,2024,47(6):1-7

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  • 在线发布日期: 2024-06-07
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