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A Multi-Sensor Approach for Comprehensive Detection and Warning of Vehicle Collision Risk

机译:一种多传感器的车辆碰撞风险综合检测与预警方法

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The collision warning system, based on multi-sensor, can perceive more information than a unilateral system, just like vehicle motion status, driver intention, and road traffic environment; thus, it can provide more accurate judgments of driving safety. In this paper, physical and logical framework of a collision warning system based on multi-sensor is designed in detail. Vehicle to vehicle communication (V2V), vehicle to infrastructure communication (V2I), and vehicular sensors are used to acquire the motion status of the subject vehicle, neighboring vehicles, and pedestrians. Then, the short-term future motion status is predicted based on the Kalman algorithm, and the vehicle collision risk can be detected in advance by a collision detection algorithm. Furthermore, the safe distance threshold as a collision risk indicator is calculated and compared with the predicted distance. Finally, the vehicle collision risk can be detected according to the comparison. Simulation results show that the method is effective for judging the collision risk and providing an accurate warning prompt.
机译:与单边系统相比,基于多传感器的碰撞预警系统可以感知更多的信息,就像车辆的运动状态,驾驶员的意图和道路交通环境一样;因此,它可以提供对行驶安全性的更准确的判断。本文详细设计了基于多传感器的碰撞预警系统的物理和逻辑框架。车辆对车辆通信(V2V),车辆对基础设施通信(V2I)和车辆传感器用于获取目标车辆,相邻车辆和行人的运动状态。然后,基于卡尔曼算法预测短期未来运动状态,并且可以通过碰撞检测算法提前检测车辆碰撞风险。此外,计算作为碰撞风险指标的安全距离阈值,并将其与预测距离进行比较。最终,可以根据比较结果检测出车辆发生碰撞的风险。仿真结果表明,该方法可有效判断碰撞风险,并提供准确的警告提示。

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