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Human Factor Considered Risk Assessment of Automated Vehicle Using Vehicle to Vehicle Wireless Communication

机译:人为因素考虑的使用车对车无线通信的自动驾驶汽车风险评估

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This paper describes a human factor considered risk assessment of automated vehicle using vehicle to vehicle wireless communication (V2V communication). A human-reaction time is incorporated into the probabilistic threat assessment algorithm for the human-centered risk assessment. The V2V communication have been fused with a radar sensor to achieve more enhanced tracking performance of automated vehicle. Information fusion of two tracks, V2V communication and radar sensor, is performed using Global Nearest Neighborhood (GNN) approach. A prediction of vehicle’s motion follows the basic idea of the particle filtering. Based on the predicted behavior of vehicles, a collision risk is computed numerically and 321 driver data based human reaction time are incorporated to determine an active safety control intervention moment. The humancentered risk assessment algorithm has been applied to a collision avoidance scenario to monitor threat vehicles ahead and to find the best intervention point. Effects of the vehicular communication on a target vehicle state estimation and a vehicle safety control performance are investigated. The performance of the proposed algorithm has been investigated via computer simulation studies. It has been shown from both simulations and vehicle tests that the proposed human-centered risk assessment algorithm with the V2V communication can be beneficial to active safety systems in decision of controller intervention moment and in control of automated drive for the guaranteed safety.
机译:本文介绍了一种人为因素,它考虑了使用车辆到车辆的无线通信(V2V通信)对自动驾驶车辆进行风险评估。人为反应时间被纳入概率威胁评估算法中,以人为中心的风险评估。 V2V通信已与雷达传感器融合在一起,以实现自动车辆的更高跟踪性能。 V2V通信和雷达传感器这两个轨道的信息融合是使用全球最近邻(GNN)方法进行的。车辆运动的预测遵循粒子过滤的基本思想。基于车辆的预测行为,通过数值计算碰撞风险,并结合321个基于驾驶员反应时间的驾驶员数据来确定主动安全控制干预时间。以人为中心的风险评估算法已应用于防撞场景,以监控前方的威胁车辆并找到最佳干预点。研究了车辆通信对目标车辆状态估计和车辆安全控制性能的影响。通过计算机仿真研究了所提出算法的性能。从仿真和车辆测试都表明,提出的以V2V通信为中心的以人为中心的风险评估算法,对于主动安全系统在控制器干预力矩的决定和自动驾驶控制方面的保证安全性可能是有益的。

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