Study on Control for Prevention of Collision Caused by Failure of Localization for Map-Based Automated Driving Vehicle

Shun Nishimura, M. Omae
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Abstract

In demonstration experiments of automated driving vehicles, lane departures and collisions with roadside structures due to poor vehicle positioning and self-localization have been reported. In this study, we propose a promising method to prevent such departures and collisions, and then validate the proposed method by applying it to an actual automated driving vehicle. The proposed method monitors the target steering angles computed by the automated driving control and limits them before commanded the actuator when there is a risk of colliding with obstacles. As the above-mentioned control is lower-level, it can prevent an automated driving vehicle from colliding with obstacles without complicating upper-level controls. Experiments on an actual automated driving vehicle showed that the steering control structure of the proposed method could prevent an automated driving vehicle from colliding with obstacles by limiting its target steering angle. In addition, the method does not impose excessive limits on the steering angle when the automated driving vehicle follows a normal path and no risk of collision exists.
基于地图的自动驾驶车辆定位失败碰撞预防控制研究
在自动驾驶车辆的演示实验中,曾报道过由于车辆定位和自定位不佳导致车道偏离和与路边结构物发生碰撞的情况。在本研究中,我们提出了一种有希望的方法来防止这种偏离和碰撞,然后通过将其应用于实际的自动驾驶车辆来验证所提出的方法。该方法监测由自动驾驶控制器计算的目标转向角,并在有与障碍物发生碰撞的危险时,在命令执行器之前对其进行限制。由于上述控制是较低级别的,它可以防止自动驾驶车辆与障碍物碰撞,而不会使上层控制复杂化。在实际自动驾驶车辆上的实验表明,该方法的转向控制结构可以通过限制目标转向角度来防止自动驾驶车辆与障碍物的碰撞。此外,该方法不会对自动驾驶车辆正常行驶时的转向角度施加过多限制,不存在碰撞风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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