Autonomous vehicle platoon overtaking at a uniform speed based on improved artificial potential field method

Yan Chen, Liang Su, Yong Zhang, Feng Zhang, G. Gong
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Abstract

Amidst the advancements in autonomous driving technology, platoons composed of autonomous vehicles have garnered significant attention due to their potential to alleviate traffic congestion and enhance transportation capacity. Addressing the issue of slow-moving vehicles obstructing the roadway, this study introduces a consistent overtaking strategy, leveraging an improved artificial potential field (IAPF) method. Through the incorporation of a velocity repulsive force field, a refined obstacle position repulsive force field, and a road boundary repulsive force field, the cumulative resultant force vector experienced by the autonomous vehicle is treated holistically. This approach ensures that the vehicle traverses in the direction of the total resultant force unit vector at a predefined speed. Moreover, the repulsive and attractive force coefficients are determined to guarantee convoy safety and uniform velocity. This research sets forth the architecture of the autonomous vehicle platoon, reconceptualizing overtaking maneuvers as dynamic target-tracking challenges. Throughout the overtaking phase, the obstructive vehicle is chosen either based on specific criteria fulfillment or by designating the lead vehicle's speed to a virtual dynamic target, thus safeguarding the overtaking procedure against potential collisions. Comprehensive simulations, conducted using Matlab and Unreal Engine software platforms, corroborate the efficacy and viability of the IAPF-based consistent speed overtaking strategy. Relative to the conventional APF approach, this method facilitates safe obstacle circumvention in dynamic settings and ensures vehicle velocity remains unaffected by resultant force fluctuations, maintaining consistent speed during overtaking.
基于改进的人工势场方法的匀速自主排车超车技术
随着自动驾驶技术的发展,由自动驾驶车辆组成的车队因其在缓解交通拥堵和提高运输能力方面的潜力而备受关注。针对慢速行驶车辆阻碍道路的问题,本研究利用改进的人工势场(IAPF)方法,引入了一种连贯的超车策略。通过结合速度排斥力场、改进的障碍物位置排斥力场和道路边界排斥力场,对自动驾驶车辆所经历的累积结果力矢量进行了整体处理。这种方法可确保车辆以预定速度沿着总结果力单位向量的方向行驶。此外,还确定了排斥力系数和吸引力系数,以确保车队安全和匀速行驶。这项研究提出了自主车辆排的结构,将超车机动重新概念化为动态目标跟踪挑战。在整个超车阶段,根据特定的标准选择障碍车辆,或将领先车辆的速度指定为虚拟动态目标,从而确保超车过程不会发生潜在碰撞。使用 Matlab 和虚幻引擎软件平台进行的综合模拟证实了基于 IAPF 的一致速度超车策略的有效性和可行性。与传统的 APF 方法相比,这种方法有利于在动态环境中安全绕过障碍物,并确保车辆速度不受随之产生的力波动的影响,从而在超车过程中保持稳定的速度。
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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