Should Autonomous Vehicles Collaborate in a Complex Urban Environment or Not?

IF 7 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Smart Cities Pub Date : 2023-09-20 DOI:10.3390/smartcities6050111
Sumbal Malik, Manzoor Ahmed Khan, Hesham El-Sayed, M. Jalal Khan
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Abstract

A specialized version of collaborative driving is convoy driving. It is referred to as the practice of driving more than one vehicle consecutively in the same lane with a small inter-vehicle distance, maintaining the same speed. Extensive research has been conducted on convoys of heavy-duty trucks on the highway; however, limited research has studied convoy driving in an urban environment. The complex dynamics of an urban environment require short-lived collaboration with varying numbers of vehicles rather than collaborating over hours. The motivation of this research is to investigate how convoy driving can be realized to address the challenges of an urban environment and achieve the benefits of autonomous driving such as reduced fuel consumption, travel time, improved safety, and ride comfort. In this work, the best-fitted coalitional game framework is utilized to formulate the convoy driving problem as a coalition formation game in an urban environment. A hypothesis is formulated that traveling in a coalition is more beneficial for a vehicle than traveling alone. In connection with this, a coalitional game and an all-comprehensive utility function are designed, modeled, and implemented to facilitate the formation of autonomous vehicle coalitions for convoy driving. Multiple solution concepts, such as the Shapley allocation, the Nucleolus, and the Core, are implemented to solve and analyze the proposed convoy driving game. Furthermore, several coalition formation strategies such as traveling mode selection, selecting optimal coalitions, and making decisions about coalition merging are developed to analyze the behavior of the vehicles. In addition to this, extensive numerical experiments with different settings are conducted to evaluate and validate the performance of the proposed study. The experimental results proved the hypothesis that traveling in a convoy is significantly more beneficial than traveling alone. We conclude that traveling in a convoy is beneficial for coalition sizes of two to four vehicles with an inter-vehicle spacing of less than 4 m considering the limitations of an urban environment. Traveling in a coalition allows vehicles to save on fuel, minimize travel time and enhance safety and comfort. Furthermore, the findings of this research state that achieving the enormous benefits of traveling in a coalition requires finding the right balance between inter-vehicle distance and coalition size. In the future, we plan to extend this work by studying the evolving dynamics of the coalitions and the environment.
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自动驾驶汽车是否应该在复杂的城市环境中进行协作?
协同驾驶的一个特殊版本是车队驾驶。它指的是多辆车在同一车道上连续行驶,车际距离较小,保持相同的速度。对高速公路上的重型卡车车队进行了广泛的研究;然而,对城市环境下车队驾驶的研究有限。城市环境的复杂动态需要与不同数量的车辆进行短期协作,而不是长时间协作。本研究的动机是研究如何实现车队驾驶,以应对城市环境的挑战,并实现自动驾驶的好处,如降低油耗、旅行时间、提高安全性和乘坐舒适性。本文利用最合适的联盟博弈框架,将城市环境下的车队驾驶问题表述为联盟形成博弈。提出了一个假设,即在联盟中行驶比单独行驶对车辆更有利。为此,设计、建模并实现了一个联盟博弈和一个全综合效用函数,以促进车队自动驾驶车辆联盟的形成。采用Shapley分配、Nucleolus和Core等多个求解概念对车队驾驶博弈进行求解和分析。在此基础上,提出了行驶方式选择、最优联盟选择、联盟合并决策等联盟形成策略,对车辆的行为进行了分析。除此之外,还进行了不同设置的大量数值实验,以评估和验证所提出研究的性能。实验结果证明了在车队中旅行比独自旅行更有益的假设。我们得出的结论是,考虑到城市环境的限制,在车队中行驶有利于2到4辆车的联盟规模,车辆间距小于4米。在联盟中行驶可以节省燃料,最大限度地减少行驶时间,提高安全性和舒适性。此外,本研究的结果表明,要实现在联盟中旅行的巨大利益,需要在车辆间距离和联盟规模之间找到适当的平衡。在未来,我们计划通过研究联盟和环境的演变动态来扩展这项工作。
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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来源期刊
Smart Cities
Smart Cities Multiple-
CiteScore
11.20
自引率
6.20%
发文量
0
审稿时长
11 weeks
期刊介绍: Smart Cities (ISSN 2624-6511) provides an advanced forum for the dissemination of information on the science and technology of smart cities, publishing reviews, regular research papers (articles) and communications in all areas of research concerning smart cities. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible, with no restriction on the maximum length of the papers published so that all experimental results can be reproduced.
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