利用自动驾驶汽车专用道管理早间通勤的停车政策设计

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引用次数: 0

摘要

具有自动泊车功能的自动驾驶汽车(AV)的出现对停车政策和管理提出了新的要求。在一个既有普通车道又有 AV 专用车道的交通系统中,本研究旨在考察和比较不同停车政策对早晨通勤的有效性。具体来说,本文提出了三种停车位分配政策,即先到先得(FCFS)、提前预约(AR)以及它们的组合(CB),以引导乘客的出行选择。乘客可以在普通车道上单独驾驶普通车辆(RV),也可以在专用自动驾驶车道上搭乘共享自动驾驶车辆(SAV)。本文揭示了三种停车政策下不同场景的发生条件和由此产生的 SAV 渗透率。此外,还给出了两种关键参数对不同场景的区域划分,并绘制了典型的出发模式图。数值结果表明,CB 政策对总出行成本的影响始终优于 FCFS 和 AR 政策。最佳 CB 政策可以通过所有停车位的最佳数量和未保留停车位的比例来量化。这些发现有助于改善交通流的时空分布,并在即将到来的自动驾驶时代有效分配交通资源。
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Parking policy design for managing morning commute with dedicated autonomous vehicle lane

The advent of autonomous vehicles (AVs) with self-parking capability puts forward new requirements for parking policy and management. In a transportation system with both general and dedicated AV lanes, this work aims to examine and compare the effectiveness of different parking policies on the morning commute. To be specific, three policies of parking space allocation, namely, first-come-first-service (FCFS), advanced reservation (AR), and their combination (CB), are proposed to guide the commuters’ travel choices. Commuters can drive regular vehicles (RVs) alone on the general lane or ridesharing shared autonomous vehicles (SAVs) on the dedicated AV lane. The occurrence conditions and the resultant SAV penetration rates for various scenarios under three parking policies are revealed. The area division for various scenarios with respect to two key parameters is presented, and the typical departure patterns are plotted as well. The numerical results clarify that the CB policy always has a better effect on the total travel cost than FCFS and AR policies. The optimal CB policy is quantified in terms of the optimal amount of all parking spaces and the proportion of unreserved parking spaces. These findings help to improve the spatial and temporal distribution of traffic flow and allocate transportation resources efficiently in the coming era of autonomous driving.

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来源期刊
CiteScore
16.20
自引率
16.00%
发文量
285
审稿时长
62 days
期刊介绍: Transportation Research Part E: Logistics and Transportation Review is a reputable journal that publishes high-quality articles covering a wide range of topics in the field of logistics and transportation research. The journal welcomes submissions on various subjects, including transport economics, transport infrastructure and investment appraisal, evaluation of public policies related to transportation, empirical and analytical studies of logistics management practices and performance, logistics and operations models, and logistics and supply chain management. Part E aims to provide informative and well-researched articles that contribute to the understanding and advancement of the field. The content of the journal is complementary to other prestigious journals in transportation research, such as Transportation Research Part A: Policy and Practice, Part B: Methodological, Part C: Emerging Technologies, Part D: Transport and Environment, and Part F: Traffic Psychology and Behaviour. Together, these journals form a comprehensive and cohesive reference for current research in transportation science.
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