An analysis of the value of optimal routing and signal timing control strategy with connected autonomous vehicles

IF 2.8 3区工程技术 Q3 TRANSPORTATION

Journal of Intelligent Transportation Systems Pub Date : 2024-03-03 Epub Date: 2022-09-24 DOI:10.1080/15472450.2022.2129021

Tang Li , Fangce Guo , Rajesh Krishnan , Aruna Sivakumar

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引用次数: 0

Abstract

With the emergence of connected and automated technologies, Connected Autonomous Vehicles (CAVs) are able to communicate and interact with other vehicles and signal controllers. Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communications open up an opportunity to improve routing and signal timing efficiency with additional information from CAVs, such as prior travel time and signal green time. Most of the existing research on routing and signal timing for Human Driven Vehicles (HDVs) has to face the fact that human drivers only have partial knowledge about travel costs and traffic status on the road network, which typically reduces the system efficiency. In this paper, the impacts of additional information from CAVs on routing and signal timing efficiency in terms of total travel time have been investigated. An Optimal Routing and Signal Timing (ORST) control strategy for CAVs has been proposed and compared with four existing routing and signal timing strategies where drivers have different levels of information. The results of the simulation demonstrate that with additional information from CAVs, ORST can reduce about 49% of the total travel time compared with Stochastic User Equilibrium (SUE) and about 10% of the total travel time compared with User Equilibrium (UE).

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联网自动驾驶车辆的最佳路线和信号配时控制策略的价值分析

随着互联和自动化技术的出现，互联自动驾驶汽车 (CAV) 能够与其他车辆和信号控制器进行通信和互动。车对车（V2V）和车对基础设施（V2I）通信为利用来自 CAV 的额外信息（如之前的行驶时间和信号绿灯时间）改善路由选择和信号配时效率提供了机会。人类驾驶车辆（HDV）的路由选择和信号配时方面的现有研究大多不得不面对这样一个事实，即人类驾驶员只能部分了解出行成本和路网交通状况，这通常会降低系统效率。本文研究了来自 CAV 的额外信息对路由选择和信号配时效率的影响。本文提出了一种适用于 CAV 的最优路由和信号配时（ORST）控制策略，并将其与现有的四种路由和信号配时策略（驾驶员拥有不同程度的信息）进行了比较。仿真结果表明，与随机用户均衡（SUE）相比，在获得 CAV 的额外信息后，ORST 可减少约 49% 的总行驶时间，而与用户均衡（UE）相比，ORST 可减少约 10% 的总行驶时间。

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

Journal of Intelligent Transportation Systems 工程技术-运输科技

CiteScore

8.80

自引率

19.40%

发文量

审稿时长

15 months

期刊介绍： The Journal of Intelligent Transportation Systems is devoted to scholarly research on the development, planning, management, operation and evaluation of intelligent transportation systems. Intelligent transportation systems are innovative solutions that address contemporary transportation problems. They are characterized by information, dynamic feedback and automation that allow people and goods to move efficiently. They encompass the full scope of information technologies used in transportation, including control, computation and communication, as well as the algorithms, databases, models and human interfaces. The emergence of these technologies as a new pathway for transportation is relatively new. The Journal of Intelligent Transportation Systems is especially interested in research that leads to improved planning and operation of the transportation system through the application of new technologies. The journal is particularly interested in research that adds to the scientific understanding of the impacts that intelligent transportation systems can have on accessibility, congestion, pollution, safety, security, noise, and energy and resource consumption. The journal is inter-disciplinary, and accepts work from fields of engineering, economics, planning, policy, business and management, as well as any other disciplines that contribute to the scientific understanding of intelligent transportation systems. The journal is also multi-modal, and accepts work on intelligent transportation for all forms of ground, air and water transportation. Example topics include the role of information systems in transportation, traffic flow and control, vehicle control, routing and scheduling, traveler response to dynamic information, planning for ITS innovations, evaluations of ITS field operational tests, ITS deployment experiences, automated highway systems, vehicle control systems, diffusion of ITS, and tools/software for analysis of ITS.