Urban traffic signal control with connected and automated vehicles: A survey

被引:286
|
作者
Guo, Qiangqiang [1 ]
Li, Li [2 ]
Ban, Xuegang [1 ]
机构
[1] Univ Washington, Dept Civil & Environm Engn, Seattle, WA 98195 USA
[2] Tsinghua Univ, BNRist, Dept Automat, Beijing 100084, Peoples R China
基金
中国国家自然科学基金;
关键词
Urban traffic control (UTC); Connected and automated vehicles (CAVs); Mobile sensing; Traffic state estimation; TRAVEL-TIME ESTIMATION; GLOBAL POSITIONING SYSTEM; QUEUE LENGTH ESTIMATION; TRAJECTORY RECONSTRUCTION; INTEGRATED OPTIMIZATION; INTERSECTION MANAGEMENT; TRANSPORTATION SYSTEMS; DISTRIBUTED CONTROL; PRIORITY CONTROL; PROBE VEHICLES;
D O I
10.1016/j.trc.2019.01.026
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
Inefficient traffic control is pervasive in modem urban areas, which would exaggerate traffic congestion as well as deteriorate mobility, fuel economy and safety. In this paper, we systematically review the potential solutions that take advantage of connected and automated vehicles (CAVs) to improve the control performances of urban signalized intersections. We review the methods and models to estimate traffic flow states and optimize traffic signal timing plans based on CAVs. We summarize six types of CAV-based traffic control methods and propose a conceptual mathematical framework that can be specified to each of six three types of methods by selecting different state variables, control inputs, and environment inputs. The benefits and drawbacks of various CAV-based control methods are explained, and future research directions are discussed. We hope that this review could provide readers with a helpful roadmap for future research on CAV-based urban traffic control and draw their attention to the most challenging problems in this important and promising field.
引用
收藏
页码:313 / 334
页数:22
相关论文
共 50 条
  • [21] Traffic Signal Control Under Mixed Traffic With Connected and Automated Vehicles: A Transfer-Based Deep Reinforcement Learning Approach
    Song, Li
    Fan, Wei
    IEEE ACCESS, 2021, 9 : 145228 - 145237
  • [22] Centralized Traffic Control via Small Fleets of Connected and Automated Vehicles
    Daini, Chiara
    Goatin, Paola
    Delle Monache, Maria Laura
    Ferrara, Antonella
    2022 EUROPEAN CONTROL CONFERENCE (ECC), 2022, : 371 - 376
  • [23] Approaches of Computing Traffic Load for Automated Traffic Signal Control: A Survey
    Gupta, Pratishtha
    Purohit, G. N.
    Gupta, Adhyana
    PROCEEDINGS OF THE SECOND INTERNATIONAL CONFERENCE ON SOFT COMPUTING FOR PROBLEM SOLVING (SOCPROS 2012), 2014, 236 : 931 - 945
  • [24] Integrating traffic signal optimization with vehicle microscopic control to reduce energy consumption in a connected and automated vehicles environment
    Jiang, Zhongtai
    Yu, Dexin
    Luan, Siliang
    Zhou, Huxing
    Meng, Fanyun
    JOURNAL OF CLEANER PRODUCTION, 2022, 371
  • [25] Cooperative control of self-learning traffic signal and connected automated vehicles for safety and efficiency optimization at intersections
    Zhang, Gongquan
    Li, Fengze
    Ren, Dian
    Huang, Helai
    Zhou, Zilong
    Chang, Fangrong
    ACCIDENT ANALYSIS AND PREVENTION, 2025, 211
  • [26] CVLight: Decentralized learning for adaptive traffic signal control with connected vehicles
    Mo, Zhaobin
    Li, Wangzhi
    Fu, Yongjie
    Ruan, Kangrui
    Di, Xuan
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2022, 141
  • [27] Hierarchical Velocity Control Considering Traffic Signal Timings for Connected Vehicles
    Guo, Lulu
    Chu, Hongqing
    Ye, Jin
    Gao, Bingzhao
    Chen, Hong
    IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2023, 8 (02): : 1403 - 1414
  • [28] Coupled Control of Traffic Signal and Connected Autonomous Vehicles at Signalized Intersections
    Wang, Dan
    Wu, Zhizhou
    Ma, Guosheng
    Gao, Zhibo
    Yang, Zhidan
    JOURNAL OF ADVANCED TRANSPORTATION, 2023, 2023
  • [29] Multi-Commodity Traffic Signal Control and Routing With Connected Vehicles
    de Souza, Felipe
    Carlson, Rodrigo Castelan
    Mueller, Eduardo Rauh
    Ampountolas, Konstantinos
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (05) : 4111 - 4121
  • [30] Multi-objective coordinated control strategy for mixed traffic with partially connected and automated vehicles in urban corridors
    Wan, Changxin
    Shan, Xiaonian
    Hao, Peng
    Wu, Guoyuan
    Physica A: Statistical Mechanics and its Applications, 2024, 635