Study of Dynamic Traffic Management Based on Automated Driving/ADAS with Connected System

被引:0
|
作者
Irie Y. [1 ]
Sano M. [2 ]
Matsunaga H. [2 ]
Akasaka D. [3 ]
Miura M. [4 ]
机构
[1] Toyota Motor Corporation, 2-3-18, Kudanminami, Chiyoda-ku, Tokyo
[2] Regional & Transportation Planning Institute Ltd., 2-19, Kitahamahigashi, Chuo-ku, Osaka
[3] MathWorks Japan Akasaka, 4-15-1, Akasaka, Minato-ku,Garden City, Tokyo
[4] PTV Group Japan Ltd., Phil Park Kamikitazawa 2F, 4-15-13, Kamikitazawa, Setagaya-ku, Tokyo
关键词
ACC (E2); connected system; dynamic lane management; traffic control system; traffic management system;
D O I
10.20485/JSAEIJAE.15.2_82
中图分类号
学科分类号
摘要
This study examined the feasibility of improving traffic flow on urban highways using AD/ADAS and connected systems. The focus was on congested merging areas with the aim of maintaining the speed immediately after merging. The effectiveness of lane-based vehicle relocation and speed control measures was evaluated to achieve this goal. This study also considered realistic specifications for connected systems, considering constraints such as cost limitations. The feasibility of improving traffic flows through strategies such as lane utilization management and speed control was investigated and potential new challenges were identified. © 2024 Society of Automotive Engineers of Japan, Inc. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike license. All Rights Reserved.
引用
收藏
页码:82 / 89
页数:7
相关论文
共 50 条
  • [21] Control of Connected and Automated Vehicles Driving on Dedicated Bus Lane Under Mixed Traffic
    Pang M.-B.
    Chai Z.-X.
    Gong D.-Y.
    Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology, 2021, 21 (04): : 118 - 124
  • [22] Navigating the Impact of Connected and Automated Vehicles on Mixed Traffic Efficiency: A Driving Behavior Perspective
    Yue, Wenwei
    Wu, Xianhui
    Li, Changle
    Cheng, Nan
    Duan, Peibo
    Han, Zhu
    IEEE INTERNET OF THINGS JOURNAL, 2024, 11 (23): : 37770 - 37784
  • [23] Dynamic Risk Management for Safely Automating Connected Driving Maneuvers
    Grobelna, Marta
    Zacchi, Joao-Vitor
    Schleiss, Philipp
    Burton, Simon
    2021 17TH EUROPEAN DEPENDABLE COMPUTING CONFERENCE (EDCC 2021), 2021, : 9 - 16
  • [24] Risk-based maximum speed advisory system for driving safety of connected and automated bus
    Tak, Sehyun
    Kim, Sari
    Lee, Donghoun
    IET INTELLIGENT TRANSPORT SYSTEMS, 2024, 18 : 2896 - 2920
  • [25] A Novel Approach for Mixed Manual/Connected Automated Freeway Traffic Management
    Li, Duo
    Wagner, Peter
    SENSORS, 2020, 20 (06)
  • [26] Stability analysis and connected vehicles management for mixed traffic flow with platoons of connected automated vehicles
    Qin, Yanyan
    Luo, Qinzhong
    Wang, Hua
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2023, 157
  • [27] An impact study of integrating connected automated vehicles with conventional traffic
    Zhang, Yue
    Cassandras, Christos G.
    ANNUAL REVIEWS IN CONTROL, 2019, 48 : 347 - 356
  • [28] Design of Integrated Risk Management-Based Dynamic Driving Control of Automated Vehicles
    Kim, Kyuwon
    Lee, Kyoungjun
    Ko, Bongchul
    Kim, Beomjun
    Yi, Kyongsu
    IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE, 2017, 9 (01) : 57 - 73
  • [29] Integrated Traffic Management System under Connected Environment
    Yang, Hao
    Oguchi, Ken
    2019 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC), 2019, : 3379 - 3386
  • [30] Driving aggressiveness management policy to enhance the performance of mixed traffic conditions in automated driving environments
    Lee, Seolyoung
    Jeong, Eunbi
    Oh, Minsoo
    Oh, Cheol
    TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2019, 121 : 136 - 146