A multi-agent approach to cooperative traffic management and route guidance

被引：105

作者：

Adler, JL ^{[1
]}

Satapathy, G ^{[1
]}

Manikonda, V ^{[1
]}

Bowles, B ^{[1
]}

Blue, VJ ^{[1
]}

机构：

[1] Intelligent Automat Inc, Rockville, MD 20855 USA

来源：

TRANSPORTATION RESEARCH PART B-METHODOLOGICAL | 2005年 / 39卷 / 04期

基金：

美国国家科学基金会;

关键词：

transportation management; route guidance; intelligent agents;

D O I：

10.1016/j.trb.2004.03.005

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This paper explores the use of cooperative, distributed multi-a-gent systems to improve dynamic routing and traffic management. On the supply-side, real-time control over the transportation network is accomplished through an agent-based distributed hierarchy of system operators. Allocation of network capacity and distribution of traffic advisories are performed by agents that act on behalf of information service providers. Driver needs and preferences are represented by agents embedded in intelligent In-vehicle route guidance systems. Negotiation between ISP and driver agents seek a more efficient route allocation across time and space. Results from simulation experiments suggest that negotiation can achieve more optimal network performance and increased driver satisfaction. (C) 2004 Elsevier Ltd. All rights reserved.

引用

页码：297 / 318

页数：22

共 50 条

[1] A cooperative multi-agent transportation management and route guidance system
Adler, JL
Blue, VJ
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2002, 10 (5-6) : 433 - 454
[2] Dynamic Pricing and Route Guidance: A Multi-Agent System for Effective Parking and Traffic Management
Ben Hassine, Sana
Kooli, Elyes
Mraihi, Rafaa
TRANSPORTATION RESEARCH RECORD, 2024, 2678 (10) : 45 - 66
[3] A multi-agent urban traffic control system cooperated with dynamic route guidance
Chen, Xin
Yang, Zhao-Sheng
Wang, Hai-Yang
PROCEEDINGS OF 2006 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2006, : 330 - +
[4] Multi-Agent Reinforcement Learning for Traffic Signal Control: A Cooperative Approach
Kolat, Mate
Kovari, Balint
Becsi, Tamas
Aradi, Szilard
SUSTAINABILITY, 2023, 15 (04)
[5] Study on integration of urban traffic control and route guidance based on multi-agent technology
Li, RM
Shi, QX
2003 IEEE INTELLIGENT TRANSPORTATION SYSTEMS PROCEEDINGS, VOLS. 1 & 2, 2003, : 1740 - 1744
[6] Intersection-centric route guidance implementation for traffic simulation based on multi-agent
Zhi, Xiao-Fan
Liao, Zhi-Cheng
Zhang, Shi-Vong
PROCEEDINGS OF 2007 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2007, : 3844 - 3849
[7] A Cooperative Multi-Agent System in Traffic Control
Han Quanye
Wang Xiaoming
Dang Jianwu
PROCEEDINGS OF THE 27TH CHINESE CONTROL CONFERENCE, VOL 5, 2008, : 577 - 580
[8] A Multi-agent Based Approach for Railway Traffic Management Problems
Liu, Jin
Chen, Lei
Roberts, Clive
Li, Zhu
Wen, Tao
2018 INTERNATIONAL CONFERENCE ON INTELLIGENT RAIL TRANSPORTATION (ICIRT), 2018,
[9] An Intelligent Multi-agent Approach for Road Traffic Management Systems
Almejalli, Khaled
Dahal, Keshav
Hossain, Alamgir
2009 IEEE CONTROL APPLICATIONS CCA & INTELLIGENT CONTROL (ISIC), VOLS 1-3, 2009, : 825 - 830
[10] A multi-agent architecture for cooperative inter-jurisdictional traffic congestion management
Logi, F
Ritchie, SG
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2002, 10 (5-6) : 507 - 527

← 1 2 3 4 5 →