research-article

Inverse pheromone-based decentralized route guidance for connected vehicles

Authors:

Tri-Hai Nguyen,

Jason J. JungAuthors Info & Claims

SAC '21: Proceedings of the 36th Annual ACM Symposium on Applied Computing

Pages 459 - 463

https://doi.org/10.1145/3412841.3441925

Published: 22 April 2021 Publication History

Abstract

The increasing number of vehicles needs effective routing schemes to be introduced, which is a challenge due to the uncertainty of the traffic network. This paper, inspired by the ant colony optimization algorithm, proposes an inverse pheromone-based routing method to solve the dynamic traffic routing problem in the connected vehicle environment. Traditionally, the pheromone is used to attract other ants; however, the inverse pheromone represents the negative effect. Each connected vehicle is modeled as an ant that deposits its pheromones on the road segments. The more pheromone deposited on a road segment, the more congestion is in that road segment. The connected vehicles should then avoid the high congestion path and select a less congested road segment for travel. The proposed method is implemented in a decentralized traffic management system in which the connected vehicles share information to support route choice decision-making process. Results from simulations performed with a realistic map in the Simulation of Urban Mobility demonstrate that the proposed method outperforms the conventional pheromone-based routing method by reducing the average trip duration by 13% on average.

References

[1]

Parvaneh Asghari, Amir Masoud Rahmani, and Hamid Haj Seyyed Javadi. 2019. Internet of Things applications: A systematic review. Computer Networks 148 (2019), 241--261.

[2]

Christian Blum and Marco Dorigo. 2004. The hyper-cube framework for ant colony optimization. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 34, 2 (2004), 1161--1172.

Digital Library

[3]

Khac-Hoai Nam Bui and Jason J Jung. 2018. Internet of agents framework for connected vehicles: A case study on distributed traffic control system. J. Parallel and Distrib. Comput. 116 (2018), 89--95.

[4]

Khac-Hoai Nam Bui and Jason J Jung. 2019. ACO-based dynamic decision making for connected vehicles in IoT system. IEEE Transactions on Industrial Informatics 15, 10 (2019), 5648--5655.

[5]

Zhiguang Cao, Siwei Jiang, Jie Zhang, and Hongliang Guo. 2016. A unified framework for vehicle rerouting and traffic light control to reduce traffic congestion. IEEE transactions on intelligent transportation systems 18, 7 (2016), 1958--1973.

Digital Library

[6]

Shanzhi Chen, Hui Xu, Dake Liu, Bo Hu, and Hucheng Wang. 2014. A vision of IoT: Applications, challenges, and opportunities with china perspective. IEEE Internet of Things journal 1, 4 (2014), 349--359.

[7]

José Capela Dias, Penousal Machado, Daniel Castro Silva, and Pedro Henriques Abreu. 2014. An inverted ant colony optimization approach to traffic. Engineering Applications of Artificial Intelligence 36 (2014), 122--133.

Digital Library

[8]

Marco Dorigo, Mauro Birattari, and Thomas Stutzle. 2006. Ant colony optimization. IEEE computational intelligence magazine 1, 4 (2006), 28--39.

[9]

Kponyo Jerry, Kuang Yujun, Opare Kwasi, Zhang Enzhan, and Tebe Parfait. 2015. NetLogo implementation of an ant colony optimisation solution to the traffic problem. IET Intelligent Transport Systems 9, 9 (2015), 862--869.

[10]

Pablo Alvarez Lopez, Michael Behrisch, Laura Bieker-Walz, Jakob Erdmann, Yun-Pang Flötteröd, Robert Hilbrich, Leonhard Lücken, Johannes Rummel, Peter Wagner, and Evamarie WieBner. 2018. Microscopic traffic simulation using sumo. In 2018 21st International Conference on Intelligent Transportation Systems (ITSC). IEEE, IEEE, Maui, HI, USA, 2575--2582.

[11]

Ning Lu, Nan Cheng, Ning Zhang, Xuemin Shen, and Jon W Mark. 2014. Connected vehicles: Solutions and challenges. IEEE internet of things journal 1, 4 (2014), 289--299.

[12]

Tri-Hai Nguyen and Jason J Jung. 2020. ACO-based Approach on Dynamic MSMD Routing in IoV Environment. In 2020 16th International Conference on Intelligent Environments (IE). IEEE, IEEE, Madrid, Spain, 68--73.

[13]

Tri-Hai Nguyen and Jason J Jung. 2020. Multiple ACO-based method for solving dynamic MSMD traffic routing problem in connected vehicles. Neural Computing and Applications (2020), 1--10.

[14]

Tri-Hai Nguyen, Luong Vuong Nguyen, Jason J Jung,Israel Edem Agbehadji, Samuel Ofori Frimpong, and Richard C Millham. 2020. Bio-Inspired Approaches for Smart Energy Management: State of the Art and Challenges. Sustainability 12, 20 (2020), 8495.

[15]

Anirudh Paranjothi, Mohammad S Khan, and Sherali Zeadally. 2020. A survey on congestion detection and control in connected vehicles. Ad Hoc Networks 108 (2020), 102277.

[16]

Kian Lun Soon, Joanne Mun-Yee Lim, and Rajendran Parthiban. 2019. Coordinated Traffic Light Control in Cooperative Green Vehicle Routing for Pheromone-based Multi-Agent Systems. Applied Soft Computing 81 (2019), 105486.

[17]

Xin-She Yang, Suash Deb,Yu-Xin Zhao, Simon Fong, and Xingshi He. 2018. Swarm intelligence: past, present and future. Soft Computing 22, 18 (2018), 5923--5933.

Digital Library

[18]

Ouarda Zedadra, Antonio Guerrieri, Nicolas Jouandeau, Giandomenico Spezzano, Hamid Seridi, and Giancarlo Fortino. 2018. Swarm intelligence-based algorithms within IoT-based systems: A review. J. Parallel and Distrib. Comput. 122 (2018), 173--187.

Cited By

Liao SWu YMa KNiu Y(2024)Ant Colony Optimization With Look-Ahead Mechanism for Dynamic Traffic Signal Control of IoV SystemsIEEE Internet of Things Journal10.1109/JIOT.2023.328679911:1(366-377)Online publication date: 1-Jan-2024
https://doi.org/10.1109/JIOT.2023.3286799
Jung JNguyen LPark LNguyen T(2023)Cooperative Negotiation-Based Traffic Control for Connected Vehicles at Signal-Free IntersectionIntelligent Distributed Computing XV10.1007/978-3-031-29104-3_32(297-306)Online publication date: 9-Apr-2023
https://doi.org/10.1007/978-3-031-29104-3_32
Nguyen TJung J(2022)ACO-based traffic routing method with automated negotiation for connected vehiclesComplex & Intelligent Systems10.1007/s40747-022-00833-39:1(625-636)Online publication date: 27-Jul-2022
https://doi.org/10.1007/s40747-022-00833-3

Index Terms

Inverse pheromone-based decentralized route guidance for connected vehicles
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Cooperation and coordination
      2. Multi-agent systems

Recommendations

Development of a methodology to demonstrate the environmental impact of connected vehicles under lane-changing conditions

This paper describes a lane-change model for connected vehicles, and evaluates the environmental impact per road level of service (LOS) when a host vehicle makes a lane change. During manual driving, the host vehicle accelerates or decelerates to create ...
Multiple ACO-based method for solving dynamic MSMD traffic routing problem in connected vehicles
Abstract
In this study, we focus on dynamic traffic routing of connected vehicles with various origins and destinations; this is referred to as a multi-source multi-destination traffic routing problem. Ant colony optimization (ACO)-based routing method, ...
Real-Time Vehicle Route Guidance Based on Connected Vehicles
GREENCOM-ITHINGS-CPSCOM '13: Proceedings of the 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing

With advances in connected vehicle technology, real-time vehicle route guidance systems gradually become indispensable equipments for drivers. Conventional route guidance systems are designed to direct a vehicle along the shortest path from the origin ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

SAC '21: Proceedings of the 36th Annual ACM Symposium on Applied Computing

March 2021

2075 pages

ISBN:9781450381048

DOI:10.1145/3412841

Conference Chairs:
Chih-Cheng Hung
Kennesaw State University
,
Jiman Hong
Soongsil University, South Korea
,
Program Chairs:
Alessio Bechini
University of Pisa, Italy
,
Eunjee Song
Baylor University

Copyright © 2021 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGAPP: ACM Special Interest Group on Applied Computing

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 April 2021

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

National Research Foundation of Korea

Conference

SAC '21

Sponsor:

SIGAPP

SAC '21: The 36th ACM/SIGAPP Symposium on Applied Computing

March 22 - 26, 2021

Virtual Event, Republic of Korea

Acceptance Rates

Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
84
Total Downloads

Downloads (Last 12 months)23
Downloads (Last 6 weeks)3

Reflects downloads up to 17 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Liao SWu YMa KNiu Y(2024)Ant Colony Optimization With Look-Ahead Mechanism for Dynamic Traffic Signal Control of IoV SystemsIEEE Internet of Things Journal10.1109/JIOT.2023.328679911:1(366-377)Online publication date: 1-Jan-2024
https://doi.org/10.1109/JIOT.2023.3286799
Jung JNguyen LPark LNguyen T(2023)Cooperative Negotiation-Based Traffic Control for Connected Vehicles at Signal-Free IntersectionIntelligent Distributed Computing XV10.1007/978-3-031-29104-3_32(297-306)Online publication date: 9-Apr-2023
https://doi.org/10.1007/978-3-031-29104-3_32
Nguyen TJung J(2022)ACO-based traffic routing method with automated negotiation for connected vehiclesComplex & Intelligent Systems10.1007/s40747-022-00833-39:1(625-636)Online publication date: 27-Jul-2022
https://doi.org/10.1007/s40747-022-00833-3

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents