research-article

Multiple ACO-based method for solving dynamic MSMD traffic routing problem in connected vehicles

Authors:

Tri-Hai Nguyen,

Jason J. JungAuthors Info & Claims

Neural Computing and Applications, Volume 33, Issue 12

Pages 6405 - 6414

https://doi.org/10.1007/s00521-020-05402-8

Published: 01 June 2021 Publication History

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, together with the idea of coloring ants, is proposed to solve the defined problem in a distributed manner. Using the concept of coloring ants, traffic flows of connected vehicles to different destinations can be distinguished. To evaluate the performance of the proposed method, we perform simulations on the multi-agent NetLogo platform. The simulation results indicate that the ACO-based routing method outperforms the shortest path-based routing method (i.e., given the same simulation period, the average travel time decreases by 8% on average and by 11% in the best case, whereas the total number of arrived vehicles increases by 13% on average and by 23% in the best case).

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Cited By

Xia QQiu SLiu MLin X(2024)Task planning of space debris removal based on a hierarchical exploration artificial bee colony algorithmNeural Computing and Applications10.1007/s00521-023-09399-836:12(6597-6612)Online publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1007/s00521-023-09399-8
Sun YWu ZMeng KZheng Y(2023)Vehicular Task Offloading and Job Scheduling Method Based on Cloud-Edge ComputingIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.330043724:12(14651-14662)Online publication date: 1-Dec-2023
https://dl.acm.org/doi/10.1109/TITS.2023.3300437
Guo LDai Q(2022)End-to-end variational graph clustering with local structural preservationNeural Computing and Applications10.1007/s00521-021-06639-734:5(3767-3782)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1007/s00521-021-06639-7

Index Terms

Multiple ACO-based method for solving dynamic MSMD traffic routing problem in connected vehicles
1. Computing methodologies
  1. Artificial intelligence
2. Theory of computation
  1. Design and analysis of algorithms

Index terms have been assigned to the content through auto-classification.

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Information

Published In

cover image Neural Computing and Applications

Neural Computing and Applications Volume 33, Issue 12

Jun 2021

887 pages

ISSN:0941-0643

EISSN:1433-3058

Issue’s Table of Contents

© Springer-Verlag London Ltd., part of Springer Nature 2020.

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 June 2021

Accepted: 24 September 2020

Received: 08 May 2020

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National Research Foundation of Korea

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Cited By

Xia QQiu SLiu MLin X(2024)Task planning of space debris removal based on a hierarchical exploration artificial bee colony algorithmNeural Computing and Applications10.1007/s00521-023-09399-836:12(6597-6612)Online publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1007/s00521-023-09399-8
Sun YWu ZMeng KZheng Y(2023)Vehicular Task Offloading and Job Scheduling Method Based on Cloud-Edge ComputingIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.330043724:12(14651-14662)Online publication date: 1-Dec-2023
https://dl.acm.org/doi/10.1109/TITS.2023.3300437
Guo LDai Q(2022)End-to-end variational graph clustering with local structural preservationNeural Computing and Applications10.1007/s00521-021-06639-734:5(3767-3782)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1007/s00521-021-06639-7

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