ACO-based traffic routing method with automated negotiation for connected vehiclesopen access
- Authors
- Tri-Hai Nguyen; Jung, Jason J.
- Issue Date
- Feb-2023
- Publisher
- SPRINGER HEIDELBERG
- Keywords
- Ant colony optimization; Automated negotiation; Connected vehicle; Traffic routing; Inverted pheromone
- Citation
- COMPLEX & INTELLIGENT SYSTEMS, v.9, no.1, pp 625 - 636
- Pages
- 12
- Journal Title
- COMPLEX & INTELLIGENT SYSTEMS
- Volume
- 9
- Number
- 1
- Start Page
- 625
- End Page
- 636
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/58579
- DOI
- 10.1007/s40747-022-00833-3
- ISSN
- 2199-4536
2198-6053
- Abstract
- Most traffic control systems are centralized, where all the collected data can be analyzed to make a decision. However, there are problems with computational complexity and, more seriously, real-time decision-making. This paper proposes a decentralized traffic routing system based on a new pheromone model of ant colony optimization algorithm and an automated negotiation technique in a connected vehicle environment. In particular, connected vehicles utilize a new pheromone model, namely the inverted pheromone model, which generates a repulsive force between vehicles and gives negative feedback to the congested roads. They also perform a collective learning-based negotiation process for distributing traffic flows throughout the road networks, reducing traffic congestion. Via extensive simulations based on the Simulation of Urban Mobility, the proposed system shows that it can significantly reduce travel time and fuel consumption compared to existing systems.
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Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
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