Publication Type
Journal Article
Version
publishedVersion
Publication Date
12-2017
Abstract
Arriving on time and total travel time are two important properties for vehicle routing. Existing route guidance approaches always consider them independently, because they may conflict with each other. In this article, we develop a semi-decentralized multiagent-based vehicle routing approach where vehicle agents follow the local route guidance by infrastructure agents at each intersection, and infrastructure agents perform the route guidance by solving a route assignment problem. It integrates the two properties by expressing them as two objective terms of the route assignment problem. Regarding arriving on time, it is formulated based on the probability tail model, which aims to maximize the probability of reaching destination before deadline. Regarding total travel time, it is formulated as a weighted quadratic term, which aims to minimize the expected travel time from the current location to the destination based on the potential route assignment. The weight for total travel time is designed to be comparatively large if the deadline is loose. Additionally, we improve the proposed approach in two aspects, including travel time prediction and computational efficiency. Experimental results on real road networks justify its ability to increase the average probability of arriving on time, reduce total travel time, and enhance the overall routing performance.
Keywords
Intelligent transportation systems, multiagent-based route guidance, arriving on time, probability tail model, total travel time
Discipline
Operations Research, Systems Engineering and Industrial Engineering | Transportation
Research Areas
Intelligent Systems and Optimization
Publication
ACM Transactions on Intelligent Systems and Technology
Volume
9
Issue
3
First Page
1
Last Page
21
ISSN
2157-6904
Identifier
10.1145/3078847
Publisher
Association for Computing Machinery (ACM)
Citation
CAO, Zhiguang; GUO, Hongliang; and ZHANG, Jie.
A multiagent-based approach for vehicle routing by considering both arriving on time and total travel time. (2017). ACM Transactions on Intelligent Systems and Technology. 9, (3), 1-21.
Available at: https://ink.library.smu.edu.sg/sis_research/8202
Copyright Owner and License
Publisher
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1145/3078847
Included in
Operations Research, Systems Engineering and Industrial Engineering Commons, Transportation Commons