Abstract
Nowadays, the rapid development of intelligent navigation systems has profound impacts on the routing of traffic users. With the assistance of these intelligent navigation systems, traffic users can obtain more accurate information about a traffic network such as traffic capacities, feasible paths, congestion status, etc. In this paper, we focus on a game-theory-based traffic congestion analysis model which considers incomplete traffic information (e.g., variabilities of path information) generated by intelligent navigation systems. The variabilities of path information are treated as incomplete information associated with different subsets of arcs. We adopt the notions of user equilibrium with incomplete information (UEII) and system optimum with incomplete information (SOII) in this study. Based on these two new notions, we extend two classical theorems and combine them into a new model to analyze the relationship between UEII and SOII. Finally, numerical cases are given to illustrate the implication of UEII and SOII in practical implementations.
| Original language | English |
|---|---|
| Pages (from-to) | 1391-1404 |
| Number of pages | 14 |
| Journal | Journal of Combinatorial Optimization |
| Volume | 43 |
| Issue number | 5 |
| DOIs | |
| State | Published - Jul 2022 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2020, Springer Science+Business Media, LLC, part of Springer Nature.
Keywords
- Braess paradox
- Incomplete information
- Intelligent navigation systems
- System optimum
- Traffic congestion
- User equilibrium
ASJC Scopus subject areas
- Computer Science Applications
- Discrete Mathematics and Combinatorics
- Control and Optimization
- Computational Theory and Mathematics
- Applied Mathematics
