Traffic congestion in urban areas causes economic and time loss. Such traffic congestion is caused by selfish routing where users aim to minimize their own travel time. Even if a navigation system provides them with recommended routes, they may not follow the routes, due to dissatisfaction with the expected travel time. In this article, inspired by the concept of ``Nudge,'' we propose ``selfish yet optimal routing,'' where all users rationally aim to minimize their own travel time but social optimal routing emerges from such selfish routing by adjusting their perceived traffic information appropriately. We propose a scheme to derive nudging traffic information that fills the gap between selfish routing criterion and altruistic one by internalizing the marginal cost into the perceived traffic information. Users will conduct the selfish routing under their perceived traffic information, which unconsciously results in the optimal routing. Through numerical experiments using both the artificial road network and the real one, we show that the proposed scheme achieves almost the same performance compared with the optimal routing. In addition, the proposed scheme reduces the average travel time by 19.1% compared with notification of actual traffic information, in case of the central-area road network of Nagoya city, Japan.
Takanori Hara, Masahiro Sasabe, Shoji Kasahara, Selfish Yet Optimal Routing by Adjusting Perceived Traffic Information of Road Networks, IEEE Open Journal of Intelligent Transportation Systems, 1, pp.120-133, September 2020.
@article{hara20SelfishOptimalRouting,
author = "Hara, Takanori and Sasabe, Masahiro and Kasahara, Shoji",
title = "Selfish {{Yet Optimal Routing}} by {{Adjusting Perceived Traffic Information}} of {{Road Networks}}",
year = "2020",
month = "September",
journal = "IEEE Open Journal of Intelligent Transportation Systems",
volume = "1",
pages = "120--133",
doi = "10.1109/OJITS.2020.3019935"
}