Abstract
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.
Highlights
T RAFFIC congestion in urban areas has been one of the serious problems all over the world because it causes both economic and time loss
We assume the travel time of each road e ∈ E follows Bureau of Public Roads (BPR) function te(fe) = te(1 + α(fe/ce)β ) [60]. te denotes the travel time without road congestion, which is proportional to the ratio of length to speed limit of road e. ce denotes the capacity of road e, which is proportional to the ratio of road e’s size, i.e., road width, to the size of a user. α and β represent the degree of road congestion
Traffic congestion in urban areas is mainly caused by selfish routing of users and results in considerable economic and time loss
Summary
T RAFFIC congestion in urban areas has been one of the serious problems all over the world because it causes both economic and time loss. It has been forecasted that traffic congestion will increase total costs of the four advanced economies, i.e., U.K., France, Germany, and the USA, by 46% from 2013 to 2030 [2]. Such a traffic congestion problem can be modeled as a congestion game in game theory [3]. Route selection by a certain user corresponds to the usage of roads included in the selected route. When all users select their own routes, the
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