Traffic Flow Analysis Dovetailed with Evolutionary Game Theory
In this chapter, we concern ourselves with traffic flow as another meaningful example of a situation in which evolutionary game theory can be applied. Although the study of traffic flow was originally thought to be best explained using fluid dynamics, a multi-agent simulation technique that has been widely used in the field of evolutionary games has been applied to the problem, under the name of cellular automaton (CA). In this chapter, we first explain how traffic flow can be modeled. Next, we discuss how evolutionary game theory can be applied to this traffic flow. One can consider the dynamics of traffic flow to be like a multi-player game, with vehicles being controlled by drivers who compete to access to a road as a finite resource in order to reduce their personal travel time. This implies that traffic flow may change its phase depending on traffic density, and that it entails a social dilemma that might also change its game class, depending on the density. We reveal that various social dilemmas are hidden behind different aspects of traffic flows, which may be considered remarkable. Traffic flow is a game committed by agents – drivers, which seems some sort of human drama unlike we naturally think that traffic flow is governed by rigid physics because the theory of fluid dynamics, one of the representative hard-core physics fields, has been applied to it.
KeywordsTraffic Flow Social Dilemma Open Boundary Condition Evolutionary Game Theory Lane Change
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