Road traffic optimisation using an evolutionary game

  • Authors:
  • Syed Md. Galib;Irene Moser

  • Affiliations:
  • Swinburne University of Technology, Australia, Melbourne, Australia;Swinburne University of Technology, Australia, Melbourne, Australia

  • Venue:
  • Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
  • Year:
  • 2011

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Abstract

In a commuting scenario, drivers expect to arrive at their destinations on time. Drivers have an expectation as to how long it will take to reach the destination. To this end, drivers make independent decisions regarding the routes they take. Independent decision-making is uncoordinated and unlikely to lead to a balanced usage of the road network. However, a well-balanced traffic situation is in the best interest of all drivers, as it minimises their travel times on average over time. This study investigates the possibility of using an Evolutionary Game, Minority Game (MG), to achieve a balanced usage of a road network through independent decisions made by drivers assisted by the MG algorithm. The experimental results show that this simple game-theoretic approach can achieve a near-optimal distribution of traffic in a network. An optimal distribution can be assumed to lead to equitable travel times which are close to the possible minimum considering the number of cars in the network.