Algorithms for the Traffic Light Setting Problem on the Graph M odel

As the number of vehicles increases rapidly, traffic congestion has become a serious problem in a city. The traffic light settingproblem is to investigate how to set the given traffic lights such that the total waiting time of vehicles on the roads is minimized. In this paper, we use a graph model to represent the traffic network. On this model, some characteristics of the setting problem are presented and analyzed. We first devise a branch and bound algorithm for obtaining the optimal solution of the traffic light setting problem. In addition, the genetic algorithm (GA), the particle swarm optimization (PSO) and the ant colony optimization (ACO) algorithm are also adopted to get the near optimal solution. Then, to extend this model, we add the assumption that each vehicle can change its direction. In our experiments, we also transform the map of Kaohsiung city into our graph model and test each algorithm on this graph. Our results show that GA seems to be a good strategy for setting traffic lights.

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