Temperature parameter control using RasID algorithm in Q value-based Dynamic programming with Boltzmann distribution

This paper proposes a global traffic control method, Q Value-based Dynamic Programming with Boltzmann distribution to improve the efficiency of Intelligent Transportation System. Three kinds of temperature parameter control strategies have been designed to improve the optimal route search problems. In addition, Random Search with Intensification and Diversification(RasID) is used to optimize the parameters of these three temperature control strategies. The simulation results show that the proposed method could get more suitable parameter sets for improving the efficiency of the traffic system under different traffic environment conditions.