Parameters tuning using RasID algorithm in Q value-based Dynamic Programming with Boltzmann Distribution

In this paper, a new Temperature control strategy in the Q value-based Dynamic Programming with Boltzmann Distribution is proposed to improve the efficiency of Intelligent Transportation Systems. What's more, Random Search with Intensification and Diversification (RasID) is used to optimize the parameters of Temperature control strategy. The simulation results shows that more suitable parameters could be obtained by using RasID algorithm and consequently alleviate congestion and improve the efficiency of the traffic system.