Multi-routes algorithm using temperature control of Boltzmann distribution in Q value-based dynamic programming

In this paper, we propose a heuristic method trying to improve the efficiency of traffic systems in the global perspective, where the optimal traveling time for each origin-destination (OD) pair is calculated by extended Q value-based dynamic programming and the global optimum routes are produced by adjusting the temperature parameter in Boltzmann distribution. The key point is that the temperature parameter for each section is not identical, but constantly changing with the traffic of the section, which enables the diversified routing strategy depending on the latest traffics. In addition, the simulation results show that comparing with the greedy strategy and constant temperature parameter strategy, the proposed method, i.e., temperature parameter control strategy of the Q value-based dynamic programming with Boltzmann distribution, could reduce the traffic congestion effectively and minimize the negative impact of the information update interval by adopting suitable temperature parameter control strategy.