Abstract: In real-time environment, the traffic information is dynamic. This paper proposes a hybrid dynamic path optimization algorithm in real-time environment, which is based on A^* algorithm and combined with pruning algorithm. This paper also puts forward the optimization strategy by introducing the local optimal and global optimal intelligent storage of particle swarm optimization and fuzzy time window into the hybrid dynamic path optimization algorithm. The pruning threshold based on the local optimum is an effective way to control the size of the threshold. The fuzzy time window is applied to algorithm optimization time constraints and the control of the simulation time so that the algorithm can better adapt to the real-time environment. In order to verify the optimized strategy, simulation with the hybrid dynamic path optimization algorithm is conducted in which data is based on the New York map. Simulation results verify the effectiveness of the optimization strategy. Also the performance of the proposed algorithm is compared with the A^* algorithm, which demonstrate that the optimization strategy has certain adaptability and can be applied to Dynamic Route Guidance System (DRGS).

Key words: computer application, intelligent transportation system, dynamic route guidance system, route optimization algorithm, generalized adaptive A^* algorithm, pruning algorithm