Abstract—Nowadays, most of the road navigation systems planning optimal routes are conducted by the On Board Unit (OBU). If drivers want to obtain the real-time road status, a Traffic Message Channel (TMC) module is needed. However, this module can only provide the current road conditions, instead of planning appropriate routes for users. In this work, the concept of the cellular automata is used to collect the real-time road conditions and derives the appropriate paths for users. Notably, fuzzy logic is adopted for path analysis for each cell established in the cellular automata algorithm. Besides establishing the optimal routes, this research is expected to automatically meet the personal demands of all drivers, reach the load balancing in all road sections to avoid the problem of traffic jams, and allow the drivers enjoy better driving experiences. A series of simulations were conducted to compare the proposed approach with the well-known A* Search algorithm and the latest state-of-the-art path planning algorithm in the literature. The experimental results exhibited that the proposed approach is scalable in terms of the turnaround time to individual users. The practicality and feasibility of applying the proposed approach in real-time environment is thus justified.

Index Terms—Search algorithm, cellular automata, fuzzy logic, optimal path planning.

The authors are with the Department of Computer Science and Information Engineering, National Dong Hwa University, Taiwan (e-mail: cjhuang@mail.ndhu.edu.tw).

Cite:Chenn-Jung Huang, Kai-Wen Hu, Yu-Wu Wang, Heng-Ming Chen, Han-Wen Tasi, and Sheng-Yuan Chien, "An Adaptive Vehicle Path Planning System," International Journal of Computer and Communication Engineering vol. 4, no. 1, pp. 50-56, 2015.