Application of cellular automata and type-2 fuzzy logic to dynamic vehicle path planning

• To fulfill the real-time turnaround time requirement of path planning, this research proposes a novel dynamic optimal path planning method.
• The concept of the cellular automata is used to collect the real-time road conditions and derives the appropriate paths for users.
• A type-2 fuzzy logic inference system is employed for path analysis for each cell established in the cellular automata algorithm.
• The proposed work makes use of the hierarchical structure and the concept of the cellular automata to reduce the computational complexity.

Nowadays, most road navigation systems’ planning of optimal routes is conducted by the On Board Unit (OBU). If drivers want to obtain information about the real-time road conditions, a Traffic Message Channel (TMC) module is also needed. However, this module can only provide the current road conditions, as opposed to actually planning appropriate routes for users. In this work, the concept of cellular automata is used to collect real-time road conditions and derive the appropriate paths for users. Notably, type-2 fuzzy logic is adopted for path analysis for each cell established in the cellular automata algorithm. Besides establishing the optimal routes, our model is expected to be able to automatically meet the personal demands of all drivers, achieve load balancing between all road sections to avoid the problem of traffic jams, and allow drivers to 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 found in the literature. The experimental results demonstrate that the proposed approach is scalable in terms of the turnaround times for individual users. The practicality and feasibility of applying the proposed approach in the real-time environment is thus justified.

Figure optionsDownload as PowerPoint slide