Design of Simulation Program for Analysis of Shortest Path Algorithms in Grid-Based Path Planning

This study examines the analysis of algorithms used to find the shortest path between cells with different terrain types and elevation levels on a map comprising hexagonal cells ranging from 91 to 7651. A simulation program is designed for the analysis. The simulation program is implemented using the Unity 3D game engine and the C# programming language. The Unity game engine is used to design a map comprising hexagonal grid-based cells and visualize the simulation results of the shortest path finding algorithms. Each cell has neighborhood connections that determine the movement cost between cells. A smart agent is included in the simulation within the scope of the study. The smart agent perceives its environment, evaluates terrain type and elevation factors, and attempts to find the shortest path between two points with the lowest transition cost according to the selected algorithm. The performance of the algorithms is compared in terms of computation time, number of cells visited, and transition cost. The results demonstrate that the heuristic algorithms achieve high performance in terms of computation time and number of cells visited. However, it is seen that they cannot achieve the same success in terms of transition costs.