Poster: Adaptive Astar Algorithm for Calculation Time Reduction of Autonomous Vehicle's Pathfinding
Y.W. Jeon, Daejin Park · 2024
With the development of autonomous driving, multi agent pathfinding is necessary. Because a little delay can cause a collision with a median strip or other vehicles, the pathfinding process must be fast and immediate. Many autonomous vehicle companies use the cloud for central processing because of complicated calculations, but using the cloud can cause delays and disconnection. So, edge-level pathfinding must also be executed together. The A * algorithm based on dijkstra is frequently used as the prototype of the pathfinding algorithm, but it is difficult to use as it is for autonomous driving. A proper transformation of A * is essential because A * is greedy algorithm that less useful in MAPF situation, and heuristics must be modified for purposes such as ‘using less memory’ or ‘reduction of calculation time’. This paper presents the adaptive A * algorithm that explores more nodes near the wall to reduce calculation time.