Implementation of Autonomous Parking with Two Path Planning Algorithms

Sammanfattning: In urban environments, many drivers find it difficult to park, calling for an autonomous system to step in. Two path planning algorithms, Hybrid A' and RRT' Reeds-Shepp, were compared in parking scenarios with a small model car both in simulation and implementation. Two scenarios were tested: the vehicle facing inwards and outwards from the parking space, the latter requiring the vehicle to change direction at some point. The Hybrid A' algorithm proved to be more reliable than RRT' Reeds-Shepp since the latter generates random paths, while the first found longer paths that were not as optimal. RRT' Reeds-Shepp found a path in the forward scenario 9 out 10 times and 4 out of 5 in the reverse scenario. The planned paths were tested with the Stanley controller. The front wheels were given as guiding wheels both in forward and reverse, which worked well in simulation. In implementation, the first scenario matched the simulation quite closely. In the second scenario in implementation, the model cars were not able follow the path when reversing with the front wheels as guiding wheels. In conclusion, one algorithm did not outshine other but it also depended on the scenario. However, it was not optimal to use the front axle as a reference in the reverse driving situation.