Abstract
This paper analyzes the path planning problem in the automatic parking process, and studies a path planning method for automatic parking. The grid method and the ant colony optimization are combined to find the shortest path from the parking start point to the end point. The grid method is used to model the parking environment to simulate the actual parking space of automatic parking; then this paper makes some improvements to the basic ant colony optimization, finds the destination by setting the ants’ movement rules in the grid, and finds the shortest path after N iterations; since the optimal path found is a polyline, it will increase the difficulty of controlling vehicle path tracking and affect the accuracy of vehicle path tracking. The bezier curve is used to generate a smooth path suitable for vehicle walking. Finally, through matlab simulation, the obstacles in the environment are simulated, and the parking trajectory is obtained. The results show that the path planning method proposed in this paper is feasible.
Highlights
IntroductionThe problem of automatic parking path planning is to find a better movement path from the parking start point to the end point in the known parking environment, so that the vehicle can reach the expected parking location safely and without collision during the movement
The problem of automatic parking path planning is to find a better movement path from the parking start point to the end point in the known parking environment, so that the vehicle can reach the expected parking location safely and without collision during the movement.The current research status of automatic parking path planning at home and abroad is as follows: Piao CH, Zhang L, Lu S [1] and others combined the actual environment and used several arcs to form an automatic parking trajectory
In view of the shortcomings of the above-mentioned automatic parking path, this paper conducts a new research on the automatic parking algorithm, and proposes a more adaptable solution, which combines the ant colony optimization with the grid method to find the shortest path from a starting point to the end point, and the bezier curve function is added to obtain a trajectory that allows the vehicle to park, which can effectively increase the range for the driver to find the starting parking position, and avoid obstacles when other obstacles are involved in the parking environment, which increases the adaptability of automatic parking to the environment
Summary
The problem of automatic parking path planning is to find a better movement path from the parking start point to the end point in the known parking environment, so that the vehicle can reach the expected parking location safely and without collision during the movement. In view of the shortcomings of the above-mentioned automatic parking path, this paper conducts a new research on the automatic parking algorithm, and proposes a more adaptable solution, which combines the ant colony optimization with the grid method to find the shortest path from a starting point to the end point, and the bezier curve function is added to obtain a trajectory that allows the vehicle to park, which can effectively increase the range for the driver to find the starting parking position, and avoid obstacles when other obstacles are involved in the parking environment, which increases the adaptability of automatic parking to the environment
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