Local Path Planning of the Autonomous Vehicle Based on Adaptive Improved RRT Algorithm in Certain Lane Environments
Given that the rapidly exploring random tree algorithm (RRT) and its variants cannot efficiently solve problems of path planning of autonomous vehicles, this paper proposes a new, adaptive improved RRT algorithm. Firstly, an adaptive directional sampling strategy is introduced to avoid excessive sea...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-04-01
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| Series: | Actuators |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-0825/11/4/109 |
| _version_ | 1797437458104713216 |
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| author | Xiao Zhang Tong Zhu Yu Xu Haoxue Liu Fei Liu |
| author_facet | Xiao Zhang Tong Zhu Yu Xu Haoxue Liu Fei Liu |
| author_sort | Xiao Zhang |
| collection | DOAJ |
| description | Given that the rapidly exploring random tree algorithm (RRT) and its variants cannot efficiently solve problems of path planning of autonomous vehicles, this paper proposes a new, adaptive improved RRT algorithm. Firstly, an adaptive directional sampling strategy is introduced to avoid excessive search by reducing the randomness of sampling points. Secondly, a reasonable node selection strategy is used to improve the smoothness of the path by utilizing a comprehensive criterion that combines angle and distance. Thirdly, an adaptive node expansion strategy is utilized to avoid invalid expansion and make the generated path more reasonable. Finally, the expanded ellipse is used to realize vehicle obstacle avoidance in advance, and the post-processing strategy removes redundant line segments of the initial path to improve its quality. The simulation results show that the quality of the planned path is significantly improved. This path followed successfully has good trajectory stability, which shows the proposed algorithm’s effectiveness and practicability in autonomous vehicles’ local path planning. |
| first_indexed | 2024-03-09T11:20:36Z |
| format | Article |
| id | doaj.art-c9405f5a7bfe44f2a6e426e8ece0f97d |
| institution | Directory Open Access Journal |
| issn | 2076-0825 |
| language | English |
| last_indexed | 2024-03-09T11:20:36Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Actuators |
| spelling | doaj.art-c9405f5a7bfe44f2a6e426e8ece0f97d2023-12-01T00:21:25ZengMDPI AGActuators2076-08252022-04-0111410910.3390/act11040109Local Path Planning of the Autonomous Vehicle Based on Adaptive Improved RRT Algorithm in Certain Lane EnvironmentsXiao Zhang0Tong Zhu1Yu Xu2Haoxue Liu3Fei Liu4School of Automobile, Chang’an University, Xi’an 710064, ChinaCollege of Transportation Engineering, Chang’an University, Xi’an 710064, ChinaSchool of Automobile, Chang’an University, Xi’an 710064, ChinaSchool of Automobile, Chang’an University, Xi’an 710064, ChinaSchool of Automobile, Chang’an University, Xi’an 710064, ChinaGiven that the rapidly exploring random tree algorithm (RRT) and its variants cannot efficiently solve problems of path planning of autonomous vehicles, this paper proposes a new, adaptive improved RRT algorithm. Firstly, an adaptive directional sampling strategy is introduced to avoid excessive search by reducing the randomness of sampling points. Secondly, a reasonable node selection strategy is used to improve the smoothness of the path by utilizing a comprehensive criterion that combines angle and distance. Thirdly, an adaptive node expansion strategy is utilized to avoid invalid expansion and make the generated path more reasonable. Finally, the expanded ellipse is used to realize vehicle obstacle avoidance in advance, and the post-processing strategy removes redundant line segments of the initial path to improve its quality. The simulation results show that the quality of the planned path is significantly improved. This path followed successfully has good trajectory stability, which shows the proposed algorithm’s effectiveness and practicability in autonomous vehicles’ local path planning.https://www.mdpi.com/2076-0825/11/4/109path planningautonomous vehiclecollision avoidanceRRTpruning method |
| spellingShingle | Xiao Zhang Tong Zhu Yu Xu Haoxue Liu Fei Liu Local Path Planning of the Autonomous Vehicle Based on Adaptive Improved RRT Algorithm in Certain Lane Environments Actuators path planning autonomous vehicle collision avoidance RRT pruning method |
| title | Local Path Planning of the Autonomous Vehicle Based on Adaptive Improved RRT Algorithm in Certain Lane Environments |
| title_full | Local Path Planning of the Autonomous Vehicle Based on Adaptive Improved RRT Algorithm in Certain Lane Environments |
| title_fullStr | Local Path Planning of the Autonomous Vehicle Based on Adaptive Improved RRT Algorithm in Certain Lane Environments |
| title_full_unstemmed | Local Path Planning of the Autonomous Vehicle Based on Adaptive Improved RRT Algorithm in Certain Lane Environments |
| title_short | Local Path Planning of the Autonomous Vehicle Based on Adaptive Improved RRT Algorithm in Certain Lane Environments |
| title_sort | local path planning of the autonomous vehicle based on adaptive improved rrt algorithm in certain lane environments |
| topic | path planning autonomous vehicle collision avoidance RRT pruning method |
| url | https://www.mdpi.com/2076-0825/11/4/109 |
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