An Improved Local Dynamic Path Planning Algorithm for Autonomous Driving
| Autor: | Haiying Liu, Chen Huakang, Zhou Huiyuan, Chen Pengju, Jason Gu, Deng Lixia, Zhou Juanting |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
050210 logistics & transportation
0209 industrial biotechnology Computer science 05 social sciences Coordinate system 02 engineering and technology Computer Science::Robotics Set (abstract data type) 020901 industrial engineering & automation 0502 economics and business Obstacle avoidance Line (geometry) Path (graph theory) Motion planning Algorithm Arc length Cubic function |
| Zdroj: | ROBIO |
| DOI: | 10.1109/robio49542.2019.8961468 |
| Popis: | In this paper, an improved autonomous driving local dynamic path planning algorithm is proposed. Based on the predefined road center points, a set of path control points is constructed, and a one-dimensional cubic equation is used to fit the path and construct a center line. A new curved coordinate system is provided using the center line, and the path candidates are generated by arc length and lateral offset. The overall path is selected in consideration of the total cost of path safety and comfort. The results showed that under different scenarios, the proposed local path planning algorithm can plan an optimal path that does not collide with static obstacles, and can ensure the comfort of autonomous driving vehicles and the real-time path planning. |
| Databáze: | OpenAIRE |
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