A Motion Planning Method for Automated Vehicles in Dynamic Traffic Scenarios
Open Access
- 21 January 2022
- Vol. 14 (2), 208
- https://doi.org/10.3390/sym14020208
Abstract
We propose a motion planning method for automated vehicles (AVs) to complete driving tasks in dynamic traffic scenes. The proposed method aims to generate motion trajectories for an AV after obtaining the surrounding dynamic information and making a preliminary driving decision. The method generates a reference line by interpolating the original waypoints and generates optional trajectories with costs in a prediction interval containing three dimensions (lateral distance, time, and velocity) in the Frenet frame, and filters the optimal trajectory by a series of threshold checks. When calculating the feasibility of optional trajectories, the cost of all optional trajectories after removing obstacle interference shows obvious axisymmetric regularity concerning the reference line. Based on this regularity, we apply the constrained Simulated Annealing Algorithm (SAA) to improve the process of searching for the optimal trajectories. Experiments in three different simulated driving scenarios (speed maintaining, lane changing, and car following) show that the proposed method can efficiently generate safe and comfortable motion trajectories for AVs in dynamic environments. Compared with the method of traversing sampling points in discrete space, the improved motion planning method saves 70.23% of the computation time, and overcomes the limitation of the spatial sampling interval.Keywords
Funding Information
- Graduate Innovation Fund of Jilin University (101832020CX149)
This publication has 22 references indexed in Scilit:
- Drivers’ Visual Behavior-Guided RRT Motion Planner for Autonomous On-Road DrivingSensors, 2016
- A Review of Motion Planning Techniques for Automated VehiclesIEEE Transactions on Intelligent Transportation Systems, 2015
- Real-time motion planning methods for autonomous on-road driving: State-of-the-art and future research directionsTransportation Research Part C: Emerging Technologies, 2015
- Optimal trajectories for time-critical street scenarios using discretized terminal manifoldsThe International Journal of Robotics Research, 2011
- Path Planning for Autonomous Vehicles in Unknown Semi-structured EnvironmentsThe International Journal of Robotics Research, 2010
- A perception‐driven autonomous urban vehicleJournal of Field Robotics, 2008
- Junior: The Stanford entry in the Urban ChallengeJournal of Field Robotics, 2008
- Using interpolation to improve path planning: The Field D* algorithmJournal of Field Robotics, 2006
- Reactive Nonholonomic Trajectory Generation via Parametric Optimal ControlThe International Journal of Robotics Research, 2003
- A note on two problems in connexion with graphsNumerische Mathematik, 1959