Back to Search
Start Over
A Double-Layer Model Predictive Control Approach for Collision-Free Lane Tracking of On-Road Autonomous Vehicles.
- Source :
- Actuators; Apr2023, Vol. 12 Issue 4, p169, 19p
- Publication Year :
- 2023
-
Abstract
- This paper proposes a double-layer model predictive control (MPC) algorithm for the integrated path planning and trajectory tracking of autonomous vehicles on roads. The upper module is responsible for generating collision-free lane trajectories, while the lower module is responsible for tracking this trajectory. A simplified vehicle model based on the friction cone is proposed to reduce the computation time for trajectory planning in the upper layer module. To achieve dynamic and accurate collision avoidance, a polygonal distance-based dynamic obstacle avoidance method is proposed. A vertical load calculation method for the tires is introduced to design the anti-rollover constraint in the lower layer module. Numerical simulations, with static and dynamic obstacle scenarios, are conducted on the MATLAB platform and compared with two state-of-the-art MPC algorithms. The results demonstrate that the proposed algorithm outperforms the other two algorithms regarding computation time and collision avoidance efficiency. [ABSTRACT FROM AUTHOR]
- Subjects :
- PREDICTION models
AUTONOMOUS vehicles
SCHEDULING
VEHICLE models
COMPUTER simulation
Subjects
Details
- Language :
- English
- ISSN :
- 20760825
- Volume :
- 12
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Actuators
- Publication Type :
- Academic Journal
- Accession number :
- 163378595
- Full Text :
- https://doi.org/10.3390/act12040169