Back to Search
Start Over
Path Planning and Tracking for Vehicle Collision Avoidance Based on Model Predictive Control With Multiconstraints.
- Source :
- IEEE Transactions on Vehicular Technology; Feb2017, Vol. 66 Issue 2, p952-964, 13p
- Publication Year :
- 2017
-
Abstract
- A path planning and tracking framework is presented to maintain a collision-free path for autonomous vehicles. For path-planning approaches, a 3-D virtual dangerous potential field is constructed as a superposition of trigonometric functions of the road and the exponential function of obstacles, which can generate a desired trajectory for collision avoidance when a vehicle collision with obstacles is likely to happen. Next, to track the planned trajectory for collision avoidance maneuvers, the path-tracking controller formulated the tracking task as a multiconstrained model predictive control (MMPC) problem and calculated the front steering angle to prevent the vehicle from colliding with a moving obstacle vehicle. Simulink and CarSim simulations are conducted in the case where moving obstacles exist. The simulation results show that the proposed path-planning approach is effective for many driving scenarios, and the MMPC-based path-tracking controller provides dynamic tracking performance and maintains good maneuverability. [ABSTRACT FROM PUBLISHER]
Details
- Language :
- English
- ISSN :
- 00189545
- Volume :
- 66
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Vehicular Technology
- Publication Type :
- Academic Journal
- Accession number :
- 121300899
- Full Text :
- https://doi.org/10.1109/TVT.2016.2555853