UWSpace is currently experiencing technical difficulties resulting from its recent migration to a new version of its software. These technical issues are not affecting the submission and browse features of the site. UWaterloo community members may continue submitting items to UWSpace. We apologize for the inconvenience, and are actively working to resolve these technical issues.
 

A Potential Field-Based Model Predictive Path-Planning Controller for Autonomous Road Vehicles

Thumbnail Image

Files

IEEE ITS-final[1]-s.pdf (1.46 MB)

Date

2016-09-26

Authors

Rasekhipour, Yadollah
Khajepour, Amir
Chen, Shih-Ken
Litkouhi, Baktiar

Journal Title

Journal ISSN

Volume Title

Publisher

Institute of Electrical and Electronics Engineers

Abstract

Artificial potential fields and optimal controllers are two common methods for path planning of autonomous vehicles. An artificial potential field method is capable of assigning different potential functions to different types of obstacles and road structures and plans the path based on these potential functions. It does not, however, include the vehicle dynamics in the path-planning process. On the other hand, an optimal path-planning controller integrated with vehicle dynamics plans an optimal feasible path that guarantees vehicle stability in following the path. In this method, the obstacles and road boundaries are usually included in the optimal control problem as constraints and not with any arbitrary function. A model predictive path-planning controller is introduced in this paper such that its objective includes potential functions along with the vehicle dynamics terms. Therefore, the path-planning system is capable of treating different obstacles and road structures distinctly while planning the optimal path utilizing vehicle dynamics. The path-planning controller is modeled and simulated on a CarSim vehicle model for some complicated test scenarios. The results show that, with this path-planning controller, the vehicle avoids the obstacles and observes road regulations with appropriate vehicle dynamics. Moreover, since the obstacles and road regulations can be defined with different functions, the path-planning system plans paths corresponding to their importance and priorities.

Description

© IEEE 2017. Rasekhipour, Y., Khajepour, A., Chen, S.-K., & Litkouhi, B. (2016). A Potential Field-Based Model Predictive Path-Planning Controller for Autonomous Road Vehicles. IEEE Transactions on Intelligent Transportation Systems, 18(5), 1255–1267. https://doi.org/10.1109/TITS.2016.2604240

Keywords

Vehicles, Path Planning, Roads, Vehicle Dynamics, Predictive Models, Optimal Control, Collision Avoidance

LC Keywords

Citation

URI

https://doi.org/10.1109/TITS.2016.2604240
 http://hdl.handle.net/10012/11885

Collections

Waterloo Research
Mechanical and Mechatronics Engineering