A Decentralized Reinforcement Learning Controller For Collaborative Driving
Article comments
Copyright © 2006 IFAC. The definitive version is available at http://www.ifac-papersonline.net/Detailed/29815.html.
NOTE: At the time of publication, the author Christopher Clark was not yet affiliated with Cal Poly.
Abstract
Research in the collaborative driving domain strives to create control systems that coordinate the motion of multiple vehicles in order to navigate traffic both efficiently and safely. In this paper a novel individual vehicle controller based on reinforcement learning is introduced. This controller is capable of both lateral and longitudinal control while driving in a multi-vehicle platoon. The design and development of this controller is discussed in detail and simulation results showing learning progress and performance are presented.
Suggested Citation
Luke Ng, Christopher M. Clark, and Jan P. Huissoon. "A Decentralized Reinforcement Learning Controller For Collaborative Driving" Proceeings of the First IFAC Workshop on Multi-Vehicle Systems.. Oct. 2006.
Available at: http://works.bepress.com/cmclark/22