Tactical decision-making for autonomous driving: A reinforcement learning approach
Licentiate thesis, 2019
genetic algorithm
Monte Carlo tree search
deep reinforcement learning
tactical decision-making
autonomous driving
neural network
Author
Carl-Johan E Hoel
Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Engineering and Autonomous Systems
An Evolutionary Approach to General-Purpose Automated Speed and Lane Change Behavior
Proceedings of 16th IEEE International Conference On Machine Learning And Applications (ICMLA),;(2017)
Paper in proceeding
Automated Speed and Lane Change Decision Making using Deep Reinforcement Learning
IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC,;(2018)p. 2148-2155
Paper in proceeding
C. J. Hoel, K. Driggs-Campbell, K. Wolff, L. Laine, and M. J. Kochenderfer, Combining planning and deep reinforcement learning in tactical decision making for autonomous driving
Areas of Advance
Information and Communication Technology
Transport
Subject Categories
Information Science
Robotics
Computer Science
Thesis for the degree of Licentiate – Department of Mechanics and Maritime Sciences: 2019:07
Publisher
Chalmers