Tactical decision-making for autonomous driving: A reinforcement learning approach
Licentiatavhandling, 2019
genetic algorithm
Monte Carlo tree search
deep reinforcement learning
tactical decision-making
autonomous driving
neural network
Författare
Carl-Johan E Hoel
Chalmers, Mekanik och maritima vetenskaper, Fordonsteknik och autonoma system
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 i 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 i 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
Styrkeområden
Informations- och kommunikationsteknik
Transport
Ämneskategorier
Systemvetenskap
Robotteknik och automation
Datavetenskap (datalogi)
Thesis for the degree of Licentiate – Department of Mechanics and Maritime Sciences: 2019:07
Utgivare
Chalmers