Automated Speed and Lane Change Decision Making using Deep Reinforcement Learning

This paper introduces a method, based on deep reinforcement learning, for automatically generating a general purpose decision making function. A Deep Q-Network agent was trained in a simulated environment to handle speed and lane change decisions for a truck-trailer combination. In a highway driving...

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Vydané v:	Proceedings (IEEE Conference on Intelligent Transportation Systems) Ročník 2018-November; s. 2148 - 2155
Hlavní autori:	Hoel, Carl-Johan, Wolff, Krister, Laine, Leo
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.11.2018
Predmet:	Accelerated aging Artificial Intelligence (cs.AI) Decision making Machine Learning (cs.LG) Markov processes Neurons Roads Robotics (cs.RO)
ISBN:	9781728103211, 1728103215
ISSN:	2153-0009, 2153-0017, 2153-0017
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