Hierarchical Deep Reinforcement Learning with Cross-Attention and Planning for Autonomous Roundabout Navigation
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Authors
Montgomery, Bennet L.
Date
Type
thesis
Language
eng
Keyword
Reinforcement Learning , Deep Learning , Cross-Attention , Autonomous Vehicles , Planning , Roundabouts
Alternative Title
Abstract
Autonomous vehicle control is an important sub-field of autonomous vehicle research. Many challenges remain to improve the safety and performance of autonomous vehicle control systems in urban driving environments. One such urban driving environment is the roundabout junction, which presents its own unique challenges to potential solutions to autonomous vehicle control. This thesis proposes and tests a vehicle control agent as a candidate solution for urban roundabout navigation. The vehicle control agent is based on a hierarchical deep reinforcement learning architecture with a superior network selecting short-term lane-change behaviour and a subordinate network selecting longitudinal acceleration values. The road sequence followed by the agent is selected by a route planner based on Dijkstra’s algorithm. The proposed agent learns to navigate the roundabout environment safely, reaching the goal state in 100% of validation scenarios after training. The agent also outperforms an agent based on the Krauß-following model in 2 out of 5 tested metrics and matches the performance of the Krauß-following model in the remaining 3 metrics.
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Queen's University's Thesis/Dissertation Non-Exclusive License for Deposit to QSpace and Library and Archives Canada
ProQuest PhD and Master's Theses International Dissemination Agreement
Intellectual Property Guidelines at Queen's University
Copying and Preserving Your Thesis
This publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.
Attribution 4.0 International
ProQuest PhD and Master's Theses International Dissemination Agreement
Intellectual Property Guidelines at Queen's University
Copying and Preserving Your Thesis
This publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.
Attribution 4.0 International