Overview
- Nominated as an outstanding PhD thesis by Universidad Politécnica de Madrid, Spain
- Proposes a novel decision-making and planning architecture for autonomous vehicle navigation
- Describes both theoretical and experimental validations on real urban-like environments
Part of the book series: Springer Theses (Springer Theses)
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Table of contents (8 chapters)
Keywords
- Urban Automated Driving
- Autonomous Driving Navigation
- Routing and Planning Architecture
- Obstacle Avoidance Motion Planning
- Global Planning Capabilities
- Local Planning Capabilities
- Automatic Road Corridor Generation Algorithm
- Vision-based Road Corridor Adaptation Algorithm
- Optimal Motion Planning
- Optimal Path Planning
- Risk Estimation Algorithms
- Inverse Perspective Mapping
- Motion Planning
- Dynamic and Uncertain Environments
- Trajectory Planning in Dynamic Environment
- Trajectory Optimization Algorithm
- Self-generated Driving Corridors
- OSM-based Navigation
- AUTOPIA Architecture
- LiDAR-based Perception
About this book
This book describes an effective decision-making and planning architecture for enhancing the navigation capabilities of automated vehicles in the presence of non-detailed, open-source maps. The system involves dynamically obtaining road corridors from map information and utilizing a camera-based lane detection system to update and enhance the navigable space in order to address the issues of intrinsic uncertainty and low-fidelity. An efficient and human-like local planner then determines, within a probabilistic framework, a safe motion trajectory, ensuring the continuity of the path curvature and limiting longitudinal and lateral accelerations. LiDAR-based perception is then used to identify the driving scenario, and subsequently re-plan the trajectory, leading in some cases to adjustment of the high-level route to reach the given destination. The method has been validated through extensive theoretical and experimental analyses, which are reported here in detail.
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Decision-making Strategies for Automated Driving in Urban Environments
Authors: Antonio Artuñedo
Series Title: Springer Theses
DOI: https://doi.org/10.1007/978-3-030-45905-5
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-45904-8Published: 26 April 2020
Softcover ISBN: 978-3-030-45907-9Published: 26 April 2021
eBook ISBN: 978-3-030-45905-5Published: 25 April 2020
Series ISSN: 2190-5053
Series E-ISSN: 2190-5061
Edition Number: 1
Number of Pages: XVIII, 195
Number of Illustrations: 9 b/w illustrations, 108 illustrations in colour
Topics: Robotics and Automation, Transportation Technology and Traffic Engineering, Operations Research/Decision Theory