Decision-making Strategies for Automated Driving in Urban Environments (Hardcover, 1st ed. 2020)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Springer Theses
Release date:	April 2020
First published:	2020
Authors:	Antonio Artunedo
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	195
Edition:	1st ed. 2020
ISBN-13:	978-3-03-045904-8
Categories:	Books > Professional & Technical > Civil engineering, surveying & building > Highway & traffic engineering Books > Business & Economics > Business & management > Management & management techniques > Operational research Books > Business & Economics > Business & management > Management & management techniques > Management decision making > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > Robotics Promotions
LSN:	3-03-045904-7
Barcode:	9783030459048

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