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Decision-making strategies for autom...

Artunedo, Antonio.

Decision-making strategies for automated driving in urban environments

Record Type:	Electronic resources : Monograph/item
Title/Author:	Decision-making strategies for automated driving in urban environmentsby Antonio Artunedo.
Author:	Artunedo, Antonio.
Published:	Cham :Springer International Publishing :2020.
Description:	xviii, 195 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Automated vehiclesDecision making.
Online resource:	https://doi.org/10.1007/978-3-030-45905-5
ISBN:	9783030459055$q(electronic bk.)

Decision-making strategies for automated driving in urban environments
Artunedo, Antonio.

Decision-making strategies for automated driving in urban environments[electronic resource] /by Antonio Artunedo. - Cham :Springer International Publishing :2020. - xviii, 195 p. :ill., digital ;24 cm. - Springer theses,2190-5053. - Springer theses..

Introduction -- Literature Overview -- Decision Making Architecture -- Global Planning and Mapping -- Motion Prediction and Manoeuvre Planning -- Optimal Trajectory Generation -- Integration and Demonstrations.

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.

ISBN: 9783030459055$q(electronic bk.)

Standard No.: 10.1007/978-3-030-45905-5doiSubjects--Topical Terms:

858838
Automated vehicles
--Decision making.

LC Class. No.: TL152.8 / .A788 2020

Dewey Class. No.: 629.046

Decision-making strategies for automated driving in urban environments
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245 1 0 $a Decision-making strategies for automated driving in urban environments $h [electronic resource] / $c by Antonio Artunedo.
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505 0 $a Introduction -- Literature Overview -- Decision Making Architecture -- Global Planning and Mapping -- Motion Prediction and Manoeuvre Planning -- Optimal Trajectory Generation -- Integration and Demonstrations.
520 $a 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.
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650 1 4 $a Robotics and Automation. $3 357111
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950 $a Intelligent Technologies and Robotics (Springer-42732)