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Decision-making strategies for autom...
~
Artunedo, Antonio.
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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 environments/ by Antonio Artunedo.
Author:
Artunedo, Antonio.
Published:
Cham :Springer International Publishing : : 2020.,
Description:
xviii, 195 p. :ill., digital ;24 cm.
[NT 15003449]:
Introduction -- Literature Overview -- Decision Making Architecture -- Global Planning and Mapping -- Motion Prediction and Manoeuvre Planning -- Optimal Trajectory Generation -- Integration and Demonstrations.
Contained By:
Springer eBooks
Subject:
Automated vehicles - Decision making. -
Online resource:
https://doi.org/10.1007/978-3-030-45905-5
ISBN:
9783030459055
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
Standard No.: 10.1007/978-3-030-45905-5doiSubjects--Topical Terms:
3451379
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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Introduction -- Literature Overview -- Decision Making Architecture -- Global Planning and Mapping -- Motion Prediction and Manoeuvre Planning -- Optimal Trajectory Generation -- Integration and Demonstrations.
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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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Intelligent Technologies and Robotics (Springer-42732)
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EB TL152.8 .A788 2020
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