Decision-making Strategies for Automated Driving in Urban Environments
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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Decision-making Strategies for Automated Driving in Urban Environments
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.
109.99
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Decision-making Strategies for Automated Driving in Urban Environments
195
Decision-making Strategies for Automated Driving in Urban Environments
195Hardcover(1st ed. 2020)
$109.99
109.99
In Stock
Product Details
ISBN-13: | 9783030459048 |
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Publisher: | Springer International Publishing |
Publication date: | 04/26/2020 |
Series: | Springer Theses |
Edition description: | 1st ed. 2020 |
Pages: | 195 |
Product dimensions: | 6.10(w) x 9.25(h) x (d) |
About the Author
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