Planning Universal On-Road Driving Strategies for Automated Vehicles (Paperback, 1st ed. 2018)

Steffen Heinrich describes a motion planning system for automated vehicles. The planning method is universally applicable to on-road scenarios and does not depend on a high-level maneuver selection automation for driving strategy guidance. The author presents a planning framework using graphics processing units (GPUs) for task parallelization. A method is introduced that solely uses a small set of rules and heuristics to generate driving strategies. It was possible to show that GPUs serve as an excellent enabler for real-time applications of trajectory planning methods. Like humans, computer-controlled vehicles have to be fully aware of their surroundings. Therefore, a contribution that maximizes scene knowledge through smart vehicle positioning is evaluated. A post-processing method for stochastic trajectory validation supports the search for longer-term trajectories which take ego-motion uncertainty into account. About the Author Steffen Heinrich has a strong background in robotics and artificial intelligence. Since 2009 he has been developing algorithms and software components for self-driving systems in research facilities and for automakers in Germany and the US.

General

Imprint:	Springer
Country of origin:	Netherlands
Series:	AutoUni - Schriftenreihe, 119
Release date:	April 2018
First published:	2018
Authors:	Steffen Heinrich
Dimensions:	210 x 148mm (L x W)
Format:	Paperback
Pages:	133
Edition:	1st ed. 2018
ISBN-13:	978-3-658-21953-6
Categories:	Books > Professional & Technical > Transport technology > Intelligent & automated transport system technology Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Computing & IT > Applications of computing > Artificial intelligence > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > Robotics Promotions
LSN:	3-658-21953-X
Barcode:	9783658219536

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