東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁 到查詢結果 [ subject:"Numeric Computing." ]

切換: 標籤 | MARC模式 | ISBD

Planning universal on-road driving s...

Heinrich, Steffen.

FindBook

Google Book

Amazon

博客來

Planning universal on-road driving strategies for automated vehicles

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Planning universal on-road driving strategies for automated vehicles/ by Steffen Heinrich.
作者:	Heinrich, Steffen.
出版者:	Wiesbaden :Springer Fachmedien Wiesbaden : : 2018.,
面頁冊數:	xv, 133 p. :ill. (some col.), digital ;24 cm.
內容註:	A Framework for Universal Driving Strategy Planning -- Sampling-Based Planning in Phase Space -- A Universal Approach for Driving Strategies -- Modeling Ego Motion Uncertainty.
Contained By:	Springer eBooks
標題:	Autonomous vehicles. -
電子資源:	http://dx.doi.org/10.1007/978-3-658-21954-3
ISBN:	9783658219543

Planning universal on-road driving strategies for automated vehicles
Heinrich, Steffen.

Planning universal on-road driving strategies for automated vehicles[electronic resource] /by Steffen Heinrich. - Wiesbaden :Springer Fachmedien Wiesbaden :2018. - xv, 133 p. :ill. (some col.), digital ;24 cm. - AutoUni-schriftenreihe ;Band 119. - AutoUni-schriftenreihe ;Band 119..

A Framework for Universal Driving Strategy Planning -- Sampling-Based Planning in Phase Space -- A Universal Approach for Driving Strategies -- Modeling Ego Motion Uncertainty.

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. Contents A Framework for Universal Driving Strategy Planning Sampling-Based Planning in Phase Space A Universal Approach for Driving Strategies Modeling Ego Motion Uncertainty Target Groups Scientists and students in the field of robotics, computer science, mechanical engineering Engineers in the field of vehicle automation, intelligent systems and robotics 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.

ISBN: 9783658219543

Standard No.: 10.1007/978-3-658-21954-3doiSubjects--Topical Terms:

2179092
Autonomous vehicles.

LC Class. No.: TL152.8 / .H456 2018

Dewey Class. No.: 629.22

Planning universal on-road driving strategies for automated vehicles
LDR:02774nmm a2200337 a 4500 001 2142143
003 DE-He213
005 20181112092253.0
006 m d
007 cr nn 008maaau
008 181214s2018 gw s 0 eng d
020 $a 9783658219543 $q (electronic bk.)
020 $a 9783658219536 $q (paper)
024 7 $a 10.1007/978-3-658-21954-3 $2 doi
035 $a 978-3-658-21954-3
040 $a GP $c GP
041 0 $a eng
050 4 $a TL152.8 $b .H456 2018
072 7 $a TJFM1 $2 bicssc
072 7 $a TEC037000 $2 bisacsh
072 7 $a TEC004000 $2 bisacsh
082 0 4 $a 629.22 $2 23
090 $a TL152.8 $b .H469 2018
100 1 $a Heinrich, Steffen. $3 3321510
245 1 0 $a Planning universal on-road driving strategies for automated vehicles $h [electronic resource] / $c by Steffen Heinrich.
260 $a Wiesbaden : $b Springer Fachmedien Wiesbaden : $b Imprint: Springer, $c 2018.
300 $a xv, 133 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a AutoUni-schriftenreihe ; $v Band 119
505 0 $a A Framework for Universal Driving Strategy Planning -- Sampling-Based Planning in Phase Space -- A Universal Approach for Driving Strategies -- Modeling Ego Motion Uncertainty.
520 $a 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. Contents A Framework for Universal Driving Strategy Planning Sampling-Based Planning in Phase Space A Universal Approach for Driving Strategies Modeling Ego Motion Uncertainty Target Groups Scientists and students in the field of robotics, computer science, mechanical engineering Engineers in the field of vehicle automation, intelligent systems and robotics 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.
650 0 $a Autonomous vehicles. $3 2179092
650 0 $a Driver assistance systems. $3 1569172
650 1 4 $a Engineering. $3 586835
650 2 4 $a Robotics and Automation. $3 1066695
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 890894
650 2 4 $a Numeric Computing. $3 892606
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a AutoUni-schriftenreihe ; $v Band 119. $3 3321511
856 4 0 $u http://dx.doi.org/10.1007/978-3-658-21954-3
950 $a Engineering (Springer-11647)