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020 _a9783658219543
_9978-3-658-21954-3
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082 0 4 _a629.892
_223
100 1 _aHeinrich, Steffen.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aPlanning Universal On-Road Driving Strategies for Automated Vehicles
_h[electronic resource] /
_cby Steffen Heinrich.
250 _a1st ed. 2018.
264 1 _aWiesbaden :
_bSpringer Fachmedien Wiesbaden :
_bImprint: Springer,
_c2018.
300 _aXV, 133 p. 59 illus., 25 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAutoUni - Schriftenreihe,
_x1867-3635 ;
_v119
500 _aAcceso multiusuario
505 0 _aA Framework for Universal Driving Strategy Planning -- Sampling-Based Planning in Phase Space -- A Universal Approach for Driving Strategies -- Modeling Ego Motion Uncertainty.
520 _aSteffen 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.
541 _fUABC ;
_cTemporal ;
_d01/01/2021-12/31/2023.
650 0 _aRobotics.
650 0 _aAutomation.
650 0 _aArtificial intelligence.
650 0 _aNumerical analysis.
650 1 4 _aRobotics and Automation.
_0https://scigraph.springernature.com/ontologies/product-market-codes/T19020
650 2 4 _aArtificial Intelligence.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I21000
650 2 4 _aNumeric Computing.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I1701X
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783658219536
776 0 8 _iPrinted edition:
_z9783658219550
830 0 _aAutoUni - Schriftenreihe,
_x1867-3635 ;
_v119
856 4 0 _zLibro electrónico
_uhttp://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-3-658-21954-3
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cLIBRO_ELEC
999 _c243158
_d243157