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200 1 $aAutomatic differentiation$eTechnique and Application$fLouis B. Rall
210   $aBerlin$cSpringer-Verlag$d1981.
215   $aVIII, 165
225 1 $aLecture notes in computer science$v120
700  1$aRall,$bLouis B.$04717
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035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/70107
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100   $a20202105d2021      |y         0
101 0 $aeng
135   $aurmn|---annan
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aProbabilistic Motion Planning for Automated Vehicles
210   $aKarlsruhe$cKIT Scientific Publishing$d2021
215   $a1 online resource (194 p.)
225 1 $aSchriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie
311 08$a3-7315-1070-7 
330   $aIn motion planning for automated vehicles, a thorough uncertainty consideration is crucial to facilitate safe and convenient driving behavior. This work presents three motion planning approaches which are targeted towards the predominant uncertainties in different scenarios, along with an extended safety verification framework. The approaches consider uncertainties from imperfect perception, occlusions and limited sensor range, and also those in the behavior of other traffic participants.
606   $aMechanical engineering & materials$2bicssc
610   $aAutomated Vehicles
610   $aAutomatisiertes Fahren
610   $aBewegungsplanung
610   $aDecision-Making
610   $aEntscheidungsfindung
610   $aMotion Planning
610   $aPlanning under Uncertainty
610   $aPlanung unter Unsicherheiten
610   $aPOMDP
615  7$aMechanical engineering & materials
700   $aNaumann$b Maximilian$4auth$01319540
906   $aBOOK
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996   $aProbabilistic Motion Planning for Automated Vehicles$93033941
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