probabilistic-motion-planning-for-automated-vehicles.pdf

In 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 s...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Γλώσσα:English
Έκδοση: KIT Scientific Publishing 2021
id oapen-20.500.12657-48815
record_format dspace
spelling oapen-20.500.12657-488152021-05-28T00:56:46Z Probabilistic Motion Planning for Automated Vehicles Naumann, Maximilian Bewegungsplanung Planung unter Unsicherheiten Entscheidungsfindung Automatisiertes Fahren POMDP Motion Planning Planning under Uncertainty Decision-Making Automated Vehicles bic Book Industry Communication::T Technology, engineering, agriculture::TG Mechanical engineering & materials In 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. 2021-05-27T09:28:02Z 2021-05-27T09:28:02Z 2021 book ONIX_20210527_9783731510703_12 1613-4214 9783731510703 https://library.oapen.org/handle/20.500.12657/48815 eng Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie application/pdf n/a probabilistic-motion-planning-for-automated-vehicles.pdf KIT Scientific Publishing 10.5445/KSP/1000126389 10.5445/KSP/1000126389 44e29711-8d53-496b-85cc-3d10c9469be9 9783731510703 44 194 Karlsruhe open access
institution OAPEN
collection DSpace
language English
description In 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.
title probabilistic-motion-planning-for-automated-vehicles.pdf
spellingShingle probabilistic-motion-planning-for-automated-vehicles.pdf
title_short probabilistic-motion-planning-for-automated-vehicles.pdf
title_full probabilistic-motion-planning-for-automated-vehicles.pdf
title_fullStr probabilistic-motion-planning-for-automated-vehicles.pdf
title_full_unstemmed probabilistic-motion-planning-for-automated-vehicles.pdf
title_sort probabilistic-motion-planning-for-automated-vehicles.pdf
publisher KIT Scientific Publishing
publishDate 2021
_version_ 1771297625553764352