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dc.contributor.authorReschke, Johannes
dc.date.accessioned2022-10-10T12:51:36Z
dc.date.available2022-10-10T12:51:36Z
dc.date.issued2022
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/58529
dc.description.abstractEspecially pedestrians rely on the interaction with other road users. The introduction of automated driving systems withdraws this communication from drivers and thus, vehicles need to interact with pedestrians. Therefore, multiple vehicle-pedestrian-communication concepts are evaluated. A driver intention prediction allows pedestrians to learn these newly introduced signals, while driver and vehicle communicate simultaneously.en_US
dc.languageGermanen_US
dc.relation.ispartofseriesSpektrum der Lichttechniken_US
dc.subject.classificationthema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineeringen_US
dc.subject.otherFahrzeug-Fußgänger-Kommunikation; Symbole; Farben; Neuronale Netze; Automatisiertes Fahren; Vehicle-Pedestrian-Communication; Symbols; Colors; Neural Networks; Automated Drivingen_US
dc.titleFahrerintentionserkennung zur lichtbasierten Kommunikation mit Fußgängernen_US
dc.typebook
oapen.identifier.doi10.5445/KSP/1000145569en_US
oapen.relation.isPublishedBy44e29711-8d53-496b-85cc-3d10c9469be9en_US
oapen.collectionAG Universitätsverlage
oapen.series.number27en_US
oapen.pages266en_US
peerreview.anonymityAll identities known
peerreview.id51a542ec-eaeb-47c2-861d-6022e981a97a
peerreview.open.reviewNo
peerreview.publish.responsibilityBooks or series editor
peerreview.review.stagePre-publication
peerreview.review.typeFull text
peerreview.reviewer.typeEditorial board member
peerreview.reviewer.typeExternal peer reviewer
peerreview.titleDissertations in Series (Dissertationen in Schriftenreihe)


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