Schneider, Katharina (2018)
Object contrast determination based on peripheral Vision undernight-time driving conditions.
Technische Universität Darmstadt
Dissertation, Erstveröffentlichung
Kurzbeschreibung (Abstract)
The introduction of LED technologies into headlamp development has led to the systematic progress in headlamp design to improve visibility. Current LED light distributions consist of a specific number of horizontal and vertical segments, it tends to a spatially finely resolved adaptation of the light distribution, the so-called pixel light. This results in a much more precise light distribution, each segment can be individually controlled and dimmed. The aim of this technology is to be able to respond appropriately to the appearance of road users (pedestrians, wild animals or oncomingtraffic), firstly by reducing the light intensit yof the corresponding camera pixels in order to prevent glare and secondly to force it to the objects’ direction. The environment surrounding the traffic area element shall be illuminated in such a way as to achieve maximum visibility. The basis of this work is an investigation dealing with detection of objects in nighttime traffic in relation to vehicle lighting technology. The present study examines the foveal and peripheral vision by means of detection. The intention is to obtain an insight into the cognitive abilities and different areas within the visual field for different visual conditions in night-time road traffic.
Typ des Eintrags: | Dissertation | ||||
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Erschienen: | 2018 | ||||
Autor(en): | Schneider, Katharina | ||||
Art des Eintrags: | Erstveröffentlichung | ||||
Titel: | Object contrast determination based on peripheral Vision undernight-time driving conditions | ||||
Sprache: | Englisch | ||||
Referenten: | Khanh, Prof. Dr. Tran Quoc ; Schierz, Prof. Dr. Christoph | ||||
Publikationsjahr: | 17 Dezember 2018 | ||||
Ort: | Darmstadt | ||||
Datum der mündlichen Prüfung: | 17 Januar 2018 | ||||
URL / URN: | https://tuprints.ulb.tu-darmstadt.de/8300 | ||||
Kurzbeschreibung (Abstract): | The introduction of LED technologies into headlamp development has led to the systematic progress in headlamp design to improve visibility. Current LED light distributions consist of a specific number of horizontal and vertical segments, it tends to a spatially finely resolved adaptation of the light distribution, the so-called pixel light. This results in a much more precise light distribution, each segment can be individually controlled and dimmed. The aim of this technology is to be able to respond appropriately to the appearance of road users (pedestrians, wild animals or oncomingtraffic), firstly by reducing the light intensit yof the corresponding camera pixels in order to prevent glare and secondly to force it to the objects’ direction. The environment surrounding the traffic area element shall be illuminated in such a way as to achieve maximum visibility. The basis of this work is an investigation dealing with detection of objects in nighttime traffic in relation to vehicle lighting technology. The present study examines the foveal and peripheral vision by means of detection. The intention is to obtain an insight into the cognitive abilities and different areas within the visual field for different visual conditions in night-time road traffic. |
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URN: | urn:nbn:de:tuda-tuprints-83003 | ||||
Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau | ||||
Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Elektromechanische Konstruktionen (aufgelöst 18.12.2018) 18 Fachbereich Elektrotechnik und Informationstechnik > Lichttechnik (ab Okt. 2021 umbenannt in "Adaptive Lichttechnische Systeme und Visuelle Verarbeitung") |
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Hinterlegungsdatum: | 23 Dez 2018 20:55 | ||||
Letzte Änderung: | 23 Dez 2018 20:55 | ||||
PPN: | |||||
Referenten: | Khanh, Prof. Dr. Tran Quoc ; Schierz, Prof. Dr. Christoph | ||||
Datum der mündlichen Prüfung / Verteidigung / mdl. Prüfung: | 17 Januar 2018 | ||||
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