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Titel:

Predicting Pedestrian Crossing Intention at Signalized Intersections Using Roadside LiDAR Sensors

Dokumenttyp:
Konferenzbeitrag
Art des Konferenzbeitrags:
Textbeitrag / Aufsatz
Autor(en):
Álvarez-Ossorio Martinez, Santiago; Margreiter, Martin
Abstract:
Detecting, tracking, and predicting pedestrians crossing intention as they approach an intersection could increase the safety and efficiency of signalized intersections. LiDAR (Light Detection And Ranging) traffic sensors, capable of detecting, classifying and tracking objects, could play an essential role in multimodal intelligent infrastructure. In particular, they could complement or even substitute existing traffic sensors such as inductive loops or pedestrian push-buttons. In this paper, w...     »
Stichworte:
roadside LiDAR, pedestrian crossing intention, signalized intersection, pedestrian prediction
Dewey-Dezimalklassifikation:
620 Ingenieurwissenschaften
Herausgeber:
The National Academies of Sciences, Engineering, and Medicine
Kongress- / Buchtitel:
102nd Annual Meeting of the Transportation Resarch Board (TRBAM)
Datum der Konferenz:
08.01. - 12.01.2023
Publikationsdatum:
10.01.2023
Jahr:
2023
Sprache:
en
TUM Einrichtung:
Lehrstuhl für Verkehrstechnik
Format:
Text
 BibTeX