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Titel:

Roadside LiDAR Sensors for Data Privacy Conform VRU Detection

Dokumenttyp:
Konferenzbeitrag
Art des Konferenzbeitrags:
Textbeitrag / Aufsatz
Autor(en):
Ilic, Mario; Margreiter, Martin; Alvarez-Ossorio, Santiago; Pechinger, Mathias; Bogenberger, Klaus
Seitenangaben Beitrag:
340-343
Kapitel Beitrag:
Category 14: Safety
Abstract:
Detailed and reliable data is crucial to ensure the efficient, reliable, and safe operation of future transportation networks. However, the more detailed the information about traffic participants is, the less data privacy regarding individual mobility patterns or identification of individuals is typically guaranteed. This work presents the use of roadside LiDAR sensors for the detection and tracking of vulnerable road users (VRU) and vehicles in a privacy-compliant way based on an exemplary har...     »
Stichworte:
LiDAR, Light Detection and Ranging, VRU, Vulnerable Road Users, Data Collection
Kongress- / Buchtitel:
9th International Symposium on Transportation Data & Modelling (ISTDM2023)
Ausrichter der Konferenz:
Joint Research Center JRC
Datum der Konferenz:
2023-06-20
Jahr:
2023
Reviewed:
ja
Sprache:
en
WWW:
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TUM Einrichtung:
Lehrstuhl für Verkehrstechnik
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