Infrastructure-based Perception with Cameras and Radars for Cooperative Driving Scenarios
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Date
2024-07-15
Authors
Tsaregorodtsev, Alexander
Buchholz, Michael
Belagiannis, Vasileios
Journal Title
Journal ISSN
Volume Title
Publication Type
Beitrag zu einer Konferenz
Published in
2024 IEEE Intelligent Vehicles Symposium (IV), 2024
Abstract
Roadside infrastructure has enjoyed widespread adoption for various tasks such as traffic surveillance, traffic monitoring, control of traffic flow, and prioritization of public transit and emergency vehicles. As automated driving functions and vehicle communications continue to be researched, cooperative and connected driving scenarios can now be realized. Cooperative driving, however, imposes stringent environmental perception and model requirements. In particular, road users, including pedestrians and cyclists, must be reliably detected and accurately localized. Furthermore, the perception framework must have low latency to provide up-to-date information. In this work, we present a refined, camera-based reference point detector design that does not rely on annotated infrastructure datasets and incorporates fusion with cost-effective radar sensor data to increase system reliability, if available. The reference point detector design is realized with box and instance segmentation object detector models to extract object ground points. In parallel, objects are extracted from radar target data through a clustering pipeline and fused with camera object detections. To demonstrate the real-world applicability of our approaches for cooperative driving scenarios, we provide an extensive evaluation of data from a real test site.
Description
Faculties
Fakultät für Ingenieurwissenschaften, Informatik und Psychologie
Institutions
Institut für Mess-, Regel- und Mikrotechnik
Citation
DFG Project uulm
EU Project THU
PoDIUM / PDI connectivity and cooperation enablers building trust and sustainability for CCAM / EC / HE / 101069547
Other projects THU
LUKAS / Verbundprojekt: LUKAS - Lokales Umfeldmodell für das kooperative, automatisierte Fahren in komplexen Verkehrssituationen; Teilvorhaben: Infrastrukturseite Datenverarbeitung und kooperative Handlungsplanung / BMWi / 19A20004F
License
CC BY 4.0 International
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DOI external
DOI external
10.1109/IV55156.2024.10588604
Institutions
Periodical
Degree Program
DFG Project THU
item.page.thu.projectEU
item.page.thu.projectOther
Series
Keywords
Automatisiertes Fahren, Roadside Infrastructure, Autonomes Fahrzeug, Automated Vehicles, Cooperative Driving, Connected Driving, Vernetztes Fahren, Autonomes Fahrzeug, Automated vehicles, DDC 620 / Engineering & allied operations