Vincent Albert Wolff, M. Sc.
Vincent Albert Wolff, M. Sc.
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Appelstraße 9a
30167 Hannover
30167 Hannover
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Vincent Albert Wolff, M. Sc.
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Persönliche Informationen
Curriculum Vitae
Vincent Wolff completed his bachelor and master degree at Leibniz Universität Hannover in Computer Engineering, with a focus on communication technology and human-computer interaction. In his master thesis an application for interactive low-latency streaming via WebRTC was implemented.
Since October 2020 he works as a research assistant towards a doctoral degree at the Institute of Communication Technology. His research focuses on Car-to-X communication, especially in the field of collective perception.
Research Interests
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Car-to-X communication
- Collective and collaborative perception: Sharing sensor information between vehicles
- Track-to-track fusion
- Vulnerable Road User Perception
- Deployment of Infrastructure (Road Side Units)
Teaching
- Mobilkommunikation (SoSe 2021,2022,2023)
- Rechnernetze Labor WiSe 2023/2024
- Rechnernetze Labor WiSe 2020/2021
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Publikationsliste
Konferenzbeiträge
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(2024): Mitigating Vulnerable Road Users Occlusion Risk Via Collective Perception: An Empirical Analysis, Accepted for 35th IEEE Intelligent Vehicles Symposium 2024
DOI: 10.1109/IV55156.2024.10588697
arXiv: 2404.07753 -
(2024): An Application Layer Multi-Hop Collective Perception Service for Vehicular Adhoc Networks, 35th IEEE Intelligent Vehicles Symposium 2024
DOI: 10.1109/IV55156.2024.10588398
arXiv: 2404.07761 -
(2024): A Data-Driven Analysis of Vulnerable Road User Safety in Interaction with Connected Automated Vehicles, 15th IEEE Vehicular Networking Conference 2024
DOI: 10.1109/VNC61989.2024.10575978
arXiv: 2404.14935 -
(2024): Vulnerable Road User Clustering for Collective Perception Messages: Efficient Representation Through Geometric Shapes, 15th IEEE Vehicular Networking Conference 2024
DOI: 10.1109/VNC61989.2024.10575972
arXiv: 2404.14925 -
(2023): Enhancing Vulnerable Road User Awareness of Intelligent Transport Systems Through Relay and Aggregation of Collective Perception Messages with Road Side Units, Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems
DOI: 10.5220/0011973300003479 -
(2023): LiDaSim: A Lightweight Dataset-Based Simulation Framework for Vehicular Ad Hoc Networks, IEEE Vehicular Technology Conference (IEEE VTC-Fall 2023)
DOI: 10.1109/VTC2023-Fall60731.2023.10333499 -
(2022): Tracking Accuracy Based Generation Rules of Collective Perception Messages, IEEE ITSC 2022
DOI: 10.1109/ITSC55140.2022.9922147
Buchbeiträge
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(2024): Infrastructure-Assisted Collective Perception Service with Emphasis on Vulnerable Road User Perception, Smart Cities, Green Technologies, and Intelligent Transport Systems. Communications in Computer and Information Science, vol 1989.
DOI: 10.1007/978-3-031-70966-1_10
Diplom-/Masterarbeiten
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(2024): Implementation of a Vulnerable Road User Awareness Service With Adaption of Transmission Parameters for Safety Enhancement, MA, KN (Betreuer: Vincent Wolff)
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(2023): Implementierung eines Forwarding-basierten Collective Perception Service in Fahrzeug-Ad-hoc-Netzwerken, MA, KN (Betreuer: Vincent Wolff)
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(2022): Enhancing the Environmental Awareness of Intelligent Transport Systems using Car-to-X Communication, MA, KN (Betreuer: Vincent Wolff)
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(2020): Parameterization of WebRTC Framework for an Interactive Free-Viewpoint Streaming Application (Betreuer: Tilak Varisetty)
Studien-/Bachelorarbeiten
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(2022): Implementierung eines Infrastrukturgestützten Collective Perception Services und Vergleich verschiedener Regeln zur Generierung von Nachrichten, BA, KN (Betreuer: Vincent Wolff)
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Forschungsprojekte
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Zukunftslabor MobilitätDas Zukunftslabor Mobilität ist mit dem Ziel entstanden, die Entwicklung von Transportsystemen und mobilitätsunterstützenden IT-Systemen zu fördern, die sich in die bestehende Infrastruktur integrieren. Für zukünftige Verkehrsmodelle mit stetig wachsender Vernetzung werden Kommunikationskonzepte entwickelt.Leitung: Prof. Dr.-Ing. Thomas Vietor (Koordination)Team:Jahr: 2020Laufzeit: 5 Jahre
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