- AutorIn
- Ali Mohammadi Department of Mechanics and Maritime Sciences, Chalmers University of Technology, Sweden
- Giulio B. PiccininiDepartment of Mechanics and Maritime Sciences, Chalmers University of Technology, Sweden
- Marco DozzaDepartment of Mechanics and Maritime Sciences, Chalmers University of Technology, Sweden
- Titel
- Understanding the interaction between cyclists and automated vehicles
- Untertitel
- Results from a cycling simulator study
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-824621
- Konferenz
- International Cycling Safety Conference (ICSC). Dresden, 08.-10. November 2022
- Quellenangabe
- Contributions to the 10th International Cycling Safety Conference 2022 (ICSC2022)
Herausgeber: Prof. Dr. Tibor Petzoldt
Herausgeber: Prof. Dr. Regine Gerike
Herausgeber: Juliane Anke
Herausgeber: Dr. Madlen Ringhand
Herausgeber: Bettina Schröter
Erscheinungsort: Dresden
Verlag: Technische Universität Dresden
Erscheinungsjahr: 2022
Seiten: 33-35 - Erstveröffentlichung
- 2022
- DOI
- https://doi.org/10.25368/2022.427
- Abstract (EN)
- Cycling as an active mode of transport is increasing across all Europe [1]. Multiple benefits are coming from cycling both for the single user and the society as a whole. With increasing cycling, we expect more conflicts to happen between cyclists and vehicles, as it is also shown by the increasing cyclists' share of fatalities, contrary to the passenger cars' share [2]. Understanding cyclists' behavioral patterns can help automated vehicles (AVs) to predict cyclist's behavior, and then behave safely and comfortably when they encounter them. As a result, developing reliable predictive models of cyclist behavior will help AVs to interact safely with cyclists.
- Freie Schlagwörter (DE)
- Interaktion mit Radfahrern, gefährdete Verkehrsteilnehmer, Berechnungsmodelle, automatisierte Fahrzeuge, ICSC
- Freie Schlagwörter (EN)
- cyclists' interaction, vulnerable road users, computational models, automated vehicles, ICSC
- Publizierende Institution
- Technische Universität Dresden, “Friedrich List” Faculty of Transport and Traffic Sciences, Institute of Transport Planning and Road Traffic
- URN Qucosa
- urn:nbn:de:bsz:14-qucosa2-824621
- Veröffentlichungsdatum Qucosa
- 19.12.2022
- Dokumenttyp
- Konferenzbeitrag
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
CC BY 4.0