- Titel
- A RoundD-like Roundabout Scenario in CARLA Simulator
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-859645
- Konferenz
- 4th Symposium on Management of Future Motorway and Urban Traffic Systems (MFTS). Dresden, 30. November - 2. Dezember
- Quellenangabe
- Proceedings of the 4th Symposium on Management of Future Motorway and Urban Traffic Systems 2022 - 9
Herausgeber: Wang, Meng
Herausgeber: Jaekel, Birgit
Herausgeber: Lehnert, Martin
Herausgeber: Zhou, Runhao
Herausgeber: Li, Zirui
Erscheinungsort: Dresden
Verlag: TUDpress
Erscheinungsjahr: 2023
Titel Schriftenreihe: Verkehrstelematik
Bandnummer Schriftenreihe: 9
Seiten: 69-76
ISBN: 978-3-95908-296-9 - DOI
- https://doi.org/10.25368/2023.100
- Abstract (EN)
- Evaluating the challenges and opportunities of cooperative autonomous vehicles (CAV) require an adapted simulation methodology reproducing realistic driving and sensory contexts. In this paper, we propose a RounD-like CARLA scenario reproducing in CARLA the driving context recorded in the RounD dataset. We focus in particular on roundabout scenarios, as they are considered particularly challenging for CAV. We present the methodology followed to generate the CARLA scenario and describe challenges to reproduce trajectories corresponding to RounD. Origin and destination of vehicles, waypoint and speed are extracted from RounD for CARLA vehicles to closely reproduce the driving patterns observed in RounD. The benefit of such scenario are manyfold, such as evaluating control algorithms of CAVs, deep AI reinforcement learning, or vehicular sensor data sampling under realistic driving contexts. It notably will reduce the gap of AI mechanisms for CAV between simulation scenarios and realistic conditions.
- Freie Schlagwörter (DE)
- Carla, Kreisverkehr, RounD, synthetisches Szenario, Verkehrssimulation für C-ITS
- Freie Schlagwörter (EN)
- Carla, roundabout, RounD, synthetic scenario, traffic simulation for C-ITS
- Klassifikation (DDC)
- 360
- Klassifikation (RVK)
- ZO 4620
- ZO 3100
- Herausgeber (Institution)
- Technische Universität Dresden
- Verlag
- TUDpress, Dresden
- URN Qucosa
- urn:nbn:de:bsz:14-qucosa2-859645
- Veröffentlichungsdatum Qucosa
- 23.06.2023
- Dokumenttyp
- Konferenzbeitrag
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
