TrafficGen: Learning to Generate Diverse and Realistic Traffic Scenarios-Reference-Cited by-同舟云学术

TrafficGen: Learning to Generate Diverse and Realistic Traffic Scenarios

Published:2023-05-29 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Robotics and Automation (ICRA)
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Author:

Feng Lan¹,Li Quanyi²,Peng Zhenghao³,Tan Shuhan⁴,Zhou Bolei³

Affiliation:

1. ETH Zurich

2. The University of Edinburgh

3. University of California,Los Angeles

4. The University of Texas at Austin

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10160211/10160212/10160296.pdf?arnumber=10160296

Reference32 articles.

1. General Lane-Changing Model MOBIL for Car-Following Models

2. Metasirn: Learning to generate synthetic datasets;kar;Proceedings of the IEEE International Conference on Computer Vision,2019

3. Drivergym: Democratising reinforcement learning for autonomous driving;kothari;ArXiv Preprint,2021

4. Enhanced intelligent driver model to access the impact of driving strategies on traffic capacity

5. Argoverse 2: Next generation datasets for self-driving perception and forecasting;wilson;Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 1),2021

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