Leveraging vehicle connectivity and autonomy for highway bottleneck congestion mitigation using reinforcement learning-Reference-Cited by-同舟云学术

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Leveraging vehicle connectivity and autonomy for highway bottleneck congestion mitigation using reinforcement learning

Published:2023-05-25 Issue: Volume: Page:1-26
ISSN:2324-9935
Container-title:Transportmetrica A: Transport Science
language:en
Short-container-title:Transportmetrica A: Transport Science

Author:

Ha Paul (Young Joun)¹²,Chen Sikai³,Dong Jiqian¹²,Labi Samuel¹²

Affiliation:

1. Center for Connected and Automated Transportation (CCAT), Purdue University, West Lafayette, IN, USA

2. Lyles School of Civil Engineering, Purdue University, West Lafayette, IN, USA

3. Department of Civil and Environmental Engineering, University of Wisconsin–Madison, Madison, WI, USA

Funder

U.S. Department of Transportation

Publisher

Informa UK Limited

Subject

General Engineering,Transportation

Link

https://www.tandfonline.com/doi/pdf/10.1080/23249935.2023.2215338

Reference77 articles.

1. Evaluation of variable speed limits for real-time freeway safety improvement

2. Variable Speed Limits: Safety and Operational Impacts of a Candidate Control Strategy for Freeway Applications

3. Microscopic modeling of cyclists interactions with pedestrians in shared spaces: a Gaussian process inverse reinforcement learning approach

4. Real-World Carbon Dioxide Impacts of Traffic Congestion

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