Reinforcement learning approach to develop variable speed limit strategy using vehicle data and simulations-Reference-Cited by-同舟云学术

Reinforcement learning approach to develop variable speed limit strategy using vehicle data and simulations

Published:2024-02-08 Issue: Volume: Page:1-18
ISSN:1547-2450
Container-title:Journal of Intelligent Transportation Systems
language:en
Short-container-title:Journal of Intelligent Transportation Systems

Author:

Kim Yunjong¹,Kang Kawon²,Park Nuri²,Park Juneyoung³,Oh Cheol³

Affiliation:

1. Department of Transportation and Logistics Engineering, Hanyang University Erica Campus, Ansan, Republic of Korea

2. Department of Smart City Engineering, Hanyang University Erica Campus, Ansan, Republic of Korea

3. Department of Transportation and Logistics Engineering, Department of Smart City Engineering, Hanyang University Erica Campus, Ansan, Republic of Korea

Funder

Transportation and Logistics Research Program

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/15472450.2024.2312808

Reference51 articles.

1. Implementation of Variable Speed Limits to Improve Safety of Congested Expressway Weaving Segments in Microsimulation

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

3. Crash Risk Assessment Using Intelligent Transportation Systems Data and Real-Time Intervention Strategies to Improve Safety on Freeways

4. Predicting Freeway Crashes from Loop Detector Data by Matched Case-Control Logistic Regression

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

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A reinforcement learning based autonomous vehicle control in diverse daytime and weather scenarios;Journal of Intelligent Transportation Systems;2024-06-26