Bandwidth-Based Traffic Signal Coordination Models for Split or Mixed Phasing Schemes in Various Types of Networks
Author:
Affiliation:
1. School of Transportation and Civil Engineering, Nantong University, Nantong, China
2. School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, China
Funder
National Natural Science Foundation of China
Natural Science Foundation of the Jiangsu Higher Education Institutions of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Mechanical Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/8784355/9999144/10287578.pdf?arnumber=10287578
Reference33 articles.
1. Robustness and Adaptability of Reinforcement Learning-Based Cooperative Autonomous Driving in Mixed-Autonomy Traffic
2. Physics-Informed Deep Learning for Traffic State Estimation: Illustrations With LWR and CTM Models
3. Cooperative Deep Reinforcement Learning for Large-Scale Traffic Grid Signal Control
4. Comfort-Oriented Motion Planning for Automated Vehicles Using Deep Reinforcement Learning
5. Network-level multiband signal coordination scheme based on vehicle trajectory data
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