Toward a Dynamic Reversible Lane Management Strategy by Empowering Learning-Based Predictive Assignment Scheme
Author:
Affiliation:
1. Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, USA
2. Department of Civil Engineering, University of Texas, El Paso, TX, USA
Funder
Pacific NW Transportation Consortium
Connected Sensor and Infrastructure Networks”
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Mechanical Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/6979/9972869/09889237.pdf?arnumber=9889237
Reference48 articles.
1. Stacked bidirectional and unidirectional LSTM recurrent neural network for forecasting network-wide traffic state with missing values
2. Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting
3. Time-Varying Lane-Based Capacity Reversibility for Traffic Management
4. Microscopic Traffic Simulation Model-Based Optimization Approach for the Contraflow Lane Configuration Problem
5. The Reversible Lane Network Design Problem (RL-NDP) for Smart Cities with Automated Traffic
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2. An In-Depth Review of Revolutionizing Traffic Control Systems Leveraging Software-Defined Networking (SDN);2024 IEEE 14th Symposium on Computer Applications & Industrial Electronics (ISCAIE);2024-05-24
3. Dynamic Lane Assignment and Signal-Timing Collaborative Optimization Considering the Effect of Lane Switching;Transportation Research Record: Journal of the Transportation Research Board;2024-03-25
4. OAS Deep Q-Learning-Based Fast and Smooth Control Method for Traffic Signal Transition in Urban Arterial Tidal Lanes;Sensors;2024-03-13
5. Cooperative Longitudinal Driving and Lane Assignment Strategy for Left-Turn Connected and Autonomous Vehicles at Signalized Intersections With a Contraflow Left-Turn Lane;IEEE Transactions on Intelligent Transportation Systems;2024
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