Title
A Novel Ramp Metering Approach Based on Machine Learning and Historical Data
Document Type
Article
Publication Date
12-1-2020
Abstract
The random nature of traffic conditions on freeways can cause excessive congestion and irregularities in the traffic flow. Ramp metering is a proven effective method to maintain freeway efficiency under various traffic conditions. Creating a reliable and practical ramp metering algorithm that considers both critical traffic measures and historical data is still a challenging problem. In this study we use simple machine learning approaches to develop a novel real-time ramp metering algorithm. The proposed algorithm is computationally simple and has minimal data requirements, which makes it practical for real-world applications. We conduct a simulation study to evaluate and compare the proposed approach with an existing traffic-responsive ramp metering algorithm.
Recommended Citation
Ghanbartehrani, Saeed; Sanandaji, Anahita; Mokhtari, Zahra; and Tajik, Kimia, "A Novel Ramp Metering Approach Based on Machine Learning and Historical Data" (2020). Industrial and Systems Engineering Open Access Publications. 5.
https://ohioopen.library.ohio.edu/ise-oapub/5