A Novel Ramp Metering Approach Based on Machine Learning and Historical Data

• URL: http://arxiv.org/abs/2005.13992v1
• Date: Tue, 26 May 2020 21:05:01 GMT
• Title: A Novel Ramp Metering Approach Based on Machine Learning and Historical Data
• Authors: Anahita Sanandaji, Saeed Ghanbartehrani, Zahra Mokhtari, Kimia Tajik
• Abstract summary: Ramp metering is a proven method to maintain freeway efficiency under various traffic conditions. We use machine learning approaches to develop a novel real-time prediction model for ramp metering.
• Score: 0.7349727826230861
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The random nature of traffic conditions on freeways can cause excessive congestions 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 machine learning approaches to develop a novel real-time prediction model for ramp metering. We evaluate the potentials of our approach in providing promising results by comparing it with a baseline traffic-responsive ramp metering algorithm.

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