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

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 consi...

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Bibliographic Details
Published in:arXiv.org 2020-05
Main Authors: Sanandaji, Anahita, Ghanbartehrani, Saeed, Mokhtari, Zahra, Tajik, Kimia
Format: Article
Language:English
Subjects:
Algorithms
Driving conditions
Highways
Machine learning
Prediction models
Roads & highways
Traffic
Traffic congestion
Traffic flow
Online Access:Get full text
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Summary: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.
ISSN:2331-8422
DOI:10.48550/arxiv.2005.13992