{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T06:03:15Z","timestamp":1781676195998,"version":"3.54.5"},"reference-count":62,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2020,9,23]],"date-time":"2020-09-23T00:00:00Z","timestamp":1600819200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["MAKE"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/make2040021","type":"journal-article","created":{"date-parts":[[2020,9,23]],"date-time":"2020-09-23T09:28:08Z","timestamp":1600853288000},"page":"379-396","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["A Novel Ramp Metering Approach Based on Machine Learning and Historical Data"],"prefix":"10.3390","volume":"2","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7750-2744","authenticated-orcid":false,"given":"Saeed","family":"Ghanbartehrani","sequence":"first","affiliation":[{"name":"Industrial and Systems Engineering Department, Ohio University, Athens, OH 45701, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8896-6413","authenticated-orcid":false,"given":"Anahita","family":"Sanandaji","sequence":"additional","affiliation":[{"name":"Analytics and Information Systems Department, Ohio University, Athens, OH 45701, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zahra","family":"Mokhtari","sequence":"additional","affiliation":[{"name":"Bright Horizons, Watertown, MA 02472, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kimia","family":"Tajik","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97330, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,9,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1109\/TITS.2002.806803","article-title":"Freeway ramp metering: An overview","volume":"3","author":"Papageorgiou","year":"2002","journal-title":"IEEE Trans. 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