{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T04:29:53Z","timestamp":1787027393436,"version":"build-2736575974"},"reference-count":41,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,8,7]],"date-time":"2023-08-07T00:00:00Z","timestamp":1691366400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Vehicular Ad Hoc Network (VANETs) need methods to control traffic caused by a high volume of traffic during day and night, the interaction of vehicles, and pedestrians, vehicle collisions, increasing travel delays, and energy issues. Routing is one of the most critical problems in VANET. One of the machine learning categories is reinforcement learning (RL), which uses RL algorithms to find a more optimal path. According to the feedback they get from the environment, these methods can affect the system through learning from previous actions and reactions. This paper provides a comprehensive review of various methods such as reinforcement learning, deep reinforcement learning, and fuzzy learning in the traffic network, to obtain the best method for finding optimal routing in the VANET network. In fact, this paper deals with the advantages, disadvantages and performance of the methods introduced. Finally, we categorize the investigated methods and suggest the proper performance of each of them.<\/jats:p>","DOI":"10.3390\/a16080381","type":"journal-article","created":{"date-parts":[[2023,8,8]],"date-time":"2023-08-08T12:38:59Z","timestamp":1691498339000},"page":"381","update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Investigating Routing in the VANET Network: Review and Classification of Approaches"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-0229-2460","authenticated-orcid":false,"given":"Arun Kumar","family":"Sangaiah","sequence":"first","affiliation":[{"name":"International Graduate Institute of Artificial Intelligence, National Yunlin University of Science and Technology, Douliu 64002, Taiwan"},{"name":"Department of Electrical and Computer Engineering, Lebanese American University, Byblos 13-5053, Lebanon"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-4932-1660","authenticated-orcid":false,"given":"Amir","family":"Javadpour","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology (Cyberspace Security), Harbin Institute of Technology, Shenzhen 518057, China"},{"name":"ADiT-Lab, Electrical and Telecommunications Department, Instituto Polit\u00e9cnico de Viana do Castelo, 4900-367 Viana do Castelo, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chung-Chian","family":"Hsu","sequence":"additional","affiliation":[{"name":"Department of Information Management, International Graduate Institute of Artificial Intelligence, National Yunlin University of Science and Technology, Douliu 64002, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0001-9975-6462","authenticated-orcid":false,"given":"Anandakumar","family":"Haldorai","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Sri Eshwar College of Engineering, Coimbatore 642109, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0009-0000-0293-602X","authenticated-orcid":false,"given":"Ahmad","family":"Zeynivand","sequence":"additional","affiliation":[{"name":"Department of Electrical & Computer Engineering, Tarbiat Modares University, Tehran 14115-111, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e6960","DOI":"10.1002\/cpe.6960","article-title":"Optimization of reinforcement routing for wireless mesh network using machine learning and high-performance computing","volume":"34","author":"Singh","year":"2022","journal-title":"Concurr. 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