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A review of travel and arrival-time prediction methods on road networks: classification, challenges and opportunities
Transportation plays a key role in today’s economy. Hence, intelligent transportation systems have attracted a great deal of attention among research communities. There are a few review papers in this area. Most of them focus only on travel time prediction. Furthermore, these papers do not include r...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8444094/ https://www.ncbi.nlm.nih.gov/pubmed/34604519 http://dx.doi.org/10.7717/peerj-cs.689 |
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author | Abdi, Asad Amrit, Chintan |
author_facet | Abdi, Asad Amrit, Chintan |
author_sort | Abdi, Asad |
collection | PubMed |
description | Transportation plays a key role in today’s economy. Hence, intelligent transportation systems have attracted a great deal of attention among research communities. There are a few review papers in this area. Most of them focus only on travel time prediction. Furthermore, these papers do not include recent research. To address these shortcomings, this study aims to examine the research on the arrival and travel time prediction on road-based on recently published articles. More specifically, this paper aims to (i) offer an extensive literature review of the field, provide a complete taxonomy of the existing methods, identify key challenges and limitations associated with the techniques; (ii) present various evaluation metrics, influence factors, exploited dataset as well as describe essential concepts based on a detailed analysis of the recent literature sources; (iii) provide significant information to researchers and transportation applications developer. As a result of a rigorous selection process and a comprehensive analysis, the findings provide a holistic picture of open issues and several important observations that can be considered as feasible opportunities for future research directions. |
format | Online Article Text |
id | pubmed-8444094 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84440942021-09-30 A review of travel and arrival-time prediction methods on road networks: classification, challenges and opportunities Abdi, Asad Amrit, Chintan PeerJ Comput Sci Data Mining and Machine Learning Transportation plays a key role in today’s economy. Hence, intelligent transportation systems have attracted a great deal of attention among research communities. There are a few review papers in this area. Most of them focus only on travel time prediction. Furthermore, these papers do not include recent research. To address these shortcomings, this study aims to examine the research on the arrival and travel time prediction on road-based on recently published articles. More specifically, this paper aims to (i) offer an extensive literature review of the field, provide a complete taxonomy of the existing methods, identify key challenges and limitations associated with the techniques; (ii) present various evaluation metrics, influence factors, exploited dataset as well as describe essential concepts based on a detailed analysis of the recent literature sources; (iii) provide significant information to researchers and transportation applications developer. As a result of a rigorous selection process and a comprehensive analysis, the findings provide a holistic picture of open issues and several important observations that can be considered as feasible opportunities for future research directions. PeerJ Inc. 2021-09-08 /pmc/articles/PMC8444094/ /pubmed/34604519 http://dx.doi.org/10.7717/peerj-cs.689 Text en © 2021 Abdi and Amrit https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. |
spellingShingle | Data Mining and Machine Learning Abdi, Asad Amrit, Chintan A review of travel and arrival-time prediction methods on road networks: classification, challenges and opportunities |
title | A review of travel and arrival-time prediction methods on road networks: classification, challenges and opportunities |
title_full | A review of travel and arrival-time prediction methods on road networks: classification, challenges and opportunities |
title_fullStr | A review of travel and arrival-time prediction methods on road networks: classification, challenges and opportunities |
title_full_unstemmed | A review of travel and arrival-time prediction methods on road networks: classification, challenges and opportunities |
title_short | A review of travel and arrival-time prediction methods on road networks: classification, challenges and opportunities |
title_sort | review of travel and arrival-time prediction methods on road networks: classification, challenges and opportunities |
topic | Data Mining and Machine Learning |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8444094/ https://www.ncbi.nlm.nih.gov/pubmed/34604519 http://dx.doi.org/10.7717/peerj-cs.689 |
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