Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Abdi, Asad, Amrit, Chintan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
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
_version_ 1784568421509234688
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
work_keys_str_mv AT abdiasad areviewoftravelandarrivaltimepredictionmethodsonroadnetworksclassificationchallengesandopportunities
AT amritchintan areviewoftravelandarrivaltimepredictionmethodsonroadnetworksclassificationchallengesandopportunities
AT abdiasad reviewoftravelandarrivaltimepredictionmethodsonroadnetworksclassificationchallengesandopportunities
AT amritchintan reviewoftravelandarrivaltimepredictionmethodsonroadnetworksclassificationchallengesandopportunities