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Personalized Route Planning System Based on Driver Preference

At present, most popular route navigation systems only use a few sensed or measured attributes to recommend a route. Yet the optimal route considered by drivers needs be based on multiple objectives and multiple attributes. As a result, these existing systems based on a single or few attributes may...

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Detalles Bibliográficos
Autores principales: Wang, Ren, Zhou, Mengchu, Gao, Kaizhou, Alabdulwahab, Ahmed, Rawa, Muhyaddin J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8747472/
https://www.ncbi.nlm.nih.gov/pubmed/35009553
http://dx.doi.org/10.3390/s22010011
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author Wang, Ren
Zhou, Mengchu
Gao, Kaizhou
Alabdulwahab, Ahmed
Rawa, Muhyaddin J.
author_facet Wang, Ren
Zhou, Mengchu
Gao, Kaizhou
Alabdulwahab, Ahmed
Rawa, Muhyaddin J.
author_sort Wang, Ren
collection PubMed
description At present, most popular route navigation systems only use a few sensed or measured attributes to recommend a route. Yet the optimal route considered by drivers needs be based on multiple objectives and multiple attributes. As a result, these existing systems based on a single or few attributes may fail to meet such drivers’ needs. This work proposes a driver preference-based route planning (DPRP) model. It can recommend an optimal route by considering driver preference. We collect drivers’ preferences, and then provide a set of routes for their choice when they need. Next, we present an integrated algorithm to solve DPRP, which speeds up the search process for recommending the best routes. Its computation cost can be reduced by simplifying a road network and removing invalid sub-routes. Experimental results demonstrate its effectiveness.
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spelling pubmed-87474722022-01-11 Personalized Route Planning System Based on Driver Preference Wang, Ren Zhou, Mengchu Gao, Kaizhou Alabdulwahab, Ahmed Rawa, Muhyaddin J. Sensors (Basel) Article At present, most popular route navigation systems only use a few sensed or measured attributes to recommend a route. Yet the optimal route considered by drivers needs be based on multiple objectives and multiple attributes. As a result, these existing systems based on a single or few attributes may fail to meet such drivers’ needs. This work proposes a driver preference-based route planning (DPRP) model. It can recommend an optimal route by considering driver preference. We collect drivers’ preferences, and then provide a set of routes for their choice when they need. Next, we present an integrated algorithm to solve DPRP, which speeds up the search process for recommending the best routes. Its computation cost can be reduced by simplifying a road network and removing invalid sub-routes. Experimental results demonstrate its effectiveness. MDPI 2021-12-21 /pmc/articles/PMC8747472/ /pubmed/35009553 http://dx.doi.org/10.3390/s22010011 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wang, Ren
Zhou, Mengchu
Gao, Kaizhou
Alabdulwahab, Ahmed
Rawa, Muhyaddin J.
Personalized Route Planning System Based on Driver Preference
title Personalized Route Planning System Based on Driver Preference
title_full Personalized Route Planning System Based on Driver Preference
title_fullStr Personalized Route Planning System Based on Driver Preference
title_full_unstemmed Personalized Route Planning System Based on Driver Preference
title_short Personalized Route Planning System Based on Driver Preference
title_sort personalized route planning system based on driver preference
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8747472/
https://www.ncbi.nlm.nih.gov/pubmed/35009553
http://dx.doi.org/10.3390/s22010011
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