Cloud-Assisted Mobile Crowd Sensing for Route and Congestion Monitoring

Accurate and reliable real-time urban traffic management can benefit urban citizens’ daily life by reducing stress, travel time and carbon footprint. The provision of reliable and accurate traffic information has however proven to be a major challenge in intelligent transportation systems...

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Autores principales:	Ozgun Yilmaz, Levent Gorgu, Michael J. O'grady, Gregory M. P. O'hare
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Crowd intelligence intelligent transportation system mobile crowd sensing real-time traffic management traffic congestion Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/c7961b1b04a94308a60087f3d4e3094e
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id	oai:doaj.org-article:c7961b1b04a94308a60087f3d4e3094e
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spelling	oai:doaj.org-article:c7961b1b04a94308a60087f3d4e3094e2021-12-03T00:00:42ZCloud-Assisted Mobile Crowd Sensing for Route and Congestion Monitoring2169-353610.1109/ACCESS.2021.3129932https://doaj.org/article/c7961b1b04a94308a60087f3d4e3094e2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9624168/https://doaj.org/toc/2169-3536Accurate and reliable real-time urban traffic management can benefit urban citizens’ daily life by reducing stress, travel time and carbon footprint. The provision of reliable and accurate traffic information has however proven to be a major challenge in intelligent transportation systems. Citizens carrying smartphones can be exploited as an important provider of traffic information and the mobile crowd sensing paradigm can be used as a solution to this challenge. In this paper, an urban traffic monitoring system which exploits the power of participatory sensing and cloud messaging is proposed. Crowd intelligence which is used to estimate traffic congestion levels, arrival times, while average road speed is harvested from crowd sensed data. Traffic congestion control at route level is implemented with a route guidance system. Proactive warnings or recommendations to drivers in the vicinity of, or on the route to, reported events are provided. The drivers can also report short-term traffic events and physical road conditions for road monitoring. Real-world experiments have been conducted with a prototype implementation and the results demonstrate both system feasibility and traffic estimation accuracy.Ozgun YilmazLevent GorguMichael J. O'gradyGregory M. P. O'hareIEEEarticleCrowd intelligenceintelligent transportation systemmobile crowd sensingreal-time traffic managementtraffic congestionElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 157984-157996 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Crowd intelligence intelligent transportation system mobile crowd sensing real-time traffic management traffic congestion Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Crowd intelligence intelligent transportation system mobile crowd sensing real-time traffic management traffic congestion Electrical engineering. Electronics. Nuclear engineering TK1-9971 Ozgun Yilmaz Levent Gorgu Michael J. O'grady Gregory M. P. O'hare Cloud-Assisted Mobile Crowd Sensing for Route and Congestion Monitoring
description	Accurate and reliable real-time urban traffic management can benefit urban citizens’ daily life by reducing stress, travel time and carbon footprint. The provision of reliable and accurate traffic information has however proven to be a major challenge in intelligent transportation systems. Citizens carrying smartphones can be exploited as an important provider of traffic information and the mobile crowd sensing paradigm can be used as a solution to this challenge. In this paper, an urban traffic monitoring system which exploits the power of participatory sensing and cloud messaging is proposed. Crowd intelligence which is used to estimate traffic congestion levels, arrival times, while average road speed is harvested from crowd sensed data. Traffic congestion control at route level is implemented with a route guidance system. Proactive warnings or recommendations to drivers in the vicinity of, or on the route to, reported events are provided. The drivers can also report short-term traffic events and physical road conditions for road monitoring. Real-world experiments have been conducted with a prototype implementation and the results demonstrate both system feasibility and traffic estimation accuracy.
format	article
author	Ozgun Yilmaz Levent Gorgu Michael J. O'grady Gregory M. P. O'hare
author_facet	Ozgun Yilmaz Levent Gorgu Michael J. O'grady Gregory M. P. O'hare
author_sort	Ozgun Yilmaz
title	Cloud-Assisted Mobile Crowd Sensing for Route and Congestion Monitoring
title_short	Cloud-Assisted Mobile Crowd Sensing for Route and Congestion Monitoring
title_full	Cloud-Assisted Mobile Crowd Sensing for Route and Congestion Monitoring
title_fullStr	Cloud-Assisted Mobile Crowd Sensing for Route and Congestion Monitoring
title_full_unstemmed	Cloud-Assisted Mobile Crowd Sensing for Route and Congestion Monitoring
title_sort	cloud-assisted mobile crowd sensing for route and congestion monitoring
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/c7961b1b04a94308a60087f3d4e3094e
work_keys_str_mv	AT ozgunyilmaz cloudassistedmobilecrowdsensingforrouteandcongestionmonitoring AT leventgorgu cloudassistedmobilecrowdsensingforrouteandcongestionmonitoring AT michaeljogrady cloudassistedmobilecrowdsensingforrouteandcongestionmonitoring AT gregorympohare cloudassistedmobilecrowdsensingforrouteandcongestionmonitoring
_version_	1718374014474256384

Cloud-Assisted Mobile Crowd Sensing for Route and Congestion Monitoring

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