Using big data safety analytics for proactive traffic management

<p dir="ltr">The advent of the Big Data era has transformed the outlook of numerous fields in science and engineering. The transportation arena also has great expectations of taking advantage of Big Data enabled by the popularization of Intelligent Transportation Systems (ITS). The c...

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المؤلف الرئيسي: Mohamed A. Abdel-Aty (19794429) (author)
منشور في: 2015
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author Mohamed A. Abdel-Aty (19794429)
author_facet Mohamed A. Abdel-Aty (19794429)
author_role author
dc.creator.none.fl_str_mv Mohamed A. Abdel-Aty (19794429)
dc.date.none.fl_str_mv 2015-11-12T09:00:00Z
dc.identifier.none.fl_str_mv 10.5339/jlghs.2015.itma.67
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/Using_big_data_safety_analytics_for_proactive_traffic_management/27160560
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Engineering
Electrical engineering
Information and computing sciences
Data management and data science
Big Data
Intelligent Transportation Systems (ITS)
Traffic Management
Data Analytics
Safety Analysis
Congestion Management
dc.title.none.fl_str_mv Using big data safety analytics for proactive traffic management
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p dir="ltr">The advent of the Big Data era has transformed the outlook of numerous fields in science and engineering. The transportation arena also has great expectations of taking advantage of Big Data enabled by the popularization of Intelligent Transportation Systems (ITS). The challenges in the transportation system are many, ranging from increase in travel demand, growth in congestion, need to improve safety to the reality of limited resources. Thus there is a need for more Pro-Active Traffic Management to dynamically manage recurrent and non-recurrent incident-related congestion based on prevailing traffic conditions. Processing this large data requires different analytical and data mining techniques. The presentation addresses several concepts and examples of using big data analytics. Dr. Abdel-Aty presents examples from many projects currently ongoing at the University of Central Florida (UCF). These projects deal with applications of big data analytics in safety and operation. The speech shows examples of UCF research using big data in safety analysis, adverse weather conditions and safety planning. Real-time safety, operation and adverse weather analysis are presented. For example, the viability of monitoring and improving traffic safety and operation on urban expressways in Central Florida using real-time Microwave Vehicle Detection System (MVDS) data is researched. From the perspectives of volume, velocity and variety, the MVDS should be regarded as one of the main sources of Big Data. The detection system archives spot speed, volume, lane occupancy, and vehicle type per lane on a minute basis. Real-time safety risk evaluation was developed for several expressways based on these data. Other big data applications involve combination of census, planning, safety, roadway and land use data to improve safety planning.</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: Journal of Local and Global Health Science, title discontinued as of (2017)<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.5339/jlghs.2015.itma.67" target="_blank">https://dx.doi.org/10.5339/jlghs.2015.itma.67</a></p>
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spelling Using big data safety analytics for proactive traffic managementMohamed A. Abdel-Aty (19794429)EngineeringElectrical engineeringInformation and computing sciencesData management and data scienceBig DataIntelligent Transportation Systems (ITS)Traffic ManagementData AnalyticsSafety AnalysisCongestion Management<p dir="ltr">The advent of the Big Data era has transformed the outlook of numerous fields in science and engineering. The transportation arena also has great expectations of taking advantage of Big Data enabled by the popularization of Intelligent Transportation Systems (ITS). The challenges in the transportation system are many, ranging from increase in travel demand, growth in congestion, need to improve safety to the reality of limited resources. Thus there is a need for more Pro-Active Traffic Management to dynamically manage recurrent and non-recurrent incident-related congestion based on prevailing traffic conditions. Processing this large data requires different analytical and data mining techniques. The presentation addresses several concepts and examples of using big data analytics. Dr. Abdel-Aty presents examples from many projects currently ongoing at the University of Central Florida (UCF). These projects deal with applications of big data analytics in safety and operation. The speech shows examples of UCF research using big data in safety analysis, adverse weather conditions and safety planning. Real-time safety, operation and adverse weather analysis are presented. For example, the viability of monitoring and improving traffic safety and operation on urban expressways in Central Florida using real-time Microwave Vehicle Detection System (MVDS) data is researched. From the perspectives of volume, velocity and variety, the MVDS should be regarded as one of the main sources of Big Data. The detection system archives spot speed, volume, lane occupancy, and vehicle type per lane on a minute basis. Real-time safety risk evaluation was developed for several expressways based on these data. Other big data applications involve combination of census, planning, safety, roadway and land use data to improve safety planning.</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: Journal of Local and Global Health Science, title discontinued as of (2017)<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.5339/jlghs.2015.itma.67" target="_blank">https://dx.doi.org/10.5339/jlghs.2015.itma.67</a></p>2015-11-12T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.5339/jlghs.2015.itma.67https://figshare.com/articles/journal_contribution/Using_big_data_safety_analytics_for_proactive_traffic_management/27160560CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/271605602015-11-12T09:00:00Z
spellingShingle Using big data safety analytics for proactive traffic management
Mohamed A. Abdel-Aty (19794429)
Engineering
Electrical engineering
Information and computing sciences
Data management and data science
Big Data
Intelligent Transportation Systems (ITS)
Traffic Management
Data Analytics
Safety Analysis
Congestion Management
status_str publishedVersion
title Using big data safety analytics for proactive traffic management
title_full Using big data safety analytics for proactive traffic management
title_fullStr Using big data safety analytics for proactive traffic management
title_full_unstemmed Using big data safety analytics for proactive traffic management
title_short Using big data safety analytics for proactive traffic management
title_sort Using big data safety analytics for proactive traffic management
topic Engineering
Electrical engineering
Information and computing sciences
Data management and data science
Big Data
Intelligent Transportation Systems (ITS)
Traffic Management
Data Analytics
Safety Analysis
Congestion Management