Using big data safety analytics for proactive traffic management - Mohamed A. Abdel-Aty (19794429) (2015)
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. Other Information Published in: Journal of Local and Global Health Science, title discontinued as of (2017) License: https://creativecommons.org/licenses/by/4.0/ See article on publisher's website: https://dx.doi.org/10.5339/jlghs.2015.itma.67