Traffic and mobility data collection for real-time applications
Author(s)Lopes, J.; Bento, Joao; Huang, E.; Antoniou, Constantinos; Ben-Akiva, Moshe E.
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Successful development of effective real-time traffic management and information systems requires high quality traffic information in real-time. This paper presents the state-of-the-art of traffic and general mobility sensory technology and a suite of methods for data pre-processing and cleaning for real-time applications. We propose a suite of methods and techniques to be applied from traffic data acquisition, preprocessing, transformation and integration until data advanced processing and transfer. Next, we detail some techniques for data preprocessing and integration, or fusion, phases. Even though the comprehensive use of historical traffic data and assignment models to support the most part of online services and operations, real-time data is extremely important to promote models' accuracy and, therefore, the reliability of information and outputs derived from data fusion and processing. Together with techniques and theoretical formulas we present a case study applied to the Portuguese Brisa's A5 motorway, a 25 km inter-urban highway between Lisbon and Cascais. Traffic on this motorway heading to Lisbon in the morning rush hours typically experiences high levels of congestion. Brisa, the motorway operator company, has equipped A5 with a variety of traffic sensors to be used in a real-time multi-purpose way, either for traffic management and control or for traveler information and third-part applications.
DepartmentMassachusetts Institute of Technology. Department of Civil and Environmental Engineering; Massachusetts Institute of Technology. Intelligent Transportation Research Center
Proceedings of the 2010 13th International IEEE Conference on Intelligent Transportation Systems (ITSC)
Institute of Electrical and Electronics Engineers
Lopes, J. et al. “Traffic and Mobility Data Collection for Real-time Applications.” 2010 13th International IEEE Annual Conference on Intelligent Transportation Systems Madeira Island, Portugal, September 19-22, 2010, IEEE, 2010. 216–223. CrossRef. Web. © 2010 IEEE.
Final published version
INSPEC Accession Number: 11639519