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Open AccessArticle

Integrating Data Mining and Microsimulation Modelling to Reduce Traffic Congestion: A Case Study of Signalized Intersections in Dhaka, Bangladesh

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School of Environment, Education and Development (SEED), University of Manchester, Arthur Lewis Building (1st Floor), Oxford Road, Manchester M13 9PL, UK
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School of Urban and Regional Planning, The University of Iowa, Iowa City, IA 52242, USA
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Pi Labs Bangladesh Ltd., Dhaka 1215, Bangladesh
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Dmoney Bangladesh Limited, Dhaka 1212, Bangladesh
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SilvaCarbon-NASA/UMD fellowship 2018, US forest service, Washington, DC 20250-1111, USA
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Author to whom correspondence should be addressed.
Urban Sci. 2019, 3(2), 41; https://doi.org/10.3390/urbansci3020041
Received: 5 March 2019 / Revised: 3 April 2019 / Accepted: 10 April 2019 / Published: 12 April 2019
A growing body of research has applied intelligent transportation technologies to reduce traffic congestion at signalized intersections. However, most of these studies have not considered the systematic integration of traffic data collection methods when simulating optimum signal timing. The present study developed a three-part system to create optimized variable signal timing profiles for a congested intersection in Dhaka, regulated by fixed-time traffic signals. Video footage of traffic from the studied intersection was analyzed using a computer vision tool that extracted traffic flow data. The data underwent a further data-mining process, resulting in greater than 90% data accuracy. The final data set was then analyzed by a local traffic expert. Two hybrid scenarios based on the data and the expert’s input were created and simulated at the micro level. The resultant, custom, variable timing profiles for the traffic signals yielded a 40% reduction in vehicle queue length, increases in average travel speed, and a significant overall reduction in traffic congestion. View Full-Text
Keywords: traffic congestion; intelligent transportation; vehicle detection; microscopic traffic simulation; VISSIM; urban transportation; road traffic monitoring; traffic signal control; data mining; openCV traffic congestion; intelligent transportation; vehicle detection; microscopic traffic simulation; VISSIM; urban transportation; road traffic monitoring; traffic signal control; data mining; openCV
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Labib, S.; Mohiuddin, H.; Hasib, I.M.A.; Sabuj, S.H.; Hira, S. Integrating Data Mining and Microsimulation Modelling to Reduce Traffic Congestion: A Case Study of Signalized Intersections in Dhaka, Bangladesh. Urban Sci. 2019, 3, 41.

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