Abstract
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.
Highlights
With the continuing growth in both urban populations and the number of personal vehicles, traffic congestion and delays in journey time are critical issues for the overall sustainability of urban transportation systems around the globe [1,2,3,4]
There is a growing body of literature that recognizes the importance of real-time/near real-time optimized traffic signaling systems as aids in overcoming traffic congestion, increasing traffic safety, and reducing the level of
Improving traffic conditions in fast-growing urban areas of the developing world is a matter of ongoing concern to urban planners, traffic managers, and environmental advocates to both uplift travel efficiency and the quality of the natural world
Summary
With the continuing growth in both urban populations and the number of personal vehicles, traffic congestion and delays in journey time are critical issues for the overall sustainability of urban transportation systems around the globe [1,2,3,4]. The consequences of traffic congestion (e.g., increases in traffic safety issues, delays, and traffic-related air pollution) have been widely investigated in different city contexts globally [4,5,6]. These issues are of significant interest to transportation planners and managers tasked with overcoming increasing urban transportation challenges. The overall system developed for the video analysis unit detected the vehicle types, and later, the query sectionsystem produced a trafficfor condition summary intersection presented. The error percentages indicate that, overall, the and the vehicle volume extracted by the video analysis unit. The numbers indicate that the video video analysis demonstrated, approximately, a error when detecting and counting vehicle volume. Thiserror finding indicates thatand despite miscounting the videothe analysis demonstrated, approximately, a 5%
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