Estimation and analysis of urban traffic flow
Joonsoo Lee, Alan C. Bovik
Abstract
Joonsoo Lee, Alan C. Bovik
Abstract
This paper describes methods for extracting traffic flow information from urban traffic scenes. The ultimate goal is to collect a macroscopic view of traffic flow information in a fully automatic and segmentation-free way. First, traffic flow is calculated by optical flow estimation. Then, traffic flow regions are defined by the initial traffic flow, and further analysis is performed only in the defined traffic flow regions. Basic statistics of the traffic flow vectors are studied. It is shown that traffic flow computed by optical flow estimation effectively captures traffic scene activity. Also, the statistics of traffic flow vectors contain meaningful and interesting characteristics. An example application demonstrates the applicability and potential uses of the statistics.
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This paper describes methods for extracting traffic flow information from urban traffic scenes. The ultimate goal is to collect a macroscopic view of traffic flow information in a fully automatic and segmentation-free way. First, traffic flow is calculated by optical flow estimation. Then, traffic flow regions are defined by the initial traffic flow, and further analysis is performed only in the defined traffic flow regions. Basic statistics of the traffic flow vectors are studied. It is shown that traffic flow computed by optical flow estimation effectively captures traffic scene activity. Also, the statistics of traffic flow vectors contain meaningful and interesting characteristics. An example application demonstrates the applicability and potential uses of the statistics.
Key concepts: Traffic flow (computer networking), Computer science, Flow (mathematics), Traffic wave, Traffic generation model, Microscopic traffic flow model, Data mining, Transport engineering