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HAAR Characteristics-Based Traffic Volume Method Measurement for Street Intersections

HAAR Characteristics-Based Traffic Volume Method Measurement for Street Intersections
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Author(s): Santiago Morales (Universidad Nacional de Colombia, Colombia), César Pedraza Bonilla (Universidad Nacional de Colombia, Colombia)and Felix Vega (Universidad Nacional de Colombia, Colombia)
Copyright: 2020
Pages: 28
Source title: Pattern Recognition Applications in Engineering
Source Author(s)/Editor(s): Diego Alexander Tibaduiza Burgos (Universidad Nacional de Colombia, Colombia), Maribel Anaya Vejar (Universidad Sergio Arboleda, Colombia)and Francesc Pozo (Universitat Politècnica de Catalunya, Spain)
DOI: 10.4018/978-1-7998-1839-7.ch011

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Abstract

Traffic volume is an important measurement to design mobility strategies in cities such as traffic light configuration, civil engineering works, and others. This variable can be determined through different manual and automatic strategies. However, some street intersections, such as traffic circles, are difficult to determine their traffic volume and origin-destination matrices. In the case of manual strategies, it is difficult to count every single car in a mid to large-size traffic circle. On the other hand, automatic strategies can be difficult to develop because it is necessary to detect, track, and count vehicles that change position inside an intersection. This chapter presents a vehicle counting method to determine traffic volume and origin-destination matrix for traffic circle intersections using two main algorithms, Viola-Jones for detection and on-line boosting for tracking. The method is validated with an implementation applied to a top view video of a large-size traffic circle. The video is processed manually, and a comparison is presented.

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