Measuring traffic lane-changing by converting video into space–time still images
Empirical data is needed in order to extend our knowledge of traffic behavior. Video recordings are used to enrich typical data from loop detectors. In this context, data extraction from videos becomes a challenging task. Setting automatic video processing systems is costly, complex, and the accurac...
| Autores: | , , , |
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| Formato: | artículo |
| Fecha de publicación: | 2019 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/132475 |
| Acesso em linha: | https://hdl.handle.net/2117/132475 https://dx.doi.org/10.1111/mice.12430 |
| Access Level: | acceso abierto |
| Palavra-chave: | Traffic flow--Measurement Circulació -- Mesurament Àrees temàtiques de la UPC::Enginyeria civil::Infraestructures i modelització dels transports::Transport per carretera |
| Resumo: | Empirical data is needed in order to extend our knowledge of traffic behavior. Video recordings are used to enrich typical data from loop detectors. In this context, data extraction from videos becomes a challenging task. Setting automatic video processing systems is costly, complex, and the accuracy achieved is usually not enough to improve traffic flow models. In contrast “visual” data extraction by watching the recordings requires extensive human intervention. A semiautomatic video processing methodology to count lane-changing in freeways is proposed. The method allows counting lane changes faster than with the visual procedure without falling into the complexities and errors of full automation. The method is based on converting the video into a set of space–time still images, from where to visually count. This methodology has been tested at several freeway locations near Barcelona (Spain) with good results. A user-friendly implementation of the method is available on http://bit.ly/2yUi08M. |
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