Dynamic OD transit matrix estimation: formulation and model-building environment
The aim of this paper is to provide a detailed description of a framework for the estimation of time-sliced origin-destination (OD) trip matrices in a transit network using counts and travel time data of Bluetooth Smartphone devices carried by passengers at equipped transit-stops. A Kalman filtering...
| Autores: | , , |
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| Formato: | capítulo de livro |
| Fecha de publicación: | 2015 |
| 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:2117/27608 |
| Acesso em linha: | https://hdl.handle.net/2117/27608 https://dx.doi.org/10.1007/978-3-319-08422-0_51 |
| Access Level: | acceso abierto |
| Palavra-chave: | Demand Estimation Information Systems Advanced Transport Information Systems Kalman Filtering Classificació AMS::90 Operations research, mathematical programming Àrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa |
| Resumo: | The aim of this paper is to provide a detailed description of a framework for the estimation of time-sliced origin-destination (OD) trip matrices in a transit network using counts and travel time data of Bluetooth Smartphone devices carried by passengers at equipped transit-stops. A Kalman filtering formulation defined by the authors has been included in the application. The definition of the input for building the space-state model is linked to network scenarios modeled with the transportation planning platform EMME. The transit assignment framework is optimal strategy-based, which determines the subset of paths related to the optimal strategies between all OD pairs |
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