Transport systems analysis: models and data
Rapid advancements in new technologies, especially information and communication technologies (ICT), have significantly increased the number of sensors that capture data, namely those embedded in mobile devices. This wealth of data has garnered particular interest in analyzing transport systems, wit...
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/397841 |
| Acceso en línea: | https://hdl.handle.net/2117/397841 https://dx.doi.org/10.57645/20.8080.02.1 |
| Access Level: | acceso abierto |
| Palabra clave: | Operations research Management science Programming (Mathematics) optimization simulation data analytics traffic assignment traffic simulation 90B Investigació operativa i ciències de l'administració i la direcció 90C Programació matemàtica Classificació AMS::90 Operations research, mathematical programming::90B Operations research and management science Classificació AMS::90 Operations research, mathematical programming::90C Mathematical programming Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica |
| Sumario: | Rapid advancements in new technologies, especially information and communication technologies (ICT), have significantly increased the number of sensors that capture data, namely those embedded in mobile devices. This wealth of data has garnered particular interest in analyzing transport systems, with some researchers arguing that the data alone are sufficient enough to render transport models unnecessary. However, this paper takes a contrary position and holds that models and data are not mutually exclusive but rather depend upon each other. Transport models are built upon established families of optimization and simulation approaches, and their development aligns with the scientific principles of operations research, which involves acquiring knowledge to derive modeling hypotheses. We provide an overview of these modeling principles and their application to transport systems, presenting numerous models that vary according to study objectives and corresponding modeling hypotheses. The data required for building, calibrating, and validating selected models are discussed, along with examples of using data analytics techniques to collect and handle the data supplied by ICT applications. The paper concludes with some comments on current and future trends. |
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