Transport systems analysis: models and data
Rapid advancements in new technologies, especially information and communication technologies (ICT), have signifcantly 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...
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| Formato: | artículo |
| Fecha de publicación: | 2023 |
| 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:2117/397585 |
| Acesso em linha: | https://hdl.handle.net/2117/397585 https://dx.doi.org/10.57645/20.8080.02.1 |
| Access Level: | acceso abierto |
| Palavra-chave: | Data sets Optimization Simulation Data Analytics Traffic assignment Traffic Simulation Conjunts de dades Àrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa::Simulació |
| Resumo: | Rapid advancements in new technologies, especially information and communication technologies (ICT), have signifcantly 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 suffcient 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 scientifc 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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