The research will provide an innovative analysis of the complexity of the interaction between information and travel behaviour from the new perspective of the knowledge-based society and the use of big data for transport. The project, carried by the professorship MIDT (Mobilité Intelligente et Dynamiques Territoriales – Intelligent Mobility and Territorial Dynamics) at the Université Technologique de Compiègne (Sorbonne Universités - UTC) has several purposes: planning and programming of public transport as well as control the quality of service; managing mobility; supplying new services for the customers. To this end, the scientific goals are: - to push one step forward research on travel behaviour; - to understand the specific role of information delivery on behaviour for different users' typologies; - to propose tailored transport policies, well suiting users’ needs. Through a mixed method, joining a qualitative and a quantitative approach, the project will develop a framework for collecting, analysing and extracting urban mobility information from several sources. Active research and development allow us to continuously improve our services, current progresses are being made in the fields of: - automatic mode detection, thanks to machine learning techniques; - automatic scope inference, thanks to time series analysis and spatial POI detection; - automatic zoning and OD matrix construction, thanks to big data processing and spatial statistics.

My-Moby: a customer oriented tool to support integrated transport and resilient communities / Pronello, C.; Gaborieau, J. B.. - STAMPA. - (2018). (Intervento presentato al convegno 7th Transport Research Arena TRA 2018 tenutosi a Vienna, Austria. nel April 16-19, 2018).

My-Moby: a customer oriented tool to support integrated transport and resilient communities

Pronello C.;
2018

Abstract

The research will provide an innovative analysis of the complexity of the interaction between information and travel behaviour from the new perspective of the knowledge-based society and the use of big data for transport. The project, carried by the professorship MIDT (Mobilité Intelligente et Dynamiques Territoriales – Intelligent Mobility and Territorial Dynamics) at the Université Technologique de Compiègne (Sorbonne Universités - UTC) has several purposes: planning and programming of public transport as well as control the quality of service; managing mobility; supplying new services for the customers. To this end, the scientific goals are: - to push one step forward research on travel behaviour; - to understand the specific role of information delivery on behaviour for different users' typologies; - to propose tailored transport policies, well suiting users’ needs. Through a mixed method, joining a qualitative and a quantitative approach, the project will develop a framework for collecting, analysing and extracting urban mobility information from several sources. Active research and development allow us to continuously improve our services, current progresses are being made in the fields of: - automatic mode detection, thanks to machine learning techniques; - automatic scope inference, thanks to time series analysis and spatial POI detection; - automatic zoning and OD matrix construction, thanks to big data processing and spatial statistics.
2018
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2733717