02672nam a22004097a 4500 00006682 ES-MaONT 20211006062654.0 210901s2021 fr db||f t|||i00| 0 eng d 9789282169155 (PDF) doi 10.1787/08378837-en ES-MaONT Big Data for Travel Demand Modelling : summary and conclusions / International Transport Forum París : OECD Publishing, 12 August 2021 p. ; 1 documento PDF texto (visual) isbdcontent electrónico isbdmedia recurso en línea rdacarrier ITF Roundtable Reports ; 186 This report examines how big data from mobile phones and other sources can help forecast travel demand. It identifies the strengths and potential use cases for big data in transport modelling and mobility analysis, presents ways to address potential biases, commercial sensitivities and privacy threats and offers recommendations for governance arrangements that make data sharing easier. Transport planners use big data from mobile network operators, smartphone apps and smart cards to complement traditional travel surveys. The new data sources help transport planners understand and forecast travel demand. The study recommend 1) Collect data only for defined purposes and only the minimum required 2) Develop guidelines for the use of big data in transport models 3) Enable the collection of location data through smartphone apps 4) Protect privacy through multiple solutions 5) Define a roadmap for household travel surveys 6) Design and test smartphone-assisted household travel surveys 7) Leverage artificial intelligence for data mining 8) Create and promote a recognised data steward function in the public and private sectors 9) Invest in the data-related training of the public-sector workforce Tecnologías habilitadoras digitales 18 Big data demanda viajes gobernanza intercambio datos movilidad pronóstico teléfonos móviles transporte viajes International Transport Forum 3475 Organización de Cooperación y Desarrollo Económico 2843 ITF Roundtable Reports 3476 https://www.itf-oecd.org/sites/default/files/docs/big-data-travel-demand-modelling.pdf 0 Acceso al documento pdf https://www.oecd-ilibrary.org/transport/big-data-for-travel-demand-modelling_08378837-en 0 Más información pdf udc INF 6682 6682 0 0 0 3 1 7627 01 01 online 2021-09-01 0 1000020176875 2021-09-01 00:00:00 2021-09-01 INF pdf