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