Transport and Covid-19: responses and resources

Big Data for Travel Demand Modelling

Summary and Conclusions
Big Data for Travel Demand Modelling: Summary and Conclusions

This report examines how big data from mobile phones and other sources can help to forecast travel demand. It identifies the strengths and potential use-cases for big data in transport modelling and mobility analysis. It also examines potential biases, commercial sensitivities and threats to privacy. The report presents approaches to resolve such issues and offers recommendations for governance arrangements that make data sharing easier.

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Policy Insights

  • Collect data only for defined purposes and only the minimum required.
  • Develop guidelines for the use of big data in transport models.
  • Enable the collection of location data through smartphone apps.
  • Protect privacy through multiple solutions.
  • Define a roadmap for household travel surveys.
  • Design and test smartphone-assisted household travel surveys.
  • Leverage artificial intelligence for data mining.
  • Create and promote a recognised data steward function in the public and private sectors.
  • Invest in the data-related training of the public-sector workforce.

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