FRID Project Explores New Ways to Improve Transport Planning
Reliable decision support for investments in transport infrastructure depends on an accurate understanding of how people travel today and how travel patterns may evolve in the future. The FRID project addresses this challenge by investigating how multiple sources of mobility data can be combined to improve both the description of current travel behaviour and forecasts of future travel demand.
Traditionally, travel surveys have served as the primary source of information on travel patterns, providing insights into mode choice, trip purposes, origins and destinations, and traveller characteristics. However, declining response rates have increasingly raised concerns about the representativeness of survey-based data. The FRID project explores how travel surveys can be complemented with passively collected mobility data to create more robust and reliable transport analyses.
In its final report, the project develops and evaluates methods for data fusion in two key areas: integrated descriptions of current travel patterns and forecasting models for mode and destination choice in regional travel. These methods are tested through a case study in Norrköping, where four different data sources are combined: travel survey data, mobile phone network data, public transport smartcard data, and vehicle GPS data.
The results demonstrate that combining multiple data sources can provide a more comprehensive and resilient picture of travel behaviour while accounting for differences in data quality and reliability. At the same time, the study highlights several practical challenges associated with data fusion. One of the most significant findings is that the traveller samples represented in different datasets may differ systematically in ways that are not directly observable but nonetheless influence travel choices. For joint model estimation to produce reliable results, certain assumptions about the datasets must therefore be satisfied.
The study concludes that travel surveys remain indispensable for capturing information such as trip purpose, travel party size, and socio-economic characteristics. Nevertheless, data fusion offers considerable potential to reduce dependence on surveys with low response rates and limited representativeness. To fully realize this potential, however, improvements in data quality are needed across all types of mobility data.
Researchers, practitioners, and stakeholders are warmly invited to a review seminar of the FRID project, where the project's final report and findings will be presented and discussed.
Date: 13 October 2026
Time: 14:00–15:00
Location: Online via Microsoft Teams
Teams link: Please contact
ida.kristoffersson@vti.se
for the meeting link.