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Tool Inventory

TRavelVU
TRavelVU

Application Area

  • Data gathering
  • Analysis, scenarios and measure selection
  • Appraisal and assessment
  • Evaluation and monitoring
  • Dissemination and communication

Tool Type

  • Method / Approach
  • Mobile app
  • Software

Target Audience

  • Rural areas
  • Small cities
  • Medium-sized cities
  • Large cities
  • Metropolitan regions
  • Other

Summary

 

TRavelVU is a digital travel survey method. It is cheaper than data gathering through traditional methods and delivers more accurate and more reliable results.

Because of the low price, data can also be collected more often and over longer time periods, giving a better understanding of travel behaviour in different conditions (e.g. seasons, different days for the same person, etc).

TRavelVU relies on sensors in smartphones to collect travel survey data and provides a user interface which allows respondents to check, confirm or correct the route they travelled.

TRavelVU makes it possible to monitor and evaluate transport projects and policy goals in a new way. By understanding travel – even better than we do today with traditional travel survey methods – we can support local authorities in helping their citizens to avoid journeys, shift to more sustainable modes and evaluate transport projects.

TRavelVU particularly provides improved data on cycling and pedestrian trips, including valuable data on where people walk and cycle for which there is essentially no data today. It also provides a fuller picture of how individuals travel (rather than just a single day of data) which can help understand the reasons that people opt for unsustainable modes and encourage them to choose more sustainable options.

Good Example

TRavelVU has been used to collect data for workplace travel survey performed in Lund, Stockholm and Gothenburg (in Sweden), for evaluating the implementation of tramline being built in Lund (Sweden), in research projects in TU Dresden (Germany) and NTNU (Norway). It will be used to test mobility management applications in a research project in Stockholm, Sweden (summer 2017) as well as large scale test and demonstration with comparison to other data collection methods in Gothenburg, Sweden (autumn 2017).

Input Data

Respondents must be recruited

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