Developed together with the Norwegian Public Road Administration, MobTrans integrates data from mobile phone operators, transportation models, national travel surveys and the Norwegian Road Database (NVDB) in transport analyses. The tool can be used for mappings of traffic flows, land-use planning while predicting CO2 emissions from different scenarios. MobTans stems from a project in Lillehammer Municipality, Norway. Here the purpose was to test if it was possible to replicate identified transportation flows from other data sources in mobile phone data.
For this project, the mobile phone operator was Telia. The data provided by Telia contained information on the total number of trips between zones for different periods as well as on three different sub-trip categories: work trips, home trips and other trips.
New Ideas Bring New Challenges
Using mobile phone data in transport analyses is a new idea. And with new ideas, new challenges arise. Due to GDPR-requirements, the anonymised data do not provide information about the mode usage of the trips (by foot, cycle, or car) nor are trips registered if less than five trips in any subcategory occur. This likewise means that mobile phone data cannot be used in real-time since very few flows fulfil the criteria of five trips, which is why MobTrans uses monthly data for analysis.
A Sustainable Way of Planning
Despite the challenges posed by the GDPR-requirements, MobTrans provides new insights into transport planning:
“MobTrans stands out due to its success in combining multiple data sources into an algorithm that estimates the mode share for the different mobile trips between the zones. This means that the client will be able to predict expected travel behaviour of an area without the need for running a transportation model, thereby minimising the costs significantly,” Andre Uteng, consultant in Ramboll Smart Mobility, explains.
With its unique insights into travel flows within and between areas and regions, MobTrans is useful in the planning process in, for instance, land-use planning. By capturing travel flows, it is possible to estimate expected travel behaviour from, of example, new housing developments. Like other transportation models, MobTrans provides estimations on the number of trips for each mode and the likely destinations of the trips. Using the estimated values, MobTrans also estimates the likely CO2 emissions and motor-vehicle kilometres per person for each area.