Trip matrices from mobile location data

Personalised study area and zoning system

Personalised study period and temporal resolution

Segmentation by travellers’ sociodemografic profile: age, gender, income, place of residence, etc.

Trip purpose

Recurrence of the trip

Transport mode

Vehicle type (e.g., identification of heavy freight vehicles)

Route choice

Fusion with traffic counts for conversion from person-trips to vehicle-trips through

The planning and management of transport infrastructure and services requires accurate, reliable and updated travel demand information. Traditional data collection methods, such as household travel surveys and roadside interviews, provide rich travel and demographic data, but they are expensive and require weeks or even months to complete, which limits the size of the sample and the frequency with which information is updated. New big data sources, such as mobile network data, smart card data, geocoded records from mobile apps and GPS navigation data, make it possible to complement or even replace traditional travel surveys, overcoming some of their main limitations. Mobile network data, originally generated for billing purposes or for the purpose of managing mobile networks, are particularly interesting for this application, thanks to the possibility of obtaining very large samples for practically all population segments. 

By partnering with mobile network operators, Nommon collects anonymised mobile data records that are then processed and blended with other data sources to produce origin-destination matrices and other travel demand indicators. Nommon’s technology for the processing of mobile location data is the result of an intensive research effort to meet the needs of the transport industry, and is widely recognised as one of the most advanced of its kind worldwide.

Added value and synergies with other data sources

The use of origin-destination matrices extracted from mobile network data has several advantages:

  • Mobile data provide large-scale, well-distributed samples of the whole population, allowing the estimation of trip matrices of a higher quality than those obtained through traditional travel surveys, particularly regarding trip distribution.
  • Information can be obtained at a fraction of the cost required by travel surveys.
  • The use of mobile phone records allows the obtention of up-to-date information at any moment, opening the door to the study of specific periods (holiday periods, long weekends, special events, etc.) or even to continuous monitoring of mobility patterns and travel demand.

On the other hand, the information about travel demand that can be obtained from mobile network data has a number of limitations, in particular regarding the identification of certain transport modes and trip purposes. In most transportation projects, the best approach usually involves the synergistic combination of mobile phone trip matrices with other data sources, such as surveys, ticketing data and traffic counts. We work in close collaboration with our clients to devise the combination of data sources that is best adapted to the requirements and constraints of each specific project.