April 27, 2020

Optimising Public Transport Using Anonymous Location Data

Location data from mobile devices provide us with the knowledge necessary for efficient and long-term planning of public transport. In cooperation with telecom operator Telia, Ramboll works on a project aiming to inform transport modelling in Finland. Using anonymous and aggregated data from Telia Crowd Insights, Ramboll seeks to assess how people based on today’s patterns were to travel if a new rail line were to be built. The aggregated data set is created according to GDPR rules, and with this method it is not possible to track individuals.

The rapid change of cities calls for constant development of urban environments to accommodate the like-wise changing lives of the people. By anonymising and analysing location data from mobile devices, we can understand our cities better and, thereby, recognise where crowds form in order to serve these better in terms of urban planning, retail, events and public transport. As everyone owns a mobile phone, a continuous flow of data of new travel patterns amongst people is obtained, thus providing relevant operators with fresh information to support future decision-making. It is through these data that Ramboll was set to assess how a new rail line with a maximum speed of 250 km/h was to be built in Finland.
  • The data provided by Telia Crowd Insights increases our understanding of how people move today. By inputting these data into our strategic models, we have even more accurate estimations of the future of travel patterns. The BRUTUS-Methodology enables a highly detailed analysis of multi-modal transport demand on the individual level by tracing back simulated people throughout all the travel and activities during the day using any mode, including the new potential rail line, Jukka-Pekka Pitkänen, Global Division Director at Ramboll Smart Mobility, says.
The analysis is based on data from two regions in Finland, South-West Finland and the Capital Region. Data was entered into Ramboll’s data-driven simulation model, Brutus, as well as the national four-step EMME-model to forecast how people would travel if a new rail line was built. The key performance indicators for impact assessment (from both strategic models) were included in order to determine the passenger potential of the new transport mode with different infrastructure and timetable options. The result was optimal timetables and service offerings recommendable for future planning and operations of a new rail line.
The cooperative project between Ramboll and Telia Crowd Insights, therefore, had a dual purpose. Firstly, to provide client and all stakeholders with a better understanding of the potential of a new rail line in Finland and an idea of how infrastructure and train services could be optimised accordingly. And secondly, to optimise the service for passengers, thereby improving the business cases for the Finnish Transport Infrastructure Agency and the stakeholders of the new track.