Big Data & Analytics to design more efficient routes and change the location of bus stops or the frequency of services
Despite its fleet of vehicles and modern infrastructure, the Estonian city of Tartu spotted inefficiencies in the routes its urban buses were taking. It therefore began to restructure its network from a strategic point of view to improve mobility for its residents and tourists.
The first step was to analyse the routes of its 27 lines. Many of these routes were circular, which increased total journey time and the wait between changes. To solve this issue, it implemented a new "simple routes" model, replacing the circular routes with other pendulum-shaped routes, which meant that travellers could reach almost all destinations with only one change. Moreover, thanks to these pendulum routes, buses came more frequently and problems such as two buses coinciding with similar journeys at the same time could be overcome.
To add value to the route analysis, large quantities of data about tourist and resident mobility were compiled. The results of analysis using Big Data & Analytics techniques produced a set of alternative bus networks, comparing possible solutions based on parameters such as running costs, the number of buses needed, journey times, accessibility and emissions.
The city, conscious of the complexity of the new models, implemented a survey system for residents about their transport preferences, so as to adjust the new timetables and routes to their needs as far as possible.
The whole process was undertaken with the help of a private company, a partner of the University of Tartu, which specialises in obtaining data from mobile devices using geo-positioning.
Following the first set of results, the city has provided data about the impact of the plan on mobility. Between September 2018 and September 2019, the number of individual bus journeys increased by 40%, monthly subscriptions rose by 10% and 90-day subscriptions grew by 21%. The average service time also improved, falling to seven minutes.
- Movilidad/Transporte
- Sistemas Analítica Datos (Big data/BI...)
- Sistemas de información geográfica (GIS)
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