Digital Transport Model in Tallinn

Organisation type

Public administration at local level

Use case area

Transport

Geographic scope

Estonia

Domain

Environment
Governance and implementation

Challenge:

Tallinn needed a comprehensive solution to predict mobility needs and improve urban transport planning. The city faced issues with traffic congestion and the need for better public transport coordination. There was also a requirement to understand the complex movement patterns of different commuters and create a holistic view of the city’s transport ecosystem. Buses and trams often encountered delays, making the public transportation network less reliable for daily commuters. Moreover, there was a noticeable lack of synchronisation between various models of transport, causing an extended travel time.

Approach:

Tallinn, in collaboration with PTV Group, launched an innovative digital transport model to address traffic issues. This model integrates data from 130,000 road sections and over 12,000 nodes, continuously updated with traffic frequencies and movement patterns across various transport modes. It distinguishes between 12 user groups, including mixed-mode commuters (e.g., parents dropping children off when going to work), and enhances accuracy with social surveys and real-time traffic data. Key steps in building the model included implementing integrated supply models for different transport modes, determining model areas and traffic zones, setting up a land use data model, designing a tour-based passenger demand model, generating fixed matrices for commercial traffic, calibrating and validating the model, and developing forecast scenarios. The transport planning software supports mobility system evolution through data-based scenario assessments. To effectively evaluate many possible future variants, short model run times are critical. The algorithms are therefore continuously optimised with new methods and techniques, such as contraction hierarchies and parallel processing.

Outcomes:

The digital model significantly enhances urban planning by forecasting transportation demands, reducing congestion, and optimising public transport routes. City planners use the model to predict the impact of new developments, adjust infrastructure plans, and better coordinate transport systems. As a result, Tallinn has improved travel efficiency, reduced environmental impacts, and better synchronised different transport modes, including public transport and freight systems.

Data Sources:

The system collects and integrates a wide range of data, including historical traffic data, real-time traffic flows, social surveys, public transport usage patterns, and geographic information. It also uses road network data, tracking pedestrians, private cars, buses, trams, and freight to form a holistic view of the transport ecosystem.

Additional Information:

Point of Contact:

https://www.tallinn.ee/en/contacts-tallinn-city