With the help of Tallinn’s new transport model, it is possible to forecast and analyze people’s mobility needs and better plan both urban transport and urban space more broadly. This is not an individual study, but a permanent tool that can be used to assess whether and how decisions concerning urban space and traffic support strategic goals, Tallinn strategy chief Raido Roop writes in response to comment from Reform Tallinn councilor Partel-Peeter Pere.
According to the city’s long-term strategy, until 2035, most people in the Tallinn region should travel by public transport, bicycle or on foot. User-friendly mobility services should allow for a convenient and cost-effective combination of different modes of transport. The strategic goal is to significantly reduce car traffic so that traffic is less polluting and calm and free of congestion.
Convenient and fast public transport, among other things, helps to achieve these goals. Public transport in Tallinn is already one of the newest in the world, and more than two-thirds of the city’s buses will be renewed this year, as they will switch from diesel buses to gas buses first.
Until 2025, it is planned to abandon the active use of diesel buses in the service of routes, i.e. diesel buses will only be used as emergency buses in emergency situations. Electric and hydrogen buses have a long way to go.
It is planned to start the renewal of Tallinn’s public transport network this year, and a new transport model is key. The strength of the model is that it contains all the data available to the city, from which it is possible to assess the needs of people to move from one place in the city to another.
The model takes into account how many people enter or leave the vehicle at which public transport stop, but also more broadly with people’s needs and movement patterns: in addition to moving between two different points, such as from work to home, more complex movement patterns.
Like other multimodal transport models, Tallinn’s new transport model takes into account the needs of different social groups. The transport behavior of a working person, a school student and a home pensioner are different and this is suggested by sociological research, the data of which can still be included in the new transport model.
With the help of the model, it is possible to distinguish 12 different types of road users or user groups, including students, workers and pensioners with and without a car, both from Tallinn and elsewhere in Harju County. It helps to anticipate and take into account the transport needs of different people in the city. In this sense, the model is also innovative on a global scale, and is a complex new-generation transport model that is currently being introduced in Western Europe. In addition to creating the model, the Tallinn Transport Authority has trained people who perform analytical work using the model. As people still shape urban space with the help of the model, their competencies need to be developed.
No specific data source has been fully and uncritically trusted in the creation of the model. For example, although basic data on people’s residences come from registers, based on socio-economic surveys and calibration, register data have been smoothed to close the gap between official statistics and reality.
The model also takes into account that not all public transport passengers carry a green card in a bus, tram or trolley. Therefore, the number of entrants to public transport has been counted and the actual number of passengers has been compared with the validation data in order to reflect the reality in the best possible way.
With the help of the transport model, it is possible to take into account smaller areas when making decisions that affect traffic in the city as a whole: how many people move there, how they move and how it affects the bigger picture. In addition to public transport and cars, Tallinn’s transport model also allows pedestrians and cyclists to be taken into account.
The model is designed to increase the attractiveness of other, less resource-intensive modes, including walking and cycling, as travel costs for one mode of transport increase. Newer and more accurate data for each mode of transport can also be entered into the model as the situation changes or higher quality demand data becomes available.
All in all, decision-makers now have a digital tool at their disposal to predict transport problems and understand their causes, and to make decisions that support the city’s overall development.
Among other things, the transport model can be used to assess the feasibility and impact of major infrastructure investments on traffic, or to play and analyze scenarios in transport planning to predict changes in traffic on other major arteries if traffic on a major city is temporarily blocked or closed.
With the help of the model, it is possible to find answers to the questions why congestion occurs in some places or what reorganizations are needed to reduce the inconvenience caused by road repairs, or how major construction of state roads around Tallinn will affect traffic within the city. (ERR/Business World Magazine)
