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Modelling the development of urban public transport networks

The most detailed information about the movement of passengers around a city can be obtained from the data on ticket validations combined with a database of navigation markers of ground transport. In Russia, the processing of this data was first developed in 2010 by the specialists of IEC-city. That year, 100% of public vehicles in Moscow were succesfully equipped with GLONASS and the ticket validation system.

This technology provides detailed information about the journey made by each passenger. This allows a matrix to be built with each stop and each 5-minute interval of any day accuracy. In contrast to the gravitational flow construction technique, the validations method reflects the fact of ticket validation by the same passenger in different parts of the city.

In cities not equipped with electronic fare collecting systems, we conduct surveys by installing passenger traffic counting equipment on a limited number of carrier rolling stock. The number of passengers boarding, leaving and remaining is measured at every stop. This allows the creation of in-route correspondence matrices and evaluation of citywide travel on public transport.

In order to forecast passenger traffic, we analyze the age and gender structure of the target area, broken down by district. In addition, we use the urban development plans for the area. This holistic approach allows us to modify the current correspondence matrix for the forecast period and to ensure high accuracy of future passenger traffic projections.

Analysis and forecasting of information about passenger flows obtained for each stop allows the effects to be calculated in detail for various development scenarios of route networks and lines (infrastructjre) for all means of transport, including overall journey time, including transfers and its minimization.

TransCAD software is used for calculating the correspondence distribution. This is the best suited software for processing data on public transport. The model can be set with a network of all types of transport, with its own speed, transfer time, etc. This allows accurate and realistic calibration of the model.

Each possible solution for a new route network is evaluated in terms of the following indicators:

  • The total time spent by passengers and the time they would be saving (in cash equivalent);
  • Socio-economic effects (reduction in the number of traffic accidents and fatalities, reduction in environmental pollution, etc.);
  • Capital and operating costs of the project life cycle (usually 30 years).
The most efficient option is recommended for implementation. It is the option that guarantees a maximum socio-economic effect per unit of capital and per operating costs for the project life cycle.