Forecasting of travel demand in urban public transport

The key of the planning of public transport systems is the accurate prediction of the traffic load, or the correct execution of the planning stage assignment. This requires not only a well-functioning assignment method, but also reliable passenger data. Reliable passenger data means time-dependent origin-destination matrix. To solve the problem of lack of time-dependent passenger data we have developed a forecasting method. It consists of three stages. In the first stage we collect full scope cross-section data. This can be done either with personnel or an automatic counting system. If personnel are used it costs a lot and there are many possible errors. However the results in most cases are good enough. Automatic counting system can be either a counter machine or even a simple “Check in” E-ticketing system. In the second stage, we link boarding and alighting. As result we get the origin-destination matrix for each run. This method is based on the likelihood of alighting at a given stop. In the third stage, we combine origin-destination matrices of the runs through transfers. At this stage we assume that the probability of a transfer between two runs in a given stop is proportional to the travel possibilities in this relation. To view the entire method in the practice we proved it in a Hungarian cities. The results were reliable, so they could be use in the planning process.