The Analysis of the Effects of a Fare Free Public Transport Travel Demand Based on E-Ticketing

The traditional approach in public transport planning was to collect travel demand data for a more extended period and compose timetables to serve this demand. There are two significant identifiable issues. In the rural areas and off-peak hours, public transport operators provide much more capacities than needed. On the other hand, more capacities than scheduled are needed on certain lines at certain departures on some sporadically occurring occasions. The problem is how to react to short-term changes (daily) triggered by exceptional circumstances and events and midterm changes (weekly, monthly basis) in travel demand. We can trigger changes in travel demand chiefly by introducing a desirable (almost for free) tariff system applied to specific populations. No long-term travel response data exists for this kind of intervention, but an immediate response in public transport supply is needed. In Slovenia, public transport for free for the whole population over 65 years was introduced. With the modern ticketing system, which was designed to be as simple as possible for users (that means >> check-in only << at the moment of boarding), the research task was to analyze the travel behavior of the retired population, faced with a new attractive option to travel, based on data of purchased tickets and their afterward validation, for better mid-and long-term planning. Our study finds that ITS technology (in this case, e-ticketing system) can satisfactorily solve the discussed planning and management task.

Automated summary

The traditional approach in public transport planning involves collecting long-term travel demand data and creating timetables accordingly. However, short-term and midterm changes in travel demand pose challenges. One potential solution is introducing a free tariff system for specific populations to stimulate travel demand changes. Slovenia implemented free public transport for citizens aged over 65, and by analyzing the travel behavior of retirees using ticketing data, they were able to improve planning and management effectively.