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With this relatively new method for data collection – TravelVu – it is possible to obtain a completely new type of data which has proven to be significantly more precise than data collected with previous methods. The possibilities are endless for how we can find answers to questions for how to increase and make more efficient use of the public transport system. For example, we can better understand how types of errands and destinations differ with different transport lines, or not only where changes happen but also detailed information about the trips to/from public transport.
The overall goal of public transport is a doubled market share. In the process of finding ways to achieve this, we have discovered that in-depth knowledge of how travellers behave is often lacking. With this relatively new method for data collection – TravelVu – it is possible to obtain a completely new type of data which has proven to be significantly more precise than data collected with previous methods.
Public transport has a pretty good idea of who their travellers are but less of an idea of their traveller’s habits and behaviours towards public transport not to mention information about those not using public transport. With data from TravelVu, travellers and their errands, as well as which lines they use, can be reported. This can help the industry design additional services for increased use.
Knowledge of actual travel times and durations is often low even though it is an important factor for choice of travel mode. Using data from TravelVu, travel times and durations can be described more accurately. For example, the total time can be divided into connecting journeys, waiting and exchange times and the actual time spent on the train or bus. It is also possible to review how travel on public transfer changes throughout the day, or throughout the week.
Today the industry has a good idea of where travellers get on and off public transport, but where travellers switch lines or transfer to another mode of transport is difficult to get a clear picture of. Data from TravelVu not only can report where transfers are taking place but can also map the connecting relations geographically for a better picture over travel patterns.
Public transport authorities have a good idea of the trips taken along their routes, but less of an idea of the habits and behaviours of those who do not travel by public transport, especially for travel done outside the usual commutes to school and work. These trips and travellers have a potential to be attracted to public transport options. By plotting data from TravelVu, target points and / or errands can be identified where public transport has a low market share.
Stephan Bösch
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