A dramatic increase in car traffic poses a significant challenge to the city of Debrecen, with the number of cars doubling since the 1990s. Many people use a private vehicle to commute from low-density residential areas, as their destination is often too far to cycle and there is a lack of secure bicycle parking near transportation hubs. The city is looking for ways to encourage people to leave their cars at home by connecting these suburban areas to the public transport network using sustainable alternatives.
Asistobe’s SaaS Suite allows city planners to explore, predict and optimise their entire public transport network. Transport planners can use the software to gain a visual understanding of how people move around. It can also be used to make precise predictions on future transport demands, while employing optimisation algorithms to maximise public transport efficiency and cost-effectiveness.
During the project, Asistobe will develop a new AI algorithm as part of the SaaS Suite. The algorithm will identify the potential of public transport network optimisation activities and allow the city to analyse real transport demand. Based on early indications, Debrecen’s resource efficiency can be improved by 15%. Asistobe will also improve the tool’s onboarding process to accommodate new data sources.
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Encourage active mobility among commuters from low density areas between home and public transport networks.
The goal of the project is to reduce the number of people commuting daily by private vehicle.
The Asistobe solution will boost public transport network predictions and optimisation, thereby promoting more sustainable means of transport among commuters.
