Identifiying suitable areas for mobility stations with the help of data

The mobility sector needs to drastically reduce GHG emissions. Therefore, cities need to plan and optimise their transport systems to reduce commuting times and the energy used for various means of transportation, while also increasing the efficiency of traffic planning. This can be achieved by finding local areas where different means of transport intersect and developing these areas into so-called mobility stations. The overarching goal of the project is to use existing data from the city of Mainz, which is then merged and analysed to identify optimal locations for the construction of mobility stations.

In partnership with Mainzer Stadtwerke AG, DKSR is developing a concept for data analysis that uses static, dynamic, and synthetic data sets to identify these optimised spots for mobility stations. The specific aim is to develop a computer-based, quantitative model that can detect these optimal locations for the mobility stations. The model is to be developed based on already-identified user groups and show different possible scenarios for the construction of the stations. The basis is user-specific KPIs, which are 'blended' with each other in such a way that optimal locations for mobility stations emerge for the users.

The use case acts as a proof of concept for the project "Kommunale DatenWerke (Municipal Data Factory)," which aims at driving innovation and collaboration by facilitating seamless data exchange among different municipal stakeholders and fostering efficient, data-driven services.