For the start2park research project we developed a new data-based collection methodology in collaboration with ReLUT (Research Lab for Urban Transport) at FH Frankfurt and bliq, a provider of innovative solutions in the field of mobility, to collect parking data using an app. Machine learning and artificial intelligence are used to gain new insights into sustainable mobility and thus improve the quality of life in urban areas.

The start2park app is the central component of the research project start2park – parking search recording, understanding and forecasting. In order to understand and forecast parking search (parking search time and parking search distance), the start2park app generates a database for the first time, which can be used to develop both an explanatory and a forecasting model for parking search traffic.

Find more information on the project website.

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