MICD, together with TU Delft, is launching a study on the conversion of cycling data into useful policy recommendations for governments. Based on large amounts of data collected by public authorities, analysts will assess the quality of the data, which trends they observe and how these insights may form the basis for the future design of cities.

Duration
2023

Partners (TU Delft)
TU Delft-CEG, department of Transport & Planning

Partners (other)
Rijkswaterstaat, NDW, Tour de Force

As a cycling country, the Netherlands has excellent cycle paths and high-quality bicycle parking facilities. The government wants to further stimulate bicycle use in the coming years. This will require major investments. To responsibly manage these investments, the need for numerical substantiation increases. Think of statistics on the expected effect of expanding infrastructure and what this infrastructure has to consist of.

In recent years, the government has collected a lot of cycling data using GPS trackers with the help of volunteer participants. Scientists from the Transport & Planning department of TU Delft’s Faculty of Civil Engineering and Geosciences will analyse this data together with MICD. The challenge for the research group is to derive elements from these large amounts of data, which municipalities and provinces can use to assess, adjust and monitor their mobility policy. In designing cities and towns, governments have to take many different factors into account. Often, there are also (seemingly) conflicting interests. In a limited space, good accessibility is important for cyclists, pedestrians, cars and logistics traffic. Obviously, safety is a key factor. But sustainability, liveability and recreation also weigh heavily. So how do we take all these aspects into account while simultaneously stimulating the use of bicycles?

The expert knowledge of TU Delft and MICD is crucial for analysing the GPS data and making the connection with daily practice. This research constitutes a first step in a national uniform working method in the field of GPS-data driven innovation of cycling policy. In addition, the study provides valuable insights and advice for future data collection.