As one of the most well-known forms of active mobility, cycling is an environmentally friendly way to explore a destination, becoming increasingly prevalent worldwide. However, safety is the most severe issue facing cyclists and the essential factor for people who are hesitant to use bikes. In this context, we propose a safety assessment method for cycling routes in urban environments. This work presents how to automatically generate a safe cycling map integrating volunteered geographic information with GIS analysis. We start by extracting the indicators that can possibly contribute to cycling safety from OpenStreetMap. Then, we set up a multivariate linear regression equation to solve the importance of indicators. Afterward, we generate a weighted graph model that represents cycling safety. Taking the City of Bonn, Germany, as an example, we implement our approach for this region. The experiment results show that Bonn is a city for safe cycling, confirming the claim that Bonn is a bike-friendly city. Our findings can also be used to plan the safest route for cycling, thereby enhancing the overall biking experience in Bonn.
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Li et al. (2024) studied this question.
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