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Title	Geospatial Risk Assessment Of Cyclist Accidents In Urban Areas: A K-Means Clustering Approach
ID_Doc	27990
Authors	Brito B.; Costa D.G.; Silva I.
Year	2024
Published	2024 IEEE 22nd Mediterranean Electrotechnical Conference, MELECON 2024
DOI	http://dx.doi.org/10.1109/MELECON56669.2024.10608791
Abstract	This paper presents a geospatial assessment approach to evaluate the risk of cyclist accidents in urban areas. Utilizing data about road intersections, bike lanes, and bus stops, the proposed data-driven methodology integrates multiple urban infrastructure data and employs K-means clustering to identify distinct risk clusters within a city. The resulting clusters offer valuable information for targeted interventions and urban planning, supporting the development of safer cities for cyclists. This innovative approach, leveraging geospatial analytics and clustering techniques, provides a practical framework for city planners and policymakers to prioritize and implement measures for enhancing cyclist safety, for any urban area in the world. Experimental results for the city of Münster, Germany, are presented to support the validation of the proposed approach, highlighting how the achieved results could promote more sustainable smart cities. Historical records of accidents involving cyclists are also considered as an important evaluation step. © 2024 IEEE.
Author Keywords	Bike lanes; Bus stops; City planning; Cyclist safety; Road intersections; Smart cities

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