Geospatial Risk Assessment of Cyclist Accidents in Urban Areas: A K-means Clustering Approach

• Type: Article in International Conference Proceedings Book
• Date: 2024

Authors

Brito, B (Author) Other; Costa, DG (Author) FEUP; Silva, I (Author) Other

Conference proceedings International

Title: 2024 IEEE 22ND MEDITERRANEAN ELECTROTECHNICAL CONFERENCE, MELECON 2024

Pages: 744-749

IEEE 22nd Mediterranean Electrotechnical Conference (MELECON)

Porto, PORTUGAL, JUN 25-27, 2024

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Other information

Authenticus ID: P-012-PBX

DOI: 10.1109/melecon56669.2024.10608791

Abstract (EN): 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 Munster, 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6