Optimising Cyclist Road-Safety Scenarios Through Angle-of-View Analysis Using Buffer and GIS Mapping Techniques
In the present era, achieving sustainability requires the development of planning strategies to develop a safer urban infrastructure. This study examines the realistic aspects of cyclist safety by analysing cyclists’ fields of view, using Geographic Information Systems (GIS) and spatial data analysi...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
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| Series: | Infrastructures |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2412-3811/10/7/184 |
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| Summary: | In the present era, achieving sustainability requires the development of planning strategies to develop a safer urban infrastructure. This study examines the realistic aspects of cyclist safety by analysing cyclists’ fields of view, using Geographic Information Systems (GIS) and spatial data analysis. The research introduces novel geoprocessing tools-based GIS techniques that mathematically simulate cyclists’ angles of view and the distances to nearby environmental features. It provides precise insights into some potential hazards and infrastructure challenges encountered while cycling. This research focuses on managing and analysing the data collected, utilising OpenStreetMap (OSM) as vector-based supporting data. It integrates cyclists’ behavioural data with the urban environmental features encountered, such as intersections, road design, and traffic controls. The analysis is categorised into specific classes to evaluate the impacts of these aspects of the environment on cyclists’ behaviours. The current investigation highlights the importance of integrating the objective environmental elements surrounding the route with subjective perceptions and then determining the influence of these environmental elements on cyclists’ behaviours. Unlike previous studies that ignore cyclists’ visual perspectives in the context of real-world data, this work integrates objective GIS data with cyclists’ field of view-based modelling to identify high-risk areas and highlight the need for enhanced safety measures. The proposed approach equips urban planners and designers with data-informed strategies for creating safer cycling infrastructure, fostering sustainable mobility, and mitigating urban congestion. |
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| ISSN: | 2412-3811 |