Ye, Ying;
Zhong, Chen;
Suel, Esra;
(2024)
Unpacking the perceived cycling safety of road environment using street view imagery and cycle accident data.
Accident Analysis & Prevention
, 205
, Article 107677. 10.1016/j.aap.2024.107677.
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Abstract
Cycling, as a routine mode of travel, offers significant benefits in promoting health, eliminating emissions, and alleviating traffic congestion. Many cities, including London, have introduced various policies and measures to promote ’active travel’ in view of its manifold advantages. Nevertheless, the reality is not as desirable as expected. Existing studies suggest that cyclists’ perceptions of cycling safety significantly hinder the broader adoption of cycling. Our study investigates the perceived cycling safety and unpacks the association between the cycling safety level and the road environment, taking London as a case study. First, we proposed novel cycling safety level indicators that incorporate both collision and injury risks, based on which a tri-tiered cycling safety level prediction spanning the entirety of London's road network has been generated with good accuracy. Second, we assessed the road environment by harnessing imagery features of street view reflecting the cyclist's perception of space and combined it with road features of cycle accident sites. Finally, associations between road environment features and cycling safety levels have been explained using SHAP values, leading to tailored policy recommendations. Our research has identified several key factors that contribute to a risky environment for cycling. Among these, the “second road effects,” which refers to roads intersecting with the road where the accident occurred, is the most critical to cycling safety levels. This would also support and further contribute to the literature on road safety. Other results related to road greenery, speed limits, etc, are also discussed in detail. In summary, our study offers insights into urban design and transport planning, emphasising the perceived cycling safety of road environment.
Type: | Article |
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Title: | Unpacking the perceived cycling safety of road environment using street view imagery and cycle accident data |
Location: | England |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1016/j.aap.2024.107677 |
Publisher version: | http://dx.doi.org/10.1016/j.aap.2024.107677 |
Language: | English |
Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third-party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
Keywords: | Science & Technology, Social Sciences, Technology, Life Sciences & Biomedicine, Ergonomics, Public, Environmental & Occupational Health, Social Sciences, Interdisciplinary, Transportation, Engineering, Social Sciences - Other Topics, Perceived Cycling safety, Road environment, Street view imagery, Interpretable machine learning, TRANSPORT, IMPACT, BEHAVIOR, LEVEL, RISK |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis |
URI: | https://discovery.ucl.ac.uk/id/eprint/10198854 |
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