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Perceived traffic safety’s impact on cycling route choice with street-level images
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DOI：10.1007/s11116-026-10793-z.png)
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Abstract
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Perceived traffic safety influences cycling behavior, yet its value relative to travel time and other route attributes remains unquantified. Building on the stated choice experiment and street-level image dataset of Terra et al. (2025), we extract safety perception scores from cycling-perspective images using a computer vision model and estimate mixed logit models to test whether perceived safety affects route choice after controlling for visual street-level features. Cyclists are willing to accept 64 additional seconds of travel time for a one-unit increase in perceived safety (scale: $$-2$$ very unsafe to $$+2$$ very safe). Safety preferences vary across demographic groups: older cyclists, recreational cyclists, and those with positive cycling attitudes place more weight on safety, while commuters prioritize speed. These willingness-to-pay estimates enable planners to quantify perceived safety improvements for cost-benefit analyses and to score existing cycling networks for targeted infrastructure upgrades. (Replication code: https://github.com/koito19960406/cycling_safety_perception ).
Keywords:
Cycling route choice
Traffic safety perception
Street-level imagery
Computer vision
Discrete choice modeling
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