Risk Perception Accuracy Among Urban Cyclists: Behavioral and Infrastructural Influences in Loja, Ecuador

Urban cycling faces the challenge of cyclist vulnerability due to infrastructural deficiencies and complex traffic environments. This study evaluates the accuracy of risk perception among 153 urban cyclists in Loja, Ecuador, using a mixed-methods design that integrates self-reported behaviors (Cycling Behavior Questionnaire—CBQ), visual assessments of 12 road segments, and objective risk classifications derived from the CycleRAP methodology. Results show a notable misalignment between perceived and actual risk, with consistent underestimation of extreme-risk scenarios and overestimation of low-risk ones. The combined CBQ score (violations + errors) emerged as the strongest predictor of inaccurate risk perception in decision tree models, explaining 28.75% of the model’s predictive power. Interestingly, cycling experience did not improve accuracy; frequent cyclists with high violation/error scores and older age showed the poorest perception, while young cyclists with moderate behavior scores exhibited higher accuracy. These results suggest that the relationship between cycling experience and risk assessment is more complex than commonly assumed. Findings highlight the need for behavioral interventions to correct misperceptions, alongside infrastructural measures that address objective hazards. Given the limited number of road segments and moderate sample size, subgroup analyses may be underpowered and should be interpreted with caution.