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Blackspot identification is a global concern in road safety. The accident-based method has been widely employed over the past few decades but remains reactive, as it depends on accidents occurring and causing harm. To overcome its limitations, proactive methods based on surrogate indicators have emerged. However, apart from Traffic Conflict Technology (TCT), other surrogate indicators lack a comprehensive framework spanning from extraction to practical application, emphasizing a key priority for future research. Despite numerous proposed methods, critical evaluation of their strengths, limitations, and application contexts remains limited. Additionally, the literature often overlooks the measurement of ‘potential accident risk’ in blackspot identification. Due to the rarity and randomness of accidents, even high-risk sections may record accident counts below the threshold during observation. This paper reviews 182 studies, examining blackspot identification methods and exploring potential accident risk through surrogate indicators. It underscores the importance of integrating potential risk into identification processes and summarizes the application of these methods across countries with varying income levels. Finally, it outlines the connection between blackspot identification and accident severity analysis, offering recommendations for future research.
Zhang et al. (Mon,) studied this question.