Road safety is a major concern that raises significant worries, especially regarding accidents involving pedestrians. Often, the study of interaction between pedestrians and vehicles focuses on various measurable factors such as vehicle speed and pedestrian crossing speed, often overlooking human behaviors that have a significant impact on this interaction. In this regard, studying road risks poses a challenge that requires a systematic approach to successful overcoming. In this article, we compare both fuzzy and intuitionistic approaches to assess pedestrians' exposure to accident risks. These two approaches take uncertainty into account in a more natural way than classical methods based on precise values. Being more adept at handling uncertainty than classical methods, these approaches provide a finer understanding of reality, thus enabling the development of more tailored safety measures to protect pedestrians. Comparative analysis of the results highlights a significant improvement in the accuracy of risk assessments, underscoring the effectiveness of these approaches in the context of road safety.