Despite advances in route optimization and navigational technologies, pedestrians still face challenges navigating complex urban spaces. This study aims to identify and quantify the multidimensional factors that influence pedestrian navigation, with the focus on why people get lost. The collected data from an online survey in which 64 participants reported the locations and contextual information of their getting lost events. Building upon literature, expert interviews, and collected data, we identify and quantify 14 environmental, situational, and personal factors influencing pedestrian navigation. We utilize a dual-analytical approach that combines expert-led analytic hierarchy process (AHP) analysis with data-driven regression models to derive distinct weighting schemes for the factors. While the approach based on experts’ opinion (i.e. AHP) demonstrates that familiarity, self-orientation skills, and access to reliable navigation tools are the most important contributing factors, data-driven models additionally highlight the significance of environmental complexity, such as angular distance between exits and number of landmarks near decision points. Importantly, expert-led and data-driven methods reveal different but complementary influences on pedestrian navigation, underscoring the value of combining specialist knowledge with insights derived from observed data to improve our understanding and guide the creation of more navigable urban environments.
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Wang et al. (2026) studied this question.
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