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• W4280494683 endingPage "106707" @default.
• W4280494683 startingPage "106707" @default.
• W4280494683 abstract "Despite improvements to road safety, accidents involving pedestrians are still numerous, for example in the UK there were over 20,000 pedestrian casualties on public roads in 2019. One of the potential causal factors is pedestrian distraction. Therefore, this study aimed to predict pedestrian intention to cross the road under conditions of distraction (using phone maps, talking to another pedestrian, listening to music through headphones), by applying the Theory of Planned Behaviour (TPB) using an online survey. This also involved investigation of the impact of selected traffic characteristics (traffic density, vehicle speed) and crossing type (pelican, zebra, unmarked). The survey consisted of 72 questions and took approximately 15 min to complete. The results (N = 81) revealed that the TPB construct of perceived behavioural control (PBC) was a significant predictor of intention to cross the road while distracted across all scenarios. Furthermore, crossing type was a significant predictor of PBC across all scenarios, with marked crossings facilitating feelings of PBC. Findings suggest that high feelings of PBC, as measured through ease and confidence, are linked with stronger intention to cross the road while distracted. This understanding of pedestrian motivation can be used to help design interventions (such as auditory and visual pedestrian warnings) that prevent conflict between distracted pedestrians and vehicles. These interventions should target marked crossing types, whereby pedestrians are more likely to cross while distracted." @default.
• W4280494683 created "2022-05-22" @default.
• W4280494683 creator A5025775908 @default.
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• W4280494683 date "2022-08-01" @default.
• W4280494683 modified "2023-10-14" @default.
• W4280494683 title "Predicting the intention of distracted pedestrians at road crossings" @default.
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• W4280494683 doi "https://doi.org/10.1016/j.aap.2022.106707" @default.
• W4280494683 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35594743" @default.
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