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Identifying contributing factors and locations of pedestrian severe crashes using hazard-based duration model

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dc.contributor.author Kakhani, A. pt_BR
dc.contributor.author Jalayer, M. pt_BR
dc.contributor.author Kidando, E. pt_BR
dc.contributor.author Roque, C. A. pt_BR
dc.contributor.author Patel, D. pt_BR
dc.date.accessioned 2025-01-31T15:47:23Z pt_BR
dc.date.accessioned 2025-04-22T12:57:37Z
dc.date.available 2025-01-31T15:47:23Z pt_BR
dc.date.available 2025-04-22T12:57:37Z
dc.date.issued 2024-04 pt_BR
dc.identifier.uri http://repositorio.lnec.pt:8080/jspui/handle/123456789/1018209
dc.description.abstract Pedestrian safety remains a significant concern, with the growing number of severe pedestrian crashes resulting in substantial human and economic costs. Previous research into pedestrian crashes has extensively analyzed the influences of weather, lighting, and pedestrian demographics. However, these studies often overlook the critical spatial variables that contribute to pedestrian crashes. Our study aims to explore these overlooked spatial variables by examining the distance pedestrians travel before encountering a severe crash. This approach provides a supplementary perspective in safety analysis, emphasizing the importance of pedestrian movement patterns. The model considers various factors that may influence pedestrian traveled distance before being involved in a severe crash, such as weather conditions, lighting conditions, and pedestrian demographics. Ohio’s pedestrian-involved crashes were gathered and analyzed as a case study. The results indicated that 50 % of fatal pedestrian crashes occurred within 0.84 miles of the pedestrians’ residences. Moreover, it was shown that factors including lighting condition, pedestrian age, drug toxication, and the location at impact significantly influence the pedestrians traveled distance. These findings provide valuable insights into the spatial distribution of pedestrian crashes and shed light on the factors contributing to their severity. By understanding these relationships, policymakers and urban planners can design targeted interventions such as improving street lighting, implementing traffic calming measures, and developing safety awareness campaigns for specific age groups, to enhance pedestrian safety and reduce the incidence of severe crashes. pt_BR
dc.language.iso eng pt_BR
dc.publisher Elsevier pt_BR
dc.rights restrictedAccess pt_BR
dc.subject Hazard-Based Duration Model pt_BR
dc.subject Pedestrian Crash pt_BR
dc.subject Traveled Distance pt_BR
dc.subject Cox Model pt_BR
dc.subject Crash Severity pt_BR
dc.title Identifying contributing factors and locations of pedestrian severe crashes using hazard-based duration model pt_BR
dc.type workingPaper pt_BR
dc.description.pages 107500 pt_BR
dc.description.volume 198 pt_BR
dc.description.sector CD/CD pt_BR
dc.description.magazine Accident Analysis & Prevention pt_BR
dc.contributor.peer-reviewed SIM pt_BR
dc.contributor.academicresearchers SIM pt_BR
dc.contributor.arquivo NAO pt_BR


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