Traffic injury prevention · 2022
Modeling factors contributing to dockless e-scooter injury accidents in Austin, Texas.
СтатьяПоддержка исследования: вне правительства СШАПоддержка правительства СШАНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Azimian Amin, Jiao Junfeng
Аннотация
OBJECTIVE: Over the past few years, increased e-scooter ridership has raised concerns about the growing number of injury accidents involving e-scooters. Additionally, given the lack of appropriate e-scooter accident data, the extent to which built environment and socioeconomic factors affect e-scooter safety is unclear. In consideration of these issues, this study was aimed at identifying the factors contributing to the number of e-scooter injury accidents in Austin.
METHODS: We developed zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) models on the basis of 2018 dockless e-scooter injury accident data collected from the Patch platform. The results indicated that the ZIP model better fit the accident data.
RESULTS: Significant variables included the ratio of 18- to 34-year-old males to their female counterparts, the median annual household income (in thousands), the ratio of public transport users to private transport users, the land use entropy index, the percentage of restaurants, and the percentage of educational centers in the study site.
CONCLUSIONS: As e-scooter accidents are likely to occur in dense urban settings, a critical initiative is to develop new infrastructure, such as bike lanes, and/or extend sidewalks beyond core urban areas. Another highly recommended measure is to implement a demerit point system for the suspension of riders who engage in unsafe behaviors. Lastly, launching educational campaigns by e-scooter operators and law enforcement agencies will raise riders' awareness about road and personal safety.
METHODS: We developed zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) models on the basis of 2018 dockless e-scooter injury accident data collected from the Patch platform. The results indicated that the ZIP model better fit the accident data.
RESULTS: Significant variables included the ratio of 18- to 34-year-old males to their female counterparts, the median annual household income (in thousands), the ratio of public transport users to private transport users, the land use entropy index, the percentage of restaurants, and the percentage of educational centers in the study site.
CONCLUSIONS: As e-scooter accidents are likely to occur in dense urban settings, a critical initiative is to develop new infrastructure, such as bike lanes, and/or extend sidewalks beyond core urban areas. Another highly recommended measure is to implement a demerit point system for the suspension of riders who engage in unsafe behaviors. Lastly, launching educational campaigns by e-scooter operators and law enforcement agencies will raise riders' awareness about road and personal safety.