Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Investigating the Impact of Various Risk Factors on Victims of Traffic Accidents
In this study, our goal was to determine the impact of various risk factors on traffic accidents in the city of Shenyang, China, and to discuss the various common factors that influence pedestrian and non-motor vehicle accidents. A total of 1227 traffic accidents from 2015 to 2017 were analyzed, of which, 733 were accidents involving pedestrians and 494 were non-motor vehicle accidents. Among these traffic accidents, pedestrians and non-motor vehicle users had either minor or no responsibility. Sixteen influencing factors, including main responsible party attributes, pedestrian/non-motor vehicle user attributes, time attributes, space attributes, and environmental attributes were analyzed with regards to their impact on accidents using the binary logistic regression model (BLR) and the classification and regression tree analysis model (CART). Age, administrative division, and time of year were the three most common factors for pedestrian and non-motor vehicle accidents. For pedestrian accidents, the personal influencing factors of the main responsible party included illegal acts while driving and hit-and-run behavior. Factors affecting pedestrian and non-motor vehicle accidents also had different orders of importance.
Investigating the Impact of Various Risk Factors on Victims of Traffic Accidents
In this study, our goal was to determine the impact of various risk factors on traffic accidents in the city of Shenyang, China, and to discuss the various common factors that influence pedestrian and non-motor vehicle accidents. A total of 1227 traffic accidents from 2015 to 2017 were analyzed, of which, 733 were accidents involving pedestrians and 494 were non-motor vehicle accidents. Among these traffic accidents, pedestrians and non-motor vehicle users had either minor or no responsibility. Sixteen influencing factors, including main responsible party attributes, pedestrian/non-motor vehicle user attributes, time attributes, space attributes, and environmental attributes were analyzed with regards to their impact on accidents using the binary logistic regression model (BLR) and the classification and regression tree analysis model (CART). Age, administrative division, and time of year were the three most common factors for pedestrian and non-motor vehicle accidents. For pedestrian accidents, the personal influencing factors of the main responsible party included illegal acts while driving and hit-and-run behavior. Factors affecting pedestrian and non-motor vehicle accidents also had different orders of importance.
Investigating the Impact of Various Risk Factors on Victims of Traffic Accidents
Jianyu Wang (Autor:in) / Huapu Lu (Autor:in) / Zhiyuan Sun (Autor:in) / Tianshi Wang (Autor:in) / Katrina Wang (Autor:in)
2020
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
Metadata by DOAJ is licensed under CC BY-SA 1.0
Post-traumatic stress reactions in young victims of road traffic accidents
Taylor & Francis Verlag | 2017
|Factors which contribute to traffic accidents
Taylor & Francis Verlag | 1976
|Investigating Driver Injury Severity in Traffic Accidents Using Fuzzy ARTMAP
Online Contents | 2002
|Classification of traffic accidents’ factors using TrafficRiskClassifier
Elsevier | 2024
|