This study aims to divide traffic into meaningful clusters （regimes） and to investigate their impact on accident likelihood and accident severity. Furthermore, the likelihood of pow- ered-two-wheelers （PTWs） invol...This study aims to divide traffic into meaningful clusters （regimes） and to investigate their impact on accident likelihood and accident severity. Furthermore, the likelihood of pow- ered-two-wheelers （PTWs） involvement in an accident is examined. To achieve the aims of the study, traffic and accident data during the period 2006-2011 from two major arterials in Athens were collected and processed. Firstly, a finite mixture cluster analysis was imple- mented to classify traffic into clusters. Afterwards, discriminant analysis was carried out in order to correctly assign new cases to the existing regimes by using a training and a testing set. Lastly, Bayesian logistic regression models were developed to investigate the impact of traffic regimes on accident likelihood and severity. The findings of this study suggest that urban traffic can be divided into different regimes by using average traffic occupancy and its standard deviation, measured by nearby upstream and downstream loop detectors. The results revealed potential hazardous traffic conditions, which are discussed in the paper. In general, high occupancy values increase accident likelihood, but tend to lead slight acci- dents, while PTWs are more likely to be involved in an accident, when traffic occupancy is high. Transitions from high to low occupancy also increase accident likelihood.展开更多
Purpose： Rear-end crashes attribute to a large portion of total crashes in China, which lead to many casualties and property damage, especially when involving commercial vehicles. This paper aims to investigate the c...Purpose： Rear-end crashes attribute to a large portion of total crashes in China, which lead to many casualties and property damage, especially when involving commercial vehicles. This paper aims to investigate the critical factors for occupant injury severity in the specific rear-end crash type involving trucks as the front vehicle （W）. Methods： This paper investigated crashes occurred from 2011 to 2013 in Beijing area, China and selected 100 qualified cases i.e., rear-end crashes involving trucks as the FV. The crash data were supplemented with interviews from police officers and vehicle inspection. A binary logistic regression model was used to build the relationship between occupant injury severity and corresponding affecting factors. More- over, a multinomial logistic model was used to predict the likelihood of fatal or severe injury or no injury in a rear-end crash. Results： The results provided insights on the characteristics of driver, vehicle and environment, and the corresponding influences on the likelihood of a rear-end crash. The binary logistic model showed that drivers＇ age, weight difference between vehicles, visibility condition and lane number of road signifi- cantly increased the likelihood for severe injury of rear-end crash. The multinomial logistic model and the average direct pseudo-elasticity of variables showed that night time, weekdays, drivers from other provinces and passenger vehicles as rear vehicles significantly increased the likelihood of rear drivers being fatal. Conclusion： All the abovementioned significant factors should be improved, such as the conditions of lighting and the layout of lanes on roads. Two of the most common driver factors are drivers＇ age and drivers＇ original residence. Young drivers and outsiders have a higher injury severity. Therefore it is imperative to enhance the safety education and management on the young drivers who steer heavy duty truck from other cities to Beiiing on weekdays.展开更多
For the purpose of exploring the factors affecting injury severity of children and adolescents involved in traffic crashes in Greece,disaggregate crash data including 13,431 involving children and adolescents from all...For the purpose of exploring the factors affecting injury severity of children and adolescents involved in traffic crashes in Greece,disaggregate crash data including 13,431 involving children and adolescents from all regions of Greece for the period 2006–2015 were utilized.In order to identify factors affecting injury severity and account for potential unobserved heterogeneity,a series of mixed logit models were utilized.To explore and address potential temporal instability of crash-related risk factors,the likelihood ratio test was applied.Results indicated that night crashes,crashes outside urban areas as well as crashes involving bicycles or powered-two-wheelers are associated with higher injury severity of children and adolescents.Interestingly,crashes involving pedestrians are associated with lower injury severity than head-on collisions and run-off-road collisions with fixed objects.Side and sideswipe crashes also result in lower injury severities.The likelihood ratio test indicated that crash-related factors are instable when comparing the models utilizing data before and after 2010 respectively.This study contributes to the current knowledge in the field,as to the best of our knowledge this is the first study that addresses unobserved heterogeneity when analyzing child and adolescent injury severity.Overall,the findings of this study provide useful insights and could assist in unveiling crash risk factors and prioritize programs and measures to promote road safety of children and adolescents.展开更多
基金supported by the special fund for research grants of NTUA for PhD studies
文摘This study aims to divide traffic into meaningful clusters （regimes） and to investigate their impact on accident likelihood and accident severity. Furthermore, the likelihood of pow- ered-two-wheelers （PTWs） involvement in an accident is examined. To achieve the aims of the study, traffic and accident data during the period 2006-2011 from two major arterials in Athens were collected and processed. Firstly, a finite mixture cluster analysis was imple- mented to classify traffic into clusters. Afterwards, discriminant analysis was carried out in order to correctly assign new cases to the existing regimes by using a training and a testing set. Lastly, Bayesian logistic regression models were developed to investigate the impact of traffic regimes on accident likelihood and severity. The findings of this study suggest that urban traffic can be divided into different regimes by using average traffic occupancy and its standard deviation, measured by nearby upstream and downstream loop detectors. The results revealed potential hazardous traffic conditions, which are discussed in the paper. In general, high occupancy values increase accident likelihood, but tend to lead slight acci- dents, while PTWs are more likely to be involved in an accident, when traffic occupancy is high. Transitions from high to low occupancy also increase accident likelihood.
文摘Purpose： Rear-end crashes attribute to a large portion of total crashes in China, which lead to many casualties and property damage, especially when involving commercial vehicles. This paper aims to investigate the critical factors for occupant injury severity in the specific rear-end crash type involving trucks as the front vehicle （W）. Methods： This paper investigated crashes occurred from 2011 to 2013 in Beijing area, China and selected 100 qualified cases i.e., rear-end crashes involving trucks as the FV. The crash data were supplemented with interviews from police officers and vehicle inspection. A binary logistic regression model was used to build the relationship between occupant injury severity and corresponding affecting factors. More- over, a multinomial logistic model was used to predict the likelihood of fatal or severe injury or no injury in a rear-end crash. Results： The results provided insights on the characteristics of driver, vehicle and environment, and the corresponding influences on the likelihood of a rear-end crash. The binary logistic model showed that drivers＇ age, weight difference between vehicles, visibility condition and lane number of road signifi- cantly increased the likelihood for severe injury of rear-end crash. The multinomial logistic model and the average direct pseudo-elasticity of variables showed that night time, weekdays, drivers from other provinces and passenger vehicles as rear vehicles significantly increased the likelihood of rear drivers being fatal. Conclusion： All the abovementioned significant factors should be improved, such as the conditions of lighting and the layout of lanes on roads. Two of the most common driver factors are drivers＇ age and drivers＇ original residence. Young drivers and outsiders have a higher injury severity. Therefore it is imperative to enhance the safety education and management on the young drivers who steer heavy duty truck from other cities to Beiiing on weekdays.
基金funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 754462
文摘For the purpose of exploring the factors affecting injury severity of children and adolescents involved in traffic crashes in Greece,disaggregate crash data including 13,431 involving children and adolescents from all regions of Greece for the period 2006–2015 were utilized.In order to identify factors affecting injury severity and account for potential unobserved heterogeneity,a series of mixed logit models were utilized.To explore and address potential temporal instability of crash-related risk factors,the likelihood ratio test was applied.Results indicated that night crashes,crashes outside urban areas as well as crashes involving bicycles or powered-two-wheelers are associated with higher injury severity of children and adolescents.Interestingly,crashes involving pedestrians are associated with lower injury severity than head-on collisions and run-off-road collisions with fixed objects.Side and sideswipe crashes also result in lower injury severities.The likelihood ratio test indicated that crash-related factors are instable when comparing the models utilizing data before and after 2010 respectively.This study contributes to the current knowledge in the field,as to the best of our knowledge this is the first study that addresses unobserved heterogeneity when analyzing child and adolescent injury severity.Overall,the findings of this study provide useful insights and could assist in unveiling crash risk factors and prioritize programs and measures to promote road safety of children and adolescents.
