Using hierarchical Bayesian binary probit models to analyze crash injury severity on high speed facilities with real-time traffic data

Yu, Rongjie; Abdel-Aty, Mohamed

doi:10.1016/j.aap.2013.08.009

Cited by 115 publications

(41 citation statements)

References 16 publications

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“…To the best of our knowledge there are no studies with real-time data that explore PTW accident risk, the literature review indicated that relevant studies have a more general scope and explore accident risk (Abdel-Aty and Pande, 2005; Abdel-Aty et Ahmed and Abdel-Aty, 2012;Xu et al, 2013a andHassan and Abdel-Aty, 2013;Abdel-Aty et al 2012;Yu and Abdel-Aty, 2013b), accident frequency (Yu and Abdel-Aty, 2013a;Yu et al, 2013) or accident severity (Christoforou et al, 2010;Golob et al, 2008;Abdel-Aty, 2014a and2014b;Xu et al, 2013b;Jung et al, 2010). It is also noted, that the vast majority of studies exploit data from freeways.…”

Section: Introductionmentioning

confidence: 88%

Investigation of powered 2-wheeler accident involvement in urban arterials by considering real-time traffic and weather data

Theofilatos

Yannis

2016

Traffic Injury Prevention

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Section: Introductionmentioning

confidence: 88%

Investigation of powered 2-wheeler accident involvement in urban arterials by considering real-time traffic and weather data

Theofilatos

Yannis

2016

Traffic Injury Prevention

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“…It has been stated that there is an increasing relationship between the higher speed and severity of the accidents (Chen et al, 2000;Yu et al, 2014;Dadashova et al, 2014). Almost 22% of the accident related fatalities have been estimated to be caused by inadequate speed (Chen et al, 2000) as it was observed in fatal accidents in Spain during year.…”

Section: Road Accident Predictorsmentioning

confidence: 99%

Simulation Study of the Effect of Decreasing Truck Traffic Flow on Safety on Almeria-Barcelona Corridor

Dadashova

2016

Libro De Actas CIT2016. XII Congreso De Ingeniería Del Transporte

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In this paper the effect of truck traffic on road safety has been analyzed through simulation study. The main objective of the study is to quantify the effect of the decreasing average annual daily traffic of heavy duty vehicles (trucks) on road safety. As the road safety indicators the frequency road accidents is considered. The data used in the study were collected from one of the most crowded routes in Spain which connects Almeria (southeast) with Barcelona (northeast). The observed data covers year 2010 and were classified into 2 road types: dual carriageways and toll roads. The estimation was carried out using negative binomial model and Markov Chain Monte Carlo simulation. Using the estimation results new traffic scenarios were proposed where the traffic flow is assumed to change its values. A total of 33 scenarios were proposed and new accidents data were generated through MCMC sampling. The comparison of the simulated and observed accident data shows that the effect of decreasing truck traffic flow could meliorate road safety in the route. The simulation tool could be applied to evaluate the effects of freight modal shift from road to rail.

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“…Likewise, the effectiveness of speed cameras in the reduction of road traffic collisions and related casualties has been extensively demonstrated (see Pilkington and Kinra 2005;Wilson et al 2006, among others), which would seem to confirm that high speeds increase the risk of collision. Speeding, moreover, has been shown to be directly related to the severity of accidents (see, among others, Dissanayake and Lu 2002;Jun et al 2007Jun et al , 2011, while Yu and Abdel-Aty (2014) report that marked variations in speed prior to a crash increase the likelihood of severe accidents.…”

Section: Introductionmentioning

confidence: 99%

Quantile Regression with Telematics Information to Assess the Risk of Driving above the Posted Speed Limit

Pérez-Marín

Guillén

Alcañiz

et al. 2019

Risks

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We analyzed real telematics information for a sample of drivers with usage-based insurance policies. We examined the statistical distribution of distance driven above the posted speed limit-which presents a strong positive asymmetry-using quantile regression models. We found that, at different percentile levels, the distance driven at speeds above the posted limit depends on total distance driven and, more generally, on factors such as the percentage of urban and nighttime driving and on the driver's gender. However, the impact of these covariates differs according to the percentile level. We stress the importance of understanding telematics information, which should not be limited to simply characterizing average drivers, but can be useful for signaling dangerous driving by predicting quantiles associated with specific driver characteristics. We conclude that the risk of driving for long distances above the speed limit is heterogeneous and, moreover, we show that prevention campaigns should target primarily male non-urban drivers, especially if they present a high percentage of nighttime driving.

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Using hierarchical Bayesian binary probit models to analyze crash injury severity on high speed facilities with real-time traffic data

Cited by 115 publications

References 16 publications

Investigation of powered 2-wheeler accident involvement in urban arterials by considering real-time traffic and weather data

Investigation of powered 2-wheeler accident involvement in urban arterials by considering real-time traffic and weather data

Simulation Study of the Effect of Decreasing Truck Traffic Flow on Safety on Almeria-Barcelona Corridor

Quantile Regression with Telematics Information to Assess the Risk of Driving above the Posted Speed Limit

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