Comparison of four statistical and machine learning methods for crash severity prediction
A Bayesian spatial random parameters Tobit model for analyzing crash rates on roadway segments
Critical factors and paths influencing construction workers' safety risk tolerances
Critical factors and paths influencing construction workers’ safety risk tolerances
Analyzing pedestrian crash injury severity at signalized and non-signalized locations
Evaluating the safety impact of adaptive cruise control in traffic oscillations on freeways
Macroscopic hotspots identification: A Bayesian spatio-temporal interaction approach
Driver drowsiness detection based on non-intrusive metrics considering individual specifics
The effects of texting on driving performance in a driving simulator: the influence of driver age
Effectiveness of low speed autonomous emergency braking in real-world rear-end crashes
Augmented reality warnings in vehicles: Effects of modality and specificity on effectiveness
Modeling crash spatial heterogeneity: random parameter versus geographically weighting
The economic burden of injury: Health care and productivity costs of injuries in the Netherlands
The influence of daily sleep patterns of commercial truck drivers on driving performance
Revisiting crash spatial heterogeneity: A Bayesian spatially varying coefficients approach
The impact of walking while using a smartphone on pedestrians’ awareness of roadside events
A multivariate random-parameters Tobit model for analyzing highway crash rates by injury severity
Multivariate crash modeling for motor vehicle and non-motorized modes at the macroscopic level
Validation of the Driver Behaviour Questionnaire in a representative sample of drivers in Australia
A multivariate spatial crash frequency model for identifying sites with promise based on crash types
Truck crash severity in New York city: An investigation of the spatial and the time of day effects