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
A multivariate random-parameters Tobit model for analyzing highway crash rates by injury severity
Innovative motor insurance schemes: A review of current practices and emerging challenges
Comparing spatially static and dynamic vibrotactile take-over requests in the driver seat
Evaluating the safety impact of adaptive cruise control in traffic oscillations on freeways
The impact of walking while using a smartphone on pedestrians’ awareness of roadside events
Augmented reality warnings in vehicles: Effects of modality and specificity on effectiveness
Revisiting crash spatial heterogeneity: A Bayesian spatially varying coefficients approach
Safety analytics for integrating crash frequency and real-time risk modeling for expressways
Truck crash severity in New York city: An investigation of the spatial and the time of day effects
Multivariate poisson lognormal modeling of crashes by type and severity on rural two lane highways
Pre-crash scenarios at road junctions: A clustering method for car crash data
Child pedestrian safety knowledge, behaviour and road injury in Cape Town, South Africa
The effect of performance feedback on drivers’ hazard perception ability and self-ratings
A preliminary investigation of the relationships between historical crash and naturalistic driving