Prioritizing rear-end crash explanatory factors for injury severity level using deep learning and global sensitivity analysis
Traffic accidents are usually unique events with unpredictable geographical and temporal
dimensions; thus, accident injury severity level (INJ-SL) analysis presents formidable …
dimensions; thus, accident injury severity level (INJ-SL) analysis presents formidable …
Factors affecting injury severity at pedestrian crossing locations with Rectangular RAPID Flashing Beacons (RRFB) using XGBoost and random parameters discrete …
This paper evaluates the effectiveness of Rectangular Rapid Flashing Beacons (RRFB) on
crash severity. The study used and compared XGBoost and Random Parameters Discrete …
crash severity. The study used and compared XGBoost and Random Parameters Discrete …
Analysis of accident injury-severity outcomes: The zero-inflated hierarchical ordered probit model with correlated disturbances
G Fountas, PC Anastasopoulos - Analytic methods in accident research, 2018 - Elsevier
In accident injury-severity analysis, an inherent limitation of the traditional ordered probit
approach arises from the a priori consideration of a homogeneous source for the accidents …
approach arises from the a priori consideration of a homogeneous source for the accidents …
Analysis of stationary and dynamic factors affecting highway accident occurrence: A dynamic correlated grouped random parameters binary logit approach
Traditional accident analysis typically explores non-time-varying (stationary) factors that
affect accident occurrence on roadway segments. However, the impact of time-varying …
affect accident occurrence on roadway segments. However, the impact of time-varying …
A new econometric approach for modeling several count variables: a case study of crash frequency analysis by crash type and severity
There is limited adoption of research modeling crash severity frequency considering
different crash types due to the challenge associated with analyzing large number of …
different crash types due to the challenge associated with analyzing large number of …
Variance-based global sensitivity analysis for rear-end crash investigation using deep learning
Traffic accidents are rare events with inconsistent spatial and temporal dimensions; thus,
accident injury severity (INJ-S) analysis faces a significant challenge in its classification and …
accident injury severity (INJ-S) analysis faces a significant challenge in its classification and …
A Bayesian spatial Poisson-lognormal model to examine pedestrian crash severity at signalized intersections
Reducing nonmotorized crashes requires a profound understanding of the causes and
consequences of the crashes at the facility level. Generally, existing literature on bicyclists …
consequences of the crashes at the facility level. Generally, existing literature on bicyclists …
Addressing endogeneity in modeling speed enforcement, crash risk and crash severity simultaneously
Speeding is one of the major significant causes of high crash risk and the associated injury
severity outcomes. To combat such significant safety concerns, a speed limit enforcement …
severity outcomes. To combat such significant safety concerns, a speed limit enforcement …
Analysis of crash proportion by vehicle type at traffic analysis zone level: A mixed fractional split multinomial logit modeling approach with spatial effects
In traffic safety literature, crash frequency variables are analyzed using univariate count
models or multivariate count models. In this study, we propose an alternative approach to …
models or multivariate count models. In this study, we propose an alternative approach to …
Exploring the impact of truck traffic on road segment-based severe crash proportion using extensive weigh-in-motion data
Fixed proportions by severity assumption in Highway Safety Manual could be violated since
the proportions of severe crashes are likely to be affected by truck traffic characteristics …
the proportions of severe crashes are likely to be affected by truck traffic characteristics …