This study applied logistic regression to accident-related data collected from traffic-police records in order to examine the contributing factors to accident severity. A total of 560 subjects involved in severe accidents was sampled. The accident severity (dependent variable) in this study is a dichotomous variable with two categories, Fatal or Injury. Therefore, each of the subjects sampled i...

The present study aimed to clarify the associations among radiation exposure or psychological exposure to the Fukushima nuclear power plant accident (i.e., fear/anxiety immediately after the accident), current radiation anxiety, and psychological distress among non-evacuee community residents in Fukushima five years after the Great East Japan Earthquake, which occurred in March 2011. A question...

conclusions during car crashes, especially car rollover, unbelted occupants are more likely to sustain multiple severe injuries and death. law enforcement of the seat belt usage for all occupants (front and rear seat) is obligatory to reduce severe injuries sustained as a result of car accidents, especially in vehicles with low safety. results a total of 560 patients used seat belts (68.1%). th...

in this work, the time series modeling was used to predict the tazareh coal mine risks. for this purpose, initially, a monthly analysis of the risk constituents including frequency index and incidence severity index was performed. next, a monthly time series diagram related to each one of these indices was for a nine year period of time from 2005 to 2013. after extrusion of the trend, seasonali...

This report describes a Bayesian method for estimating accident rates at individual sites, which takes into account the fact that the total traffic count usually used to measure exposure is generally not known with certainty. The first step involves deriving an approximation for the probability distribution of total traffic conditioned on a short count sample. This approximation is then used to...

Clustering and classification approaches have been commonly applied in reducing the heterogeneity in accident data. As part of an effort to understand the features of the heterogeneity, this study assessed accident data from the perspective of accident occurrences. Using the rule-based classification method, rough set theory, rules were derived which consisted of indispensable factors to certai...

Accident prediction models (APMs) have been extensively used in site ranking with the objective of identifying accident hotspots. Previously this has been achieved by using a univariate count data or a multivariate count data model (e.g. multivariate Poisson-lognormal) for modelling the number of accidents at different severity levels simultaneously. This paper proposes an alternative method to...

Pavement rehabilitation could affect the accident severity index (ASI) since restoration measures means more safety for road users. No research or project has been carried out to identify hazard points to build a linear model based on crash severity index. One of the very popular accident severity index models used in all countries is based on linear models to rehabilitate pavements and this pa...