One of the most important and effective factors in prioritizing high accident prone segments of roads for pedestrians is accident cause which up to now has been neglected in current methods. Since accidents are not additives due to various reasons, prioritizing these segments without considering the accident cause makes the selection of high accident prone segments inaccurate. In this paper, by...

During last decades, owing to the increase in a number of vehicles, the rate of accident occurrence grows significantly. Efforts must be made to provide efficient tools to prioritize segments requiring safety improvement and identify influential factors on accidents. This objective of the research was to determine the safety oriented threshold of International Roughness Index (IRI) to recognize...

Big data analytics for traffic accidents is a hot topic and has significant values for a smart and safe traffic in the city. Based on the massive traffic accident data from October 2014 to March 2015 in Xiamen, China, we propose a novel accident occurrences analytics method in both spatial and temporal dimensions to predict when and where an accident with a specific crash type will occur conseq...

This paper presents an evolutionary algorithm for recognizing high and low crash road segments using Genetic Algorithm as a dynamic segmentation method. Social and economic costs as well as physical and mental injuries make the governments perceiving to road safety indexes in order to diminish the consequences of road accidents. Due to the limitation of budget for safety...

In our previous studies,1,2,3) it was shown that the mortality from motor vehicle accident is affected by various psychosocial factors such as social mobility, high income, aging population, occupation, type of automobiles and climate . In this study, we aim at exploring neurobehavioral predictors which could distinguish the traffic accident-prone drivers from safe drivers ; eleven factors are ...