This research is about the implementation of close range photogrammetry (CRP) technique to investigate the traffic accident scene. CRP technique representing and measuring the 3D objects using data stored in 2D photographs. It is non-contact measurement requiring multiple pictures capture to measure objects of interest. Currently, a police officer uses a conventional technique to collect data o...

 Introduction: Causes of death vary globally, and they depend regionally on lifestyle and socio-cultural factors. The purpose of this study was to determine accident-related mortality in Southern Khorasan Province, Iran, in the year 2010.  Methods: This descriptive-analytical study involved all the death cases in the year 2010 in Southern Khorasan. The data were collected from the death regi...

Many modeling approaches have been proposed to help forecast and detect incidents. Accident has received the most attention from researchers due to its impacts economically. The traffic congestion costs billions of dollars to economy. The main reasons of major percentage of traffic congestion are the incidents. Road accidents continue to increase in digital age. There are many reasons for road ...

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...

Nowadays vehicles are increasing day by day in town and cities roads. It is a well-known problem to manage traffics on the roads in towns and cities. A lot of accident occurs on the road due to careless driving and Technical faults in vehicles. The main problem of traffic authorities is to manage the traffic on the road for the smooth functioning of vehicles that can reduce the accident and vio...

This paper employs deep learning in detecting the traffic accident from social media data. First, we thoroughly investigate the 1-year over 3 million tweet contents in two metropolitan areas: Northern Virginia and New York City. Our results show that paired tokens can capture the association rules inherent in the accident-related tweets and further increase the accuracy of the traffic accident ...

This study describes the experimental application of Machine Learning techniques to build prediction models that can assess the injury risk associated with traffic accidents. This work uses an freely available data set of traffic accident records that took place in the city of Porto Alegre/RS (Brazil) during the year of 2013. This study also provides an analysis of the most important attributes...

The continuous development of sensors and the Internet Things has produced a large amount traffic data with location information. improvement safety benefits from availability accident data. Managers can patrol control relevant areas in advance limited police resources, according to short-term predictions. As result, possibility accidents be reduced, level improved. traditional approach predict...