One of the applications neural networks is to predict fault section results traffic utilizing combined model estimation and self-learning models with smart sensors. The prediction can autonomously develop internal network fit pre-entered “traffic accident” data occurrence accident sections. In this paper, we propose waiting time for accidents in case by using a fuzzy expert system, comparison e...

Accident prediction models, also known as safety performance functions, have several important uses in modern day safety analysis. Unfortunately, calibration of these models is not straightforward. This paper documents a research effort that demonstrates the complexity of calibrating these models for urban intersections. These complexities relate to the specification of the functional form, the...

In this paper, models are developed which enable a prediction of how the impact of speed management schemes on accidents varies both with speed changes and with site and scheme characteristics. It was found that, the impact of schemes with vertical deflections is independent of the change in mean speed: an accident reduction of 44% is predicted by the model irrespective of the impact on speed. ...

With the development of artificial intelligence, techniques such as machine learning, object detection, and trajectory tracking have been applied to various traffic fields detect accidents analyze their causes. However, detecting using closed-circuit television (CCTV) an emerging subject in learning remains challenging because complex environments limited vision. Traditional research has limita...

The present study of sleepiness and accident risk in a HI-FI car simulator aimed to provide subject-level relative risks (RR) with 95% confidence intervals (CI) for different levels of subjective sleepiness measured with the Karolinska Sleepiness Scale (KSS), 1 = very alert, 9 = very sleepy, fighting sleep, an effort to staying awake. Five male and five female shift workers, mean age 37 years, ...

To minimize industrial accidents, it's critical to evaluate a firm's priorities for prevention factors and strategies since such evaluation provides decisive information for preventing industrial accidents and maintaining safety management. Therefore, this paper proposes the evaluation of priorities through statistical testing of prevention factors with a cause analysis in a cause and effect mo...

Although there is currently significant development in active vehicle safety (AVS) systems, the number of accidents, injury severity levels and fatalities has not reduced. In fact, human error, low performance, drowsiness and distraction may account for a majority in all the accident causation. Active safety systems are unaware of the context and driver status, so these systems cannot improve t...

PURPOSE This pilot study sought to examine the relationship between functional health patterns and accident proneness. METHODS A quantitative-descriptive design was employed assessing accident proneness by collecting data on the occurrence of accidents among a sample of university graduates, and examining this in relation to biographical data and information collated using the Functional Heal...