The paper presents a driver model which classifies visual distraction based on the detection of atypical driving behavior. The model forwards the information to a driver adaptive collision mitigation system (CMS) and activates the acoustic warning earlier in case of distraction. Therefore the model requires the knowledge of the normal driving behavior. For that reason we introduce a design meta...

The purpose of this effort was to apply signal detection theory to descriptively model the impact of five grade crossing safety factors to understand their effect on driver decision making. The safety factors consisted of: improving commercial motor vehicle driver safety through federal regulations, increasing locomotive conspicuity with alerting lights, increasing locomotive conspicuity with r...

The purpose of this paper is to develop a driver drowsiness and monitoring system that could act as an assistant the during driving process. aimed at reducing fatal crashes caused by driver’s distraction. For drowsiness, operates analysing eye blinks yawn frequency while for distraction, works based on head pose estimation tracking. alarm will be triggered if any these conditions occur. Main pa...

Inappropriate speed is a major cause of traffic accidents. Different measures have been considered to control traffic speed, and intelligent speed adaptation (ISA) systems are one of the alternatives. These systems know the speed limits and try to improve compliance with them. This paper deals with an informative ISA system that provides the driver with an advance warning before reaching a road...

background : major injuries and death in accidents have roots in drowsiness. sleepiness is a main result of insufficient sleep. it is vital to explore drowsiness and its level. there are various sorts of methods in the forms of subjective and objective approaches. the goal of this study was to detect the association of subjective and interpretive drowsiness with facial dynamic changes. methods:...

The front vehicle detection and alarm system proposed by this article can be applied to forward collision warning (FCW), forward distance estimation (FDE), and time to collision (TTC) estimation. Using the CCD camera to capture the road image in front for the image processing algorism, the image processing algorism is the key point which decides the accuracy and reliability of vehicle safety sy...

The Crash Warning Interface Metrics (CWIM) project addressed issues of the driver-vehicle interface (DVI) for Advanced Crash Warning Systems (ACWS). The focus was on identifying the effects of certain warning system features (e.g., warning modality) and on establishing common methods and metrics that may be generally applied for evaluating DVIs in different vehicles. The project did not have th...

The emergence of Body Sensor Networks (BSNs) constitutes a new and fast growing trend for the development of daily routine applications. However, in the case of heterogeneous BSNs integration with Vehicular ad hoc Networks (VANETs) a large number of difficulties remain, that must be solved, especially when talking about the detection of human state factors that impair the driving of motor vehic...

For real-world driver drowsiness detection from videos, the variation of head pose is so large that the existing methods on global face is not capable of extracting effective features, such as looking aside and lowering head. Temporal dependencies with variable length are also rarely considered by the previous approaches, e.g., yawning and speaking. In this paper, we propose a Longterm Multi-gr...