In recent years due to improvements of technology within automobile industry, design process of advanced driver assistance systems for collision avoidance and traffic management has been investigated in both academics and industrial levels. Detection of traffic signs is an effective method to reach the mentioned aims. In this paper a new intelligent driver assistance system based on traffic...

Because of the increased number traffic accidents, there is an urgent need to control and reduce driving mistakes. Driver fatigue or drowsiness one these major Many algorithms have been developed address this issue by detecting alerting driver potentially dangerous condition. The algorithms’ main problem their detection accuracy, as well time required detect status alert driver. accuracy...

Soldiers incurred injuries or even lost their lives due to rollovers while driving military vehicles. A recent report identified that the one cause of rollovers is the driver’s inability to assess rollover threats, such as a cliff, soft ground, water, or a culvert on the passenger side of the vehicle, due to the vehicle’s width. To reduce the number of rollover accidents, a road-edge detection ...

Accurate classification of eye state is a prerequisite for preventing automobile accidents due to driver drowsiness. Previous methods of classification, based on features extracted for a single eye, are vulnerable to eye localization errors and visual obstructions, and most use a fixed threshold for classification, irrespective of variations in the driver’s eye shape and texture. To address the...

A robust and efficient lane detection system is an essential component of Lane Departure Warning Systems, which are commonly used in many vision-based Driver Assistance Systems (DAS) in intelligent transportation. Various computation platforms have been proposed in the past few years for the implementation of driver assistance systems (e.g., PC, laptop, integrated chips, PlayStation, and so on)...

Due to the increasing of traffic accidents, there is an urgent need control and reduce driving mistakes. Driver fatigue or drowsiness one these major Algorithms have been developed address this issue by detecting alerting driver dangerous condition. The problem algorithms their accuracy, well as time required detect status alert driver. accuracy represent a critical condition that affects reduc...

Advanced driver assistance systems, such as unintentional lane departure warning systems, have recently drawn much attention and efforts. In this study, we explored utilizing the nonlinear binary support vector machine (SVM) technique to predict unintentional lane departure, which is innovative as the SVM methodology has not previously been attempted for this purpose in the literature. Furtherm...

Most of the collision warning systems currently available in the automotive market are mainly designed to warn against imminent rear-end and lane-changing collisions. No collision warning system is commercially available to warn against imminent turning collisions at intersections, especially for left-turn collisions when a driver attempts to make a left-turn at either a signalized or non-signa...

In America, 60% of adults reported that they have driven a motor vehicle while feeling drowsy, and at least 15-20% of fatal car accidents are fatigue-related. This study translates previous laboratory-oriented neurophysiological research to design, develop, and test an On-line Closed-loop Lapse Detection and Mitigation (OCLDM) System featuring a mobile wireless dry-sensor EEG headgear and a cel...

this paper presents an automatic drowsy driver monitoring and accident prevention system that is based on monitoring the changes in the eye blink duration. Our proposed method detects the drowsiness in eyes using the proposed mean sift algorithm. Our new method detects eye blinks via a standard webcam in real-time YUY2_640x480 resolution. Experimental results in the eyeblink database showed tha...