There are some previous researches that are used to be referred to develop a real-time system on drowsiness detection. These are researches and journals that are related to this project either directly or indirectly:- Alioua et al. [17] proposed a robust and novel algorithm which does not require any training data or any special cameras for eye state analysis by iris detection using Circular Hough Transform (CHT) technique. The experimental results were represented as statistical measures such as Confusion Matrix, Correct Classification Rate and kappa Statistic. The experiment was performed on 7 real video sequences and it provided 99% correct classification rate and 88% kappa statistic value. For future work, they focused on inserting …show more content…
In PERCLOS estimation, for each frame, linear support vector machine (LSVM) method was used to classify edge detected eye images. In gaze estimation, exponentially smoothed vertical and horizontal movements of the pupils were taken into consideration. This methodology achieved an overall accuracy of 70.99% for offline tests of eye state detection while the real time eye state detection provided a precision of 78.57% and recall of 18.33% and 83.64% overall accuracy. The gaze estimation methodology achieves 80.5% accuracy. For future work, they focused on performing parallel optimizations in order to achieve high performance, fine tune the system’s fatigue detection function based on machine learning. Dahiphale and Sathyanarayana [14] designed and tested driver vigilance level monitoring system on raspberry pi. The system contained two main parts including driver’s face and eye detection part using Viola Jones face detection with AdaBoost (Adaptive- Boosting) method and Circular Hough Transform technique and driver’s face tracking part using CAMSHIFT (Continuously Adaptive Mean Shift). They focused on vehicle states, weather conditions, signal changes for person in different conditions such as illness in future works. Hichri et al. [15] proposed a robust system for drowsiness detection of drivers based on eye state in real-time. The system contained two main parts
Good morning everyone, today we call our world as busy world or multitasks world and with the rush-rush-rush mentality most people have these days; it's no surprise that more and more people are driving while distracted. Eating, talking or texting on a mobile phone, making adjustments to the radio, talking with passengers -- all take a driver's focus off of the road.
204 participants agreed to install video cameras and sensors in their vehicles for thirty-one days in a row, while providing their phone records for analysis. The results from the study showed that driving performance is directly influenced by how well drivers visually attend to the road. This visual attention is required in order to be aware of events as they occur. When the driver is distracted by looking at and manipulating a hands-held phone, their visual attention is substantially affected (NHTSA,
Distracted driving poses an immense problem across the United States, and the issue only seems to continue growing. According to the National Highway Traffic Safety Administration (NHTSA), “In 2015 alone, 3,477 people were killed” in cases involving distracted driving, and of those killed, “teens were the largest age group reported as distracted at the time of fatal crashes” (“Distracted Driving”, n.d.). These terrifying statistics cannot be ignored. Distracted driving is a national epidemic, and unless society addresses the problem properly and efficiently, the risky driving behavior will continue to plague our streets, endangering peoples’ lives and leading to more fatalities.
Based on what the author stated in the introduction of Distracted Driver, “Driving a motor vehicle is serious business and you need to be well-rested and attentive in order to be a safe driver.”
Many levels of driver distraction are there depending on how it influences and impacts on the driver performance and accident hazard in different possible manners. Driving performance depends on various interrelated factors: ability of the user, experience of the user, driving task complexity, design and the activities with in-vehicle technologies. Performance of driving are defined in terms of following three measures:
Distracted driving is an increasing problem in the United States and among younger drivers. According to reports, distracted driving is similar to drunk driving because it diverts the person’s attention away from driving. Every year, thousands of people die from distracted driving. With laws, education, and campaigns could reduce the amount of deaths per year ("Facts and Statistics").
Imagine you’re on your way to work and you get a text message from a friend or family member. Although you know that it is wrong to check while you are driving, you still check it anyways because you have done it plenty of times and got away with it. Then you look back up and realize that you are on the other side of the road and there is a car heading your way. You swerve back into your lane just in time to miss the incoming car and you realize how those three seconds could have completely changed your life. This is an experience many young and older distracted drivers have at least once in their lives. Now if you are wondering what are the risks that comes with distracted driving, what is the hype surrounding this social problem, and want learn how problem can be solved, you have come to the right place. Throughout this paper I will introduce to you what distracted driving is. Following that I will reveal the claim makers and their strategies to gain awareness about distracted driving. After that I will give the proposed solutions including direct cost, indirect cost, and the money estimated money needed carry out these costs. Finally, I will reveal what I have learned about this problem
Distracted driving is one of the fastest growing problems in the United States. It is starting to be considered as serious as drunk driving based on the dangerous outcomes. According to the Department of Transportation (2012), “distracted driving was a cause of roughly 450,000 accident-related injuries and nearly 5,500 fatalities in 2009 alone” (para. 1). Drivers who allow themselves to become distracted while driving are not only endangering themselves, but other innocent bystanders.
1 in 4 people have reported having microsleeps while driving. A microsleep is a brief moment of loss of attention that results in a blank stare or prolonged eye closure when someone is extremely tired. This can happen very easily on the road when someone is driving.
Driving in Montana is at high risk for teen drivers without any statewide laws against distracted driving. According to research done by Virginia Tech Transportation Institute in 2009, “…Text messaging on a cell phone was associated with the highest risk of all cell phone related tasks.” The study was conducted by observing continuously drivers for over six million miles of driving. The major focus was done on eye glance analyses. The assessment of where drivers looked when involved in driving events which were critical for safety, and how cell phone usage impacted the driver was analyzed. The tasks, which drew the driver’s eyes away from forward focus and attention, created the highest
PYC 4950 was a three credit psychology research course that took place during August 28, 2017 and lasted until December 11, 2017. The research involved the following devices and topics: G.S.R. (galvanic skin response), E.E.G. (Electroencephalography), and eye tracking. However, the preliminary focus of this term’s research involved using EEG and eye tracking. Both of these devices were used together on a person in a driving study. This study was conducted using a driving simulator. Data collected from E.E.G. and eye tracking will show brain activity and eye movement while a person is driving with different variables such as conversing with the person while they are driving. This data will be further interpreted and
Through this routine of advanced technology analysis, it has been established to increase the results and have hastened the procedure of identifying suspects of crimes. Facial recognition is also necessary for public involvement and observation as it also aids law enforcement officials to more easily zone in on possible suspects of a crimes being caught. With the use of facial recognition, it constantly has been proven quite an effective method with the incorporation of this technique.
The researchers used eye tracking to get an accurate measure of the persons gaze while the amount of time and fatigue increased. Subjective fatigue and engagement was measured at all stages of the experiment and was measured in two ways. The first way was the Rating Scale Mental Effort which is seven vertical scales which go from 0 to 150 and assessed different aspects of mental fatigue. The second way was subjects were asked “How tired do you feel?” & “How engaged were you in the task?” both of which subjects responded on a 0 to 100 vertical scale that went by increments of 5 and had only two anchors “very much” & “not at all”. Physiological signs of engagement were measured by eye-trackers for the pupils and EEG scanners which specifically looked for the
For so many decades, accidents have been happening each and every time secondary to driver drowsiness following a tedious driver or sleep deprivation or even drunk drivers. With the drowsy driver monitoring and warning system, it will reduce the possibility of an accidents of drowsy drivers to a minimal range. This system detects a drowsy driver through image processing of the driver’s behavior while in the car. In case of a detection of a drowsy driver, the system will then give a warning
A threat agent is the facilitator of an attack however; a threat is a constant danger to an asset.