scholarly journals Fatigue driving detection based on electrooculography: a review

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yuanyuan Tian ◽  
Jingyu Cao
Keyword(s):  
Monitoring System ◽  
Traffic Safety ◽  
Traffic Accidents ◽  
Feature Fusion ◽  
State Of The Art ◽  
Low Cost ◽  
Advantages And Disadvantages ◽  
Art Research ◽  
Fatigue Driving ◽  
Better Than

AbstractTo accurately identify fatigued driving, establishing a monitoring system is one of the important guarantees of improving traffic safety and reducing traffic accidents. Among many research methods, electrooculogram signal (EOG) has unique advantages. This paper presents a systematic literature review of these technologies and summarizes a basic framework of fatigue driving monitoring system based on EOGs. Then we summarize the advantages and disadvantages of existing technologies. In addition, 80 primary references published during the last decade were identified. The multi-feature fusion technique based on EOGs performs better than other traditional methods due to its low cost, low power consumption and low intrusion, while its application is still limited which needs more efforts to obtain good and generalizable results. And then, an overview of the literature on technology is given, revealing a premier and unbiased survey of the existing empirical research of classification techniques that have been applied to fatigue driving analysis. Finally, this paper adds value to the current literature by investigating the application of EOG signals in fatigued driving and the design of related systems, future guidelines have been provided to practitioners and researchers to grasp the major contributions and challenges in the state-of-the-art research.

scholarly journals Fatigue Detection with Spatial-Temporal Fusion Method on Covariance Manifolds of Electroencephalography

Entropy ◽  
2021 ◽  
Vol 23 (10) ◽  
pp. 1298
Author(s):  
Nan Zhao ◽  
Dawei Lu ◽  
Kechen Hou ◽  
Meifei Chen ◽  
Xiangyu Wei ◽  
...  
Keyword(s):  
Traffic Accidents ◽  
Covariance Matrices ◽  
Temporal Information ◽  
Pressure Work ◽  
Spatial Features ◽  
Eeg Data ◽  
High Level ◽  
Fatigue Driving ◽  
Fatigue Detection ◽  
Better Than

With the increasing pressure of current life, fatigue caused by high-pressure work has deeply affected people and even threatened their lives. In particular, fatigue driving has become a leading cause of traffic accidents and deaths. This paper investigates electroencephalography (EEG)-based fatigue detection for driving by mining the latent information through the spatial-temporal changes in the relations between EEG channels. First, EEG data are partitioned into several segments to calculate the covariance matrices of each segment, and then we feed these matrices into a recurrent neural network to obtain high-level temporal information. Second, the covariance matrices of whole signals are leveraged to extract two kinds of spatial features, which will be fused with temporal characteristics to obtain comprehensive spatial-temporal information. Experiments on an open benchmark showed that our method achieved an excellent classification accuracy of 93.834% and performed better than several novel methods. These experimental results indicate that our method enables better reliability and feasibility in the detection of fatigued driving.

Research on Intelligent Steering Wheel Technology Based on Multi Sensor

2014 ◽  
Vol 488-489 ◽  
pp. 1130-1133
Author(s):  
Yuan Bai ◽  
Xiao Dong Tan
Keyword(s):  
Traffic Safety ◽  
Automobile Industry ◽  
Traffic Accidents ◽  
Drunk Driving ◽  
Steering Wheel ◽  
Private Car ◽  
Driving Condition ◽  
Fatigue Driving

At present, the automobile industry is developing rapidly, the private car is widely popularized, and the hidden dangers of traffic safety exist. The phenomenon of drunk driving and fatigue driving becomes more and more serious, and the improvement for steering wheel could effectively prevent traffic accidents. This paper introduces and analyzes the intelligence of steering wheel in three major aspects, they respectively include intelligent grip detection, which tests if a driver is of fatigue driving; hart rate detection, which tests if a driver is in normal driving condition; alcohol detection, which tests if a driver drinks too much, and it predicts the possibility of accident from the drivers state, and timely gives out signal to warn the driver.

AN INTEGRATED METHOD OF IDENTIFYING AND RANKING DANGER SPOTS FOR PEDESTRIANS ON MICROLOCATION

Transport ◽  
2012 ◽  
Vol 27 (1) ◽  
pp. 49-59 ◽  
Author(s):  
Dalibor Pešić ◽  
Milan Vujanić ◽  
Krsto Lipovac ◽  
Boris Antić
Keyword(s):  
Research Methods ◽  
Traffic Safety ◽  
Traffic Accidents ◽  
Pedestrian Safety ◽  
Integrated Method ◽  
Advantages And Disadvantages ◽  
Road Users ◽  
Safety Improvement ◽  
Degree Of Exactness ◽  
Vulnerable Road Users

In traffic safety, various methods, procedures and techniques are adapted for traffic safety needs. Diverse methods lead to a different degree of exactness, accuracy and precision. The selection of research methods depends primarily on the research objective. Research methods most frequently applied for traffic safety include a statistical method, experiment, observation, tests, a questionnaire and interview, a comparison and analogy, etc. Each method has its advantages and disadvantages; however, a well devised combination of several methods and the reliability of research results can be increased. The problem of danger for pedestrians, as vulnerable road users, is constantly expressed and present in all regions. Therefore, special attention should be paid to pedestrian safety. To determine danger spots for pedestrians, the analyses of traffic accidents are most frequently used, which is the so called reactive approach to traffic safety improvement. Apart from the reactive approach, for the purpose of preventing traffic accidents in the future, it is necessary to combine some of the methods that can proactively indicate potential danger spots for pedestrians. This paper shows the method of identifying and ranking danger spots for pedestrians on micro locations, which incorporates the analysis of traffic accidents, the examination of the subjective attitudes of participants in traffic and the use of a conflict technique. Along with the so called ‘overlapping’ danger spots detected in the analysis of traffic accidents, danger spots detected based on the analysis of the subjective attitudes of pedestrians and drivers and danger spots detected in the conflict technique, a map of the so called objective and subjective danger spots is obtained. By eliminating all such identified danger spots, black spots as well as potential traffic accidents are removed. The method presented in this paper can be a very useful tool for decision-makers, for improving pedestrian safety on a micro location and for allocating funds.

Multiwafer Movpe of III-Nitride Films for Led and Laser Applications

1997 ◽  
Vol 482 ◽  
Author(s):  
R. Beccard ◽  
O. Schoen ◽  
B. Schineller ◽  
D. Schmitz ◽  
M. Heuken ◽  
...  
Keyword(s):  
Room Temperature ◽  
State Of The Art ◽  
Low Cost ◽  
Free Exciton ◽  
Single Layer ◽  
Laser Applications ◽  
Room Temperature Photoluminescence ◽  
Cost Of Ownership ◽  
P Type ◽  
Better Than

AbstractProcess for mass production of GaN and its related alloys, InGaN and AlGaN, have been optimized to achieve high device yield and low cost of ownership. Here we present some of the latest results obtained from AIX 2000 HT Planetary Reactor® in a configuration of 7×2” which provides unique uniformity capabilities due to the two fold rotation of the substrates. GaiN single layers with background electron concentrations below 5·1016 cm-3 and intended doping levels up to 1018 cm-3 p-type and 1020 cm-3 n-type with state of the art homogeneities have been achieved. Thickness homogeneities have been shown to be better than 1% standard deviation on full 2” wafers, while composition uniformity of ternary material is determined by room temperature photoluminescence mappings. Low temperature photoluminescence and reflectance spectra of single layer GaN revealed free exciton transitions.

scholarly journals Preliminary on Human Driver Behavior: A Review

2020 ◽  
Vol 7 (2) ◽  
pp. 29-34
Author(s):  
Xiao Yan ◽  
Ashardi Abas
Keyword(s):  
Traffic Accidents ◽  
Measurement Techniques ◽  
Accident Rate ◽  
Advantages And Disadvantages ◽  
Non Invasive ◽  
Detection Technology ◽  
Human Driver ◽  
Objective Detection ◽  
Fatigue Driving

Drowsiness is one of the main factors causing traffic accidents. Research on drowsiness can effectively reduce the traffic accident rate. According to the existing literature, this paper divides the current measurement techniques into subjective and objective ones. Among them, invasive detection and non-invasive detection based on vehicles or drivers are the main objective detection methods.Then, this paper studies the characteristics of drowsiness, and analyzes the advantages and disadvantages of each detection method in practical application. Finally, the development of detection technology is prospected, and provides ideas for the follow-up development of fatigue driving detection technology.

scholarly journals Biometrical driver face verification

2018 ◽  
Vol 19 (6) ◽  
pp. 68-72
Author(s):  
Jolanta Chmielińska ◽  
Jacek Jakubowski
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Monitoring System ◽  
Transfer Learning ◽  
Traffic Safety ◽  
Face Verification ◽  
Advantages And Disadvantages ◽  
Driver Monitoring ◽  
Learning Technique

The paper discusses the problem of face verification in a driver monitoring system for the purpose of traffic safety. Two different methods of face verification were proposed. Both of them are based on a convolutional neural network and were developed with the use of a transfer learning technique. In the paper, the results produced by both proposed method have been presented and compared. Moreover, their advantages and disadvantages have been discussed.

scholarly journals Correlational Neural Networks

2016 ◽  
Vol 28 (2) ◽  
pp. 257-285 ◽  
Author(s):  
Sarath Chandar ◽  
Mitesh M. Khapra ◽  
Hugo Larochelle ◽  
Balaraman Ravindran
Keyword(s):  
Canonical Correlation ◽  
State Of The Art ◽  
Representation Learning ◽  
Advantages And Disadvantages ◽  
Common Representation ◽  
Series Of Experiments ◽  
The Common ◽  
Cross Language ◽  
Joint Representation ◽  
Better Than

Common representation learning (CRL), wherein different descriptions (or views) of the data are embedded in a common subspace, has been receiving a lot of attention recently. Two popular paradigms here are canonical correlation analysis (CCA)–based approaches and autoencoder (AE)–based approaches. CCA-based approaches learn a joint representation by maximizing correlation of the views when projected to the common subspace. AE-based methods learn a common representation by minimizing the error of reconstructing the two views. Each of these approaches has its own advantages and disadvantages. For example, while CCA-based approaches outperform AE-based approaches for the task of transfer learning, they are not as scalable as the latter. In this work, we propose an AE-based approach, correlational neural network (CorrNet), that explicitly maximizes correlation among the views when projected to the common subspace. Through a series of experiments, we demonstrate that the proposed CorrNet is better than AE and CCA with respect to its ability to learn correlated common representations. We employ CorrNet for several cross-language tasks and show that the representations learned using it perform better than the ones learned using other state-of-the-art approaches.

Review on Visibility Monitoring in Expressway under Foggy Condition

2014 ◽  
Vol 607 ◽  
pp. 651-656
Author(s):  
Long Biao Zhu ◽  
Jie Wang ◽  
Xi Huang ◽  
Heng Wang ◽  
Peng Liu
Keyword(s):  
Monitoring System ◽  
Traffic Safety ◽  
Digital Imaging ◽  
Influence Factor ◽  
Imaging Method ◽  
Scattering Method ◽  
Transmission Method ◽  
Existing Problems ◽  
Advantages And Disadvantages ◽  
Status And Trends

Visibility monitoring under foggy condition is very essential to traffic safety on expressway. The definition and influence factor of visibility are summarized. The main advantages and disadvantages of three common methods- transmission method, scattering method, digital imaging method and related visibility meters are analyzed and compared here. The domestic and foreign status and trends of visibility research on foggy expressway are mainly introduced from thick fog forecast, warning and monitoring system, visibility detection device. Aiming at the existing problems of visibility monitoring in expressway, some suggestions for improvement are put forward at last.

scholarly journals A Fatigue Driving Detection Algorithm Based on Facial Motion Information Entropy

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Feng You ◽  
Yunbo Gong ◽  
Haiqing Tu ◽  
Jianzhong Liang ◽  
Haiwei Wang
Keyword(s):  
Real Time ◽  
Traffic Safety ◽  
Information Entropy ◽  
Detection Algorithm ◽  
Facial Motion ◽  
Facial Information ◽  
Video Frames ◽  
Fatigue Driving ◽  
Fatigue Detection ◽  
Better Than

Research studies on machine vision-based driver fatigue detection algorithm have improved traffic safety significantly. Generally, many algorithms asses the driving state according to limited video frames, thus resulting in some inaccuracy. We propose a real-time detection algorithm involved in information entropy. Particularly, this algorithm relies on the analysis of sufficient consecutive video frames. First, we introduce an improved YOLOv3-tiny convolutional neural network to capture the facial regions under complex driving conditions, eliminating the inaccuracy and affections caused by artificial feature extraction. Second, we construct a geometric area called Face Feature Triangle (FFT) based on the application of the Dlib toolkit as well as the landmarks and the coordinates of the facial regions; then we create a Face Feature Vector (FFV), which contains all the information of the area and centroid of each FFT. We use FFV as an indicator to determine whether the driver is in fatigue state. Finally, we design a sliding window to get the facial information entropy. Comparative experiments show that our algorithm performs better than the current ones on both accuracy and real-time performance. In simulated driving applications, the proposed algorithm detects the fatigue state at a speed of over 20 fps with an accuracy of 94.32%.

scholarly journals The Time-Space Approach in the Analysis of Traffic Safety on Rural Road

2017 ◽  
Vol 6 (1) ◽  
pp. 66-76 ◽  
Author(s):  
Svetlana Bačkalić ◽  
Boško Matović ◽  
Anja Bašić
Keyword(s):  
Traffic Safety ◽  
Traffic Accidents ◽  
Time Coordinate ◽  
Advantages And Disadvantages ◽  
Road Section ◽  
Rural Road ◽  
Time Space ◽  
The Mean ◽  
Mean Time ◽  
Space Approach

Abstract Analysis of the traffic safety factors in some region (road, section of road, road’s kilometer) is an important task in the field of traffic safety. It is necessary to constantly monitor, analyze, compare traffic safety situation in order to develop and improve measures for increasing the level of traffic safety. The first part of each analysis is finding of positions of traffic accidents and its casualties, in other words it is necessary to find its coordinates in the space-time coordinate system. This paper shows results of the descriptive statistical analysis of traffic accidents frequency on the rural road for the period 2005-2011. It will be point out advantages and disadvantages of this approach and also it will be suggested a new individual approach for determinate the mean time between consecutive traffic accidents.

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