scholarly journals Study of driving skill level discrimination based on human physiological signal characteristics

RSC Advances ◽  
2018 ◽  
Vol 8 (73) ◽  
pp. 42160-42169
Author(s):  
Fuwang Wang ◽  
Qing Xu ◽  
Rongrong Fu ◽  
Guangbin Sun
Keyword(s):  
Research Work ◽  
Skill Level ◽  
Physiological Signal ◽  
Driving Skill ◽  
Signal Characteristics ◽  
Driver's License ◽  
License Examination

The study of driving skill level discrimination based on EEG, EOG and ECG characteristics, which uses the driver's license examination “subject two”, is carried out in our current research work.

scholarly journals Automated Driving License Evaluation

2021 ◽  
pp. 983-988
Author(s):  
Gopinath A R ◽  
Aishwarya S S ◽  
Lakshmi K R ◽  
Lakshmi Devi M S ◽  
Divya Bharathi H Y
Keyword(s):  
Evaluation System ◽  
Test Method ◽  
Testing System ◽  
Automated Driving ◽  
Driving License ◽  
Driving Skills ◽  
Driving Skill ◽  
Driver's License ◽  
Manual Test ◽  
Skill Evaluation

The paper is regarding the automating of driver’s license testing system and updating the results to the person through website and conjointly through registered email. Usually, while driving test the person who requested for license have to be compelled to show his driving skills ahead of the authorities. The person need to operate the vehicle according to several rules. If he fails, he/she are knocked out and have to appear for the driving test next time. The Officials observe mistakes of the applicant physically. The proposed solution for the automation of existing manual test method permits the elimination of intervention of humans and improves the accuracy of driving test thereby going paperless, with Driving Skill Evaluation System. In the proposed system, we have a tendency of taking data from sensor as inputs from hardware simulator and stores into the database. In this system, the person participating in the test are obsereved by sensors. Therefore weather the person is qualified or not is informed to the applicant as well as the authorities. Gradual increase in number of road hazards are due to less practice in driving and illegal driving license given to the unskilled drivers by taking bribe. To beat this drawback, automated driving license test will be advantageous. This solution is introduced for ensuring the quality in approving in license to enhance safety.

Racing Driver Modeling Based on Driving Behavior

2021 ◽  
Author(s):  
Jinzhen Wang ◽  
Yiming Cheng ◽  
Liangyao Yu
Keyword(s):  
Preliminary Test ◽  
Control Model ◽  
Skill Level ◽  
Driver Model ◽  
Test Results ◽  
Singularity Detection ◽  
Handling Characteristics ◽  
Driving Skill ◽  
Dynamic Velocity ◽  
The Given

Abstract The driver model is an important link in the research of shared autonomy control. In order to simulate the driver’s handling characteristics in the complex human-vehicle-road closed-loop system, the driver model is required to accomplish the driving operation under specific working conditions. In this paper, a lateral-longitudinal combined racing driver model is designed. The lateral control model adopts the preview model with far and near viewpoints and the dynamic velocity controller is added into the longitudinal control model to obtain the expected speed of the target trajectory. Finally, the racing driver model proposed in this paper is validated through simulation on track conditions of FSAE. In the given conditions, the result shows the racing driver model outperforms the typical driver model in lateral path tracking and the speed of racing driver model is higher than typical model on straight and corners. Meanwhile, the representation of driving skills is a key step to enhance the adaptive control of vehicles in the future. The control parameters can be adjusted according to the driver’s skill information to make the vehicle control system adapt to the driver’s skill level. This paper introduces the method of driving skill recognition based on wavelet transform and Lipschitz singularity detection theory and the preliminary test results prove the feasibility of using this method to characterize the driver’s operating skill level.

Driver Licensing Tests as a Predictor of Subsequent Violations

1976 ◽  
Vol 18 (6) ◽  
pp. 565-573 ◽  
Author(s):  
John A. Conley ◽  
Russell Smiley
Keyword(s):  
Driver Education ◽  
Chi Square ◽  
Pearson Product Moment Correlation ◽  
Driving Experience ◽  
Valid Predictor ◽  
Driver's License ◽  
Traffic Violations ◽  
Pencil And Paper ◽  
License Examination ◽  
Driver Licensing

A total of 22,523 licensed drivers were allowed to accumulate driving experience for over four years from March, 1969 until May, 1973, following which their records were analyzed for moving violations. A subpopulation of 5,848 drivers received at least one such violation during that time, and 1,048 had been involved in an accident. The violation types and cumulated violation points were compared with errors in driving knowledge as measured by Conley's written driver license examination. Chi-Square and Pearson Product Moment Correlation analysis yielded few patterns of significance where knowledge was a valid predictor of subsequent traffic violations at the 90% confidence level. Other potential predictors, such as sex and source of driver education, also proved fruitless. The overall conclusion was that there is no consistent pattern of knowledge, sex of the driver, or source of education to suggest predictability of moving traffic violations. These results point out the need to re-evaluate current pencil and paper tests as valid determinors of the readiness of an individual for a driver's license.

The Operating Diagnostics in the Computer Aided Systems of Production Processes

2015 ◽  
Vol 791 ◽  
pp. 3-9 ◽  
Author(s):  
Piotr Wittbrodt ◽  
Alfred Paszek
Keyword(s):  
Production Systems ◽  
Research Work ◽  
Manufacturing Processes ◽  
Initial Structure ◽  
Diagnostic Systems ◽  
Future Directions ◽  
Production Processes ◽  
Vibroacoustic Signal ◽  
Signal Characteristics ◽  
Decision Making System

The paper presents the operational diagnostic problems in production systems. It briefly discusses the estimation of vibroacoustic signal characteristics used in diagnostic systems, the possibility of applications have been pointed out. Basing on the elements of the fuzzy logic, decision-making system in the areas of ambiguity during machining has been presented.An initial structure of the integrated supporting system of manufacturing processes dedicated to small and medium-sized enterprises in the metal industry have been shown. Future directions of authors’ research work have been indicated.

GEP-based predictive modeling of breathing resistances of wearing respirators on human body via sEMG and RSP sensors

Sensor Review ◽  
2019 ◽  
Vol 39 (4) ◽  
pp. 439-448
Author(s):  
Yumiao Chen ◽  
Zhongliang Yang
Keyword(s):  
Human Body ◽  
Repeated Measures ◽  
Gene Expression Programming ◽  
Research Work ◽  
Reliability And Validity ◽  
Good Prediction ◽  
Content Type ◽  
Physiological Signal ◽  
Subjective Perceptions ◽  
Breathing Resistance

PurposeBreathing resistance is the main factor that influences the wearing comfort of respirators. This paper aims to demonstrate the feasibility of using the gene expression programming (GEP) for the purpose of predicting subjective perceptions of breathing resistances of wearing respirators via surface electromyography (sEMG) and respiratory signals (RSP) sensors.Design/methodology/approachThe authors developed a physiological signal monitoring system with a specific garment. The inputs included seven physical measures extracted from (RSP) and (sEMG) signals. The output was the subjective index of breathing resistances of wearing respirators derived from the category partitioning-100 scale with proven levels of reliability and validity. The prediction model was developed and validated using data collected from 30 subjects and 24 test combinations (12 respirator conditions × 2 motion conditions). The subjects evaluated 24 conditions of breathing resistances in repeated measures fashion.FindingsThe results show that the GEP model can provide good prediction performance (R2= 0.71, RMSE = 0.11). This study demonstrates that subjective perceptions of breathing resistance of wearing respirators on the human body can be predicted using the GEP via sEMG and RSP in real-time, at little cost, non-invasively and automatically.Originality/valueThis is the first paper suggesting that subjective perceptions of subjective breathing resistances can be predicted from sEMG and RSP sensors using a GEP model, which will remain helpful to the scientific community to start further human-centered research work and product development using wearable biosensors and evolutionary algorithms.

Characterisation of driving skill level using driving simulator tests

2007 ◽  
Vol 5 (3/4) ◽  
pp. 219 ◽  
Author(s):  
William C. Lin ◽  
Yuen Kwok Chin ◽  
Brian S. Repa ◽  
Manxue Lu ◽  
Robert L. Nisonger ◽  
...  
Keyword(s):  
Driving Simulator ◽  
Skill Level ◽  
Driving Skill

Enumeration and Identification of Asbestos Fibres in Water

1974 ◽  
Vol 32 ◽  
pp. 526-527 ◽  
Author(s):  
O. Mudroch ◽  
J. R. Kramer
Keyword(s):  
Water Supply ◽  
Water Samples ◽  
Drainage Basin ◽  
Lake Superior ◽  
Research Work ◽  
List Type ◽  
The West ◽  
Asbestos Fibre ◽  
Amphibole Asbestos

Approximately 60,000 tons per day of waste from taconite mining, tailing, are added to the west arm of Lake Superior at Silver Bay. Tailings contain nearly the same amount of quartz and amphibole asbestos, cummingtonite and actinolite in fibrous form. Cummingtonite fibres from 0.01μm in length have been found in the water supply for Minnesota municipalities.The purpose of the research work was to develop a method for asbestos fibre counts and identification in water and apply it for the enumeration of fibres in water samples collected(a) at various stations in Lake Superior at two depth: lm and at the bottom.(b) from various rivers in Lake Superior Drainage Basin.

Sign in / Sign up

Export Citation Format

Share Document