• 전자공학회논문지 IE
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• v.49 no.2
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• pp.30-39
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• 2012

An effective drowsy driver detection system is needed, because the probability of accident is high for drowsy driving and its severity is high at the time of accident. However, the drowsy driver detection system that uses bio-signals or vision is difficult to be utilized due to high cost. Thus, this paper proposes a drowsy driver detection algorithm by using steering angle sensor, which is attached to the most of vehicles at no additional cost, and vehicle information such as brake switch, throttle position signal, and vehicle speed. The proposed algorithm is based on jerk criterion, which is one of drowsy driver's steering patterns. In this paper, threshold value of each variable is presented and the proposed algorithm is evaluated by using acquired vehicle data from hardware in the loop simulation (HILS) through CAN communication and MATLAB program.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1079-1085
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• 2012

For precise motion control, S-curve velocity profile is generally used but it has disadvantage of relatively long calculation time for floating-point arithmetics. In this paper, we present a new generating method for velocity profile to reduce delay time of profile generation so that it overcomes such disadvantage and enhances the efficiency of precise motion control. In this approach, the velocity profile is designed based on the gamma correction expression that is generally used in image processing to obtain a smoother movement without any critical jerk. The proposed velocity profile is designed to support both T-curve and S-curve velocity profile. It can generate precise profile by adding an offset to the velocity profile with decimals under floating point that are not counted during gamma correction arithmetic operation. As a result, the operation time is saved and the efficiency is improved. The proposed method is compared with the existing method that generates velocity profile using ring buffer on a 8-bit low-cost MCU. The result shows that the proposed method has no delay in generating driving profile with good accuracy of each cycle velocity. The significance of the proposed method lies in reduction of the operation time without degrading the motion accuracy. Generated driving signal also shows to verify effectiveness of the proposed method.

• Earthquakes and Structures
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• v.22 no.2
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• pp.185-201
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• 2022

Structural Health Monitoring (SHM) is used to provide reliable information about the structure's integrity in near realtime following extreme incidents such as earthquakes, considering the inevitable aging and degradation that occurs in operating environments. This paper experimentally investigates an integrated wireless sensor network (Wi-SN) based monitoring technique for damage detection in concrete structures. An effective SHM technique can be used to detect potential structural damage based on post-earthquake data. Two novel methods are proposed for damage detection in reinforced concrete (RC) building structures including: (i) Jerk Energy Method (JEM), which is based on time-domain analysis, and (ii) Modal Contributing Parameter (MCP), which is based on frequency-domain analysis. Wireless accelerometer sensors are installed at each story level to monitor the dynamic responses from the building structure. Prior knowledge of the initial state (immediately after construction) of the structure is not required in these methods. Proposed methods only use responses recorded during ambient vibration state (i.e., operational state) to estimate the damage index. Herein, the experimental studies serve as an illustration of the procedures. In particular, (i) a 3-story shear-type steel frame model is analyzed for several damage scenarios and (ii) 2-story RC scaled down (at 1/6th) building models, simulated and verified under experimental tests on a shaking table. As a result, in addition to the usual benefits like system adaptability, and cost-effectiveness, the proposed sensing system does not require a cluster of sensors. The spatial information in the real-time recorded data is used in global damage identification stage of SHM. Whereas in next stage of SHM, the damage is detected at the story level. Experimental results also show the efficiency and superior performance of the proposed measuring techniques.

• Science of Emotion and Sensibility
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• v.14 no.4
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• pp.571-580
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• 2011

The purpose of this study was to evaluate the effects of secondary task such as sending text message (STM) and searching navigation (SN) using the variable indicating control of vehicle ((Medial-Lateral Coefficient of Variation, MLCV), (Anterior-Posterior Coefficient of Variation, APCV)) and motion signal (Jerk-Cost function, JC). Participants included 50s taxi drivers; 14 males and 14 females. Participants were instructed to keep a certain distance (30m) from the car ahead with constant speed (80km/hr or 100km/hr). Experiement consisted of driving alone for 1minute and driving with secondary task for 1minute. Both MLCV and APCV were significantly increased during Driving + Sending Text Message(STM) and Driving + Searching Navigation(SN) than Driving only. Also, JC was increased during Driving + STM and Driving + SN than Driving only. In this study, we found that even in the experts group who are taxi driver and have 25 years driving experience, the smoothness of motion is decreased and the control of vehicle is disturbed when they were performing secondary tasks like sending text message or searching navigation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.2
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• pp.56-62
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• 2010

The purpose of this study was to compare the difference of driving pattern between male and female drivers for a straight driving and unexpected situation using driving simulator and motion data. The participants included total 60 university students; 30 males aged 24.3$\pm$1.4 years and 30 females aged 23.2$\pm$1.9 years with 1~3 years of driving experience. The driving task required participants to keep the constant distance (20m, 25m or 30m) with preceding vehicle running at 55~65km/hr speed using driving simulator which was programed unexpected situation for two minutes. Simulator and motion data were acquired. The acquired data was divided in straight driving block for 40 second and unexpected situation block for 2 second. The coefficient of variation (CV) of lane keeping and jerk-cost (JC) function were analyzed for straight driving and unexpected situation blocks. The results show that CV was smaller in males than females for both straight and unexpected situation blocks (p < .05). JC was smaller in females than males for both straight and unexpected situation blocks. As the distance of vehicles become longer, JC was smaller for both male and female (p < .05).