• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.297-298
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• 2022

현재 도로 위 차량은 다양한 기능이 탑재되어 있고, 이는 운전자의 편의와 안전을 위해 발전해왔다. 하지만 음주운전과 안전운전 불이행에 의한 교통사고는 꾸준히 발생하고 있으며, 이 사고율은 단순히 제도적 규제와 운전자의 주의만으로는 감소시키기 어렵다고 판단된다. 본 논문은 제도적인 규범만이 아닌 기계적인 차원에서의 음주운전 사고 예방과 안전운전 불이행 사고의 방지를 하기 위해 '음주측정 시동 및 안전운전 보조시스템'을 제안한다. 이러한 문제를 해결하고자 알코올 측정 센서를 통해 시동을 걸기 전 음주측정을 해 음주운전의 가능성을 차단하고 초음파 센서를 이용하여 전, 후·측방 감지를 하고 주변의 장애물과 운전자의 부주의 시 즉각적인 피드백을 제공해 안전운전 불이행 사고를 방지할 수 있다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.3
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• pp.603-610
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• 2017

Various type of pavement deterioration such as crack, bumpy, pothole is rapidly increasing according to the accelerated environmental changes like heavy rainfall, frequent snowing, difference temperature, etc. Accident related to pothole that cause fatal traffic accidents has been increased more than five times over the next five years starting from 2008. As direct or indirect damage by pothole which caused injuries and car damages increases every year, quicker and more efficient management measures are necessary. This study presents the algorithm for materials quantity take-off. The algorithm was suggested by correlation in pothole size and area. Suggested algorithm were confirmed the validity through the 15 field survey in capital area. According to the results of survey, usually the residual materials at which 5~7 kg was generated decreased to 1~2 kg. It showed that automatic pothole detection system is expected not only to reduce materials and resources, but also to contribute to quality improvements of pavement through more accurate material take-off from the situation of constructing rely on their own judgement.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.481-484
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• 2011

Recent Automotive technology is driven from mechanical device to the electronic components which improve the vehicle's safety and convenience. The future competitiveness of the car will come from safety issues and energy efficiency, convenience and the application of the technologies. In this study, various techniques for driver drowsiness detection are introduced and compared with each others. The advantages and disadvantages of commercially available technologies and developed technologies are compared. To enhance the detection resolution, multiple sensing technologies are introduced in this paper. The feasibility of two drowsiness detection methods, that is, existing camera image recognition method and bio signal analysis method, are tested. The direct drowsiness detection by the camera image of eyes and driver's vital signs detected indirectly are combined and analyzed by the developed noble algorithm for stress, fatigue, drowsiness detection with a more accurate high-drowsiness detection.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.1-17
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• 2018

The living lab is a user-participatory innovation space where users can solve problems by themselves. Living Lab members are able to participate in all aspects of product development from technology conception. In this study, to prevent pedestrian accidents, auto-image sensing signal system was developed in Jeonju City, using the Living Lab method. In addition, we measured effectiveness of the auto-image sensing signal system with respect to pedestrian waiting time, pedestrian and driver signal violation, and pedestrian jaywalking. It was also compared the measures before installation, after installation and after applying Living Lab method. As a result, all of the three measures of effectiveness appeared to be more effective after Living Lab than after installation. Overall, this study is very significant in that it is the first case where the living lab is applied in transportation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.116-125
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• 2020

Incalculable damage will be incurred if the national infrastructure that provides services using GNSS signals is affected by jamming signals. To prevent this, a nationwide GNSS jamming monitoring network is necessary to detect the occurrence of a jamming signal, determine the type, and properly localize the jammer position. In this paper, 2-D images for live GNSS signals were generated to verify the environment of the jamming signals through the presence and type of GNSS jamming signals at K-City, which are the test beds for self-driving vehicles, and Incheon International Airport. The analysis was also conducted to detect the occurrence of the jamming signals, determine the type, and measure the jamming signal strength. As a result, a CWI type of jamming signal was detected in L2 band at K-City and in L5 band at Incheon International Airport.

• Journal of Korea Multimedia Society
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• v.13 no.1
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• pp.66-75
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• 2010

We proposed an occupant sensing system using single video camera and ultrasonic sensor for the advanced airbag. To detect the occupant form and the face position in real-time, we used the skin color and motion information. We made the candidate face block image using the threshold value of the color difference signal corresponding to skin color and difference value of current image and previous image of luminance signal to gel motion information. And then it detects the face by the morphology and the labeling. In case of night without color and luminance information, it detects the face by using the threshold value of the luminance signal get by infra-red LED instead of the color difference signal. To evaluate the performance of the proposed occupant detection system, it performed various experiments through the setting of the IEEE camera, ultrasonic sensor, and infra-red LED in vehicle jig.

• International Journal of Highway Engineering
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• v.10 no.2
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• pp.159-166
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• 2008

Video image processing systems (VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on a wide-area detection algorithm provide traffic parameters such as flow and velocity as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. However, unlike human vision, VIPS cameras have difficulty in recognizing vehicle movements over a detection zone longer than 100 meters. Over such a distance, the camera operators need to zoom in to recognize objects. As a result, vehicle tracking with a single camera is limited to detection zones under 100m. This paper develops a methodology capable of monitoring individual vehicle trajectories based on image processing. To improve traffic flow surveillance, a long distance tracking algorithm for use over 200m is developed with multi-closed circuit television (CCTV) cameras. The algorithm is capable of recognizing individual vehicle maneuvers and increasing the effectiveness of incident detection.

• Journal of Internet of Things and Convergence
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• v.9 no.2
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• pp.61-69
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• 2023

In recent years, due to heightened environmental awareness, Electric Power Steering (EPS) has been increasingly adopted as the steering control unit in manufactured vehicles. This has had numerous benefits, such as improved steering power, elimination of hydraulic hose leaks and reduced fuel consumption. However, for EPS systems to respond to actions, sensors must be employed; this means that the consistency of the sensor's linear variation is integral to the stability of the steering response. To ensure quality control, a reliable method for detecting defects and assessing linearity is required to assess the sensitivity of the EPS sensor to changes in the internal design characters. This paper proposes a data-driven defect and linearity assessment monitoring system, which can be used to analyze EPS component defects and linearity based on vehicle speed interval division. The approach is validated experimentally using data collected from an EPS test jig and is further enhanced by the inclusion of a Graphical User Interface (GUI). Based on the design, the developed system effectively performs defect detection with an accuracy of 0.99 percent and obtains a linearity assessment score at varying vehicle speeds.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.805-808
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• 2008

In this paper, it was performed the analysis on various intersection acoustic patterns for detection rate improvement of accident sound detection system : an acoustic pattern analysis on general traffic noise, an acoustic pattern analysis on engine noise, an acoustic pattern analysis on obstruct factors for accident sound detection system. There are remarkable differences between the acoustic patterns of traffic noise and accident sound, and we most consider the acoustic patterns when we compose the accident traffic detection system by acoustic because there is error range of 20[dB] according to the volume of traffic in intersection.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.4
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• pp.169-176
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• 2000

Longitudinal and lateral forces acting on tires are known to be closely related to the tract-ability braking characteristics handling stability and maneuverability of ground vehicles. In thie paper in order to develop tire force monitoring systems a monitoring model is proposed utilizing not only the vehicle dynamics but also the roll motion. Based on the monitoring model three monitoring systems are developed to estimate the tire force acting on each tire. Two monitoring systems are designed utilizing the conventional estimation techniques such as SMO(Sliding Mode Observer) and EKF(Extended Kalman Filter). An additional monitoring system is designed based on a new SKFMEC(Scaled Kalman Filter with Model Error Compensator) technique which is developed to improve the performance of EKF method. Tire force estimation performance of the three monitoring systems is compared in the Matlab simulations where true tire force data is generated from a 14 DOF vehicle model with the combined-slip Magic Formula tire model. The built in our Lab. simulation results show that the SKFMEC method gives the best performance when the driving and road conditions are perturbed.