• Journal of the Ergonomics Society of Korea
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• v.29 no.1
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• pp.1-5
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• 2010

The purpose of the paper is to review current trends and future issues of automotive ergonomics. The current trends include 1) universal design considering for regional differences, elderly drivers, female drivers, 2) quantification of driver's discomfort 3) trade-off between design trends and comfort, 4) digital ergonomic evaluation with digital human models 5) optimization of driver's interface. The future issues of automotive ergonomics cover 1) intelligent driver assistance system 2) Fun-to-drive and 3) differentiation from other vehicles based on ergonomics.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.12
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• pp.123-129
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• 2014

In accordance with the development of various convergence devices, cameras are being used in many types of the systems such as security system, driver assistance device and so on, and a lot of people are exposed to these system. Therefore the system should be able to recognize the human behavior and support some useful functions with the information that is obtained from detected human behavior. In this paper we use a machine learning approach based on 2D image and propose the human behavior pattern recognition methods. The proposed methods can provide valuable information to support some useful function to user based on the recognized human behavior. First proposed one is "phone call behavior" recognition. If a camera of the black box, which is focused on driver in a car, recognize phone call pose, it can give a warning to driver for safe driving. The second one is "looking ahead" recognition for driving safety where we propose the decision rule and method to decide whether the driver is looking ahead or not. This paper also shows usefulness of proposed recognition methods with some experiment results in real time.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.3
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• pp.16-24
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• 2011

The vehicle electronic control system is being developed as the legal and social demand for ensuring driver's safety is rising. The various Driver Assistance Systems with various sensors such as radars, camera, and lasers are in practical use because of the falling price of hardware and the high performance of sensor and processer. In the preceding study of this research, the program was developed to recognize the experiment vehicle's driving lane and the cars nearby or approaching the experiment vehicle throughout the images taken by CCD camera. In addition, the 'dangerous driving analysis program' which is Vision System basis was developed to analyze the cause and consequence of dangerous driving. However, the Vision system developed in the previous studyhad poor recognition rate of lane and vehicles at the time of passing a tunnel, sunrise, or sunset. Therefore, through mounting the brightness response algorithm to the Vision System, the present study is aimed to analyze the causes of driver's dangerous driving clearly by improving the recognition rate of lane and vehicle, regardless of when and where it is.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.544-551
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• 2015

In this paper, the design and implementation results of the optical flow estimator (OFE) for moving object detection (MOD) in advanced driver assistance system (ADAS). In the proposed design, Brox's algorithm with global optimization is considered, which shows the high performance in the vehicle environment. In addition, Cholesky factorization is applied to solve Euler-Lagrange equation in Brox's algorithm. Also, shift register bank is incorporated to reduce memory access rate. The proposed optical flow estimator was designed with Verilog-HDL, and FPGA board was used for the real-time verification. Implementation results show that the proposed optical flow estimator includes the logic slices of 40.4K, 155 DSP48s, and block memory of 11,290Kbits.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.1
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• pp.27-34
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• 2015

For a vision-based driver assistance system, unusual motion detection is one of the important means of preventing accidents. In this paper, we propose a real-time unusual-motion-detection model, which contains two stages: salient region detection and unusual motion detection. In the salient-region-detection stage, we present an improved temporal attention model. In the unusual-motion-detection stage, three kinds of factors, the speed, the motion direction, and the distance, are extracted for detecting unusual motion. A series of experimental results demonstrates the proposed method and shows the feasibility of the proposed model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.128-141
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• 2018

In this paper, a methodology to analyze the potential safe benefit of six cooperative driver assistance systems via V2V (vehicle-to-vehicle) communications is proposed. Although it is quite necessary to assess social impact with respect to new safety technologies for cooperative vehicles with V2V communications, there are few studies in Korea to predict the quantitative safety benefit analysis. In this study, traffic accident scenarios are classified based on traffic fatality between passenger cars. The sequential collision type is classified for a multiple pile-up with respect to collision direction such as forward, side, head-on collisions. Then movement of surrounding vehicle is considered for the scenario classification. Next, the cooperative driver assistance systems such as forward collision warning, blind spot detection, and intersection movement assistance are related with the corresponding accident scenarios. Finally, it is summarized how much traffic fatality may be reduced potentially due to the V2V communication based safety services.

• Journal of Auto-vehicle Safety Association
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• v.6 no.2
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• pp.29-35
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• 2014

Lane Keeping Assistance System(LKAS) is a kind of Advanced Driver Assistance Systems(ADAS) which are developed to automate/ adapt/ enhance vehicle systems for safety and better driving. The main system function of LKAS is to support the driver in keeping the vehicle within the current lane. LKAS acquires information on the position of the vehicle within the lane and, when required, sends commands to actuators to influence the lateral movement of the vehicle. Recently, the vehicles equipped with LKAS are commercially available in a few vehicle-advanced countries and the installation of LKAS increases for safety enhancement. The test procedures for LKAS evaluations are being discussed and developed in international committees such as ISO(the International Organization for Standardization). In Korea, the evaluations of LKAS for vehicle safety are planned to be introduced in 2016 KNCAP(Korean New Car Assessment Program). Therefore, the test procedures of LKAS suitable for domestic road and traffic conditions, which accommodate international standards, should be developed. In this paper, some bullet points of the test procedures for LKAS are discussed by extensive researches of previous documents and reports, which are released in public in regard to lateral test procedures including LKAS and Lane Departure Warning System(LDWS). Later, it can be helpful to make a draft considering domestic traffic situations for test procedures of LKAS.

• International Journal of Automotive Technology
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• v.7 no.2
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• pp.187-193
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• 2006

When emergency evasion during running is required, a driver sometimes causes a vehicle to drift, that is, a condition in which the rear wheels skid due to rapid steering. Under such conditions, the vehicle enters a very unstable state and often becomes uncontrollable. An unstable state of the vehicle induced by rapid steering was simulated and the effect of differential steering assistance was examined. Results indicate that, in emergency evasion while cornering and during which the vehicle begins to drift, unstable behavior like spins can be avoided by differential steering assistance and both the stability and control of the vehicle is improved remarkably. In addition, reduction of overshoot during spin evasion by the differential steering assistance has been shown to enable the vehicle to return to a state of stability in a short time in emergency evasion during straight-line running. Moreover, the effectiveness of differential steering assistance during emergency evasion was confirmed using a driving simulator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4489-4501
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• 2014

We propose a novel lane detection method based on classification in image sequences. Both structural and statistical features of the extracted bright shape are applied to the neural network for finding correct lane marks. The features used in this paper are shown to have strong discriminating power to locate correct traffic lanes. The traffic lanes detected in the current frame is also used to estimate the traffic lane if the lane detection fails in the next frame. The proposed method is fast enough to apply for real-time systems; the average processing time is less than 2msec. Also the scheme of the local illumination compensation allows robust lane detection at nighttime. Therefore, this method can be widely used in intelligence transportation systems such as driver assistance, lane change assistance, lane departure warning and autonomous vehicles.

• Journal of Auto-vehicle Safety Association
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• v.13 no.3
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• pp.78-85
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• 2021

Recently a traffic accident of heavy duty vehicles under the mandatory installation of ADAS (Advanced Driver Assistance System) is often reported in the media. Heavy duty vehicle accidents are normally occurring a high number of passenger's injury. According to report of Insurance Institute for Highway Safety, FCW (Forward Collision Warning) and AEB (Automatic Emergency Braking) were associated with a statistically significant 12% reduction in the rate of police-reportable crashes per vehicle miles traveled, and a significant 41% reduction in the rear-end crash rate of large trucks. Also many countries around the world, including Korea, are studying the effects of ADAS installation on accident reduction. Traffic accident statistics of passenger vehicle for business purpose in TMACS (Traffic safety information Management Complex System in Korea) tends to remarkably reduce the number of deaths due to the accident (2017(211), 2018(170), 2019(139)), but the number of traffic accidents (2017(8,939), 2018(9,181), 2019(10,095)) increases. In this paper, it is introduced a traffic accident case that could lead to high injury traffic accidents by being equipped with AEB in a bus. AEB reduces accidents and damage in general but malfunction of AEB could occur severe accident. Therefore, proper education is required to use AEB system, simply instead of focusing on developing and installing AEB to prevent traffic accidents. Traffic accident of AEB equipped vehicle may arise a new dispute between a driver's fault and vehicle defect. It is highly recommended to regulate an advanced event data recorder system.