• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.3
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• pp.65-77
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• 2013

Recent advanced sensors and communication technologies have been widely applied to advanced safety vehicle (ASV) for reducing traffic accident and injury severity. To apply the advanced safety vehicle technologies, it is important to quantify the safety benefits, which is a fundamental for justifying application. This study proposed a methodology for quantifying the effectiveness of the advanced driver assistant system (ADAS), and applied the methodology to lane departure warning system (LDWS) and automatic emergency braking system (AEBS) which are typical advanced driver assistant systems. When the proposed methodology is applied to 2008-2010 gyeonggi-province crash data, LDWS would reduce about 10~14% of relevant crashes such as head-on, run-off-the road, rollover and fixed-object collisions on the road. In addition, AEBS could potentially prevent about 50% of total rear-end crashes. The outcomes of this study support decision making for developing not only vehicular technology but also relevant safety policies.

• Journal of Sensor Science and Technology
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• v.26 no.1
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• pp.1-6
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• 2017

The advanced driver assistant system (ADAS) requires the collection of a large amount of information including road conditions, environment, vehicle status, condition of the driver, and other useful data. In this regard, large-scale sensor networks can be an appropriate solution since they have been designed for this purpose. Recent advances in sensor network technology have enabled the management and monitoring of large-scale tasks such as the monitoring of road surface temperature on a highway. In this paper, we consider the estimation and fusion problems of the large-scale sensor networks used in the ADAS. Hierarchical fusion architecture is proposed for an arbitrary topology of the large-scale sensor network. A robust cluster estimator is proposed to achieve robustness of the network against outliers or failure of sensors. Lastly, a robust hierarchical data fusion scheme is proposed for the communication channel between the clusters and fusion center, considering the non-Gaussian channel noise, which is typical in communication systems.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.856-864
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• 2008

This paper describes a vehicle low speed driving assistant (VLDA) system that is composed of laser scanner. This vehicle is designed for following lead vehicle (LV) without driver's operation. The system is made up several component systems that are based on unmanned ground vehicle (UGV). Each component system is applied to use advanced safety vehicle developed to complete UGV system. VLDA system was divided into vehicle control system and obstacle detecting system. The obstacle detecting system calculate distance and angle of LV and transmit these data to vehicle control system using front, left and right laser scanners. Vehicle control system makes vehicle control values such as steering angle, acceleration and brake position and control vehicle's movement with steering, acceleration and brake actuators. In this research, we designed VLDA system like as low speed cruise control system and test it on real road environments.

• Journal of Auto-vehicle Safety Association
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• v.10 no.3
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• pp.32-37
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• 2018

Recently, the driver can be assisted by the advanced active safety devices such as ADAS from road traffic risks. With this system, driver and passenger may freed from can driving tasks or kept eyes on forward direction while on the road. Help from adoptive cruise control, auto parking and newly develped automated driving vehicles technologies, the driver positions will vary significantly from the current standard driver position during the travel time. On this hypothesis, the objective of this study is analyze the behavior and injuries of drivers in the event of frontal impact under these abnormal driver position. Based on the KNCAP frontal impact testing method, this simulation matrix was set-up with dummies of 5 th tile female Hybrid III dummy and 50 th tile male Hybrid III dummy. The small sedan type passenger car was modeled in this simulation. The series of simulation was performed to compare the injuries and behaviour of each dummy, varying the seating status and seat position of each dummy.

• Electronics and Telecommunications Trends
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• v.34 no.1
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• pp.123-131
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• 2019

Automotive electronics are complex and require high performance with an advanced driver assistant system (ADAS) and a functioning autonomous system. Thus, considering their complexity, the processor of the electronic control unit (ECU) requires a design that ensures high performance and reliability to ensure functional safety. This study discusses the technology used for developing a processor that can ensure functional safety of current automotive electronic systems.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.137-143
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• 2009

It is necessary to develop driving assistant information in order to prevent a rear-end collision with a crashed car which is at the blind curve on highway. Laboratory experiments were performed using a driving simulator to keep the traffic environment constant. This research was evaluated the effect of driver behavior according to providing collision avoidance information which was consisted of advisory, caution, and warning information by the dangerous degree of traffic situation. Driver behavior was evaluated to analyze the collision avoidance with a crashed car, and glance behavior was examined to measure the eye movements to the display on which provided the collision avoidance information. After experiment, the significance was evaluated on provided collision avoidance information. As the result of this research, the number of collision accident is reduced when the phased information was provided. In addition, it is clear that auditory information is more important than visual information in the case of providing the second information.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.172-177
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• 2021

The HUD (Head-up Display) device for vehicles has gradually been advanced in connection with ADAS (Advanced Driver Assistant System) for the safety and the convenience of driving. In this paper, the major features (e.g. speed, RPM, etc.) of vehicles is received through the ECU and the route information is received through the navigating API, configurating the integrated GUI. And, the optical system is configured based on DLP (Digital Light Processing) to evaluate the visibility depending on the resolution change of the GUI. The IoT HUD system proposed in this paper has the scalability to flexibly add not only the ECU but also various cloud-based driving-related information.

• Journal of Korean Society of Transportation
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• v.32 no.4
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• pp.293-302
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• 2014

Recently, advanced sensors and communication technologies have been widely applied to advanced safety vehicles for reducing traffic accidents and injury severity. To apply the advanced safety vehicle technologies, it is important to quantify safety benefits, which is a fundamental for justifying application. This study proposed a methodology for quantifying the effectiveness of the Advanced Driver Assistant System (ADAS) with the Analytic Hierarchy Process (AHP). When the proposed methodology is applied to 2008-2010 Gyeonggi-province crash data, ADAS would reduce about 10.18% of crashes. In addition, Adaptive Cruise Control, Automatic Emergency Braking System, Lane Departure Warning System and Blind Spot Detection System are expected to reduce about 10.43%, 10.17%, 9.96%, and 10.18%, respectively. The outcomes of this study might support decision making for developing not only vehicular technologies but also relevant safety policies.

• International Journal of Advanced Culture Technology
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• v.4 no.4
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• pp.23-29
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• 2016

In this paper, the learning technique for CNN processor on vehicle is proposed. In the case of conventional CNN processors, weighted values learned through training are stored for use, but when there is distortion in the image due to the weather conditions, the accuracy is decreased. Therefore, the method of enhancing the input image for classification is general, but it has the weakness of increasing the processor size. To solve this problem, the CNN performance was improved in this paper through the learning method of the distorted image. As a result, the proposed method showed improvement of approximately 38% better accuracy than the conventional method.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.769-772
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• 2000

In this paper, a new lateral offset estimation method, based on image processing techniques, is proposed for driver assistant system. A new description on lane markings in the image plane is presented, and its properties are discussed and used to detect lane markings. Multi-frame lane detection and analysis are adopted to improve the proposed lateral control method. An algorithm for obstacle detection is also developed. Experimental results show that the proposed method performs lateral control effectively.