• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 춘계학술대회 논문요약집
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• pp.166-166
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• 2004

운전자 보조시스템에는 적응순항제어 (adaptive cruise control), 차선변경 (lane change), 충돌경고 (collision warning), 충돌회피 (collision avoidance), 및 자동주차 (automatic parking) 등이 있다. 이런 운전자 보조시스템은 어떤 목적을 가지고 있다. 운전자의 부담을 줄이고 안전을 위하여 차량의 주행방향에 있는 장애물이나 차량을 감지하여 차량간의 안전거리론 유지하고 자동차가 일정 속도를 유지하도록 한다. 운전자 보조시스템의 효율은 센서들로부터 얻어진 정보의 해석에 달려있다.(중략)

• 전자통신동향분석
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• 제34권1호
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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.

• 한국자동차공학회논문집
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• 제17권3호
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• pp.54-61
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• 2009

Lane keeping assistant system (LKAS) could save thousands of lives each year by maintaining lane position and is regarded as a promising active safety system. The LKAS is expected to reduce the driver workload and to assist the driver during driving. This paper proposes a model based predictive controller for the LKAS which requires cooperative driving between the driver and the assistance system. A Hardware-In-the-Loop-Simulator (HILS) is constructed for its evaluation and includes Carsim, Matlab Simulink and a lane detection algorithm. The single camera is mounted with the HILS to acquire the monitor images and to detect the lane markers. The simulation is conducted to validate the LKAS control performance in various road scenario.

• 한국ITS학회 논문지
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• 제19권5호
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• pp.29-39
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• 2020

많은 나라에서 정규 운전면허 발급 기준을 만족시키지 못할 때, 특정한 조건을 만족시키는 경우에서만 운전을 허용하는 조건부 운전면허제도를 운영하고 있다. 우리나라에서는 시각, 청각, 신체 활동 등에 어려움을 겪는 사람들이 특별히 운전할 수 있도록 자동차의 구조를 개선하거나 신체 활동 보조수단을 이용하는 조건으로 면허를 발급하고 있다. 하지만 고령 운전자가 늘어나면서 기존 조건부 운전면허의 허용 조건을 다양화하자는 주장이 제기되고 있다. 본 연구는 외국의 다양한 조건부 운전면허제도 운영 사례를 벤치마킹하여 고령자를 위한 조건부 운전면허제도의 개선 방향을 모색하고자 한다. 특히 우리나라에 없는 조건부 운전면허 조건인 시간 제한, 공간 제한, 속도 제한, 도로 제한, 차량 제한, 개인 맞춤형 등 차원에서 주요 특징을 국제 비교를 통하여 도출하고자 한다. 조건부 운전면허제도의 허용기준 다양화는 고령자뿐만 아니라 차를 운전하지 않으면 일상생활에 어려움을 겪는 모든 운전자들에게 혜택이 될 것으로 기대된다.

• 한국자동차공학회논문집
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• 제16권4호
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• pp.88-96
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• 2008

Effects of the duct inlet guide vane on the flowrate distribution characteristics of the defroster nozzle exit in a defrost duct system were investigated experimentally to design the optimum heating, ventilation and air conditioning (HVAC) system applied in an automotive compartment. A 3-dimensional hot-wire anemometer system was used to measure the velocity field in the vicinity of the defroster nozzle jet flow and the velocity distributions near the windshield interior surface. At first, two cases of with- and without-duct inlet guide vanes were considered as the test condition, and then three cases of the duct inlet guide vane were tested to determine the optimum guide vane shape and their positions. The arrangement of the duct inlet guide vanes has an effect on the improved flowrate distribution at the defroster nozzle exit and near the windshield interior surface. However, the application of the lots of guide vane to control the flow direction leads to increase the flow resistance, resulting in the decreased flowrate issuing from the defroster nozzle. The shape of the duct inlet guide vane affects not only the flowrate distribution between the driver side and the assistant driver side but also the reduction of the flow resistance in the defrost duct system.

• 드라이브 ㆍ 컨트롤
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• 제19권4호
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• pp.62-69
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• 2022

Construction machinery is exposed to accidents such as collisions, narrowness, and overturns during operation. In particular, mobile crane is operated only with the driver's vision and limited information of the assistant worker. Thus, there is a high risk of an accident. Recently, some collision avoidance device using sensors such as cameras and LiDAR have been applied. However, they are still insufficient to prevent collisions in the omnidirectional 3D space. In this study, a rotating LiDAR device was developed and applied to a 250-ton crane to obtain a full-space point cloud. An algorithm that could provide distance information and safety status to the driver was developed. Also, deep-learning segmentation algorithm was used to classify human-worker. The developed device could recognize obstacles within 100m of a 360-degree range. In the experiment, a safety distance was calculated with an error of 10.3cm at 30m to give the operator an accurate distance and collision alarm.

• 대한인간공학회지
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• 제28권3호
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• pp.63-71
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• 2009

A car navigation system as an in-vehicle route guidance information (RGI) offers a state-of-the-art technological solution to driver navigation in an unfamiliar area. However, the RGI is provided by some pre-determined options in terms of the interface between a driver and a car navigation system. Drivers occasionally pass the target intersection owing to non- or late- recognizing it. This paper is examined the position of driver's turn signal operation and intersection recognition approaching at the target intersection which is difficult to identify, as a fundamental research on developing the additional RGI connecting with the turn signal control. The field experiment was conducted to measure distances of the turn signal operation and the intersection recognition from the target intersection according to left turns, right turns, and landmarks at adjacent intersection. And glance behavior to the car navigation display was evaluated by using an eye camera. The results of the field study indicate that, most case of driving, drivers operate the turn signal until 40m to 50m before coming to the target intersection. The driving simulator experiment was performed to examine the effectiveness of providing the additional RGI when drivers did not operate the turn signal approaching at the target intersection based on the results of the field study. To provide the additional RGI is effective for the intersection identification and recognition, and expected to improve the traffic safety and the comfort for drivers.

• 한국자동차공학회논문집
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• 제21권4호
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• pp.43-53
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• 2013

Lane marking detection based on a mono camera sensor provides a low cost solution to both ITS (intelligent transportation systems) and DAS (driver assistant systems). A number of methods and implementations have been reported in the literature. However, reliable detection is still an issue. Traditional approaches are mostly based on statistics or Hough transforms. However, the former approaches usually include many irrelevant detection areas, and the latter are not practical because actual lanes are not usually suitable for the approximation with linear or polynomial equations. In this paper, we focus on increasing the reliability of detection by reducing the detection of irrelevant areas while improving the detection of actual lane marking areas, which is usually a tradeoff for most conventional approaches. We use scale-space for that. Through experiments with real images obtained from various environments, we could achieve a significant improvement over traditional approaches.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2011년도 한국컴퓨터종합학술대회논문집 Vol.38 No.1(A)
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• pp.491-493
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• 2011

Traffic sign detection is the domain of automatic driver assistant systems. There are literatures for traffic sign detection using color information, however, color-based method contains ill-posed condition and to extract the region of interest is difficult. In our work, we propose a method for traffic sign detection using k-means clustering method, back-propagation neural network, and projection histogram features that yields the robustness for ill-posed condition. Using the color information of traffic signs enables k-means algorithm to cluster the region of interest for the detection efficiently. In each step of clustering, a cluster is verified by the neural network so that the cluster exactly represents the location of a traffic sign. Proposed method is practical, and yields robustness for the unexpected region of interest or for multiple detections.

• International Journal of Advanced Culture Technology
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• 제4권4호
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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.