• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1416-1418
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• 2004

This paper proposes an image processing algorithm for detecting obstacles on road-lane using DLI(disparity of lane-related information) that is generated by stereo images acquired from dual cameras mounted on a moving vehicle. The DLI is a disparity that is acquired using single lane information from road lane detection. For the purpose to reduce processing time, we use small blocks obtained by edge-histogram based blocking logic. This algorithm detects moving objects such as preceding vehicles and obstacles. The proposed algorithm has been implemented in a personal computer with the road image data of a typical highway. We successfully performed experiments under a wide variety of road conditions without changing parameter values or adding human intervention. Experimental results also showed that the proposed DLI is quite successful.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권7호
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• pp.509-516
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• 2004

This paper proposes an image processing algorithm for detecting obstacles on road using DLI(disparity of lane-related information) that is generated by stereo images acquired from dual cameras mounted on a moving vehicle. The DLI is a disparity that is acquired using a single lane information from road lane detection. For the purpose to reduce processing time, we use small block of edge-histogram based blocking logic. This algorithm detects moving objects such as preceding vehicles and obstacles. The proposed algorithm has been implemented in a personal computer with the road image data of a typical highway. We successfully performed experiments under a wide variety of road conditions without changing parameter values or adding human intervention. Experimental results also showed that the proposed DLI is quite successful.

• 대한교통학회지
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• 제26권2호
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• pp.121-133
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• 2008

기존의 첨단차량 추종거동 모형은 선행차량과의 상대거리와 관계없이 동일한 속도이면 추종상태를 유지하는 비현실적 제약성을 내포하고 있다. 따라서 본 연구에서는 추종상황에서 차량간 적정 상대거리를 유지함과 동시에 추종차량 운전자의 안전성과 안락함을 고려하기 위해 인간공학요소를 반영한 보다 현실적인 추종거동모형을 개발하고자 하였다. 인간공학요소의 반영을 위하여 운전자의 개별특성, 환경적 요소, 속도 및 거리관계에 의해 나타나는 운전자의 불안감도(MOA, Measurement of Alarm)를 퍼지모형 구축을 통해 측정하였으며, 측정된 불안감도를 경감시키고 적정 안전거리를 확보하도록 모형을 개발하였다. 개발된 모형의 성능을 검증하기 위하여 기 개발된 GGM(General GM)모형과 동일한 시나리오에 따라 시뮬레이션을 수행하였다. 수행 결과, 선행차량과의 상대거리에 관계없이 속도가 동일하면 추종을 그대로 유지하는 GGM모형과 달리, 제안된 모형은 선행차량과의 상대거리가 안전거리 이하 또는 이상이면 상대거리를 안전거리만큼 넓히거나 좁힌 후 추종상태를 유지하였다. 이는 제안된 모형이 기존의 모형에 비해 더욱 안전한 거동을 하는 것을 나타낸다. 또한 GGM모형이 상대거리와 속도 관계에 의해 높은 불안감도를 유지하는 반면, 제안된 모형은 불안감도를 허용 불안감도까지 경감시켜 추종거동을 유지하여 운전자의 안락함을 잘 반영하는 것으로 나타났다. 따라서 운전자 불안감도의 경감 측면과 도로이용의 효율성 측면에서 제안된 모형이 기존의 GGM모형을 대폭 현실화시킨 것으로 판단되었다.

• 한국지능시스템학회논문지
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• 제19권5호
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• pp.641-647
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• 2009

본 논문에서는 새로운 방식의 적응형 순항제어 필터링 방식을 제안한다. 제안한 알고리즘은 선행 차량의 모드를 추정하는 문제를 분류기의 문제로 보고 신경망 분류기를 이용하여 이를 수행한다. 신경망은 각 모드에 대한 사후 확률을 출력하며 이를 IMM과 결합하여 선행차량의 추적을 수행한다. 끝으로 10가지 시나리오에 대하여 신경망 분류기와 IMM을 결합한 NIMM (Neural Network IMM)을 적용하여 성능을 확인한다.

• 자동차안전학회지
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• 제14권2호
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• pp.57-69
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• 2022

Recently, as interest in self-driving cars has increased worldwide, research and development on the Advanced Driver Assist System is actively underway. Among them, the purpose of Adaptive Cruise Control (ACC) is to minimize the driver's driving fatigue through the control of the vehicle's longitudinal speed and relative distance. In this study, for the research of the ACC test in the real environment, the real-road test was conducted based on domestic-road test scenario proposed in preceding study, considering ISO 15622 test method. In this case, the distance measurement method using the dual camera was verified by comparing and analyzing the result of using the dual camera and the result of using the measurement equipment. As a result of the comparison, two results could be derived. First, the relative distance after stabilizing the ACC was compared. As a result of the comparison, it was found that the minimum error rate was 0.251% in the first test of scenario 8 and the maximum error rate was 4.202% in the third test of scenario 9. Second, the result of the same time was compared. As a result of the comparison, it was found that the minimum error rate was 0.000% in the second test of scenario 10 and the maximum error rate was 9.945% in the second test of scenario 1. However, the average error rate for all scenarios was within 3%. It was determined that the representative cause of the maximum error occurred in the dual camera installed in the test vehicle. There were problems such as shaking caused by road surface vibration and air resistance during driving, changes in ambient brightness, and the process of focusing the video. Accordingly, it was determined that the result of calculating the distance to the preceding vehicle in the image where the problem occurred was incorrect. In the development stage of ADAS such as ACC, it is judged that only dual cameras can reduce the cost burden according to the above derivation of test results.

• International Journal of Automotive Technology
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• 제8권4호
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• pp.513-520
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• 2007

In this paper, we propose an approach to identify the driving environment for intelligent highway vehicles by means of image processing and computer vision techniques. The proposed approach mainly consists of two consecutive computational steps. The first step is the lane marking detection, which is used to identify the location of the host vehicle and road geometry. In this step, related standard image processing techniques are adapted for lane-related information. In the second step, by using the output from the first step, a four-stage algorithm for vehicle detection is proposed to provide information on the relative position and speed between the host vehicle and each preceding vehicle. The proposed approach has been validated in several real-world scenarios. Herein, experimental results indicate low false alarm and low false dismissal and have demonstrated the robustness of the proposed detection approach.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.303-304
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• 2006

This paper proposes detection method of vehicles using camera for auto-vehicle-system. Detection method is based on shadow detection and symmetric feature of vehicle. This method consists of three part. First is lane detection. By lane detection, we can reduce the area for vehicle detection. Second part is shadow detection. Shadow has information of vehicle width and position. Third part is symmetry. This feature is helpful for confirming the vehicle.

• 자동차안전학회지
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• 제14권4호
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• pp.35-42
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• 2022

This paper presents a stochastic model predictive control (SMPC) for stop maneuver of autonomous vehicles considering perception uncertainty of stopped vehicle. The vehicle longitudinal motion should achieve both driving comfortability and safety. The comfortable stop maneuver can be performed by mimicking acceleration profile of human driving pattern. In order to implement human-like stop motion, we propose a reference safe inter-distance and velocity model for the longitudinal control system. The SMPC is used to track the reference model which contains the position uncertainty of preceding vehicle as a chance constraint. We conduct simulation studies of deceleration scenarios against stopped vehicle in urban environment. The test results show that proposed SMPC can execute comfortable stop maneuver and guarantee safety simultaneously.

• 한국자동차공학회논문집
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• 제6권5호
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• pp.222-227
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• 1998

Collision warning systems have been an active research and development area as the interests and demands for ASV's (Advanced Safety Vehicles) have increased. This paper presents an experimental investigation of a collision warning system for automobiles. A collision warning HiLS(Hardware-in-the-Loop Simulation) system has been designed and used to test the collision warning algorithm, radar sensors, and warning displays under realistic operating conditions in the laboratory. the collision warning algorithm is operated by a warning index, which is a function of the warning distance and the braking distance. The computer calculates velocities of the preceding vehicle and following vehicle, relative distance and relative velocity of the vehicles using vehicle simulation models. The relative distance and the relative velocity are applied to the vehicle simulator controlled by a DC motor.

• 제어로봇시스템학회논문지
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• 제14권7호
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• pp.679-688
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• 2008

This paper presents an algorithm capable of detecting leading vehicles using a forward-looking camera. In fact, the accurate measurements of the contact locations of vehicles with road surface are prerequisites for the intelligent vehicle technologies based on a monocular vision. Relying on multistage processing of relevant edge features to the hypothesis generation of a vehicle, the proposed algorithm creates candidate positions being the left and right boundaries of vehicles, and searches for pairs to be vehicle boundaries from the potential positions by evaluating horizontal symmetry. The proposed algorithm is proven to be successful by experiments performed on images acquired by a moving vehicle.