• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.825-828
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• 2014

본 논문에서는 3차원 공간에서 6자유도로 움직이는 카메라의 실시간 포즈를 추적하기 위해, RGB-D 입력 영상들로부터 카메라의 실시간 주행 거리를 효과적으로 계산할 수 있는 시각 주행 거리 측정기를 제안한다. 본 논문에서 제안하는 시각 주행 거리 측정기에서는 컬러 영상과 깊이 영상의 풍부한 정보를 충분히 활용하면서도 실시간 계산량을 줄이기 위해, 특징점 위주의 저밀도 주행 거리 계산 방법을 사용한다. 또한, 본 시스템에서는 정확도 향상을 위해, 정합된 특징점들에 대한 추가적인 정상 집합정제 과정과 이들을 이용한 주행 거리 정제 작업을 반복하도록 설계하였다. TUM 대학의 벤치마크 데이터 집합을 이용하여 다양한 성능 분석 실험을 수행하였고, 이를 통해 본 논문에서 제안하는 시각 주행 거리 측정기의 높은 성능을 확인할 수 있었다.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1718-1719
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• 2008

본 논문에서는 철도차량의 능동조향을 위한 고전 PI 제어기 및 퍼지 제어기를 설계하여 그 성능을 서로 비교하였다. 철도차량에서 능동조향은 곡선부 주행 시 발생되는 승차감 저하 및 차륜/레일의 마모와 소음을 줄이고, 고속주행을 위한 조향성능 및 주행안정성을 확보하기 위한 제어기술이다. 논문에서는 차량 1량을 모델로 하여 측정된 휠-레일의 횡변위(Lateral Displacement) 정보를 토대로 휠의 요모멘트를 제어하는 전략을 사용하여 제어기를 설계하였으며, 시뮬레이션을 통해 제어기 응답 특성을 비교하였다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1991.04a
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• pp.277-283
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• 1991

일반적으로 건설중장비에 쓰이는 주행용 감속기의 종류에는 차동유성기구(Differential Planetary Drive), 2단유성기구(Two Stage Planetary Drive), 3단유성기구(Three Stage Planetary Dnive)가 있으나 전체적인 감속기의 성능 및 특성에 대해서는 자세히 알려져 있지않아 주행시스템의 국내개발이 미흡한 상황에 있다. 따라서 본 연구에서는 이러한 문제점의 1차적 해결책으로서 주행장치에 채용될 Heavy Duty용 유성기어 감속기를 차동유성기구 한개 모델과 2단유성기구 두개 모델을 시제품으로 제작하여 종류별로 동력전달효율과 감속기 내부 온도상승의 관점에서 그 성능을 비교 분석하여 각각의 특성을 제시하였다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.10a
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• pp.295-301
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• 1997

본 연구의 목적은 수도권 전동차량의 주행성능을 평가하는 방법으로 진동성능을 비교검토하기 위하여 실차측정하고 분석한 것이다. 전동차량의 제작년도별로 측정대상차량을 샘플링하여 다양한 조건에서 진동을 측정하고 실측데이타를 시간영역의 통계적 방법으로 분석한 결과 제작년도에 따른 영향도 약간 나타났으며 전동차량의 2차 현가장치의 종류에 따른 영향을 발견할 수 있었다. 또한 측정선로구간의 특성에 따른 영향도 비교적 잘 나타나고 있음을 알 수 있었다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.10
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• pp.931-940
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• 2017

This paper describes a predictive fault diagnosis algorithm for autonomous vehicles based on a kinematic model that uses a sliding mode observer. To ensure the safety of autonomous vehicles, reliable information about the environment and vehicle dynamic states is required. A predictive algorithm that can interactively diagnose longitudinal environment and vehicle acceleration information is proposed in this paper to evaluate the reliability of sensors. To design the diagnosis algorithm, a longitudinal kinematic model is used based on a sliding mode observer. The reliability of the fault diagnosis algorithm can be ensured because the sliding mode observer utilized can reconstruct the relative acceleration despite faulty signals in the longitudinal environment information. Actual data based performance evaluations are conducted with various fault conditions for a reasonable performance evaluation of the predictive fault diagnosis algorithm presented in this paper. The evaluation results show that the proposed diagnosis algorithm can reasonably diagnose the faults in the longitudinal environment and acceleration information for all fault conditions.

• Journal of the Korean Society for Railway
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• v.10 no.5
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• pp.613-618
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• 2007

The performance of the railway bogie is classified into the stability and the steering performance. Testing for the bogie stability is conducted on the roller rig, but testing for the bogie steering performance on test facility is very difficult, so the testing for the vehicle curving performance is conducted on the real curve track. Testing the railway bogie on the full scale test rig is desirable, but it caused many problems relating to test costs and test time. As a possible alternative to overcome these problems, a small scaled test rig is actively used in the field of bogie stability. Thus, in this paper, we have studied a scaled track to test the bogie steering performance. For this purpose, we designed the 1/5 scaled test track equivalent to radius 200 curve and confirmed the validity of the testing for the bogie steering performance on the sealed curve track through the testing using 1/5 scaled bogie.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.65-74
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• 2024

In recent years, image processing technology has played a critical role in the field of autonomous driving. Among them, image recognition technology is essential for the safety and performance of autonomous vehicles. Therefore, this paper aims to develop a hybrid image recognition system to enhance the safety and performance of autonomous vehicles. In this paper, various image recognition technologies are utilized to construct a system that recognizes and tracks objects in the vehicle's surroundings. Machine learning and deep learning algorithms are employed for this purpose, and objects are identified and classified in real-time through image processing and analysis. Furthermore, this study aims to fuse image processing technology with vehicle control systems to improve the safety and performance of autonomous vehicles. To achieve this, the identified object's information is transmitted to the vehicle control system to enable appropriate autonomous driving responses. The developed hybrid image recognition system in this paper is expected to significantly improve the safety and performance of autonomous vehicles. This is expected to accelerate the commercialization of autonomous vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.81-90
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• 2016

As an autonomous driving vehicle (AV) need to cope with external road conditions by itself, its perception performance for road environment should be better than that of a human driver. A vision sensor, one of AV sensors, performs lane detection function to percept road environment for performing safe vehicle steering, which relates to define vehicle heading and lane departure prevention. Performance standards for a vision sensor in an ADAS(Advanced Driver Assistance System) focus on the function of 'driver assistance', not on the perception of 'independent situation'. So the performance requirements for a vision sensor in AV may different from those in an ADAS. In assuming that an AV keep previous steering due to lane detection failure, this study calculated lane departure distances between the AV location following curved road alignment and the other one driving to the straight in a curved section. We analysed lane departure distance and time with respect to the allowance of lane detection malfunction of an AV vision sensor. With the results, we found that an AV would encounter a critical lane departure situation if a vision sensor loses lane detection over 1 second. Therefore, it is concluded that the performance standards for an AV should contain more severe lane departure situations than those of an ADAS.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.8
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• pp.241-248
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• 2022

In this paper, the PID controller and Kalman filter are applied to improve the automobile cruise control in the environment with disturbance and noise, and the performance is verified through diverse simulation. First, a mathematical model for a automobile cruise control system is introduced. Second, the performance degradation due to disturbance in the basic open-loop control based cruise control system is shown and then PID controller-based feedback control system to resolve this problem is verified. Third, to improve the performance degradation due to sensor noise that may occur during the feedback process, a Kalman filter is applied and verified. Ultimately, it is verified that the designed cruise control system with PID controller and Kalman filter not only satisfies all performance conditions but also has the ability for disturbance rejection and noise reduction.

• Journal of the Korean Society for Railway
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• v.12 no.6
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• pp.909-914
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• 2009

A suspension is the most prior apparatus to decide vehicle's running safety and ride comfort, also the suspension stiffness is the most important parameter for the designing of the vehicle. Providing the strong stiffness with the primary suspension in order to improve the running safety with high speed, but it causes a problem with a curve running performance of a railway vehicle. Therefore, many studies deal with the optimal value of suspension stiffness. In this paper, we aim to optimize the suspension system to improve running safety by varying stiffness values of railway vehicle suspension. We have proceeded an analysis by design variables which are position, length, width, stiffness and damping coefficients of primary and secondary suspension to optimize the suspension characteristics. As a result of the optimization, we verified that the derailment coefficients of inside and outside of wheel are decreased in comparison with initial model.