• 제어로봇시스템학회논문지
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• 제22권7호
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• pp.562-569
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• 2016

This paper proposes a navigation system with a robust localization method for an underwater unmanned vehicle. For robust localization with IMU (Inertial Measurement Unit), a DVL (Doppler Velocity Log), and depth sensors, the EKF (Extended Kalman Filter) has been utilized to fuse multiple nonlinear data. Note that the GPS (Global Positioning System), which can obtain the absolute coordinates of the vehicle, cannot be used in the water. Additionally, the DVL has been used for measuring the relative velocity of the underwater vehicle. The DVL sensor measures the velocity of an object by using Doppler effects, which cause sound frequency changes from the relative velocity between a sound source and an observer. When the vehicle is moving, the motion trajectory to a target position can be recorded by the sensors attached to the vehicle. The performance of the proposed navigation system has been verified through real experiments in which an underwater unmanned vehicle reached a target position by using an IMU as a primary sensor and a DVL as the secondary sensor.

• 센서학회지
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• 제10권5호
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• pp.329-336
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• 2001

This paper describes the steering control and geomagnetism cancellation for an autonomous vehicle using an MR sensor. The magneto-resistive (MR) sensor obtains the vector summation of the magnetic fields from embedded magnets and the Earth. The vehicle is controlled by the magnetic fields from embedded magnets. So, geomagnetism is the disturbance in the steering control system. In this paper, we propose a new method of the sensor arrangement in order to remove the geomagnetism and vehicle body interference. The proposed method uses two MR sensors located in a level plane and the steering controller has been developed. The controller has three input variables ($dB_x$, $dB_y$, $dB_z$) using the measured magnetic field difference, and an output variable (the steering angle). A simulation program was developed to acquire the data to teach the neural network, in order to test the ability of a neural network to learn the steering control process. Also, the computer simulation of the vehicle (including vehicle dynamics and steering) was used to verify the steering performance of the vehicle controller using the neural network. From the simulation and field test, good result was obtained and we confirmed the robustness of the neural network controller in a real autonomous vehicle.

• 한국정밀공학회지
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• 제24권10호
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• pp.83-90
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• 2007

The vehicle dynamic control system needs to detect the yaw rate of vehicle and a yaw rate sensor is required as a central component. Therefore, A sensor on the basic of the "tuning fork method" for automotive controls is being developed. The sensor was fabricated by the surface micro machining process to miniaturize its size. The sensor output offset is ${\pm}0.37^{\circ}/sec$ in the room temperature. The resonance frequency of the fabricated yaw rate sensor is measured to 5.29kHz for the drive mode. Tests of the sensor demonstrate that its performance is equivalent to that required for implementation of a yaw control system. Vehicle handling and safety are substantially improved using the sensor to implement yaw control.

• 전기학회논문지
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• 제58권7호
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• pp.1398-1404
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• 2009

This paper proposes a vehicle speed detector with anisotropic magnetoresistive (AMR) sensors and addresses experimental results to show the performance of the detector. The detector consists of two AMR sensors and mechanical and electronic apparatuses. The AMR sensor senses disturbance of the earth magnetic field caused by a vehicle moving over the sensor and then produces an output indicative of the moving vehicle. In this paper, vehicle speeds are calculated by using two AMR sensors built on a board. The speed of a vehicle is calculated by dividing the known distance between the two sensors with the time difference between two output signals from each sensor, captured sequentially while the vehicle is driving over the sensors. Some field tests have been carried to show the performance of the proposed detector and its usefulness.

• 센서학회지
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• 제22권1호
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• pp.65-70
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• 2013

The integrated sensor module of vehicle combines the functions of rain sensor, auto defog sensor, and sun angle sensor into a single module. These functions originally were applied to work separatively. This integrated sensor module should meet the each performance which appears from the individual modules up to the same level or higher. Therefore, it is important to verify the stability and the accuracy considering the characteristics of the integrated sensor module according to various situations. For the verification, we need to use the actual data of integrated sensor module measured but, a lot of time and money is needed to collect data measured under various circumstances when operating. Thus, through the development of this simulator for the control of the integrated sensor module, we can use it effectively for the initial verification of integrated sensor module by implementing the various situations. In this paper, the simulator for controlling the integrated sensor module which combines vision-based rain sensor, auto defog sensor, auto light sensor, and sun angle sensor has been developed.

• 한국분무공학회지
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• 제21권1호
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• pp.1-6
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• 2016

A gasoline injector rig which can measure cumulative injected fuel mass under a vehicle driving condition was developed. The measurement system consists of an engine control unit (ECU), data acquisition (DAQ) and injected fuel collection system using loadcells. By supplying reconstructed sensor signals which simulate the real vehicle's sensor signals to the ECU, the ECU drives injectors as if they were driven in the vehicle. The vehicle's performance was computer simulated by using $GT-Suite^{(R)}$ software based on both engine part load performance and automatic transmission shift map. Throttle valve position, engine and vehicle speed, air mass flow rate et al. were computer simulated. The used vehicle driving pattern for the simulation was FTP-75 mode. For reconstructing the real vehicle sensor signals which are correspondent to the $GT-Suite^{(R)}$ simulated vehicle's performance, the DAQ systems were used. The injected fuel was collected with mess cylinders. The collected fuel mass in the mess cylinder with elapsed time after starting FTP-75 driving mode was measured using loadcells. The developed method shows highly improved performance in fast timing and accuracy of the cumulative injected fuel mass measurement under the vehicle driven condition.

• 디지털산업정보학회논문지
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• 제17권4호
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• pp.85-94
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• 2021

The LPR system's trigger sensor makes problem occasionally due to the heave weight of vehicle or the obsolescence equipment. If we replace the hardware sensor to the deep-learning based software sensor in order to generate the trigger signal, LPR system maintenance would be a lot easier. In this paper we proposed the deep-learning sliding window based object detection and tracking algorithm for the LPR system's trigger signal generation. The gate passing vehicle's license plate recognition results are combined into the normal tracking algorithm to catch the position of the vehicle on the trigger line. The experimental results show that the deep learning sliding window based trigger signal generating performance was 100% for the gate passing vehicles including the 5.5% trigger signal position errors due to the minimum bounding box location errors in the vehicle detection process.

• 대한임베디드공학회논문지
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• 제3권1호
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• pp.42-48
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• 2008

The architecture of WSN based Vehicle Speed Measurement System is presented in this paper from Telematics Sensor Network(TSN) to Management System. To verify the feasibility of the system, we implemented the vehicle speed measurement system and evaluated the accuracy of velocity measured by the system in our testbed, an old highway located near Kyungbu highway. The system performed over 95% of accuracy at 80kmph from the measurement. In addition, the battery life time of the sensor node was evaluated by simulation analysis with real measured current consumption profiles. Assuming the maximum average daily traffic in 2005, the battery life time is expected to be over 1.6 year from the simulation result.

• 한국도로학회논문집
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• 제11권1호
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• pp.59-67
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• 2009

센싱 기술의 발달로 다양한 종류의 매체를 이용한 우수한 차량 검지장비들이 개발되고 있는 요즘, 간단한 구조의 저가형 검지장비 또한 적은 예산으로 여러 곳에 설치할 수 있다는 장점 때문에 지속적인 연구가 이루어지고 있다. 본 연구에서는 저가형 차량 검지장비로서 센서를 사선으로 설치하여 좌우 및 전후 바퀴의 통과시간 간격과 차량의 윤거값을 적용하여 차량속도를 추정하는 방법을 제안하였다. 출고된 차량의 제원조사에서 얻어진 대표 윤거값을 축거와 뒤윤거의 비율에 따라 소형과 대형 차량으로 구분하여 적용하므로 기존의 연구보다 정확한 속도추정이 가능하도록 개선하였다. 특히, 소형과 대형차량을 구분하는 파라미터를 통하여 조사지점의 차종구성 비율을 고려한 정확도 보정이 가능하다. 간단하고 저가로 개발된 본 연구의 사선형 센서를 이용한 검지장비는 적은 비용으로 교통상황을 설명하는데 효율적으로 활용될 것으로 기대된다.

• 한국산학기술학회논문지
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• 제9권4호
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• pp.1030-1038
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• 2008

교통량조사 방법은 루프검지기와 피에조센서를 주로 많이 사용하여 차량의 숫자만을 파악하여 교통주기를 계산하는 방법을 사용하나 교통량을 파악하는 방법은 단순한 교통량에만 국한되는 것이 아니라 다중교통특성인 진입로의 길이, 도로의 폭, 보행자의 수, 통과차량수, 지체차량수 등 관련되는 교통대안을 총 망라하여 새로운 교통량인 혼잡도라는 개념을 대표대안으로 선정하면 바로 교통주기에 적용할 수 있다. 본 논문에서는 서로 관련성이 없는 교통대안들을 AHP 방법을 사용하여 교통주기 계산에 즉시 사용할 수 있는 공통 분모인 새로운 교통대안을 찾아내는 알고리즘을 개발하고 이를 새로운 교통량 개념인 혼잡도라는 교통량을 찾아내는 퍼지센서 알고리즘을 구성하는데 적용한다. 시뮬레이션을 통해 타 교통제어방법과 비교하여 지체차량시간이 줄어듬을 보여준다.