• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.598-604
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• 2009

This paper proposes a vehicle detector with an anisotropic magnetoresistive (AMR) sensor and addresses experimental results to show the detector's performance. The detector consists of an AMR sensor and mechanical and electronic apparatuses. The AMR sensor, composed of four magnetoresistors, senses disturbance of the earth's magnetic field caused by a vehicle moving over the sensor and then produces an output indicative of the moving vehicle. This paper verifies performance of the detector on the basis of experimental results obtained from the field tests carried under the two traffic conditions on local highways in Korea. First, I show the vehicle counting performance on a low speed congested highway by comparing the vehicle counts measured by the detector with the exact counts. Second, both vehicle counts and average speeds calculated from the measured point-occupancy on another continuously free running highway are compared with the reference values obtained from a loop detector which has two independent loop coils, where I have used several performance indices including mean absolute percentage error (MAPE) to show the performance consistency between the two types of detectors.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.600-605
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• 2011

This paper shows field test and evaluation results for a wireless vehicle detector with anisotropic magneto-resistive (AMR) sensors. 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 fixed on a board, with constant distance. To test and evaluate the accuracy of the detector in real traffic situations, the detector was installed on a local highway and vehicle speeds and volumes were measured both in a free running and a highly congested traffic. The measurements from the detector are compared with the reference measurements obtained from a traffic camera with the Mean Absolute Percentage Errors (MAPE), which has proved the usefulness of the detector in the field.

• Journal of Electrical Engineering and Technology
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• v.11 no.5
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• pp.1190-1194
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• 2016

• Journal of Sensor Science and Technology
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• v.10 no.2
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• pp.134-141
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• 2001

This paper describes a method to steer an autonomous electric vehicle using magnetic fields. Magnets are embeded along the center of the road and a magneto-resistive sensor is mounted beneath the front bumper of the vehicle. As the vehicle moves along the road neural network controller controls the vehicle using measured magnetic field variation. Based on a single magnets modeling equation, we analyzed three dimensional magnetic field distributions of embeded magnets in series on the center of the road and performed a computer simulation using this results. In simulation study, straight and curved road was configured. The steering controller for the vehicle was designed using neural network and experiment was performed on the real embeded magnets using real autonomous electric vehicle. At the experiment we compensated the earth's magnetic fields and showed a good result driving an autonomous vehicle using proposed method.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.2
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• pp.79-86
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• 2020

This study examines the power generation characteristics of a vehicle rooftop photovoltaic module with urban driving conditions. Actual test data with an illuminometer and a thermometer were used to analyze the power generation characteristics of the vehicle rooftop photovoltaic module. In addition, the power generation characteristics were analyzed in terms of urban driving conditions, irradiance, ambient temperature, and photovoltaic module temperature. This study also analyzes the power generation characteristics of the vehicle rooftop photovoltaic module with urban driving conditions through a wavelet transform filtering method. The power generation characteristics of the vehicle rooftop photovoltaic module with urban driving conditions depend on the change in irradiance rather than that in photovoltaic module temperature.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.7
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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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.2
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• pp.133-139
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• 2013

This paper proposes a vision-based indoor localization method for autonomous vehicles. A single upward-facing digital camera was mounted on an autonomous vehicle and used as a vision sensor to identify artificial landmarks and any natural corner features. An interest point detector was used to find the natural features. Using an optical flow detection algorithm, information related to the direction and vehicle translation was defined. This information was used to track the vehicle movements. Random noise related to uneven light disrupted the calculation of the vehicle translation. Thus, to estimate the vehicle translation, a Kalman filter was used to calculate the vehicle position. These algorithms were tested on a vehicle in a real environment. The image processing method could recognize the landmarks precisely, while the Kalman filter algorithm could estimate the vehicle's position accurately. The experimental results confirmed that the proposed approaches can be implemented in practical situations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.7
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• pp.1092-1099
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• 2017

This paper proposes a novel way of vehicle detection and classification based on image features. There are two main processes in the proposed system, which are database construction and vehicle classification processes. In the database construction, there is a tight censorship for choosing appropriate images of the training set under the rigorous standard. These images are trained using Haar features for vehicle detection and histogram of oriented gradients extraction for vehicle classification based on the support vector machine. Additionally, in the vehicle detection and classification processes, the region of interest is reset using a number plate to reduce complexity. In the experimental results, the proposed system had the accuracy of 0.9776 and the $F_1$ score of 0.9327 for vehicle classification.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.119-124
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• 1998

This paper proposes a new repulsive-Maglev vehicle in which a vertical type PM linear synchronous motor (LSM) can levitate and propel simultaneously, independently of the vehicle speeds. A compact control method is developed which is based on the concept of controlling individually the levitation system by armature-current and the propulsion system by mechanical load-angle. The levitation-motion control experiments have carried out successfully together with positioning at standstill. The pitching motion has been compensated for very well by using the zero-phase-current control method proposed here.

• Journal of Ocean Engineering and Technology
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• v.32 no.2
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• pp.131-137
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• 2018

In this paper, we propose an adaptive backstepping controller to control the exact position and orientation of a remotely operated underwater vehicle with parametric model uncertainty. To further improve the angular velocity control precision of each thruster, a phase locked loop (PLL) controller has been added to the backstepping controller. A comparison of two backstepping controllers with and without the PLL control loop has been performed using simulations and experiments. The test results showed that the tracking performance could be improved by using the PLL control loop in the proposed adaptive backstepping controller.