• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.11
• /
• pp.1879-1886
• /
• 2016

In this paper, we propose a real-time recognition algorithm of lanes, stop lines and speed bumps on roads for autonomous vehicles. First, we generate a top-view using the image transmitted from a camera that is installed to see the front of a vehicle. To speed up the processing, we simplify the mapping algorithm in constructing a top-view wherein the region of interest (ROI) is concerned. The features of lanes, stop lines and speed bumps, which are composed of lines, are searched in the edge image of the top-view, then followed by labeling and clustering specialized to detect straight lines. The width of lines, distances from the center of a vehicle, and curvature of each cluster are considered to select final candidates. We verify the proposed algorithm on real roads using the commercial car (KIA K7) which is converted into an autonomous vehicle.

• Journal of Electrical Engineering and Technology
• /
• v.11 no.3
• /
• pp.715-723
• /
• 2016

This paper proposes a design of optimal PI(D) controller for brushless DC (BLDC) motor speed control by the particle swarm optimization (PSO), one of the powerful metaheuristic optimization search techniques. The proposed control system is implemented on the TMS320F28335 DSP board interfacing to MATLAB/SIMULINK. With Back EMF detection, the proposed system is considered as a class of sensorless control. This scheme leads to the speed adjustment of the BLDC motor by PWM. In this work, the BLDC motor of 100 watt is conducted to investigate the control performance. As results, it was found that the speed response of BLDC motor can be regulated at the operating speed of 800 and 1200 rpm in both no load and full load conditions. Very satisfactory responses of the BLDC system can be successfully achieved by the proposed control structure and PSO-based design approach.

• Aerospace Engineering and Technology
• /
• v.8 no.2
• /
• pp.92-97
• /
• 2009

Two conventional speed detection methods (Elapsed-time method and Pulse-count method) are analyzed and compared for a high speed motor with digital tacho pulse with non-uniformity. In general, the elapsed-time method usually has better performance than a pulse-count method in case sufficiently high speed clock is used to measure the time difference. But if a tacho pulse non-uniformity exists in the reaction wheel - most of reaction wheel has a certain amount of non-uniformity - the accuracy of the elapsed-time method is degraded significantly. Thus the performance degradation is analyzed with respect to the level of non-uniformity of tacho pulse distribution and an allowable bound is suggested.

• Journal of Korean Society of Transportation
• /
• v.24 no.2 s.88
• /
• pp.127-137
• /
• 2006

This Paper Presents a novel incident detection method for using the speed-density difference between detectors. When a incident is happened the downstream traffic condition is mostly lower speed and higher density and the upstream is higher speed and lower density In respect of such characteristics, we can suggest a method for detecting an incident based on the speed-density information provided from detectors. The incident detection method is tested by using the accident data collected from the Cheonan-Nonsan Highway. The results show that suck an incident detection method can analyze the position of accident by comparing the speed-density difference between detectors. The work described in this paper is only at on early stage, in the sense that there are several areas to be further investigated in application of this method. such as setting a critical value for judging the incident. a level of accident wave, a varying Pattern between the incident locations and detectors, etc.

• Proceedings of the IEEK Conference
• /
• 2009.05a
• /
• pp.222-224
• /
• 2009

This paper presents an algorithm that extracts road lane's specific information by using HSI color information and performance enhancement of lane detection base on vision processing of drive assist. As a preprocessing for high speed lane detection, the optimal extraction of region of interest for lane boundary(ROI-LB) can be processed to reduction of detection region in which high speed processing is enabled and it also increases reliabilities by deleting edges those are misrecognized. Road lane is extracted with simultaneous processing of noise reduction and edge enhancement using the Laplacian filter, the reliability of feature extraction can be increased for various road lane patterns. Since noise can be removed by using saturation and brightness of HSI color model. Also it searches for the road lane's color information and extracts characteristics. The real road experimental results are presented to evaluate the effectiveness of the proposed method.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.67 no.1
• /
• pp.42-46
• /
• 2018

In this paper, we propose fast object detection method of the cars by applying YOLOv2(You Only Look Once version 2) and UAVs (Unmanned Aerial Vehicles) while on the highway. We operated Darknet, OpenCV, CUDA and Deep Learning Server(SDX-4185) for our simulation environment. YOLOv2 is recently developed fast object detection algorithm that can detect various scale objects as fast speed. YOLOv2 convolution network algorithm allows to calculate probability by one pass evaluation and predicts location of each cars, because object detection process has simple single network. In our result, we could find cars on the highway area as fast speed and we could apply to the real time.

• Proceedings of the IEEK Conference
• /
• 2006.06a
• /
• pp.305-306
• /
• 2006

To avoid the large scale of damage when fire occurs in the tunnel, it is necessary to have a system to minimize the damage, and early discovery of the problem. In this paper, we have proposed algorithm using the image processing, which is the high-speed detection for the occurrence of fire or smoke in the tunnel. The fire detection is different to the forest fire detection as there are elements such as car and tunnel lightings and other variety of elements different from the forest environment. Therefore, an indigenous algorithm should be developed.The two algorithms proposed in this paper, are able to complement with each other and also they can detect the exact position, at the earlier stay of detection. In addition, by comparing properties of each algorithm throughout this experiment, we have proved the propriety of algorithm.

• Journal of the Society of Disaster Information
• /
• v.19 no.3
• /
• pp.608-623
• /
• 2023

Purpose: Recently, the number of logistics warehouses has been on the rise. In addition, as the number of such logistics warehouses increases, number of fire accidents also increases every year, increasing the importance of preventing fires in large logistics warehouses. Method: investigated aspirating smoke detectors that are emerging as adaptive fire detectors in logistics warehouses. Then, through fire simulation (FDS), logistics warehouse modeling was conducted to compare and analyze the detection speed of general smoke detectors and aspirating smoke detectors according to four stages of fire growth and three locations of fire in the logistics warehouse. Result: Growth speed in Slow-class fires and Mediumclass fires, the detection speed of aspirating smoke detectors was faster regardless of the location of the fire. However, in Fast-class fires and Ultra-Fast-class fires, it was confirmed that the detection speed of general smoke detectors was faster depending on the location of the fire. Conclusion: It was confirmed that the detection performance of the aspirating smoke detector decreased as the fire growth speed increased and the location of the fire occurred further than the receiver of the aspirating smoke detector. Therefore, even if an aspirating smoke detector is installed in a warehouse that stores combustibles with high fire growth rates, it is judged that an additional smoke detector is attached far away from the receiver of the general smoke detector to increase fire safety.

• Journal of Advanced Marine Engineering and Technology
• /
• v.25 no.2
• /
• pp.375-382
• /
• 2001

In this study, an adapted Turbo Coding Algorithm for reducing communication error of a fire detection system for marine vessels, especially image transmission via power lone. Because it is necessary that this system communicate larger and faster than previous method, this study carried out enhancement a decoding speed by adaptation CRC with Turbo Code Algorithm, improvement of metric method, and reduction of decoding delay by using of Center-to-Top method. And the results are as follows: (1) Confirmed that a Turbo Code is so useful methods for reducing communication error in lots of noise environments. (2)Proposed technology in this study speed increasing method of Turbo Coding Algorithm proves 2 times faster than normal Turbo Code and communication error reducing as well in the board made by VHDL software & chips ALTERA company.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.4 no.5
• /
• pp.90-99
• /
• 1996

To keep up with the regulation of OBD II(on board diagnostics II), many detection methods for engine misfire have been developed. Among them, the method of using the crankshaft speed fluctuation is the most noticeable in the point of view of lower cost and easier installation than any others. On the basis of the results obtained from the previous engine-dynamometer test, the integrating torque index (ITI) has been introduced. In this research, the instrumental and the interfacing systems to engine control unit(ECU) are developed for the vehicle test. Therefore, the vehicle and chassis-dynamometer test can be carried out in addition to the rough road test. From this test, the previousproposed method proved that it can be applied to the real vehicle.