• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.754-761
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• 2008

As the automobile industry and technologies are developed, driver's tend to more concern about service matters than mechanical matters. For this reason, interests about recognition of human knowledge and emotion to make safe and convenient driving environment for driver are increasing more and more. recognition of human knowledge and emotion are emotion engineering technology which has been studied since the late 1980s to provide people with human-friendly services. Emotion engineering technology analyzes people's emotion through their faces, voices and gestures, so if we use this technology for automobile, we can supply drivels with various kinds of service for each driver's situation and help them drive safely. Furthermore, we can prevent accidents which are caused by careless driving or dozing off while driving by recognizing driver's gestures. the purpose of this paper is to develop a system which can recognize states of driver's emotion and attention for safe driving. First of all, we detect a signals of driver's emotion by using bio-motion signals, sleepiness and attention, and then we build several types of databases. by analyzing this databases, we find some special features about drivers' emotion, sleepiness and attention, and fuse the results through Multi-Modal method so that it is possible to develop the system.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.335-343
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• 2024

Real-time target signal processing techniques for FMCW LiDAR are described in this paper. FMCW LiDAR is gaining attention as the next-generation LiDAR for self-driving cars because of its detection robustness even in adverse environmental conditions such as rain, snow and fog etc. in addition to its long range measurement capability. The hardware architecture which is required for high-speed data acquisition, data transfer, and parallel signal processing for frequency-domain signal processing is described in this article. Fourier transformation of the acquired time-domain signal is implemented on FPGA in real time. The paper also details the C-FAR algorithm for ensuring robust target detection from the transformed target spectrum. This paper elaborates on enhancing frequency measurement resolution from the target spectrum and converting them into range and velocity data. The 3D image was generated and displayed using the 2D scanner position and target distance data. Real-time target signal processing and high-resolution image acquisition capability of FMCW LiDAR by using the proposed parallel signal processing algorithms based on FPGA architecture are verified in this paper.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5416-5426
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• 2012

This study uses the algorithm which estimates the magnetic flux using different models in the low speed driving area and the high speed driving area by the voltage-current model synthesis magnetic flux Estimator and, from this result, estimates the magnetic flux angle to achieve the stable speed control through all the areas from the low speed to the high speed drive. In particular, the current change and the magnetic flux change under variable load were estimated in real time in the low speed area and this made the control characteristic improved in the low speed area. According to this, even under variable load, the more stable simulation and experiment could have been completed using PI current controller and PI flux controller in all the areas. As a result, the outstanding speed control characteristic has been achieved.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.4
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• pp.304-310
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• 2017

In this paper, we propose the architecture of an IPM based lane detector for autonomous vehicles to detect and control the driving route along the curved lane. In the IPM image, we divide the area into two fields, Far/Near Field, and the lane candidate region is detected using the Hough transform to perform the matching for the curved lane. In autonomous vehicles, various algorithms must be embedded in the system. To reduce the system resources, we proposed a method to minimize the number of memory accesses to the image and various parameters on the external memory. The proposed circuit has 96% lane recognition rate and occupies 16% LUT, 5.9% FF and 29% BRAM in Xilinx XC7Z020. It processes Full-HD image at a rate of 42 fps at a 100 MHz operating clock.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1903-1909
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• 2011

This paper presents the development of a core module for integrating data from vehicle by the convergence technology of mobile telematics and black-box. This emerging technology can be referred to as Black-box in Mobile (BIM). For the development of BIM, sensors and cameras were realized in a driving robot. Relevant hardware implementation was achieved to verify the functionality of BIM. The transmitted signal from the driving robot was confirmed in an Android-based portable device. Existing Black-boxes were mostly developed by major transportation companies and focused only on storing data. The proposed BIM offers not only data storage but also easy-to-use real-time monitoring while in motion. In addition, the vehicle can be monitored on parking through shock sensors. This development is considered commercially viable as it is achieved via software implementation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.595-603
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• 2015

With the advances of the big-data process technology, acquiring the real-time information from the massive image data taken by a mobile device inside a vehicle will be possible in the near future. Among the information that can be found around the vehicle, the route information is needed for safe driving. In this study, the automatic extraction of route information from the road sign imagery was dealt with. The scope of the route information in this study included the route number, route type, and their relationship with the driving direction. For the recognition of the route number, the modified Tesseract OCR (Optical Character Recognition) engine was used after extracting the rectangular-road-sign area with the Freeman chain code tracing algorithm. The route types (expressway, highway, rural highway, and municipal road) are recognized using the proposed algorithms, which are acquired from colour space analysis. Those road signs provide information about the route number as well as the roads that may be encountered along the way. In this study, such information was called “OTW (on the way)” or “TTW (to the way)” which between the two should be indicated is determined using direction information. Finally, the route number is matched with the direction information. Experiments are carried out with the road sign imagery taken inside a car. As a result, route numbers, route number type, OTW or TTW are successfully recognized, however some errors occurred in the process of matching TTW number with the direction.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.6
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• pp.1-8
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• 2016

As demand for paper cups markedly increases, this has brought about a requirement to develop fast paper cup forming machines. However, the fast manufacturing speed of these machines causes faults to occur more frequently in the final product. To reduce the possibility of producing faulty products, it is necessary to develop technologies to monitor the manufacturing process and diagnose the machine status. In this research, we selected the main driving axis of the forming machine for fault diagnosis. We searched the states of rotational elements related to the driving axis and suggested a fault diagnostic system based on spectrum analysis consisting of a real-time data acquisition device, accelerometers, and a diagnosis algorithm. To evaluate the developed fault diagnostic system, we performed experiments using a test station which resembles the actual paper cup forming machine. As a result, we were able to confirm that the proposed system was sufficiently feasible to diagnose any abnormalities in the operation of the paper cup forming machine.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1950-1958
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• 2016

Today, technique for precisely positioning vehicles is very important in C-ITS(Cooperative Intelligent Transport System), Self-Driving Car and other information technology relating to transportation. Though the most popular technology for vehicle positioning is the GPS, its accuracy is not reliable because of large delay caused by multipath effect, which is very bad for realtime traffic application. Therefore, in this paper, we proposed the Vision-Based High Accuracy Vehicle Positioning Technology. At the first step of proposed algorithm, the ROI is set up for road area and the vehicles detection. Then, center and four corners points of found vehicles on the road are determined. Lastly, these points are converted into aerial view map using homography matrix. By analyzing performance of algorithm, we find out that this technique has high accuracy with average error of result is less than about 20cm and the maximum value is not exceed 44.72cm. In addition, it is confirmed that the process of this algorithm is fast enough for real-time positioning at the $22-25_{FPS}$.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.7-16
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• 2009

Provision of advanced warning information is one of the useful countermeasures to prevent traffic accidents. Analysis of user's preference for any information contents would be a backbone in designing more effective warning information systems. This study aimed at deriving more comprehensive and valuable warning information that leads to user's safer driving by conducting a questionnaire survey. In total, 258 people including various age groups and driving experiences participated in the survey. Preferable warning information contents were identified by this study. It is expected that the results would be useful data for providing warning information to drivers.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.12
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• pp.123-129
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• 2014

In accordance with the development of various convergence devices, cameras are being used in many types of the systems such as security system, driver assistance device and so on, and a lot of people are exposed to these system. Therefore the system should be able to recognize the human behavior and support some useful functions with the information that is obtained from detected human behavior. In this paper we use a machine learning approach based on 2D image and propose the human behavior pattern recognition methods. The proposed methods can provide valuable information to support some useful function to user based on the recognized human behavior. First proposed one is "phone call behavior" recognition. If a camera of the black box, which is focused on driver in a car, recognize phone call pose, it can give a warning to driver for safe driving. The second one is "looking ahead" recognition for driving safety where we propose the decision rule and method to decide whether the driver is looking ahead or not. This paper also shows usefulness of proposed recognition methods with some experiment results in real time.