• International Journal of Highway Engineering
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• v.11 no.1
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• pp.59-67
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• 2009

With the development of high-cost vehicle detectors, low-cost detectors have also been studied due to the advantage that more detectors are provided within limited budgets. This study proposed a method to estimate vehicle speeds using vehicles' track data from auto manufacturers and time stamps obtained when vehicles' tires pass an inclined sensor (here, a tape switch sensor). In speed estimation, small vehicles and large vehicles is distinguished according to the ratio of time stamps for a wheelbase and a rear track obtained from a tape switch sensor. In particular, speed estimation can be adjusted through a parameter to determine vehicles' size so as to take into account location properties such as vehicles' classification ratio. The low-cost vehicle detector with an inclined sensor proposed in this study is expected to be widely utilized to monitor traffic conditions thanks to low cost.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.1-9
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• 2020

A smart factory is a key industrial application introduced by the 4^th industrial revolution. The automatic guided vehicle (AGV) is one of the technology realizing smart factory, but the development cost is high due to its early stage of technology. Although developing a low-cost AGV requires a lot of data, it has limited data acquisition capability because of the limited storage and the AGV movement. Hence, we propose a development environment using Bluetooth to collect data and design a lane detector. The proposed lane detector shows a high lane detection ratio regardless of light variation and a shade.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.4
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• pp.564-581
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• 1999

This paper introduces a new, small, low cost, robust and quick replaceable pavement-based vehicle detector using CW radar, magnetometer, and UHF small antennal techniques. The detector has been developed for a replacement of loop detectors having wide surface areas, for a more accurate operation under all weather conditions, and for no algorithmic change of the existing traffic information system. The detected vehicle information is sent by a small helical antenna embedded in a plastic material and received by a 5/8 $\lambda$ long GP antenna for signal processing. In a relatively good weather condition, the detector operates at 24 GHz. But in a heavy rain condition, magnetometer is activated by automatic switching.

• Journal of Information Processing Systems
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• v.1 no.1 s.1
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• pp.27-31
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• 2005

Vehicle detector system based on image processing technology is a significant domain of ITS (Intelligent Transportation System) applications due to its advantages such as low installation cost and it does not obstruct traffic during the installation of vehicle detection systems on the road[1]. In this paper, we propose architecture for vehicle detection by using image processing. The architecture consists of two main parts such as an image processing part, using high speed FPGA, decision and calculation part using CPU. The CPU part takes care of total system control and synthetic decision of vehicle detection. The FPGA part assumes charge of input and output image using video encoder and decoder, image classification and image memory control.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2483-2503
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• 2016

Traffic congestion is a severe problem in many modern cities around the world. Real-time and accurate traffic congestion identification can provide the advanced traffic management systems with a reliable basis to take measurements. The most used data sources for traffic congestion are loop detector, GPS data, and video surveillance. Video based traffic monitoring systems have gained much attention due to their enormous advantages, such as low cost, flexibility to redesign the system and providing a rich information source for human understanding. In general, most existing video based systems for monitoring road traffic rely on stationary cameras and multiple vehicle tracking method. However, most commonly used multiple vehicle tracking methods are lack of effective track initiation schemes. Based on the motion of the vehicle usually obeys constant velocity model, a novel vehicle recognition method is proposed. The state of recognized vehicle is sent to the GM-PHD filter as birth target. In this way, we relieve the insensitive of GM-PHD filter for new entering vehicle. Combining with the advanced vehicle detection and data association techniques, this multiple vehicle tracking method is used to identify traffic congestion. It can be implemented in real-time with high accuracy and robustness. The advantages of our proposed method are validated on four real traffic data.

• Journal of IKEEE
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• v.18 no.4
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• pp.471-477
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• 2014

In this paper, we propose a low-cost license plate recognition system based on smart cam system using Android. The proposed system consists of a portable device and server. Potable device Hardware consists of ARM Cortex-A9 (S5PV210) processor control unit, a power supply device, wired and wireless communication, input/output unit. We develope Linux kernel and dedicated device driver for WiFi module and camera. The license plate recognition algorithm is consisted of setting candidate plates areas with canny edge detector, extracting license plate number with Labeling, recognizing with template matching, etc. The number that is recognized by the device is transmitted to the remote server via the user mobile phone, and the server re-transfer the vehicle information in the database to the portable device. To verify the utility of the proposed system, user photographs the license plate of any vehicle in the natural environment. Confirming the recognition result, the recognition rate was 95%. The proposed system was suitable for low cost portable license plate recognition device, it enabled the stability of the system when used long time by using the Android operating system.