• Journal of Korean Society of Transportation
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• v.21 no.2
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• pp.63-70
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• 2003

Real-time information on vehicle queue at intersections is essential for optimal traffic signal control, which is substantial part of Intelligent Transport Systems (ITS). Computer vision is also potentially an important element in the foundation of integrated traffic surveillance and control systems. The objective of this research is to propose a method for detecting an exact queue lengths at signalized intersections using image processing techniques and a neural network model Fuzzy ARTMAP, which is a supervised and self-organizing system and claimed to be more powerful than many expert systems, genetic algorithms. and other neural network models like Backpropagation, is used for recognizing different patterns that come from complicated real scenes of a car park. The experiments have been done with the traffic scene images at intersections and the results show that the method proposed in the paper could be efficient for the noise, shadow, partial occlusion and perspective problems which are inevitable in the real world images.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5135-5142
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• 2011

A flexible mechanism is proposed in this paper to improve the dynamic response performance of a traffic flow control system in an urban area. The roads, vehicles, and traffic control systems are all modeled as intelligent systems, wherein a wireless communication network is used as the medium of communication between the vehicles and the roads. The necessary sensor networks are installed in the roads and on the roadside upon which reinforcement learning is adopted as the core algorithm for this mechanism. A traffic policy can be planned online according to the updated situations on the roads, based on all the information from the vehicles and the roads. This improves the flexibility of traffic flow and offers a much more efficient use of the roads over a traditional traffic control system. The optimum intersection signals can be learned automatically online. An intersection control system is studied as an example of the mechanism using Q-learning based algorithm, and simulation results showed that the proposed mechanism can improve the traffic efficiency and the waiting time at the signal light by more than 30% in various conditions compare to the traditional signaling system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.4
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• pp.25-35
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• 2008

Variable Message Sign(VMS) is one of the subsystem of Intelligent Transportation Systems (ITS), which is useful for providing real-time information on weather, traffic and highway conditions. However, there are various situations such as incidents/accidents, constructions, special events, etc., which would be occurred on segments, it is unable to control traffic with only the VMS. Thus, it is essential to use of PVMS(Portable Variable Message Signs), which can move to the location needed traffic control and provide more active traffic information than VMS. This study developed a legibility distance model for PVMS messages using in-vehicle Differential Global Positioning Data(DGPS). Traffic conditions, drivers' characteristics, weather conditions and characteristics of PVMS message were investigated for establishing the legibility model based on multiple linear regression analysis. The factors such as height of PVMS characters, spot speed, age, gender and day and night were identified as dominants affecting the variation of legibility distances. It is expected that the proposed model would play a significant role in designing PVMS messages for providing more effective real-time traffic information.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.4
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• pp.44-55
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• 2013

Intelligent transportation systems allow us to have valuable opportunities for collecting reliable wide-area coverage traffic and weather data. Significant efforts have been made in many countries to apply these data. This study identifies the critical points for classifying rain intensity by analyzing the relationship between rainfall and the amount of speed reduction. Then, traffic prediction performance by rain intensity level is evaluated using relative errors. The results show that critical points are 0.4mm/5min and 0.8mm/5min for classifying rain intensity (slight, moderate, and heavy rain). The best prediction performance is observable when previous five-block speed data is used as inputs under normal weather conditions. On the other hand, previous two or three-block speed data is used as inputs under rainy weather conditions. The outcomes of this study support the development of more reliable traffic information for providing advanced traffic information service.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.423-430
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• 2019

The convergence of the automotive industry and the ICT technology can be broadly divided into the commercial service sector and the Cooperative-ITS (C-ITS) service sector. The C-ITS service sector is using V2X communication technology as a field that aims to provide safer transportation, more green and efficient transportation, and more predictable and productive mobility. The recent convergence of self-driving cars and connected cars requires high data rates, low transmission delays, and low transmission error rates. Interest in comparison of performance between WAVE and C-V2X (LTE-V2X, 5G-V2X) has been amplified and application services by communication technology are being studied. In this paper, we design the application performance evaluation method of Hybrid V2X communication system and confirm that the decrease of packet error rate (PER) performance is caused by the increase of communication distance, not the vehicle speed.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.109-116
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• 2020

With the advent of high-speed railways, railways are one of the most frequently used means of transportation at home and abroad. In addition, in terms of environment, carbon dioxide emissions are lower and energy efficiency is higher than other transportation. As the interest in railways increases, the issue related to railway safety is one of the important concerns. Among them, visual abnormalities occur when various obstacles such as animals and people suddenly appear in front of the railroad. To prevent these accidents, detecting rail tracks is one of the areas that must basically be detected. Images can be collected through cameras installed on railways, and the method of detecting railway rails has a traditional method and a method using deep learning algorithm. The traditional method is difficult to detect accurately due to the various noise around the rail, and using the deep learning algorithm, it can detect accurately, and it combines the two algorithms to detect the exact rail. The proposed algorithm determines the accuracy of railway rail detection based on the data collected.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.8
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• pp.41-47
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• 2017

With the introduction of new technologies, ground weapons have led to the development of artificial intelligence and the attention of major developed countries. In this study, CFD was performed through the BLU-103 model to obtain aerodynamic data for aircraft that are subjected to rotational motion. To simulate the steady-state of a rotating body, the body was fixed and the principle of rotating the body by rotating the surrounding air was used. In order to examine the aerodynamic feasibility of the rotating aircraft, the analysis was carried out at intervals of $30^{\circ}$ angle from $0^{\circ}$ to $90^{\circ}$ for the simple shape and the side slip angle. It was confirmed that the drag coefficient for the simple model satisfies the quantitative results of 1.0 ~ 1.2 through CD presented in "Drag Book". The aerodynamic data was constructed by applying the valid input verified through the simple type analysis conditions to the actual shape, and the tendency was analyzed. The analysis confirmed that CX, CZ and CY increase not only in the simple model but also in the rotation of the actual model. Especially, the influence of CZ was judged to have contributed to the flight.

• Journal of Advanced Navigation Technology
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• v.23 no.6
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• pp.515-521
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• 2019

The C-ITS requires the lane level positioning of the vehicle in the land transportation environment, and it is most effective to utilize the global navigation satellite system. In the precision positioning system based on satellite navigation, the evaluation of dynamic environment of lane level positioning performance should be accompanied and the evaluation system configuration should be preceded. In addition, performance analysis must be performed according to various environments that change according to traffic or road conditions in a dynamic environment. In this paper, we describe with the performance of traffic and road environment through the evaluation system of lane positioning precision positioning user system based on satellite navigation system. The numerical performance evaluation was carried out based on the data collected by carrying out the actual driving. The performance evaluation by the actual driving trajectory and driving image comparison was performed to derive and analyse evaluation results of positioning performance according to driving condition.

• Korean Security Journal
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• no.39
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• pp.269-294
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• 2014

Korea is concerned with information security industry due to recent leak-out private information of 3 card companies. Executives are aware of damage from breach of security such as personal data spill, is more dangerous than any other financial risks. The information security industry, which was limited in physical security and network security formerly, is evolving into convergence security of public and facility security industry. The field of interest has also been changed into security of smart phone and intelligence image recently, from firewall or Anti-virus. The convergence security is originally about access control of facility, but recently its demand has been increased mostly by public institutions and major companies. The scope of the industry also varies from finance, education, distribution, national defense, medical care to automobile industry. The market of convergence security has been expanded and new various products and services of security of intelligent vehicle, 'U' healthcare, finance, smart grid and key industries are also developed. It is required to create and enhance of new curriculum and cultivate human resources for the development of knowledge information security industry. Raising standard of education and security consciousness of the nation is also necessary to strengthen the global competitiveness.

• Journal of KIISE:Software and Applications
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• v.34 no.3
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• pp.255-265
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• 2007

In this paper, we propose a new illumination-robust drowsy driver monitoring system with single CCD(Charge Coupled Device) camera for intelligent vehicle in the day and night. For this system that is monitoring driver's eyes during a driving, the eye detection and the measure of eyelid movement are the important preprocesses. Therefore, we propose efficient illumination compensation algorithm to improve the performance of eye detection and also eyelid movement measuring method for efficient drowsy detection in various illumination. For real-time application, Cascaded SVM (Cascaded Support Vector Machine) is applied as an efficient eye verification method in this system. Furthermore, in order to estimate the performance of the proposed algorithm, we collect video data about drivers under various illuminations in the day and night. Finally, we acquired average eye detection rate of over 98% about these own data, and PERCLOS(The percentage of eye-closed time during a period) are represented as drowsy detection results of the proposed system for the collected video data.