• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.9
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• pp.578-589
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• 2014

In this paper, we introduce the concept of cyber-physical intersection systems (CPIS) which interconnects roadside units (RSU) located at the intersection, on-board units (OBU) of moving vehicles, and the smartphone apps, named the Smartphone Agent (SA). At the pedestrian mode of the SA, the connectivity management schemes, such as a location update and a handover control algorithm, are proposed to better support the CPIS services while minimizing the power consumption of the pedestrian's smartphone. We develop a real prototype of the CPIS, including RSU, OBU, and the SA. Based on the numerical results collected from a pedestrian moving around the Pusan National University campus, we validate that the proposed connectivity management schemes can improve not only the power efficiency of the pedestrian's smartphone, but also the quality of the CPIS services.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.13-19
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• 2011

In this paper, a visual surveillance system using SOPC based NIOS II embedded processor and C2H compiler was implemented. In this system, the IP is constructed by C2H compiler for the output of the camera images, image processing, serial communication and network communication, then, it is implemented to effectively control each IP based on the SOPC and the NIOS II embedded processor. And, an algorithm which updates the background images for high speed and robust detection of the moving objects is proposed using the Adaptive Gaussian Mixture Model(AGMM). In results, it can detecte the moving objects(pedestrians and vehicles) under day-time and night-time. It is confirmed that the proposed AGMM algorithm has better performance than the Adaptive Threshold Method(ATM) and the Gaussian Mixture Model(GMM) from our experiments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.4
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• pp.104-111
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• 2012

It is advantageous to avoid the handover to cell whose dwell time is short or can be ignored in terms of service continuity and average throughput. This paper proposes the handover scheme that is suitable for vehicle in order to improve the wireless Internet service quality. In the proposed scheme, the handover process continues to be learned before being modeled to Discrete-Time Markov Chain (DTMC). This modeling reduces the handover frequency by preventing the handover to cell that could provide service sufficiently to passenger even when vehicle passed through the cell but there was no need to perform handover. In order to verify the proposed scheme, we observed the average number of handovers, the average RSSI and the average throughput on various moving paths that vehicle moved in the given urban environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.936-942
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• 2022

While indoor vehicle navigation is an essential component in large-scale parking garages of major cities, technical limitations and challenging propagation environments considerably degrade the accuracy of existing localization techniques. This paper proposes a proximity detection scheme using low-cost beacons where a handheld mobile device within a moving vehicle autonomously detects its approximate position and moving direction by only observing Received Signal Strength (RSS) values of beacon signals. The proposed approach essentially exploits the differential RSS technique of multi-directional beams to reduce the impact of the environment, vehicle, and mobile device. A low-cost multi-directional beacon prototype is developed using Bluetooth technology. The localization performance is evaluated using 96 beacons in an underground parking garage within an area of 394.8m×304.3m. Experimental results show that the 90th percentile of the average proximity detection error is 0.8m. Furthermore, our proposed scheme provides robust proximity detection performance with various vehicles and mobile devices.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.93-101
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• 2023

In this paper, we propose a method of creating a 3D bounding box for an object using a vanishing point to increase the accuracy of object recognition in an image when recognizing an traffic object using a video camera. Recently, when vehicles captured by a traffic video camera is to be detected using artificial intelligence, this 3D bounding box generation algorithm is applied. The vertical vanishing point (VP1) and horizontal vanishing point (VP2) are derived by analyzing the camera installation angle and the direction of the image captured by the camera, and based on this, the moving object in the video subject to analysis is specified. If this algorithm is applied, it is easy to detect object information such as the location, type, and size of the detected object, and when applied to a moving type such as a car, it is tracked to determine the location, coordinates, movement speed, and direction of each object by tracking it. Able to know. As a result of application to actual roads, tracking improved by 10%, in particular, the recognition rate and tracking of shaded areas (extremely small vehicle parts hidden by large cars) improved by 100%, and traffic data analysis accuracy was improved.

• Journal of Auto-vehicle Safety Association
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• v.6 no.1
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• pp.5-9
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• 2014

Over the past ten years, since the introduction of the side crash test regulation in Europe, much research work has been performed internationally to develop new and modified test procedures to improve the level of occupant protection offered by vehicles in side crash test. This research has been co-ordinated and finally contributed to development of an AE-MDB(Advanced European Moving Deformable Barrier) and WorldSID (Worldwide Side Impact Dummy). EuroNCAP(European New Car Assessment Program) has the plan to conduct AE-MDB side crash test using WorldSID from 2015 by replacing Progressive MDB and EuroSID II. Automobile manufacturers need to respond to these changes closely. This paper is to find dominant control factor and analyze it of WorldSID 50%ile dummy injury through AE-MDB side crash test by predicting best and worst condition. And control factors will be validated within EuroNCAP regulations. This paper is analyzed by DFSS(Design for six sigma) which contains 5 control factors and is evaluated by ANOVA with the data as a result of LS-DYNA analysis correlated with crash pulse from 50 kph AE-MDB side crash test using WorldSID 50%ile dummy.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.258-272
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• 2022

The technology implementation method was diversified into an 'autonomous cooperative driving' method to overcome the limitations of a stand-alone autonomous vehicle with vehicle sensor-based autonomous driving. The autonomous cooperative driving method involves exchanging information between roadside infrastructure and autonomous vehicles. In this process, the concept of dynamic information (LDM), a target of cooperation, was established. But, evaluation methods and standards for dynamic information have not been established. Therefore, this study, a dynamic information evaluation method based on information on pedestrians within the moving objects. In addition, autonomous cooperative driving was demonstrated, and dynamic information was also verified through the evaluation method. The significance of this study is that it established the dynamic information evaluation methodology for autonomous cooperative driving for the first time. Based on this, this study is expected to contribute to the application of safe autonomous cooperative driving technology to the field.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2291-2297
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• 2015

This paper presents a vehicle detection system using the video as a input image what has moving of vehicles.. Input image has constraints. it has to get fixed view and downward view obliquely from top of the road. Road detection is required to use only the road area in the input image. In introduction, we suggest the experiment result and the critical point of motion history image extraction method, SIFT(Scale_Invariant Feature Transform) algorithm and histogram analysis to detect vehicles. To solve these problem, we propose using applied Gaussian Mixture Model(GMM) that is the Vehicle Detection GMM(VDGMM). In addition, we optimize VDGMM to detect vehicles more and named VDGMM 2.0. In result of experiment, each precision, recall and F1 rate is 9%, 53%, 15% for GMM without road detection and 85%, 77%, 80% for VDGMM2.0 with road detection.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.5
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• pp.1055-1067
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• 1994

This paper is presented to perform linear dynamic analysis of bridges due to vehicle moving on bridges. The road surface roughness and bridge/vehicle interaction are also considered. The bridge and vehicle are modeled as 3-D bridge and vehicle model, respectively. The road surface roughness of the roadway and bridge decks are generated from power spectral density(PSD) function for good road. The PSD function proposed by C.J. Dodds and J.D. Robson is used to describe the road surface roughness for good road condition. The vehicles are modeled as two nonlinear vehicle model with 7-D.O.F of truck and 12-D.O.F of tractor-trailer and the equations of motion of the vehicles are derived using Lagrange's equation. The main girder and concrete deck are modeled as beam and shell element, respectively and rigid link is used between main girder and concrete deck. The equations of motion of the vehicles are solved by Newmark ${\beta}$ method and the equations of the motion of the bridges are solved by mode-superposition procedures. The validity of the proposed procedure is demonstrated by comparing the results with the experimental data reported by the AASHO Road Test. The comparison shows that the agreement between experiment and theory is quite satisfactory.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.593-596
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• 2018

The speed of vehicles has remained a significant factor that influences the severity of accidents and traffic accident rate in many parts of the world including South Korea. This behavior where drivers drive at speeds which exceed a posted safe threshold is known as 'speeding'. Over the past twenty years, the Korean National Police Agency (NPA) has become aware of an increased frequency of drivers who are speeding. Therefore, fixed-type ASE systems [1] have been installed on hazardous road sections of many highways. These system monitor vehicle speeds using a camera. However, the use of ASE systems has changed the behavior of the drivers. Specifically, drivers reduce speed or avoid the route where the cameras are mounted. It is not practical to install cameras at every possible location. Therefore, it is challenging to thoroughly explore the location where speeding occurs. In view of these problems, the author of this paper designed and implemented a prototype visualization system in which point and color are used to show vehicle location and associated over-speed information. All of this information was used to create a comprehensive visualization application to show information about vehicle driving. In this paper, we present an approach detecting vehicles moving at speeds which exceed a threshold and visualizing the points those violations occur on a map. This was done using vehicle trajectory data collected in Daegu city. We propose steps for exploring the data collected from those sensors. The resulting mapping has two layers. The first layer contains the dynamic vehicle trajectory data. The second underlying layer contains the static road networks. This allows comparing the speed of vehicles on roads with the known maximum safe speed of those roads, and presents the results with a visualization tool. We also compared data about people who drive over threshold safe speeds on each road on days and weekends based on vehicle trajectories. Finally, our study suggests improved times and locations where law enforcement should use monitoring with speed cameras, and where they should be stricter with traffic law enforcement. We learned that people will drive over the speed limit at midnight more than 1.9 times as often when compared with rush hour traffic at 8 o'clock in the morning, and 4.5 times as often when compared with traffic at 7 o'clock in the evening. Our study can benefit the government by helping them select better locations for installation of speed cameras. This would ultimately reduce police labor in traffic speed enforcement, and also has the potential to improve traffic safety in Daegu city.