• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.10
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• pp.948-956
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• 2014

Today, Intelligent Vehicle Detection System seeks to reduce the negative factors, such as accidents over to get the traffic information of existing system. This paper proposes detection algorithm for the illegal U-turn vehicles which can cause critical accident among violations of road traffic laws. We predicted that if calculated optical flow vectors were shown on the illegal U-turn path, they would be cause of the illegal U-turn vehicles. To reduce the high computational complexity, we use the algorithm of pyramid Lucas-Kanade. This algorithm only track the key-points likely corners. Because of the high computational complexity, we detect center lane first through the color information and progressive probabilistic hough transform and apply to the around of center lane. And then we select vectors on illegal U-turn path and calculate reliability to check whether vectors is cause of the illegal U-turn vehicles or not. Finally, In order to evaluate the algorithm, we calculate process time of the type of algorithm and prove that proposed algorithm is efficiently.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.55-69
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• 2017

Recently, the IoT (Internet of Things) environment is being developed rapidly through network which is linked to intellectual objects. Through the IoT, it is possible for human to intercommunicate with objects and objects to objects. Also, the IoT provides artificial intelligent service mixed with knowledge of situational awareness. One of the industries based on the IoT is a car industry. Nowadays, a self-driving vehicle which is not only fuel-efficient, smooth for traffic, but also puts top priority on eventual safety for humans became the most important conversation topic. Since several years ago, a research on the recognition of the surrounding environment for self-driving vehicles using sensors, lidar, camera, and radar techniques has been progressed actively. Currently, based on the WAVE (Wireless Access in Vehicular Environment), the research is being boosted by forming networking between vehicles, vehicle and infrastructures. In this paper, a research on the recognition of a traffic signs on highway was processed as a part of the awareness of the surrounding environment for self-driving vehicles. Through the traffic signs which have features of fixed standard and installation location, we provided a learning theory and a corresponding results of experiment about the way that a vehicle is aware of traffic signs and additional informations on it.

• Journal of the Korean Institute of Gas
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• v.20 no.5
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• pp.64-71
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• 2016

According to the urban gas business law, electrical corrosion prevention measures shall be installed to the buried gas pipelines and the pipe-to-soil potentials should be measured at the test box at least once a year. Most of the test boxes installed in urban area are usually located on the road where the vehicle travels, therefore, it is difficult to measure the CP potentials at the test boxes. That is, we need traffic control when carrying out the measurement of the CP potentials on daytime when the traffic is heavy, or we have to measure the potentials in the late night when the traffic is light. To solve these difficulties, we have studied remotely CP potential measuring method by using the patrol car. We have installed solid reference electrodes and data loggers under the test boxes on the site and received the CP potentials from the data loggers when the vehicle moves. It was difficult to send and receive the data because the data logger was located under the ground. We have applied 3 different method including 2 antenna systems to achieve best effective way in receiving the data. We have found the remote CP measuring method by using a car can save more 20 times of measuring time than conventional measuring methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.453-464
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• 2019

Recently, as the demand for 3D geospatial information increases, the importance of rapid and accurate data construction has increased. Although many studies have been conducted to register UAV (Unmanned Aerial Vehicle) imagery based on LiDAR (Light Detection and Ranging) data, which is capable of precise 3D data construction, studies using LiDAR data embedded in MMS (Mobile Mapping System) are insufficient. Therefore, this study compared and analyzed 9 matching algorithms based on feature points for registering reflectance image converted from LiDAR point cloud intensity data acquired from MMS with image data from UAV. Our results indicated that when the SIFT (Scale Invariant Feature Transform) algorithm was applied, it was able to stable secure a high matching accuracy, and it was confirmed that sufficient conjugate points were extracted even in various road environments. For the registration accuracy analysis, the SIFT algorithm was able to secure the accuracy at about 10 pixels except the case when the overlapping area is low and the same pattern is repeated. This is a reasonable result considering that the distortion of the UAV altitude is included at the time of UAV image capturing. Therefore, the results of this study are expected to be used as a basic research for 3D registration of LiDAR point cloud intensity data and UAV imagery.

• Journal of Korean Society of Transportation
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• v.23 no.6 s.84
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• pp.103-113
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• 2005

A pedestrian accident is generally less fully understood than the 'typical' car-to-car collision. For this reason, the analysis of the pedestrian accident is, in many respects, more complicated and demanding. The purpose of this study is to identify clearly the impact point that is the main subject of struggle in pedestrian accidents. In order to develop the model, it is very significant to classify actual accident data including impact velocity. vehicle damage and injury scale of pedestrian. These data were collected from three local branches of RTSA(Road Traffic Safely Authority). The number of collected data were 34 cases and 61.7% of them were fatal accidents. In consequence of analyzing the data by statistical method, it revealed that there is correlation between impact velocity and throw distance. It, also shows that the impact velocity has strong linear correlation to vehicle damage and injury scale. Consequently, reconstruction analysis models of pedestrian accidents considering in local circumstances(such as the physical characteristics of pedestrians and vehicles) was developed However. it is difficult to apply the result of this study to all sorts of pedestrian accidents, because the actual accident data which were used to develop the model were limited. To overcome this limitation, it is necessary to develop an analysis model applicable to diverse circumstances with a wide range of pedestrian accident data on a national basis.

• Journal of Korean Society of Transportation
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• v.22 no.5
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• pp.123-137
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• 2004

The study on traffic assignment is actively being performed which reflect networks status using time. Its background is increasing social needs to use traffic assignment models in not only hardware area of road network plan but also software area of traffic management or control. In addition, multi-class traffic assignment model is receiving study in order to fill a gap between theory and practice of traffic assignment model. This model is made up of two, one of which is multi-driver class and the other multi-vehicle class. The latter is the more realistic because it can be combined with dynamic model. On this background, this study is to build multidynamic model combining the above-mentioned two areas. This has been a theoretic pillar of ITS in which dynamic user equilibrium assignment model is now made an issue, therefore more realistic dynamic model is expected to be built by combining it with multi-class model. In case of multi-vehicle, FIFO would be violated which is necessary to build the dynamic assignment model. This means that it is impossible to build multi-vehicle dynamic model with the existing dynamic assignment modelling method built under the conditions of FIFO. This study builds dynamic network model which could relieve the FIFO conditions. At the same time, simulation method, one of the existing network loading method, is modified to be applied to this study. Also, as a solution(algorithm) area, time dependent shortest path algorithm which has been modified from existing shortest path algorithm and the existing MSA modified algorithm are built. The convergence of the algorithm is examined which is built by calculating dynamic user equilibrium solution adopting the model and algorithm and grid network.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.8
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• pp.939-944
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• 2014

Traffic accidents caused by the attention dispersion are increasing and the behavior of the attention dispersion affects the front-observing rate, road keeping ability, and reaction time for a dangerous situation. Many drivers listen to a radio broadcast and they have to change the frequency for continuously listening a radio broadcast of the specific broadcasting station in case of crossing a boundary of the particular area. In this situation, the possibility of a car accident increases, because the attention dispersion of a driver might be occurred. Especially, the risk of a car accident caused by changing the frequency of a radio is more serious in the highway, due to the high speed of a vehicle. In order to reduce the risk of a car accident caused by handling a radio during driving car, in this paper, we propose an automatic frequency conversion algorithm for vehicle radio, which saves normal system frequencies of primary broadcasting stations in a database and determines new frequency of the changed area using the location information obtained from a navigation system in a boundary of the specific area. After determining new frequency, the proposed algorithm selects a frequency with better receiving rate comparing signal-to-noise ratios (SNRs) of two signals corresponding previous and new frequencies.

• Journal of the Korean Institute of Gas
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• v.5 no.2 s.14
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• pp.30-35
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• 2001

Presently, working gas pipelines are being subjected to the influence of construction vibration. Especially on subway and road construction, gas pipelines are being influenced to construction vibration caused by use of construction equipment, passage of a large-sized vehicle and blasting. Buried gas pipelines are subjected to the influence of vibration caused by blast in the vicinity of pipeline, exposed gas pipelines are subjected to the influence of vehicle vibration. Therefore, in the study, it is developed to vibration prediction program of gas pipeline by analyzing measured construction vibration. This program is able to predict vibration of gas pipeline according to field conditions by using the results of structural finite element analysis and empirical equation by reliability analysis. And, this program contains the database of construction vibration. Additionally, this program is able to compute estimated blast vibration equation using measured blast vibration data in the field and to form graph of allowable charging gunpowder per delayed-action with the change of blast velocity. Therefore, field workers are able to predict construction vibration around gas pipeline and estimate safety of gas pipeline.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.151-157
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• 2018

Among the various sensors for measuring traffic, PVDF (polyvinylidene fluoride) piezoelectric sensors are used to classify vehicles because they can detect the axle of the vehicle. Piezoelectric sensors are embedded in road pavements and are always exposed to traffic loads and environmental loads. Therefore, the life expectancy is very short, less than 6 years. Traffic control is essential for reinstallation and data collection is interrupted during the failure period. The lifespan will increase if the sensor installation depth is increased. In this study, the sensor signal output was analyzed with a variable depth of sensor installation to verify the possibility of deeper installation. Furthermore, various parameters, such as the weight and speed, were analyzed. The wheel load is applied using APT. As a result, the MSI BL sensor output signal is higher than 100mV when installed at 3cm, which is reliable. If the location of the sensor is deeper in the pavement, the expected lifetime of the sensor is also increased. On the other hand, the MSI cable was found to be less than 100mV at the shallowest depth of 1cm, making it impossible for field applications.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.95-101
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• 2014

This paper explains effective tracking method for a vehicle cutting in a line on the road automatically. The method employs KLT based on optical flow using play-back image sequence. Main contribution of this paper is play-back image sequence that is in order image frames for rewind direction from a reference point in time. The moment when recognizing camera can read a license plate very well can usually be the reference point in time. The biggest images of object traced can usually be obtained at this moment also. When optic flow is applied, the bigger image of the object traced can be obtained, the more feature points can be obtained. More many feature points bring good result of tracking object. After the recognizing cameras read a license plate on the vehicle suspected of cut-in-line violation, and then the system extracts the play-back image sequence from the tracking cameras for watching wide range. This paper compares using play-back image sequence as normal method for tracking to using play-forward image sequence as suggested method on the results of the experiment and also shows the suggested algorithm has a good performance that can be applied to the unmanned system for watching cut-in-line violation.