• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.253-260
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• 2008

This paper is based on the ubiquitous network of telematics technology, equipped with a black box to the car by a unique address given to IPv6. The driver's black box at startup and operation of certification, and the car's driving record handling video signals in real-time sensor signals handling to analyze the records. Through the recorded data is encrypted transmission, and the Ubiquitous network of base stations, roadside sensors through seamless mobility and location tracking data to be generated. This is a file of Transportation Traffic Operations Center as a unique address IPv6 records stored in the database. The car is equipped with a black box used on the road go to Criminal cases, the code automotive black boxes recovered from the addresses and IPv6, traffic records stored in a database to compare the data integrity verification and authentication via secure. This material liability in the courtroom and the judge Forensic data are evidence of the recognition as a highly secure. convenient and knowledge in the information society will contribute to human life.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.3
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• pp.31-39
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• 2015

This paper presents the static and kinematic positioning accuracy by the real-time GPS positioning modes of the low-cost GPS receivers using NTRIP-based augmentation service. For this, acquires both the raw measurements data of the field tests by LEA 6T GPS module of u-blox AG, and correction communication via NTRIP caster with RTKLIB as an open source program for GNSS solution. With computing the positions of the check points and road tracks by six kinds of GPS positioning modes which are Single, SBAS, DGPS, PPP, RTK, and TCP/IP_RTK, compared these results to the reference position of the check points. The position error average and rmse of the static test by GPS L1 RTK surveying showed $N=0.002m{\pm}0.001m$, $E=0.004m{\pm}0.001m$ in horizontal plane, and $h=-0.116m{\pm}0.003m$ in vertical, these results are very closed to the coordinates with the geodetic receiver. Especially, in case of the kinematic test with obstacles located on both sides of road, the computed track with ambiguity fixing showed very similar trajectory considerably from VRS network RTK mode. And also, evaluate and verify the performance of the TCP/IP_RTK mode developed based on TCP/IP protocol.

• Journal of Korean Society of Transportation
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• v.23 no.6 s.84
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• pp.91-102
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• 2005

When it comes to the process of information storage, people are likely to organize individual information into the forms of groups rather than independent attributes, and put them together in their brains. Likewise, in case of finding the shortest path, this study suggests that a Hierarchical Road Network(HRN) model should be selected to browse the most desirable route, since the HRN model takes the process mentioned above into account. Moreover, most of drivers make a decision to select a route from origin to destination by road hierarchy. It says that the drivers feel difference between the link travel tine which was measured by driving and the theoretical link travel time. There is a different solution which has predicted the link travel time to solve this problem. By using this solution, the link travel time is predicted based on link conditions from time to time. The predicated link travel time is used to search the shortest path. Stochastic Process model uses the historical patterns of travel time conditions on links. The HRN model has compared favorably with the conventional shortest path finding model in tern of calculated speeds. Even more, the result of the shortest path using the HRN model has more similar to the survey results which was conducted to the taxi drivers. Taxi drivers have a strong knowledge of road conditions on the road networks and they are more likely to select a shortest path according to the real common sense.

• International Journal of Highway Engineering
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• v.11 no.3
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• pp.61-74
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• 2009

Traffic accident risk index Computation model's development apply traffic level of significance about area of road user group, road and street network area, population group etc.. through numerical formula or model by countermeasure to reduce the occurrence rate of traffic accidents. Is real condition that is taking advantage of risk by tangent section through estimation model and by method to choose improvement way to intersection from outside the country, and is utilizing being applied in part business in domestic. However, question is brought in the accuracy being utilizing changing some to take external model in domestic real condition than individual development of model. Therefore, selection intersection estimation element through traffic accidents occurrence present condition, geometry structure, control way, traffic volume, turning traffic volume etc. in 96 intersections in this research, and select final variable through correlation analysis of abstracted estimation elements. Developed intersection design model taking advantage of signal type, numeric of lane, intersection type, analysis of variance techniques through ANOVA analysis of three variables of intersection form with selected variable lastly, in signal crossing through three class intersection, distinction variable choice risk in model, no-signal crossing risk distinction analysis model and so on develop.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.3
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• pp.69-75
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• 2015

Road facilities for safe driving were designed for drivers to distinguish them during day and night, but they cannot play their role when the weather becomes worse. Recently, the road facilities have been designed by using electric and electronic technology so that they can be displayed well at a long distance, but they should be replaced very often due to their frequent breakdown. So, there are many problems in traffic calming and maintenance. In this study, to solve the above problems, semi-permanent LED beacon light was installed in the area where traffic accident are frequent, and monitoring system was developed so that the LED beacon light can be maintenanced by connecting with system. For the above installation and development, system was based on window operating system and it was developed for worker to operate it by using P.C. through connecting with wireless local area network. The result of this study led to analyzing state information on the battery of field-installed LED beacon light in real time, and manegement to effectively by predicting their life cycle.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1D
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• pp.43-50
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• 2011

The monitoring system for link travel speed using taxi probe is one of key sub-systems of ITS. Link travel speed collected by taxi probe has been widely employed for both monitoring the traffic states of urban road network and providing real-time travel time information. When sample size of taxi probe is small and link travel time is longer than a length of time interval to collect travel speed data, and in turn the missing state is inevitable. Under this missing state, link travel speed data is real-timely not collected. This missing state changes from single to multiple time intervals. Existing single interval prediction techniques can not generate multiple future states. For this reason, it is necessary to replace multiple missing states with the estimations generated by multi-interval prediction method. In this study, a multi-interval prediction method to generate the speed estimations of single and multiple future time step is introduced overcoming the shortcomings of short-term techniques. The model is developed based on Non-Parametric Regression (NPR), and outperformed single-interval prediction methods in terms of prediction accuracy in spite of multi-interval prediction scheme.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.4
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• pp.78-85
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• 2011

In vehicle ad-hoc network (VANET) environments, traffic related information such as accident information, emergency information and real time traffic condition have to be delivered to on-board-unit (OBU) or/and road-side-equipment (RSE) for preventing traffic accidents in advance. In this paper, we introduce a Multi-Channel MAC (MCM) since the existing single channel operation may cause packet transmission delay and unexpected communication failure. To offer a seamless safety message transmission during the various services, it is necessary to manage the MAC scheduler in wireless access in vehicular environments (WAVE) systems. The MCM consists of MAC softwares and MAC hardwares where the former and the later ones are implemented with real time operation system based C language and FPGA module with VHDL language, respectively. The performance and QoS are verified by practical measurements and compared with the scheme using single channel operation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.5
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• pp.203-210
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• 2011

The current sensor network analyzes the data collected by the sensing of fixed sensor nodes and provides a service. However, this method cannot actively handle the state and the change in the position of people, 'the target for sensing and the change in the environment', including home automation, building automation and real-time road & weather information, and healthcare environment, etc. To support a dynamic situation which is appropriate for an individual in this diverse environment, it is necessary to provide actively differentiated specific information according to the movement of people and the changes in the environment. In this study, a individualized sensor mobile agent middleware which provides the individualized information (the location of fire incidence and the trace for the path of spread), has been realized through the sensor network environment constructed by the installation of wireless sensor nodes mounted with mobile agent middlewares in buildings.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.3
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• pp.136-141
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• 2012

One of the main reasons for serious road accidents is driving while drowsy. For this reason, drowsiness detection and warning system for drivers has recently become a very important issue. Monitoring physiological signals provides the possibility of detecting features of drowsiness and fatigue of drivers. One of the effective signals is to measure electroencephalogram (EEG) signals and electrooculogram (EOG) signals. The aim of this study is to extract drowsiness-related features from a set of EEG signals and to classify the features into three states: alertness, drowsiness, sleepiness. This paper proposes a neural-network-based drowsiness detection system using Linear Predictive Coding (LPC) coefficients as feature vectors and Multi-Layer Perceptron (MLP) as a classifier. Samples of EEG data from each predefined state were used to train the MLP program by using the proposed feature extraction algorithms. The trained MLP program was tested on unclassified EEG data and subsequently reviewed according to manual classification. The classification rate of the proposed system is over 96.5% for only very small number of samples (250ms, 64 samples). Therefore, it can be applied to real driving incident situation that can occur for a split second.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.3
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• pp.139-147
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• 2007

In military transportation, the use of wide trailer for transporting the large and heavy weight equipments such as tank, armoured vehicle, and mobile gunnery is quite common. So, the vulnerability of causing traffic accidents for these wide military trailer to bump or collide with another car in adjacent lane is very high due to its broad width in excess of its own lane's width. Also, the possibility of these strayed accidents can be increased especially by the careless driver. In this paper, the recognition system of lane and vehicle headway direction is developed to detect the possible collision and warn the driver to prevent the fatal accident. In the system development, Kalman filtering is used first to extract the border of driving lane from the video images supplied by the CCD camera attached to the vehicle and the driving lane detection is completed with regression analysis. Next, the vehicle headway direction is recognized by using neural network scheme with the extracted parameters of the detected driving lane feature. The practical experiments for the developed system are also carried out in the real traffic road of Seoul city area and the results show us the more than 90% accuracy in recognizing the driving lane and vehicle headway direction.