• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.61-72
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• 2011

In the benefits of ITS, there are intangible gains from real-time traffic information as well as classical gains such as travel time saving. These intangible gains are difficult to be estimated by existing transportation investment appraisal commonly used in SOC investment. The major reason is not because of the absence of methodology but because of the absence of generalized values of particular benefits from real time traffic information. This research explores the value of real-time traffic information on VMS that is the most representative of ITS services, by using CVM with Double Bounded Dichotomous Choice Question. Willingness-To-Pay (WTP) functions of drivers are built with survival functions using various types of probability distribution functions such as Exponential, Log-logistic, and Weibull functions. The results reveal that Log-logistic distribution is the most appropriate distribution model to estimate WTP, and the estimated coefficients are stable through LR (Likelihood Ratio) test. For the further study, it is recommended to perform statistical tests of temporal and spatial transferability that is not examined in this research due to the lack of data.

• Management & Information Systems Review
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• v.4
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• pp.257-284
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• 2000

According as the drivers increase who have their cars, the comprehensive studies on the automobile for the traffic safety have been raised as the important problems. Visual Recognition System for radio-controled driving is a part of the sensor processor of Unmanned Autonomous Vehicle System. When a driver drives his car on an unknown highway or general road, it produces a model from the successively inputted road traffic information. The suggested Recognition System of the Road Traffic Safety Information Board is to recognize and distinguish automatically a Road Traffic Safety Information Board as one of road traffic information. The whole processes of Recognition System of the Road Traffic Safety Information Board suggested in this study are as follows. We took the photographs of Road Traffic Safety Information Board with a digital camera in order to get an image and normalize bitmap image file with a size of $200{\times}200$ byte with Photo Shop 5.0. The existing True Color is made up the color data of sixteen million kinds. We changed it with 256 Color, because it has large capacity, and spend much time on calculating. We have practiced works of 30 times with erosion and dilation algorithm to remove unnecessary images. We drawing out original image with the Region Splitting Technique as a kind of segmentation. We made three kinds of grouping(Attention Information Board, Prohibit Information Board, and Introduction Information Board) by RYB( Red, Yellow, Blue) color segmentation. We minimized the image size of board, direction, and the influence of rounding. We also minimized the Influence according to position. and the brightness of light and darkness with Eigen Vector and Eigen Value. The data sampling this feature value appeared after building the learning Code Book Database. The suggested Recognition System of the Road Traffic Safety Information Board firstly distinguished three kinds of groups in the database of learning Code Book, and suggested in order to recognize after comparing and judging the board want to recognize within the same group with Nearest Neighborhood Decision Making.