• International conference on construction engineering and project management
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• 2013.01a
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• pp.494-496
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• 2013

Cost-Benefit Analysis (CBA) is a systematic optimization process that allows users to compare different alternatives and to determine if a project is a solid investment. Many state DOTs have included CBA in their pavement management systems (PMSs) to help allocate state funds for maintenance, rehabilitation, resurfacing, and reconstruction of pavements. In a typical CBA, each pavement type has an assigned weight factor which represents the level of importance of this pavement type. To conduct an accurate CBA, it is essential to select appropriate weight factors. Arbitrarily assigning weights factors to pavements can lead to biased and inaccurate funding allocation decisions. The purpose for this paper is to outline a method to develop an ideal set of weight factors that can be utilized to conduct more accurate CBA. To this end, a matrix of all possible weight factors sets was developed. CBA was conducted for each set of weight factors to obtain a population of possible optimization solutions. Then a regression analysis was performed to establish the relationship between benefit and weight factors. Finally, a multi-objective genetic algorithm was applied to select the optimal set of weight factors. The findings from this study can be used by state DOTs to strategically manage their roadway systems in a cost effective manner.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.319-324
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• 2004

With a PMS, a maintenance plan should be drawn up after surface conditions are precisely examined and analyzed. The majority of the present PMSs are run by the fact that experts first examine surface conditions on sites, and then enter results into systems. However, considering the actual circumstances of the present time and an increase in paved road hereafter, it is inefficient that experts examine the whole paved roads in person and long-lasting PMSs can not be kept up. Therefore, in the study digital photogrammetry was used to examine asphalt concrete pavements. In a consequence, it was found that if databases are implemented in the future with quality digital image information accumulated from studies on roads, they will be able to provide the field of pavement management system with a large amount of information and data.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.3 s.30
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• pp.51-59
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• 2004

In the study, there has been a sharp upward trend in road maintenance cost as the expansion of road networks increases. Running a pavement management system(PMS) is indispensable for efficient and scientific maintenance of the whole road networks with limited maintenance budgets. With a PMS, a maintenance plan should be drawn up after surface conditions are precisely examined and analyzed. The majority of the present PMSs are run by the fact that experts first examine surface conditions on sites, and then enter results into systems. However, considering the actual circumstances of the present time and the increase in paved road hereafter, it is inefficient that experts examine the whole paved roads in person and long-lasting PMSs can not be kept up. As a result, after analyzing the accuracy of 3-D coordinates representing road surfaces that was decided using multi orientation and digital photogrammetry, the average of standard errors turned out to be 0.0427m on the X-axis, 0.0527m on the Y-axis and 0.1539m on the Z-axis. It was found to be good enough to be put to practical use for maps drawn on scales below 1 :1000, which are being currently made and used within the country, and GIS data.