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A Basic Study on Vehicle Load Analyzing System for Embedded Road (임베디드 도로를 위한 차량하중 분석시스템 기초연구)

  • Jo, Byung-Wan;Yoon, Kwang-Won;Park, Jung-Hoon;Kim, Heoun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.31 no.1D
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    • pp.127-132
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    • 2011
  • Load managing method on road became necessary since overloaded vehicles occur damage on road facilities and existing systems for preventing this damage still show many problems. Accordingly, efficient managing system for preventing overloaded vehicles could be organized by using the road itself as a scale by applying genetic algorithm to analyze the load and the drive information of vehicles. First of all, accurate analysis of load using the behavior of road itself is needed for solving illegal axle manipulation problems of overloaded vehicles and for installing intelligent embedded load analyzing system. Accordingly in this study, to use the behavior of road, the transformation was measured by installing underground box type indoor model and indoor experiment was held using genetic algorithm and 10% error were checked.

A Research for Improvement of WIM System by Abnormal Driving Patterns Analysis (비정상 주행패턴 분석을 통한 WIM 시스템 개선 연구)

  • Park, Je-U;Kim, Young-Back;Chung, Kyung-Ho;Ahn, Kwang-Seon
    • Journal of Internet Computing and Services
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    • v.11 no.4
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    • pp.59-72
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    • 2010
  • WIM(Weigh-In-Motion) is the system measuring the weight of the vehicle with a high-speed. In the existing WIM system, vehicle weight is measured based on the constant speed and the error ratio has 10%. However, because of measuring the driving pattern, that is abnormal driving pattern which is like the acceleration and down-shift of the drivers, it has the error ratio which is bigger than the real. In order to it reduces the error ratio of WIM system, the improved WIM system needs to find the abnormal driving pattern. In order to reducing the error ratio of these WIM systems, the improved WIM system can find abnormal driving patterns. In this paper, the improved WIM system which analyzes the abnormality driving pattern influencing on the error ratio of WIM system of an existing and minimizes the error span is designed. The improved WIM system has the multi step loop structure of adding the loop sensor to an existing system. In addition, the measure function defined as an intrinsic is improved and the weight measured by the abnormal driving pattern is amended. The analysis of experiment result improved WIM system can know the fact that the error span reduces by 8% less than in the existing the maximum average sampling error 22.98%.