• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.825-830
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• 2007

For the design and maintenance of highways and road structures, the statistical data are needed for the vehicle, especially heavy truck crossing. So far, static weighing has been used but it needs fixed station, crews, and it takes a lot of time. Also truck mix and headway distances cannot be obtained. Weigh-In-Motion system uses the sensor as a weighing scale and collects the axle weights, axle distances, vehicle types and etc. without stopping or slowing down the vehicle. Objectives of the study is make a determination of WIM Sensor for Implementation of U-Overloaded Vehicle Regulation System.

• Journal of Industrial Technology
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• v.23 no.A
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• pp.55-61
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• 2003

In this study, a signal processing and related techniques for development of a weight measuring system using a digital loadcell which is able to satisfy the important properties of WIM (weighing-in-motion) system have been investigated. A fast and high accurate signal processing of the digital load cell sensor for weighing-in-motion system is presented. A/D conversion system is constructed to realize a stable A/D conversion and signal processing algorithm using DSP and microprocessor. A new technique for vibration and measuring speed of the system is also investigated. The proposed method was applied to the actual design and the experimental results showed good performance of the weighing speed and stability.

• 한국ITS학회:학술대회논문집
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• 2003.11a
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• pp.67-72
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• 2003

• 한국도로학회:학술대회논문집
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• 2005.03a
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• pp.179-184
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• 2005

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.4D
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• pp.511-518
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• 2011

Truck weight data are essential for road infrastructure design, maintenance and management. WIM (Weigh-In-Motion) system provides highway planners, researchers and officials with statistical data. Recently high speed WIM data also uses to support a vehicle weight regulation and enforcement activities. This paper aims at developing axle load estimating models with high speed WIM data collected from national highway. We also suggest a method to estimate axle load using simple regression model for WIM system. The model proposed by this paper, resulted in better axle load estimation in all class of vehicle than conventional model. The developed axle load estimating model will used for on-going or re-calibration procedures to ensure an adequate level of WIM system performance. This model can also be used for missing axle load data imputation in the future.

• International Journal of Highway Engineering
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• v.14 no.5
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• pp.179-188
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• 2012

PURPOSES: The aim of this study is to analyze overloading control effectiveness of enforcing overweighted vehicles using HS-WIM (High-Speed Weigh-in-Motion) at main lane of expressway. METHODS: To analyze the weight distribution statistically, HS-WIM system should has an appropriate weighing accuracy. Thus, the weighing accuracy of the two HS-WIM systems was estimated by applying European specifications and ASTM (American Standards for Testing and Materials) for WIM in this study. Based on the results of accuracy test, overweight enforcement system has been operated at main lanes of two expressway routes in order to provide weight informations of overweighted vehicle in real time for enforcement squad. To evaluate the overloading control effectiveness with enforcement, traffic volume and axle loads of trucks for two months at the right after beginning of the enforcement were compared with data set for same periods before the enforcement. RESULTS: As the results of weighing accuracy test, both WIM systems were accepted to the most precise type that can be useful to applicate not only statistical purpose but enforcing on overweight vehicles directly. After the enforcement, the rate of overweighted trucks that weighed over enforcement limits had been decreased by 27% compared with the rate before the enforcement. Especially, the rate of overweighted trucks that weighed over 48 tons had been decreased by 91%. On the other hand, in counterpoint to decrease of the overweighted vehicle, the rate of trucks that weighed under enforcement limits had been increased by 7%. CONCLUSIONS: From the results, it is quite clear that overloading has been controlled since the beginning of the enforcement.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.3
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• pp.387-392
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• 2007

Overloaded Vehicles are one of biggest of hazard in durability decrease of roads and bridges. Thus, regulation was put in force about overloaded vehicles to reserve this problem. However, existing system had many problems. For these reasons, this paper presents solutions of U-intelligent overload vehicles regulation system based on manless and wireless for fixing of problems of existing system and construction of u-lTS. With this in mind, we studied about composition method of system, applications of USN, design of system controller, WCDMA/HSDPA and we verified performance of WIM Sensors in this paper.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.4
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• pp.399-404
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• 2011

Overload vehicles have demoralizing influence upon the social overhead capital, economics of nation, traffic flow and road safe as various components. Accordingly, this study established a ubiquitous sensor network system to develop an intelligent regulation system to monitor overloaded vehicles in motion. and Unlike WIM, after detecting the axle of driving vehicles by measuring deformation of roads, this system calculates the weights of vehicles by using signals from the strain sensors installed under the road and an analysis method. Also the study conducted an simulation test for vehicle load analysis using genetic algorithm. and tested wireless sensor for USN system.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.3
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• pp.225-232
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• 2008

Overload vehicles operate damage to road, bridge, and then increasing in maintenance and repair cost because structures are reduced durability. The existing regulation systems have many problems and need coping measure. Therefore, this paper organized Ubiquitous sensor network system for development of intelligent auto overload vehicle regulation system about high speed vehicles, also axial load WIM sensor was selected by indoor experiment through wireless protocol. And we examined possibility U-load auto overload vehicle regulation system through experiment of the transmission and reception distance. If this system will apply to road and bridge, might be effective for economy and convenience through establishment of U-IT system. And high speed vehicle that was amalgamate IT technology and existing overload regulation problems, also tested wireless sensor for USN organization. This experiment aim to organize system interface for user through perfection man-less, wireless system of Internal/External Network from high speed WIN sensor with USN organization. Accordingly, it is necessary experimentation through Test Bed for constitution External network and application of actually regulations using WCDMA/HSDPA.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1087-1105
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• 2016

Traffic load and volume is one of the most important physical quantities for bridge safety evaluation and maintenance strategies formulation. This paper aims to conduct the statistical analysis of traffic volume information and the multimodal modeling of gross vehicle weight (GVW) based on the monitoring data obtained from the weigh-in-motion (WIM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. A genetic algorithm (GA)-based mixture parameter estimation approach is developed for derivation of the unknown mixture parameters in mixed distribution models. The statistical analysis of one-year WIM data is firstly performed according to the vehicle type, single axle weight, and GVW. The probability density function (PDF) and cumulative distribution function (CDF) of the GVW data of selected vehicle types are then formulated by use of three kinds of finite mixed distributions (normal, lognormal and Weibull). The mixture parameters are determined by use of the proposed GA-based method. The results indicate that the stochastic properties of the GVW data acquired from the field-instrumented WIM sensors are effectively characterized by the method of finite mixture distributions in conjunction with the proposed GA-based mixture parameter identification algorithm. Moreover, it is revealed that the Weibull mixture distribution is relatively superior in modeling of the WIM data on the basis of the calculated Akaike's information criterion (AIC) values.