• 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.12 no.3
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• pp.17-26
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• 2010

Maintenance of the roads and bridges is a major issue for all road administrators around the world, and various initiatives are being implemented in each region for the purpose of controlling the ever increasing road maintenance cost while ensuring the safety of the vehicles driving. Efforts for such initiatives have also been made in Asia and initiatives for managing heavy-weight vehicles have recently gained momentum in Korea and Japan. We have developed a technology for unevenly installing bar-shaped sensors (piezo quartz sensors) to enable dynamic axle load measurement at a highly accurate level, and have estimated our measurement accuracy of axle load/gross weight, etc. on an actual road. The measurement accuracy of the axle load/gross weight varies significantly depending on the number of sensors installed. In our implementation, the target accuracy was set to below ${\pm}5%$ for gross weight measurement so that automatic regulation can be applied. We have achieved our target by installing 8-point measurement system. However, to have this technology widely accepted, it was necessary to reduce the system size so that it can be easily implemented. Therefore, we have estimated the relationship between the measurement accuracy and the system size (number of measurement points), and have come up with the proposal of 3-point measurement as an optimum number of measurement points, and have estimated its performance on an actual road. Additionally, we evaluated the relationship between the measurement accuracy and vehicle velocity.

• International Journal of Highway Engineering
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• v.11 no.4
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• pp.69-78
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• 2009

Korea has achieved significant economic growth with building the Gyeongbu Expressway. As the number of new road construction projects has decreased, it becomes more important to maintain optimal status of the current road networks. One of the best ways to accomplish it is weight enforcement as active control measure of traffic load. This study is to develop High-speed Weigh-in-motion System in order to enhance efficiency of weight enforcement, and to analyze patterns of overloaded trucks on highways through the system. Furthermore, it is to review possibilities of developing overweight control system with application of the HS-WIM system. The HS-WIM system developed by this study consists of two sets of an axle load sensor, a loop sensor and a wandering sensor on each lane. A wandering sensor detects whether a travelling vehicle is off the lane or not with the function of checking the location of tire imprint. The sensor of the WIM system has better function of classifying types of vehicles than other existing systems by detecting wheel distance and tire type such as single or dual tire. As a result, its measurement errors regarding 12 types of vehicle classification are very low, which is an advantage of the sensor. The verification tests of the system under all conditions showed that the mean measurement errors of axle weight and gross axle weight were within 15 percent and 7 percent respectively. According to the WIM rate standard of the COST-323, the WIM system of this study is ranked at B(10). It means the system is appropriate for the purpose of design, maintenance and valuation of road infrastructure. The WIM system in testing a 5-axle cargo truck, the most frequently overloaded vehicle among 12 types of vehicles, is ranked at A(5) which means the system is available to control overloaded vehicles. In this case, the measurement errors of axle load and gross axle load were within 8 percent and 5 percent respectively. Weight analysis of all types of vehicles on highways showed that the most frequently overloaded vehicles were type 5, 6, 7 and 12 among 12 vehicle types. As a result, it is necessary to use more effective overweight enforcement system for vehicles which are seriously overloaded due to their lift axles. Traffic volume data depending upon vehicle types is basic information for road design and construction, maintenance, analysis of traffic flow, road policies as well as research.