Investigating the Influence of Weather on Weigh-in-Motion Measurements Using In-Pavement Strain Sensors
Publication: International Conference on Transportation and Development 2024
ABSTRACT
Accurate vehicle weight monitoring is essential for efficient and effective traffic management and road maintenance, particularly in preventing potential damage from overweight vehicles to road infrastructure. Weigh-in-motion technology plays a pivotal role in traffic engineering due to its ability to rapidly collect data with minimal traffic disruption. However, the accuracy of weigh-in-motion stations need enhancement and may be affected by weather conditions, especially fluctuations in temperature. To address this concern, a field test was conducted, incorporating controlled vehicle weight, speed, and driving behavior. Additionally, electrical resistance strain transducers were configured for data collection, strategically positioned at the location of maximum bending, the bottom of the asphalt layer, 5 in. beneath the asphalt road surface. This field test, spanning 10 experiments over two years, was conducted to analyze the impact of weather factors on measured vehicle weights by strain sensor. The findings of this investigation will provide insights into the benefits of enhancing the accuracy and reliability of vehicle weight measurements, contributing to more effective traffic management and improved road maintenance practices.
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REFERENCES
Ahmed, M., Rahman, A., Islam, M., and Tarefder, R. (2015). Combined effect of asphalt concrete cross-anisotropy and temperature variation on pavement stress–strain under dynamic loading. Construction and Building Materials, 93, 685–694.
Akoglu, H. (2018). User’s guide to correlation coefficients. Turkish Journal of Emergency Medicine, 18(3), 91–93.
Alizadeh Noughabi, H. (2016). Two powerful tests for normality. Annals of Data Science, 3(2), 225–234.
Cheng, H., Liu, J., Sun, L., and Liu, L. (2021). Critical position of fatigue damage within asphalt pavement considering temperature and strain distribution. International Journal of Pavement Engineering, 22(14), 1773–1784.
Cho, S.-B., and Won, H.-H. (2003). Machine learning in DNA microarray analysis for cancer classification. 189–198.
Gajda, J., Sroka, R., and Żegleń, T. (2007). Accuracy analysis of WIM systems calibrated using pre-weighed vehicles method. Metrology and Measurement Systems, 14(4), 517–527.
Mishra, P., Pandey, C. M., Singh, U., Gupta, A., Sahu, C., and Keshri, A. (2019). Descriptive statistics and normality tests for statistical data. Annals of Cardiac Anaesthesia, 22(1), 67.
Razali, N. M., and Wah, Y. B. (2011). Power comparisons of shapiro-wilk, kolmogorov-smirnov, lilliefors and anderson-darling tests. Journal of Statistical Modeling and Analytics, 2(1), 21–33.
Saifizul, A. A., Karim, M. R., Yamanaka, H., and Okushima, M. (2013). Empirical analysis on the effect of gross vehicle weight and vehicle size on speed in car following situation. Asian Transport Studies, 2(4), 351–362.
Shapiro, S. S., and Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3/4), 591–611.
Statista Research Department. (n.d.). Number of motor vehicles in U.S. Statista. Retrieved May 24, 2023, from https://www.statista.com/statistics/183505/number-of-vehicles-in-the-united-states-since-1990/.
Thompson, G., Kroll, K., Grangroth, C., and Arnold, J. (2019). WIM Sensor Performance and Stability Across Time Periods And Variations in Temperature. ICWIM8, 284.
US Number of Registered Vehicles | Economic Indicators | CEIC. (n.d.). Retrieved August 3, 2023, from https://www.ceicdata.com/en/indicator/united-states/number-of-registered-vehicles.
Xiao, C., Ye, J., Esteves, R. M., and Rong, C. (2016). Using Spearman’s correlation coefficients for exploratory data analysis on big dataset. Concurrency and Computation: Practice and Experience, 28(14), 3866–3878.
Yang, H., Yang, Y., Zhao, G., Guo, Y., and Wang, L. (2023). Development and Temperature Correction of Piezoelectric Ceramic Sensor for Traffic Weighing-In-Motion. Sensors, 23(9), 4312.
Yang, X., Wang, X., Podolsky, J., Huang, Y., and Lu, P. (2023). Assessing Vehicle Wandering Effects on the Accuracy of Weigh-in-Motion Measurement Based on In-Pavement Fiber Bragg Sensors through a Hybrid Sensor-Camera System. Sensors, 23(21), 8707.
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International Conference on Transportation and Development 2024
Pages: 261 - 270
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Published online: Jun 13, 2024
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