Distribution Function Similarity of Overloaded Commercial Trucks Detection (Case Study: Iran)
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Monitoring overloaded vehicles is an operational aspect of ensuring the safe operation of vehicles and mitigating damages to road pavement. Since, the concentration on overloading is claimed to differ for the type of trucks, where trailers are more allegedly engaged under enforcement, this research aims to explore the differences in overload monitoring among various kinds of vehicles, including trailers, heavy trucks, and light trucks in intercity transportation. To this purpose, at the first stage, the effect of the number of weighing stations and cargo trips on overloading detection has been investigated through analysis of variance. It is followed by considering the number of registered trucks as an exposure factor to standardize the enforcement rate in the second stage. An adapted version of the statistical method of Kolmogorov-Smirnov, known as three samples, is finally utilized to investigate the similarity of distribution functions of overloading detection for three types of trucks including trailers, heavy trucks, and light trucks. Data, for registered trucks as well as detected trucks as overloading across the road network in the West-Asian country of Iran, has been collected for a year followed by categorizing into thirty-one provinces. The results revealed that whereas the number of weighing stations and cargo trips do not have significant effects on overloading detection, the similarity of distribution functions for overloading detection is different for three types of trucks over the provinces. Therefore, all types of trucks are not equally under overloading control and transport authorities should redesign overloading detection approaches throughout the enforcement instruction applied in intercity transportation.
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Shah, R., Sharma, Y., Mathew, B., Kateshiya, V., & Parmar, J. (2016). Review paper on overloading effect. International Journal of Advanced Scientific Research and Management, 1(4), 131-134. https://www.academia.edu/download/87782350/IJASRM_V1S4_039_131_134.pdf
Bagui, S., Das, A., & Bapanapalli, C. (2013). Controlling vehicle overloading in BOT projects. Procedia-Social and Behavioral Sciences, 104, 962-971. DOI: https://doi.org/10.1016/j.sbspro.2013.11.191
Saad, F. A. M., Ishak, S. Z., Sulaiman, S. A. H., &Awang, A. (2021, August). The Implication of Overloaded Truck to Developing Countries–A Review. In 2021 IEEE 12th Control and System Graduate Research Colloquium (ICSGRC) (pp. 165-170). IEEE. DOI: https://doi.org/10.1109/ICSGRC53186.2021.9515215
Hameed, S., &Prathap, R. C. (2018). Study on impact of vehicle overloading on National Highways in varying terrains. Int. J. Eng. Res. Technol.(IJERT), 7(1), 2278-0181. https://www.academia.edu/download/59387154/study-on-impact-of-vehicle-overloading-on-national-highways-in-varying-terrains-IJERTV7IS01013520190525-126845-v9glek.pdf
Mahmoudabadi, A., &Tavakkoli-Moghaddam, R. (2011). The use of a genetic algorithm for clustering the weighing station performance in transportation–A case study. Expert Systems with Applications, 38(9), 11744-11750. DOI: https://doi.org/10.1016/j.eswa.2011.03.061
Rasool, J., & Kaushal, M. (2022). A Study On Impact Of Vehicle Overloading On Jammu-Srinagar National Highway. https://www.researchgate.net/profile/Manish-Kaushal-5/publication/364342909_A_STUDY_ON_IMPACT_OF_VEHICLE_OVERLOADING_ON_JAMMU-SRINAGAR_NATIONAL_HIGHWAY/links/634cf0da9cb4fe44f32f3786/A-STUDY-ON-IMPACT-OF-VEHICLE-OVERLOADING-ON-JAMMU-SRINAGAR-NATIONAL-HIGHWAY.pdf
Mahmoudabadi, A., & Seyedhosseini, S. M. (2013). Improving the efficiency of weigh in motion systems through optimized allocating truck checking oriented procedure. IATSS research, 36(2), 123-128. DOI: https://doi.org/10.1016/j.iatssr.2012.08.002
Jacob, B., &Cottineau, L. M. (2016). Weigh-in-motion for direct enforcement of overloaded commercial vehicles. Transportation Research Procedia, 14, 1413-1422. DOI: https://doi.org/10.1016/j.trpro.2016.05.214
Yadav, N., Yadav, N., & Garg, A. (2022). Vehicle Payload Monitoring System. In IoT for Sustainable Smart Cities and Society (pp. 145-164). Cham: Springer International Publishing. DOI: https://doi.org/10.1007/978-3-030-89554-9_7
Pastore, M., &Calcagnì, A. (2019). Measuring distribution similarities between samples: A distribution-free overlapping index. Frontiers in Psychology, 10, 1089. DOI: https://doi.org/10.3389/fpsyg.2019.01089
Lee, L. (1999). Measures of distributional similarity (pp. 25–32). DOI: https://doi.org/10.48550/arXiv.cs/0001012
Sahinturk, L., & Özcan, B. (2017). The Comparison of Hypothesis Tests Determining Normality and Similarity of Samples. Journal of Naval Science and Engineering, 13(2), 21–36. https://dergipark.org.tr/en/download/article-file/402354
Vrbik, J. (2018). Small-Sample Corrections to Kolmogorov–Smirnov Test Statistic. Pioneer Journal of Theoretical and Applied Statistics, 15(1–2), 15–23. http://www.pspchv.com/Abstract-PJTAS/Abstract%20of%20PJTAS%20Volume%2015/2.%20Abstract%20%20Volum%2015,%20Issues%201-2,%20Pages%2015-23%20PJTAS.pdf
Arnold, T. B., & Emerson, J. W. (2011). Nonparametric goodness-of-fit tests for discrete null distributions. R Journal, 3(2). https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=94a9e47370c4c53cd01f7b918d1b8a9b392778c4
Lopes, R. H., Reid, I. D., & Hobson, P. R. (2007). The two-dimensional Kolmogorov-Smirnov test. http://bura.brunel.ac.uk/handle/2438/1166
Simard, R., &L'Ecuyer, P. (2011). Computing the two-sided Kolmogorov- Smirnov distribution. Journal of Statistical Software, 39, 1-18. DOI: https://doi.org/10.18637/jss.v039.i11
Drezner, Z., Turel, O., & Zerom, D. (2010). A modified kolmogorov-smirnov test for normality. Communications in Statistics: Simulation and Computation, 39(4), 693–704. DOI: https://doi.org/10.1080/03610911003615816
Mahmoudabadi, A., & Abdous, H. (2020). Do the Coaches’ Crashes and Their Usage Exposure Come from the Same Distributions? Society & Sustainability, 2(3), 10–19. DOI: https://doi.org/10.38157/society_sustainability.v2i3.165
Manski, C. F. (1983). Closest empirical distribution estimation. Econometrica: Journal of the Econometric Society, 305-319. DOI: https://doi.org/10.2307/1911991
David H. T. (1958), A three-sample Kolmogorov-Smirnov test. The Annals of Mathematical Statistics, 29, 842–851. DOI: https://doi.org/10.1214/aoms/1177706540
Kiefer J. (1959), K-sample analogues of the Kolmogorov-Smirnov and Cram´erv. Mises tests. The Annals a Mathematical Statistics, 30, 420–447. DOI: https://doi.org/10.1214/aoms/1177706261
Böhm, W., & Hornik, K. (2010). On two-periodic random walks with boundaries. Stochastic models, 26(2), 165-194. DOI: https://doi.org/10.1080/15326340903517154
Mahmoudabadi, A., & Lalaei, R. A. (2017). Developing a Breakeven Point Model Based on Enforce Rate for Installing Weigh in Motion System in Inter-City Transportation. Journal of Intelligent Transportation and Urban Planning, 5(1), 1-7. DOI: https://doi.org/10.18005/ITUP0501001
Chen, Y., Wang, K., Zhang, Y., Luo, R., Yu, S., Shi, Q., & Hu, W. (2020). Investigating factors affecting road freight overloading through the integrated use of BLR and CART: A case study in China. Transport, 35(3), 236-246. DOI: https://doi.org/10.3846/transport.2020.12635
Singh, R. A. M. E. S. H., & Srivastava, G. A. U. R. A. V. (2022). Truck overloading detection and engine locking system. Adv. and Applications in Mathe. Sci, 21(12), 7157-7162. https://www.mililink.com/upload/article/1284230911aams_vol_2112_october_2022_a43_p7157-7162_ramesh_singh_and_gaurav_srivastava.pdf
Lin, Y. H., Wu, F., Wang, R., Gu, S., &Xu, Z. (2022). Spatiotemporal Analysis of Overloaded Vehicles on a Highway Using Weigh-in-Motion Data. Journal of Transportation Engineering, Part A: Systems, 148(1), 04021098. DOI: https://doi.org/10.1061/JTEPBS.0000616
Dolcemascolo, V., Hornych, P., Jacob, B., Schmidt, F., & Klein, E. (2015). Heavy vehicle traffic and overload monitoring in France and applications. In The XXVth World Road Congress PIARC (pp. 1-12). https://proceedings-seoul2015.piarc.org/ressources/files/2/IP0372-Jacob-E.pdf
Mahmoudabadi, A., & Abolghasem, A. (2013). Application of Chaos Theory in Trucks' Overloading Enforcement. Journal of Engineering, 2013. DOI: https://doi.org/10.1155/2013/245293
Gaira, A., Parveen, A., Dabral, D., Goyal, J., & Rani, M. R. (2020). Vehicle Overloading: A Review. International Journal for Research in Applied Science & Engineering Technology (IJRASET) ISSN, 2321-9653. DOI: https://doi.org/10.22214/ijraset.2020.7002
Qiao, X. X., & Zhao, Y. D. (2018, May). Vehicle overload detection system based on magnetoresistance sensor. In 2018 International Conference on Electronics Technology (ICET)(pp. 102-105). IEEE. DOI: https://doi.org/10.1109/ELTECH.2018.8401434
Xu, S., & Zhao, Q. (2011). Study on Vehicle-mounted Overloading Control System for Passenger Vehicles. Procedia Engineering, 15, 1214-1218. DOI: https://doi.org/10.1016/j.proeng.2011.08.224
Yassenn, O., Endut, I., Hafez, M., Ishak, S., &Yaseen, H. (2015). Overloading of heavy vehicles around the world. Int. J. Eng. Sci. Res, 34-45. https://www.enrichedpublications.com/ep_admin/jounral/pdf/1723193774.pdf#page=47
Odonkor, E. N., &Ofosu, W. K. (2020). Design and construction of vehicle loading monitoring system using load sensor and GSM. International Journal of Applied Science and Technology, 10(1). DOI: https://doi.org/10.30845/ijast.v10n1p1
Nassif, H., Ozbay, K., Na, C., Lou, P., Fiorillo, G., & Park, C. (2018). Monitoring and Control of Overweight Trucks for Smart Mobility and Safety of Freight Operations. https://rosap.ntl.bts.gov/view/dot/49467/dot_49467_DS1.pdf
Alkhoori, F. A., &Maghelal, P. K. (2021). Regulating the overloading of heavy commercial Vehicles: Assessment of land transport operators in Abu Dhabi. Transportation Research Part A: Policy and Practice, 154, 287-299. DOI: https://doi.org/10.1016/j.tra.2021.10.019
Chan, Y. C. M. (2008). Truck overloading study in developing countries and strategies to minimize its impact (Doctoral dissertation, Queensland University of Technology). https://eprints.qut.edu.au/28561/
Shrivastava, A. K., & Dalvi, Dr. S. D. (2024). Mathematical Modelling and Analysis to Derive Optimum Brake Pressure for Hill Start Assist System in Commercial Vehicles. In International Journal of Innovative Science and Modern Engineering (Vol. 12, Issue 12, pp. 8–15). DOI: https://doi.org/10.35940/ijisme.e7980.12121224
Patnaik, R. K., & Tamilarasan, N. (2019). Stability Analysis of Magneto-Rheological Damper for Suspension of Commercial Vehicles. In International Journal of Engineering and Advanced Technology (Vol. 8, Issue 6, pp. 668–676). DOI: https://doi.org/10.35940/ijeat.e7943.088619
Raj, S. M. G., Let G, S., Sajini M L, M., & Abraham, P. (2019). A Web-Interface based Smart Tracking of Overloaded Vehicle. In International Journal of Innovative Technology and Exploring Engineering (Vol. 9, Issue 1, pp. 4223–4230). DOI: https://doi.org/10.35940/ijitee.a7118.119119