Distribution Function Similarity of Overloaded Commercial Trucks Detection (Case Study: Iran)
Abbas Mahmoudabadi1, Hassan Abdous2, Fatemeh Pourhossein Ghazimahalleh3
1Dr. Abbas Mahmoudabadi, Director, Master Program in Industrial Engineering, MehrAstan University, Gilan, Iran.
2Hassan Abdous, Deputy of Traffic Safety Department of Road Maintenance and Transport Organization, Tehran, Iran.
3Fatemeh Pourhossein Ghazimahalleh, Ph.D. Student, Department of Information Technology, University of Tehran, Tehran, Iran.
Manuscript received on 25 November 2024 | First Revised Manuscript received on 02 February 2025 | Second Revised Manuscript received on 20 February 2025 | Manuscript Accepted on 15 March 2025 | Manuscript published on 30 March 2025 | PP: 34-41 | Volume-13 Issue-4, March 2025 | Retrieval Number: 100.1/ijese.A101514011224 | DOI: 10.35940/ijese.A1015.13040325
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Monitoring overloaded vehicles is an operational aspect of ensuring the safe operation of vehicles and mitigating damage to road pavement. Since the concentration on overloading is claimed to differ by type of truck, with trailers allegedly being more frequently 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 end, at the first stage, the effect of the number of weighing stations and cargo trips on overloading detection was 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 Kolmogorov-Smirnov statistical method, known as the threesample test, is finally utilised to investigate the similarity of distribution functions for overloading detection among three types of trucks: trailers, heavy trucks, and light trucks. Data on registered trucks, as well as detected trucks with overloading, across the road network in the West Asian country of Iran, has been collected for a year and then categorised into thirty-one provinces. The results revealed that, whereas the number of weighing stations and cargo trips does not have a significant effect on overloading detection, the similarity of distribution functions for overloading detection differs among the three types of trucks across the provinces. Therefore, not all types of trucks are equally subject to overloading control, and transport authorities should redesign overloading detection approaches throughout the enforcement instructions applied in intercity transportation.
Keywords: Trucks’ Overloading, Traffic Enforcement, Similarity Distribution Functions, Intercity Transportation.
Scope of the Article: Data Analytics