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The performance of the pavements designed for the cumulative expected 18-kip Equivalent Single Axle Load (ESAL) applications is strongly influenced by the actual traffic loading. Commercial traffic due to a significant amount of their axle loads contribute to the early pavement deterioration. Damage assessment study due to axle loading was carried out in 1995 by National Transport Research Center (NTRC). Presently, the truck ESAL factors used for flexible and rigid pavement design are based on that study. Since then the volume as well as loading of commercial traffic has increased to a great extent. Due to weak law enforcement, haulers are getting profit for overloading and as such no revision has been made to the truck ESAL factors. Thus, there is a dire need to evaluate and assess the impact of commercial vehicles overloading on pavement. National Highway Authority (NHA) of Pakistan over the past few years has established many weigh stations on its National Highways which allow for continuous availability of loading data and provide an accurate representation of the traffic loading. Same can be used to update and develop more accurate truck ESAL factors than the study conducted by NTRC. A software LoadAnalyst was developed for calculating the Truck ESAL Factor from the large amount of weigh station data. These calculated factors can be used by pavement designers to design new pavements and pavement rehabilitation accordingly & accurately and also in establishment of appropriate commercial vehicle loading limits. As a case study, Mullan Mansoor weigh station data was used for analysis. The results showed that on the average, the calculated truck ESAL factors for flexible pavements for Mullan Mansoor weigh station data range from 5 to 16 for different classes of commercial vehicles. It has been observed that the calculated Truck ESAL factors are found higher than NTRC study for 2-Axle Trucks but for 3-Axle Tandem and 4-Axle Single Tandem Trucks, the calculated factors are on lower side. Similarly, the Truck ESAL Factors are continuously increasing over the time. |
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