The Impact of Overloaded Trucks on Congestion Costs in Urban Freeways: A Microsimulation Approach Using Weight-in-Motion Data

Abstract

Overloaded freight vehicles are widely recognized for accelerating pavement deterioration; however, their operational impacts on traffic performance and congestion costs remain insufficiently quantified. This study proposes an integrated framework combining Weight-in-Motion (WIM) data and microscopic traffic simulation to estimate congestion costs generated by overloaded trucks on urban freeways. Primary WIM data were collected for three truck categories based on the Indonesian toll road classification system, including vehicle weight, overload percentage, and operating speed. Pearson correlation and linear regression analyses were performed to develop overload–speed relationships, which were subsequently implemented in a PTV VISSIM model of a three-lane freeway under five volume-to-capacity (V/C) ratio scenarios ranging from 0.2 to 1.0. Congestion costs were estimated using travel time delay and the Indonesian Value of Time (VOT) parameter. The results indicate a strong inverse relationship between overload percentage and truck operating speed, with correlation coefficients ranging from −0.889 to −0.953. Simulation results demonstrate that congestion costs increase nonlinearly with both overload severity and traffic density, with Type 3 trucks generating the highest congestion cost of IDR 46,641/km under saturated traffic conditions. The findings reveal that overloaded trucks impose substantial operational externalities beyond pavement deterioration and highlight the importance of incorporating congestion impacts into freight enforcement and transportation policy evaluation. By integrating empirical WIM observations with traffic microsimulation, this study provides a practical approach for quantifying the economic consequences of overloaded freight operations and supporting evidence-based transport management strategies.