<p>Weigh-in-motion (WIM) sensors measure dynamic vehicle weights over the pavement surface. These sensors provide critical data for transportation infrastructure management, enabling accurate vehicle weight monitoring without disrupting traffic flow. This study investigates the impact of surface roughness, vehicle speed, and sensor configuration on the accuracy of the WIM systems. This study evaluates the effect of sensor spacing (3.05 to 15.24 m), number of sensors (1 to 10), sensor arrangement (inline vs. staggered), and vehicle speed (48.3 and 96.6 km/h) on measurement errors. Three pavement surface profiles with varying roughness levels and dynamic load profiles were used to estimate measurement errors for a Class 9 truck at speeds of 48.3 km/h and 96.6 km/h. Results indicate that surface profile significantly influences dynamic axle and gross vehicle weight (GVW) forces, with higher speeds exacerbating errors, particularly for rear tandem axles. Relative errors due to vehicle dynamics range from 20 to 40%. Varying sensor spacing did not show a clear trend, but a 3.05 m spacing is recommended for cost effectiveness and error minimization. Multiple sensors reduced measurement errors, with negligible improvements (less than 2%) beyond three to four sensors. Staggered sensor configurations proved more effective at higher speeds, with up to 5.5% lower measurement error. This study recommends using a three-sensor staggered arrangement with 3.05 m sensor spacing for best accuracy.</p>