Understanding how pavement surface conditions influence operating speed is essential for improving road safety and optimizing urban traffic performance. This research investigates how pavement surface deterioration represented by the Surface Distress Index (SDI) influences vehicle operating speeds along Kolonel Sudiarto Street, a key urban roadway in Tegal City. A quantitative descriptive method was employed, in which pavement conditions were evaluated using the SDI framework, and vehicle speeds were obtained through space mean speed (SMS) measurements. A total of 358 vehicle samples were examined through simple linear regression to quantify the influence of SDI on motorcycle and passenger car operating speeds. The findings reveal a strong and statistically significant negative association between SDI and motorcycle speed (R² = 0.947), demonstrating that higher levels of pavement distress markedly decrease motorcycle operating speeds. In contrast, the relationship between SDI and car speed is weak and not statistically significant (R² = 0.064), suggesting that car speeds are influenced more by traffic dynamics and vehicle stability than by pavement surface deterioration. Combined regression simulations further demonstrate that motorcycles are markedly more sensitive to incremental surface distress. These findings affirm the relevance of SDI as a key indicator for evaluating pavement performance and predicting speed behavior, emphasizing the need for timely maintenance interventions to support safer and more efficient urban road operations.