During its normal service life, a tire is subjected to large variations in operating conditions, such as ambient temperature, inflation pressure, and changes in tread depth. The longitudinal force response of the tire changes significantly because of each of these operating conditions. This, in turn, would directly influence the performance of the antilock braking system (ABS) installed in a vehicle. Current ABS systems are tuned for a vehicle with fixed operating thresholds that do not change. The objective of this study was to understand the influence of a tire's operating conditions on ABS efficiency and the extent of variation it can cause on stopping distance. This was done by obtaining longitudinal-slip characteristics for a given tire at various temperatures, inflation pressures, and tread depth through a traction trailer. These data were then used to simulate an ABS braking maneuver using a half-car vehicle model. The major reasons for the loss in stopping distance performance because of a drop in efficiency under each condition was then analyzed in detail. The latter part of this study explored the potential for improvement in stopping distance that could possibly be achieved through an intelligent ABS system that would use tire-sensed information, such as temperature, pressure, and tread depth to calculate essential tire characteristics in real time using an adaptive magic formula and change its tuning parameters accordingly.