After more than 30 years since the Antilock Braking System (ABS) was first introduced, it has become the most important active safety system used on passenger cars. However, it is hard to find a precise description of ABS, its stability and performance in the literature. Most of ABS algorithms currently used are not adaptive to changes of road friction conditions. The aim of our work is to provide a new ABS algorithm that is adaptive to changes of road conditions. To this end, an online parameter estimator is designed to estimate the road characteristics and maximum possible deceleration. Then, a driver demand regulator is proposed to limit the demanded deceleration to the maximum values. In this new strategy, road characteristics are estimated prior to the braking, not during the braking which makes it fast and adaptive. The proposed ABS algorithm is simulated on an artificial driving track and simulation results have been compared to a simple non-adaptive 6-phase Bosch ABS algorithm as our benchmark that is based on deceleration thresholds. Results show a better braking performance and more than 30% of reduction in braking distance.

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