The post-COVID surge in road traffic has resulted in an upsurge of accidents, posing challenges in safe on-road transit. Vehicle automation serves as one of the solutions to bring down the accident count. There has been numerous research works that develop different models to control various vehicle parameters, thereby providing safe drive. This paper presents a fuzzy logic-based adaptive cruise control system that adjusts the vehicle’s accelerator level based on its speed change and distance with respect to the leading vehicle. The system deploys a Fuzzy Mamdani model that is implemented in MATLAB. The performance of the proposed system is analyzed by conducting various case studies. The results demonstrate the system’s ability to maintain sufficient distance, thereby ensuring safe driving conditions. The suggested model is expected to enhance on-road safety while reducing the likelihood of rear-end collisions.