In recent years, active safety systems have been extensively researched and developed to enhance vehicle safety and operational performance. The paper focuses on improving Adaptive Cruise Control (ACC) systems for electric vehicles, particularly in urban traffic scenarios with low-speed ranges, where safety and stability are critical. Traditional ACC systems often struggle to handle complex traffic situations accurately at low speeds. To address this issue, the paper proposes a control strategy based on fuzzy logic, leveraging its strength in managing uncertainty and nonlinear behavior. The method evaluates parameters such as the gap to the leading vehicle and the relative speed using fuzzy logic, enabling precise speed control. Simulation results demonstrate that the strategy effectively maintains safe following distances and consistent speeds, while also improving overall efficiency. This approach not only meets the demands of urban traffic but also aligns with the performance requirements of modern electric vehicles, offering a robust solution for low-speed scenarios in increasingly congested urban environments.