The rapid urbanization and increasing environmental concerns have driven the demand for efficient and sustainable transportation solutions. Small electric vehicles are becoming a popular choice for urban commuting due to their low emissions and cost-effectiveness. However, optimizing energy consumption remains a critical challenge for enhancing the overall efficiency and practicality of these vehicles in complex urban environments. Nowadays, the Advanced Driver Assistance Systems (ADAS) of electric vehicles are flourishing. With the gradual enhancement of the computational power of onboard chips, more complex algorithms, such as Model Predict Control (MPC), can be applied in real-time to ADAS. With the advancement of communication technology, more information such as Signal Phase and Timing (SPaT) can be obtained through Vehicle-to-Infrastructure (V2I) technology, providing the potential for further enhancing the capabilities of ADAS.