Towards a Greener Future: Fuzzy Logic Applications in Smart Transportation Systems

Integrating fuzzy logic into smart transportation systems holds promise for optimizing energy consumption and enhancing sustainability. This paper presents a framework for employing fuzzy logic in managing charging schedules for electric vehicles (EVs) based on key input variables: Battery Level (BL), Charging Station Availability (CSA), and Time of Day (TD). Membership functions for these variables are defined to capture their linguistic representations, allowing for effective decision-making in uncertain environments. Fuzzy rules are established to map input variables to appropriate charging actions, considering factors such as battery status, charging station availability, and time constraints. By leveraging fuzzy logic, the proposed approach offers flexibility and adaptability in determining optimal charging schedules tailored to varying conditions. This research contributes to advancing the development of greener transportation systems by intelligently managing energy resources within the EV ecosystem.