Fuzzy Logic Speed Advisory System for Optimal Energy Efficiency Based on Fuel Consumption and Road Speed Limit

With the increasing number of vehicles on the road, the demand for fossil fuels continues to rise, and energy consumption and associated emissions present ongoing environmental challenges, which explains the urgent need for alternative solutions to attain sustainability in transportation. This study proposes a novel fuzzy logic (FL) based speed advisory system utilizing vehicle-to-infrastructure (V2I) communication to optimize energy efficiency in passenger vehicles. Two FL models are developed: the first estimates instantaneous fuel consumption based on vehicle speed gathered using V2I. The second calculates an adequate advisory speed considering fuel usage and road speed limits. Simulations are conducted in MATLAB and SUMO using realistic driving cycles and traffic patterns for a 17.45km route. Fuzzy Logic speed advisories are sent to vehicles via V2I to adjust their speeds accordingly. FL accurately predicts energy consumption with an estimated RMSE (Root Mean Square error) value of around 0.3%. Compared to the unequipped vehicles with Fuzzy Logic, FL advisory implementation reduces energy consumption, CO
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, CO, NOx, and particulate matter emissions by 49%, reducing the negative environmental impact. This innovative approach enables vehicles to optimize energy usage, promoting a more sustainable transportation system. In addition to reducing emissions, Fuzzy Logic speed advisories also improve air quality and minimize the adverse health effects caused by pollution. This significant environmental impact demonstrates FL's potential to enhance sustainability in transportation.