Fuel Consumption Prediction Of Cars Using Machine Learning: A Comparative Study

Abstract— Improving vehicle fuel economy necessitates the capacity to model and predict fuel efficiency. In this paper, the three Machine Learning models are used to compare fuel efficiency of cars for a large dataset. Linear regression, decision tree and random forest models have been used for the purpose and performance of the cars compared. The model could also help road managers better understand how much road vehicles utilize fuel and how road geometry affects their performance. The study also reveals that all three methods allow for the development of high-performing models, with the decision tree model marginally outperforming linear regression and random forest in terms of R2 and lower MSE value