Sharing Behavior in Ride-hailing Trips: A Machine Learning Inference Approach

no code implementations • 30 Jan 2022 • Morteza Taiebat, Elham Amini, Ming Xu

Using ensemble machine learning models, we find that the travel impedance variables (trip cost, distance, and duration) collectively contribute to 95% and 91% of the predictive power in determining whether a trip is requested to share and whether it is successfully shared, respectively.

BIG-bench Machine Learning