This paper explores the applications of machine learning for predicting the travel time in the ride-sourcing networks using the Uber movement dataset. Using the Python programming environment, a case study is presented to analyze the travel time of the ride-sourcing services from the central...

Unreliable travel times cause substantial costs to travelers. Nevertheless, they are not taken into account in many cost-benefit-analyses (CBA), or only in very rough ways. This paper aims at providing simple rules on how variability can be predicted, based on travel time data from Dutch...