A stochastic user-operator assignment game for empirical evaluation of a microtransit service in Luxembourg

We tackle the problem of evaluating and designing a microtransit service. Microtransit operators can allocate resources to improve upon many aspects of operation: vehicle capacities; fleet size; algorithms to improve routing, pricing, repositioning, matching; and more. We conduct the first empirical application of a model from Rasulkhani and Chow (2019) that evaluates such systems using stable matching between travellers and operator-routes. The study is conducted using a real data set of Kussbus shared by industry collaborator UFT (Utopian Future Technologies S.A.) covering 3010 trips made between April to October 2018 in Luxembourg and its French-side and Belgium-side border areas. Several modifications are made to the model to convert it into a stochastic reliability-based model to better allow it to fit to the data. Calibration results led to a VOT of 24.67 euros/hour, a base utility of trips made with Kussbus as 45 Euros, and a significance level for stability of 0.20 (54% prediction rate, 70% matches with withheld 20% test set). Analysis of the system using the model shows that the current Kussbus operation is not a stable outcome; an increase of ticket prices to a buyer-optimal policy would only reduce ridership from 465 trips to 426 trips while increasing net profit from -4135 euros to 187 euros for 615 ride requests. If the government were to intervene, we recommend they subsidize Kussbus to improve their route operating costs by requiring a buyer-optimal pricing policy as a cost reduction of 50% would increase ridership by 10%. On the other hand, if Kussbus can reduce in-vehicle travel time on their own by 20%, they can significantly increase profit several fold from the baseline.