A stochastic user-operator assignment game for microtransit service evaluation: A case study of Kussbus in Luxembourg

TL;DR

This paper introduces a stochastic matching model for microtransit services that helps operators evaluate policies and optimize ticket pricing by considering user travel utility uncertainties, demonstrated through a Luxembourg case study.

Contribution

It develops a novel stochastic stable matching model tailored for microtransit evaluation, incorporating user utility variability for better policy and pricing decisions.

Findings

Model effectively estimates operation costs and ridership forecasts.

Application to Luxembourg microtransit provides actionable insights.

Methodology for parameter estimation enhances model calibration.

Abstract

This paper proposes a stochastic variant of the stable matching model from Rasulkhani and Chow [1] which allows microtransit operators to evaluate their operation policy and resource allocations. The proposed model takes into account the stochastic nature of users' travel utility perception, resulting in a probabilistic stable operation cost allocation outcome to design ticket price and ridership forecasting. We applied the model for the operation policy evaluation of a microtransit service in Luxembourg and its border area. The methodology for the model parameters estimation and calibration is developed. The results provide useful insights for the operator and the government to improve the ridership of the service.