An online hybrid mechanism for dynamic first-mile ridesharing service

This paper leverages the “Mechanism Design” theory to design the ridesharing-based transit feeder service with mixed scheduled and on-demand passenger requests. An online hybrid mechanism is proposed with four incentive objectives: promoting passengers to participate by satisfying their mobility preferences, inducing passengers to truthfully reveal their mobility preferences, incentivizing the service provider to be financially sustainable, and incentivizing more regular commuters to early schedule the service. We propose and prove four properties, “preference-based individual rationality”, “preference-based incentive compatibility”, “financial sustainability”, and “scheduling preferability” to achieve the four incentive objectives, respectively. This online hybrid mechanism is comprised of a dynamic re-optimization methodology for re-matching and re-routing and a hybrid real-time pricing mechanism discriminative against different passenger types. In order to obtain the large-scale solutions for the online hybrid mechanism, this paper improves the solution pooling approach (SPA), which was originally proposed in our previous work for a static offline mechanism, to adapt for the online hybrid mechanism. The improved SPA successfully sustains the “preference-based individual rationality”, “financial sustainability”, and “scheduling preferability” properties. The simulation results demonstrate the superiority of the proposed online hybrid mechanism over the static offline mechanism and the outperformance of the improved SPA over the original SPA.