Stochastic dynamic switching in fixed and flexible transit services as market entry-exit real options
Document Type
Journal Article
Publication Date
2017
Subject Area
mode - bus, infrastructure - fleet management, planning - travel demand management, planning - methods
Keywords
Public transit, Market entry and exit real options, Stochastic dynamic optimization, Flexible transit, Last mile problem
Abstract
The first analytical stochastic and dynamic model for optimizing transit service switching is proposed for “smart transit” applications and for operating shared autonomous transit fleets. The model assumes a region that requires many-to-one last mile transit service either with fixed-route buses or flexible-route, on-demand buses. The demand density evolves continuously over time as an Ornstein-Uhlenbeck process. The optimal policy is determined by solving the switching problem as a market entry and exit real options model. Analysis using the model on a benchmark computational example illustrates the presence of a hysteresis effect, an indifference band that is sensitive to transportation system state and demand parameters, as well as the presence of switching thresholds that exhibit asymmetric sensitivities to transportation system conditions. The proposed policy is computationally compared in a 24-hour simulation to a “perfect information” set of decisions and a myopic policy that has been dominant in the flexible transit literature, with results that suggest the proposed policy can reduce by up to 72% of the excess cost in the myopic policy. Computational experiments of the “modular vehicle” policy demonstrate the existence of an option premium for having flexibility to switch between two vehicle sizes.
Rights
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Recommended Citation
Guo, Q.-W., Chow, J.Y.J., & Schonfeld, P. (2017). Stochastic dynamic switching in fixed and flexible transit services as market entry-exit real options. Transportation Research Part C: Emerging Technologies, Available online 23 August 2017. In Press, Corrected Proof.
Comments
Transportation Research Part C Home Page:
http://www.sciencedirect.com/science/journal/0968090X