Sampling of Redistribution of Empty Vehicles for Personal Rapid Transit

Abstract

A personal rapid transit (PRT) system uses compact, computer-guided vehicles running on dedicated guideways to carry individuals or small groups directly between pairs of stations. PRT vehicles operate on demand when a passenger requests service at his or her origin station. Because the number of trips requested from a station need not equal the number of trips ending there, some empty vehicles must move to balance the flows. The empty vehicle redistribution (EVR) problem prompts the decision to move empty vehicles reactively in response to known requests or proactively in anticipation of requests. This paper develops a new algorithm for the EVR problem called “sampling and voting” (SV). SV results in the choice of reactive movements with the use of a simple nearest-neighbor rule; the selection of proactive movements is derived by the generation of an ensemble of possible sequences of future passenger requests, the solution of a deterministic optimization problem for each sequence individually, and the discovery of the empty vehicle movements that are common among the sequences. Moving vehicles proactively is essential for providing short passenger waiting times. The new SV algorithm was tested in simulation with several case study systems, and it produced significantly shorter passenger waiting times than did existing EVR algorithms. Variants of the SV method developed here for PRT are also applicable to conventional taxi systems and emergency response systems.