Distributed management of Personal Rapid Transit (PRT) vehicles under unusual transport conditions

TL;DR

This paper introduces a distributed vehicle management algorithm for Personal Rapid Transit systems that adapts to uneven demand using a horizon parameter, demonstrated through simulations of typical and unusual scenarios.

Contribution

The paper proposes a novel distributed management algorithm for PRT vehicles that operates without central data, using a horizon parameter to adapt to varying demand conditions.

Findings

The algorithm effectively manages vehicle distribution under uneven demand.

Simulation results show adaptability to unusual transportation scenarios.

Distributed approach reduces reliance on centralized control.

Abstract

The paper presents a flexibility of management of vehicles in Personal Rapid Transit (PRT) network. The algorithm used for delivering empty vehicles for waiting passengers is based on multiparameter analysis. Due to its distributed construction, the algorithm has a horizon parameter, which specifies the maximum distance between stations the communications is performed. Every decision is made basing on an information about situation (number of vehicles standing at a station, number of vehicles travelling to a station, number of passengers waiting) sent between stations, without any central data base containing traffic conditions. The simulation of the traffic in random case (typical) and in unusual case of delivering people to a social event occurring at single place is presented. It is shown that simple manipulation with horizon parameter allows to adapt the network to extremely uneven demand and destination choice.