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Personal rapid transit (PRT) is a public and automated transport system in which a fleet of small driverless vehicles operate in order to transport passengers between a set of stations through a network of guided ways. Each customer is carried from one station to another directly with no stop in intermediate stations. This mode of transport can result in a high level of unused capacity due to the empty moves of the vehicles. In this paper, we model the problem of minimizing the energy consumed by the PRT system while assuming predeterministic list of orders; then we solve it using some constructive heuristics. Experiments are run on 1320 randomly generated test problems with various sizes. Our algorithms are shown to give good results over large trip instances.

Part 5: Modelling and OptimizationInternational audienceWe consider the real-time routing of driverless vehicles in an on-demand transit transportation system with time window. Because fast dispatching decisions are required, decentralized decisions system are generally used in these contexts. For that purpose, we introduce a new multi agent-based simulation model where intelligent vehicle agents determine their specific routes and which transportation requests to serve. They interact with passengers, who strive for minimum waiting time. Our approach offers several advantages: it is fast, make it easy for vehicles to determine their specific routes and needs little information for vehicles. We propose also a specific algorithm for the independent vehicles’agent in order to determine their specific routes. Preliminaries computational tests of our multi-agent model and our developed algorithm prove that our approach is very promising