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This article discusses empty vehicle redistribution algorithms for PRT and autonomous taxi services from a passenger service perspective. In modern literature reactive methods such as nearest neighbours are commonly used. In this article we first formulate the general matching problem on a bipartite graph of available vehicles and stations. In addition, we propose a new index-based proactive redistribution (IBR) algorithm based on predicted near-future demand at stations. Test results of six variations of combined proactive and reactive strategies on a test case in Saclay, France with 20 stations and 100 vehicles are given. The combined Nearest Neighbour / IBR provides a promising solution for both peak and off-peak demand, significantly outperforming all other methods considered, in terms of passenger waiting time (both average and maximum) as well as in terms of station queue lengths.

The matching problem of empty vehicle redistribution in autonomous taxi systems