This study investigates empty vehicle redistribution algorithms for personal rapid transit and autonomous taxi services. The focus is on passenger service and operator cost. A new redistribution algorithm is presented in this study: index‐based redistribution (IBR). IBR is a proactive method, meaning it takes into account both current demand and anticipated future demand, in contrast to reactive methods, which act based on current demand only. From information on currently waiting for passengers, predicted near‐future demand and projected arrival of vehicles, IBR calculates an index for each vehicle station, and redistribution is done based on this index. Seven different algorithm combinations are evaluated using a test case in Paris Saclay, France (20 stations and 100 vehicles). A combination of simple nearest neighbours and IBR is shown to be promising. Its results outperform the other methods tested in peak and off‐peak demand, in terms of average and maximum passenger waiting times as well as station queue length. The effect of vehicle fleet size on generalised cost is analysed. Waiting times, mileage and fleet size are taken into account while assessing this generalised cost.


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