Evolutionary Modeling of Large-Scale Public Transport Networks

1 A genetic algorithm to design efficient large-scale public transport networks is extended. It goes 2 beyond existing approaches by incorporating a dynamic demand response towards both changes 3 in the network and external disruptions. The algorithm is based on an agent-based (MATSim) 4 simulation and tested for the city of Zurich. Compared to the existing public transport system, it 5 proposes a sparser network with substantially higher frequencies. By doing so, the algorithm 6 predicts a higher transit ridership at a lower level of subsidies, thus increasing the effectiveness 7 of public transportation. Moreover, it reliably identifies corridors for potential capacity upgrades. 8 The approach may help transport planners to assess their existing public transport networks and 9 to plan public transport infrastructure for the era of automated vehicles. 10 Manser, P., H. Becker, S. Hörl and K.W. Axhausen 2

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