Abstract

In this study, an agent-based transport simulation is used to look into different design concepts for demand responsive transit (DRT). In different simulation experiments for a real-world case study of the Greater Berlin area, the DRT service area is either set to the inner-city center area or the entire city area, and the DRT pricing scheme is varied. The existing simulation framework is extended by an iterative approximation approach to improve the computational performance. The simulation results show that a small service area and too low prices may result in an unwanted mode shift effect from walk and bicycle to DRT. For higher fares, the unwanted mode shift effect is reduced and fewer users switch from bicycle and walk to DRT. The simulation experiments also show that a larger DRT service area contributes towards an increase of the desired mode shift effect from car to DRT.

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