Data underlying the publication: A bi-level framework for heterogeneous fleet sizing of ride-hailing services considering an approximated mixed equilibrium between automated and non-automated traffic

This dataset supports the research project titled <em>"A Bi-Level Framework for Heterogeneous Fleet Sizing of Ride-Hailing Services Considering an Approximated Mixed Equilibrium Between Automated and Non-Automated Traffic."</em> The dataset focuses on optimizing fleet sizing in mixed-traffic environments and incorporates a bi-level modelling approach to analyze strategic and operational interactions between automated and non-automated vehicles. The original dataset for the Delft case study has been published and is accessible via the DOI: https://doi.org/10.13140/RG.2.2.11097.83043.<br>Contents of the DatasetThis dataset includes:Delft network and mobility data.Toy network and mobility data.Experimental results.<br><br>