Data underlying the master thesis: Modelling and Assessment of an Autonomous Ride-Sharing Service’s Urban Utilization

doi: 10.4121/20418552.v2
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/20418552
Datacite citation style:
Mahtab Sharifi (2022): Data underlying the master thesis: Modelling and Assessment of an Autonomous Ride-Sharing Service’s Urban Utilization. Version 2. 4TU.ResearchData. software. https://doi.org/10.4121/20418552.v2
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Software
choose version:
version 2 - 2022-08-11 (latest)
version 1 - 2022-08-09

This collection represents the empirical portion of the author’s MSc thesis research, which involved modelling the private vehicle traffic flow for the city of Rotterdam and the simulation of an autonomous ride-sharing service's impact on CO2 emission using that model on SUMO. It has four subfolders: net_files, python_code_files, sim_runs, and output_excel_files.


The folder contains Rotterdam's processed road network configuration, zonal data, and edge specifications along with the entirety of the written python code files for the construction of the traffic model and the trip merging component of the ride-sharing service.


Three separate scenarios were simulated for this project and compared to the baseline simulation for determining the emission reduction rates, and all ten iterations of these simulations are also included in this zip file.


Finally, here are several excel sheets detailing the results and calculations for zonal attraction ranking. 

The code contains extensive comments that can be easily used to replicate or build on the published work. The readers may refer to the related thesis document for further explanations. 

history
  • 2022-08-09 first online
  • 2022-08-11 published, posted
publisher
4TU.ResearchData
format
python code, SUMO cfg and xml files, metadata GeoJson files, excel files
organizations
TU Delft, Faculty of Technology, Policy and Management, Department of Engineering, Systems and Services, Transport and Logistics

DATA

files (2)