Round-Trip Asymmetry in Sustainable and Inclusive Mobility: Travel Time Variations and Mode Dominance

The data and code scripts used for the analysis in the paper entitled "Round-Trip Asymmetry in Sustainable and Inclusive Mobility: Travel Time Variations and Mode Dominance" by Ioanna Gogousou (ioanna.gogousou@geo.tuwien.ac.at), Negar Alinaghi and Ioannis Giannopoulos submitted to 8th Conference on Sustainable Mobility CSum 2026.  The analysis focuses on the city of Vienna, Austria.

It comprises three folders within the zip file:

1. data: Contains the datasets used for the analysis. These datasets are derived from real-world transport network data. This folder includes one serialized Python object (.p file)  and geospatial boundary data stored in ESRI Shapefile format (a set of files including .shp, .shx, .dbf, .prj).
2. code: Python scripts required to perform the analysis.
3. results: Routing results used in the analysis and discussed in the associated paper.
4. plots: Visualization and results presented in the paper.

Programming Language: Python 3.13 

For reproducibility, read the READ_ME.txt file included in the zip folder.

All data files are licensed under CC BY 4.0, all software is licensed under the MIT License.

Abstract

City centers always attract people, as they concentrate work places, activities, and services. As a result, accessibility to city centers (inbound trips) has been widely studied. However, outbound trips, i.e., leaving the city center, are less explored. This one-sided focus overlooks the inherently bidirectional nature of accessibility. This work investigates differences between multimodal round-trips to the city center, using public transport and walking. The city of Vienna was segmented into hexagons and ∼ 50,000 realistic synthetic routes (in/outbound) were generated covering the entire city. Our route generation relies on a modified routing algorithm incorporating average human behaviour preferences. Using these routes as a proxy, we examine asymmetries of multimodal round-trips, focusing on adherence to behavioral filters, travel-time differences, and the dominant transport mode. The results identify areas requiring interventions for equitable and sustainable urban travel and reveal differences in the main modalities used for these trips, with implications for planning and network optimization.