Revealing differences in public transport share through district-wise comparison and relating them to network properties [Data and Code]

How to cite?

Canestrini, M., Gogousou, I., Michail, D., & Giannopoulos, I. (2024). Revealing Differences in Public Transport Share Through District-Wise Comparison and Relating Them to Network Properties. 16th International Conference on Spatial Information Theory (COSIT 2024). Schloss Dagstuhl–Leibniz-Zentrum für Informatik.

Abstract

Sustainable transport is becoming an increasingly pressing issue, with two major pillars being the reduction of car usage and the promotion of public transport. One way to approach both of these pillars is through the large number of daily commute trips in urban areas, and their modal split. Previous research gathered knowledge on influencing factors on the modal split mainly through travel surveys. We take a different approach by analysing the "raw" network and the time-optimised trips on a multi-modal graph. For the case study of Vienna, Austria we investigate how the option to use a private car influences the modal split of routes towards the city centre. Additionally, we compare the modal split across seven inner districts and we relate properties of the public transport network to the respective share of public transport. The results suggest that different districts have varying options of public transport connections towards the city centre, with a share of public transport between about 5% up to a share of 45%. This reveals areas where investments in public transport could reduce commute times to the city centre. Regarding network properties, our findings suggest, that it is not sufficient to analyse the joint public transport network. Instead, individual public transport modalities should be examined. We show that the network length and the direction of the lines towards the city centre influence the proportion of subway and tram in the modal split.

How to use?

The provided material includes data and scripts which were used for the analysis in the paper entitled "Revealing differences in public transport share through district-wise comparison and relating them to network properties", accepted for COSIT 2024, the 16th Conference on Spatial Information Theory.

It comprises three folders within the zip file:

1. code: Includes script files essential for conducting the analysis. The scripts are written in Python.
2. data: Contains the datasets for the analysis.
3. results: Includes the outcomes showcased in the associated paper.

Programming Language: Python  

For reproducibility read the README.txt; for necessary libraries refer to the requirements.txt. Both files are included in the zip folder.

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