The data and code scripts used for the analysis in the paper entitled "The Impact of Traffic Lights on Modal Split and Route Choice: A use-case in Vienna", submitted to AGILE (Association of Geographic Information Laboratories in Europe) 2024 Conference. It comprises three folders within the zip file:

Data: Contains the datasets for the analysis. Code: Includes script files essential for conducting the analysis. The scripts are written in Python. Results: Includes the outcomes showcased in the associated paper. Visualizations : Includes a jupyter notebook for the generated plots in the the associated paper. Programming Language: Python   For reproducibility read the README.txt file included in the zip folder. All data files are licensed under CC BY 4.0, all software is licensed under MIT License.

The transportation dynamics within a European city, Vienna, are examined using a multi-graph representation of the city's network. The focus is on time-optimized routing algorithms and the effects of altering the average waiting penalty at traffic lights. The impact of these modifications, whether an increase to 60, 90, or even 150 seconds or a decrease to 10 seconds, is observed in the selection of transportation modes and routes for identical origin and destination pairs. The investigation also extends to whether routes shift towards secondary street networks to avoid traffic lights as the waiting penalty increases. Experimental variations in average waiting time for cars aim to uncover detailed effects on transportation mode choices, route length and time changes, and variations in human energy expenditure. These findings could provide valuable insights into the transportation network and its possibilities and help in urban planning and policy development.  The results indicate a shift in transportation mode as the waiting penalty for cars at traffic lights increases, and in some instances, routes are redirected to roads of lower importance such as residential or service roads.