Bicycle Driving Behaviour in Germany: A Driving Parameter Dataset Across 100 Cities based on CITY CYCLING GPS trajectories
Documentation of the data | please see dataset description pdf(s) or the example of R-Code for data analysis attached. | |
Countries to which the data refer | GERMANY | |
References to related material | Lißner, S., Huber, S., v. Harten, M.: Influence of the cycling campaign CITY CYCLING on cycling behaviour in Germany, European Transport Conference. Mailand, 07.-09.09.2022, https://doi.org/10.26128/2023.65 (2023) | |
References to related material | Data in Brief | |
Description of the data | The data were collected during the NRVP project ‘MoveOn – Cycling Data for Germany’ and processed for 109 municipalities in Germany during the project ‘RiD – Cycling Behaviour in Germany’. The GPS trajectories originate from the annual cycling campaign City Cycling, German "Stadtradeln" (www.stadtradeln.de). This campaign is organized and promoted by participating cities and takes place over a freely selectable three-week period between May 1 and September 30. During this period, participants are encouraged to refrain from car use and instead use bicycles for their daily trips. Approximately 40% of participants record their trips using a smartphone app. The participant structure is described in the following publication: Lißner, S., Huber, S., v. Harten, M.: Influence of the cycling campaign CITY CYCLING on cycling behaviour in Germany, European Transport Conference. Mailand, 07.-09.09.2022, https://doi.org/10.26128/2023.65 (2023) Additionally a list of all relevant municipalities with secondary data is included and can be linked to the Trips via the variable 'ARS'. | |
Type of the data | Dataset | |
Total size of the dataset | 2681147860 | |
Author | Lissner, Sven | |
Author | Lindemann, Paul | |
Author | Huber, Stefan | |
Upload date | 2026-04-14T08:40:35Z | |
Publication date | 2026-04-14T08:40:35Z | |
Data of data creation | 2025 | |
Publication date | 2026-04-14 | |
Abstract of the dataset | The dataset presented was created as part of the cycling campaign City Cycling in Germany during the years 2022–2024. The campaign involved more than 3,000 municipalities across the entire country. Over a three-week period, which participants could freely select between May 1 and September 30, the goal was to replace as many car trips as possible with bicycle trips. Participants could use a smartphone application to record their data. The recorded GPS trajectories were transferred from the smartphone to a data lake as a database dump and were then regularly retrieved by a backend server for data pre-processing. During this process, trips, activities, modes of transport, and driving modes were identified. For the dataset presented, individual trajectories were processed with respect to several core variables characterizing cycling behaviour. The dataset was spatially filtered beforehand. A total of 109 cities and municipalities were selected based on variables such as population size, the number of campaign participants, topography, the modal share of cycling, and geographic location within Germany, in order to obtain a representative impression of cycling behaviour. As a result, more than 8 million trip records with 37 distinct variables were collected over the data years 2022–2024.The dataset was created and analysed within the scope of the DFG funded project "Bicycle Driving Behaviour in Germany", Project number 514587991 | |
Public reference to this page | https://opara.zih.tu-dresden.de/handle/123456789/2167 | |
Public reference to this page | https://doi.org/10.25532/OPARA-1150 | |
Publisher | Technische Universität Dresden | |
Licence | Attribution-NonCommercial 4.0 International | en |
URI of the licence text | http://creativecommons.org/licenses/by-nc/4.0/ | |
Specification of the discipline(s) | 4::45::410::410-02 | |
Title of the dataset | Bicycle Driving Behaviour in Germany: A Driving Parameter Dataset Across 100 Cities based on CITY CYCLING GPS trajectories | |
Research instruments | Crowdsourcing - different smartphone types | |
Software | Rust, Python, R+ | |
Software | Python, Rust | |
Project abstract | The research project "RiD-Radverkehrsverhalten in Deutschland" investigates cycling behaviour in Germany using a multi-criteria approach, with a particular focus on understanding variations in riding behaviour across different spatial and social contexts. Existing research is often based on household surveys or small and spatially limited datasets, which lack detailed information on actual riding dynamics and are insufficient for comprehensive behavioural analysis. To overcome these limitations, the project draws on a large-scale GPS dataset comprising more than three million cycling trips from over 1,400 German municipalities. The primary objective is to analyse how individual characteristics—such as age, gender, and trip purpose—as well as environmental and urban factors—such as city size, infrastructure, and topography—affect cycling behaviour. Particular attention is given to behavioural indicators derived from GPS data, including speed, acceleration, braking patterns, stop frequency, and route-related detours. These indicators enable a detailed, empirically grounded assessment of how cyclists interact with their environment in everyday travel situations. | |
Funding Acknowledgement | This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project number(s) 514587991 | |
Project title | Bicycle Driving Behaviour in Germany / RiD-Radverkehrsverhalten in Deutschland |
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