Dangerous ground or peaceful coexistence? Analysing cycling behaviour adaption on shared paths using crowdsourced GPS cycling data

Stefan Huber; Sven Lißner

doi:10.55329/hlqo1058

Authors

Stefan Huber Dresden University of Technology, Germany https://orcid.org/0000-0002-3399-3323
Sven Lißner Dresden University of Technology, Germany https://orcid.org/0000-0002-5497-3698

DOI:

https://doi.org/10.55329/hlqo1058

Keywords:

cycling behaviour adaptation, cyclist-pedestrian interaction, GPS data, shared space, Western Europe

Abstract

Walking and cycling are increasingly promoted as sustainable and health-enhancing modes, yet rising volumes in shared urban spaces intensify interactions and perceived conflict potential. While numerous studies show that pedestrian–cyclist interactions rarely result in safety-critical incidents, behavioural adaptations, such as speed reduction and crash avoiding manoeuvres, plays a key role in mitigating risk and increasing perceived safety. As most existing research relies on data-intensive methods such as video observations or simulations, this paper explores the potential of large-scale GPS cycling data to analyse conflict potential and behavioural adaptation in areas shared spaces used by pedestrians and cyclists. Considering the pedestrian zone ‘Prague Street’ in Dresden, Germany, as a case study, we combine GPS trajectories from the 2024th CITY CYCLING campaign with a time-based proxy data for pedestrian density. The results show clear behavioural adaptation: during periods of high pedestrian activity, cyclist do not only use other routes, but cycling volumes decrease and average speeds are reduced by approximately 5–8 km/h. The findings confirm established relationships between density, speed, and conflict mitigation, while highlighting both the opportunities and limitations of GPS based approaches. The study demonstrates that such data can serve as a scalable screening tool for assessing behavioural adaptation and potential risk in shared spaces. We further propose a model considering most relevant data to comprehensively analyse risk potential in near future.

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Author Biographies

Stefan Huber, Dresden University of Technology, Germany

Stefan Huber is a versatile senior researcher with expertise at the intersection of transport geography (Diploma) and traffic engineering (PhD). Since 2012, he dedicated his research, teaching, and consulting efforts to the analysis and modelling of traffic behaviour. In his doctoral thesis, he analysed bicycle route choice preferences using GPS data. He is head of the research group ‘Climate Friendly Mobility’ and co-chairs the BIKELAB at the Dresden University of Technology.

CRediT contribution: Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing–original draft, Writing–review & editing.

Sven Lißner, Dresden University of Technology, Germany

Sven Lißner is a traffic engineer and senior researcher with expertise in the field of bicycle planning, big data and traffic behaviour analysis. Since 2013, he dedicated his research, teaching, and consulting efforts to the analysis of cycling behaviour. In his doctoral thesis, he analysed cycling behaviour using GPS data. He is head of the bicycle research group ‘BIKELAB’ and is deputy of the chair of Transport Ecology at the Dresden University of Technology.

CRediT contribution: Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Validation, Visualization, Writing–review & editing.

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