Controlled Experiment Investigating Micromobility Traffic Flow Interactions: Setup, Implementation, and Preliminary Results

Yufei Yuan; Wenyi Zhang; Sicong Zhu; Qing Lan; Winnie Daamen

doi:10.17815/CD.2026.192

Authors

Yufei Yuan Delft University of Technology, Faculty of Civil Engineering and Geosciences, Delft, The Netherlands
Wenyi Zhang Delft University of Technology, Faculty of Civil Engineering and Geosciences, Delft, The Netherlands
Sicong Zhu Beijing Jiaotong University, Beijing, China
Qing Lan Hebei University of Water Resources and Electric Engineering, China
Winnie Daamen Delft University of Technology, Faculty of Civil Engineering and Geosciences, Delft, The Netherlands

DOI:

https://doi.org/10.17815/CD.2026.192

Keywords:

Micromobilty, Controlled experiment, Operational behavior, Stability, Interactive maneuver

Abstract

Travel patterns and lifestyles in cities around the world have changed in recent years due to the strong growth of travel modes commonly referred to as micromobility, including e-bike, e-scooter, and e-moped. Understanding micromobility flow dynamics is essential for designing safer, more efficient, and better-integrated urban transport systems that accommodate the unique behaviors of these emerging modes. Micromobility flow research at the operational behavioral level is limited, mainly due to the lack of empirical data. To overcome this data shortage, we performed a controlled experiment to observe one-on-one interactive behaviors on a Chinese university campus. This paper describes the approach for setting up and implementing such an experiment, from the motivation of its design using a conceptual model describing interaction behavior to the adjustments required during the experiment. The main contribution of this paper is, therefore, to collect such a dataset and to be used as a reference in future experimental data collections on micromobility flow. Moreover, we provide a qualitative description of experiences observed during the experiment. Preliminary insight into overtaking behavior between e-bike and e-scooter is further elaborated to unravel their unique operational movement and to demonstrate the data potential. Finally, we emphasize that the data potential also holds for future research into understanding and modeling other operational riding behaviors and the stability of micromobility users.

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