Gender differences in cycling motions: On objective functions for urban cycling

Societal challenges such as climate change and the energy crisis are putting bicycles at the centre of many people's mobility considerations ‐ but not all. In addition to the need for improved infrastructure, stability and comfort when cycling also play a major role. Simulations offer the possibility to investigate the influence of biometric differences on comfort and stability more cost‐effectively than the measurement methods currently used for bike fitting. Bicycle dynamics and multibody simulation of cycling motions have been the subject of research for a long time. Often data‐driven models are used that follow pre‐established measurement data. Moreover, optimal control simulations for competitive sports are available, where for example, the travel distance during a given time is maximised. However, such models are usually based on the biometric data of an average 18–25 year old male, while the influence of gender differences on cycling motions are rarely explored. Yielding towards closing this gender data gap, we use a discrete mechanics and optimal control framework (DMOCC), which benefits from its structure preserving formulation and has been successfully used for biomechanical applications before. The implemented multibody model of a leg performing a cycling motion can be adapted to individual 3D scans via the geometry parameters and the bounds on the joint angles and torques, providing the possibility to investigate the influence of biometric diversity on the resulting motions. In this first approach, we discuss several possibilities to formulate appropriate objective functions for cycling. The final aim of this study is to supplement a given bike frame by software chosen adaptations so that it optimally fits to individual biometric conditions, thus increasing comfort, the sense of safety and performance, which ultimately enables greater participation in the mobility transition for women, children, and seniors.