Rider control in bicycling is modeled by first adding the rider as a passive mechanism to the Whipple bicycle model. Next, for the rider control model a linear PID controller with and without delay is assumed, where the control inputs are the bicycle roll and steer angle with their higher derivatives, and the control output is the action-reaction steer torque applied by the rider at the handle bars. The experimental data is obtained from riding a bicycle on a narrow treadmill while applying an intermitted lateral perturbation by means of an impulse force applied at the seat post. The experiments are conducted in both the stable and the unstable forward speed range. After some filtering, a parametric control model is fitted to the data. Finally, the gains of this control model are used to identify the specific optimal control LQR cost function which the rider is using to control the bicycle on the treadmill at the various forward speeds.@en

A method is presented to estimate and measure the geometry, mass, centers of mass and the moments of inertia of a typical bicycle and rider. The results are presented in a format for ease of use with the benchmark bicycle model [1 ]. Example numerical data is also presented for a typical male rider and city bicycle.@en

The purpose of this study is to identify human control actions in normal bicycling. The task under study is the stabilization of the mostly unstable lateral motion of the bicycle-rider system. This is done by visual observation of the rider and measuring the vehicle motions. The observations show that very little upper-body lean occurs and that stabilization is done by steering control actions only. However, at very low forward speed a second control is introduced to the system: knee movement. Moreover, all control actions are performed at the pedaling frequency, whilst the amplitude of the steering motion increases rapidly with decreasing forward speed.@en