Sensor-based Training Optimization of a Cyclist Group

Abstract

Determining the optimal exercise intensity is a crucial factor to increase performance in professional cycling. Novel sensor technologies allow to optimize the training not only for an individual cyclist but also for an entire training group. A sensor-based assisted bicycle trainer (ABT) system with a control algorithm has been developed at the University of Kaiserslautern to optimize the group training in cycling. The focus of this paper is on the development of the control algorithm, a model predictive controller (MPC) for the optimization of the group training. The controller predicts the heart rate of the cyclists based on individualized heart rate models and regulates the group training by advising cyclists to change the position in the group, to adjust the group speed, or to split the group in such a way that each cyclist can meet his training plan as exactly as possible.