Author: Ashtiani, Faraz; Sreedhara, Vijay Sarthy M; Vahidi, Ardalan; Hutchison, Randolph; Mocko, Gregory
Title: Optimal Pacing of a Cyclist in a Time Trial Based on Experimentally Calibrated Models of Fatigue and Recovery Cord-id: lws2oeye Document date: 2020_7_20
ID: lws2oeye
Snippet: In this paper, we first use experimental data from six human subjects to validate and calibrate our proposed dynamic models for fatigue and recovery of cyclists in [1]. These models are used to formulate pacing strategy of a cyclist during a time trial as an optimal control problem. We first derive the optimal strategy in a time-trial using Pontryagin's Minimum Principle. We then resort to numerical solution via Dynamic Programming (DP) for simulating one of the subjects on four strategically di
Document: In this paper, we first use experimental data from six human subjects to validate and calibrate our proposed dynamic models for fatigue and recovery of cyclists in [1]. These models are used to formulate pacing strategy of a cyclist during a time trial as an optimal control problem. We first derive the optimal strategy in a time-trial using Pontryagin's Minimum Principle. We then resort to numerical solution via Dynamic Programming (DP) for simulating one of the subjects on four strategically different courses including stage 13 of the 2019 Tour de France. The DP simulation results confirm our analytical findings and also show reduced time over experimental results of the self-paced subject who is a competitive cyclist.
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