Rider control identification in cycling taking into account steering torque feedback and sensory delays

• Published in: Vehicle system dynamics Vol. 61; no. 1; pp. 200 - 224
• Main Authors: Dialynas, Georgios, Christoforidis, Christos, Happee, Riender, Schwab, A.L.
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 02-01-2023; Taylor & Francis Ltd
• Subjects: Algorithms; balance; Bicycle dynamics; Bicycles; Bicycling; Controllers; Cruise control; Drive by wire; Electric drives; Feedback; Human response; Impulse response; manual control; Response functions; rider model; Rolling motion; Steering; system identification; Torque
• ISSN: 0042-3114; 1744-5159
• DOI: 10.1080/00423114.2022.2048865

Experiments and human rider models were used to investigate bicycle balance and steering using visuo/vestibular motion and proprioceptive feedback taking into account sensory delays. An instrumented steer-by-wire bicycle designed and built at the TU Delft bicycle laboratory was used to investigate rider responses with and with reduced steering torque feedback. Steering responses and bicycle motions were measured perturbing balance with impulsive forces at the seat post. The rider was commanded to follow a straight lane at unstable (2.6 and 3.7 
) and stable speeds (4.5 and 5.6
). Bicycle speed was controlled with an electric drive and cruise control. Balance and steering responses could well be captured by linear impulse response functions which were consistent across participants. The impulse response functions were used to develop neuromuscular control models capturing rider-bicycle interaction. The Carvallo-Whipple bicycle model was extended with rider inertia and an additional degree of freedom for the steer-by-wire system. Rider behaviour was modelled as a balance and heading controller. This controller used visuo/vestibular motion feedback of roll angle and roll rate, heading angle and heading rate, and proprioceptive feedback of steering angle, velocity and torque. Results showed that the rider model followed the necessary stability condition of steer into the fall and was capable of stabilising the bicycle. Sensory delays had a negative effect on the model fit, which was resolved with an internal model and prediction algorithm. A model without steer angle and steer velocity feedback could not well capture the human response at the highest speeds and the absence of torque feedback had similar effects for all speeds, supporting the relevance of steer angle and torque feedback in bicycle control.