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 ms ^-1) and stable speeds (4.5 and 5.6 ms ^-1). 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.

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The objective of this study was to identify the dynamic response of the bicycle rider’s body during translational perturbations, in an effort to improve two-wheeler safety and comfort. A bicycle mock-up was equipped with sensors measuring three-dimensional seat and trunk accelerations and rider’s force responses at the seat, handlebars, and footpegs. The bicycle mock-up was driven by a hexapod motion platform that generated random noise perturbations in the range of 0–10 Hz. Twenty-four healthy male adults participated in this study. Responses are represented as frequency response functions capturing three-dimensional force interactions of the rider’s body at the seat, handlebars and footpegs in terms of apparent mass, and rider’s trunk motion (one-dimensional) as function of seat motion as seat-to-sternum transmissibility. Results showed that the vertical and longitudinal apparent mass for most of the bicycle interfaces followed the resonance of the seat-to-sternum transmissibility. A twice as high magnitude was observed at the resonance, although a more heavily damped system was apparent in the seat-to-sternum transmissibility. Resonant frequencies were considerably higher in the vertical direction compared to the longitudinal direction. Different dynamics were observed for the lateral measurements, where all magnitudes decreased after the base frequency, and no resonance was observed.@en

The aim of this thesis is to derive bicycle rider control models, based on experimental data, that mimic the rider in his balance control task at various forward speeds. These rider control models can help to understand cyclists falls, improve training techniques, assess the handling properties of new bicycle designs and create active balance control systems (e.g. steer assist). This thesis consists of 9 chapters; Chapter 1 introduces relevant background theory and identifies the research gap. Chapter 2 presents some effects of crosswind on the lateral dynamics of a bicycle and on rider control. The chapter gives an insight on how rider control modelling can be used to assess crosswind related falls. Simulations indicated that crosswind has a considerable effect on the stability and control of the bicycle. Increasing wind speed can make an uncontrolled bicycle resonate for all forward speeds. The rider control effort increases considerably and a constant steer torque is required to keep the bicycle at a straight heading. Chapter 3 investigates the dynamic response of the bicycle rider’s body during vertical, fore-and-aft and lateral perturbations in order to understand how riders are using postural control to restrain excessive movements and prevent falling off the seat. The analysis is presented by means of apparent mass (APMS) and seat-to-sternum transmissibility (STST) functions in the frequency domain. Measured forces at saddle, steer and pedals revealed that for each individual motion the rider applied forces in all three directions. Heave and surge motion interacted with each other and had similar responses. Sway showed totally different responses and weak interaction with the other two motions. Resonant frequencies were considerably higher in the vertical direction as compared to the longitudinal direction. Lateral measurements showed no resonance, and trunk postural control was evident in the APMS. The results of this chapter can be used to identify the parameters of biodynamic lumped human-machine models. Such models can support the development of more comfortable and safe bicycle designs and suspension systems. Chapter 4 presents the design and implementation of an instrumented steer-by-wire bicycle (SBW) that was designed and built at TU Delft bicycle laboratory. The SBW was used as a versatile experimental platform to capture the rider’s responses with (haptics on) and without steering torque feedback (haptics off) during lateral perturbation experiments. Simulations and testing of the steer-by-wire system indicated good tracking performance between 0-2.5 Hz and almost identical steer stiffness with the Carvallo Whipple bicycle model in a frequency range of 0-3 Hz and in a forward speed range of 0-10 m/s. The bicycle served its purpose successfully, the responses of the rider’s control actions with lateral perturbations were captured by means of impulse response functions (IRFs) in chapter 5. Results failed to indicate any statistically significant difference between the two steering configurations (haptics on/ off). Chapter 6 presents and validates a parametric rider control model using data presented in Chapter 5 and uses this model to further assess the effect of haptic feedback in the balance task of bicycling. Bicycle and rider mechanics have been modelled using the Carvallo Whipple bicycle model extended with rider inertia. A balancing and heading controller was added, capturing visual, vestibular and proprioceptive sensory information using feedback of roll angle, roll angle rate, heading angle, heading angle rate, steering angle and steering torque, taking into account muscular activation dynamics. Non-parametric and parametric model responses failed to indicate any statistically significant difference between the haptics on/off configurations. However, further analysing the haptic off configuration it became apparent that the rider still receives relevant torque feedback due to the inertia of the handlebars. The reduced feedback was proven to be adequate for the rider to control the bicycle without any major steering discrepancies. To further evaluate the effect of torque feedback in simulations we disconnected the handlebar torque feedback loop of the parametric rider model. In addition, we also disconnected the handlebar position and velocity feedback. Results showed that handlebar torque feedback is significantly important during the riding process. This knowledge might be crucial for the development of new safety systems that could further optimize bicycle handling and assist the rider’s steer control actions in critical situations preventing falls. Chapter 7 outlines the design and hardware selection for a bicycle simulator. The design requirements together with a detailed description of the hardware selection and testing are presented. The simulator was designed to explore human control behaviour in a safe environment. Preliminary tests showed that all subjects can balance and manoeuvre the bicycle when a simplified bicycle model is used to generate haptic feedback and project the dynamics in the virtual environment. Visual roll of the horizon turned out to be an effective tool for creating the illusion of physical roll but motion sickness was reported. This thesis ends with the discussion and conclusion Chapters 8, 9 highlighting the developed experimental facilities and the main findings of the research. The chapters herein investigate the effects of external perturbations on bicycle stability and human control using numerical modelling and experimental bicycles capable of measuring kinematics and rider applied forces. This interdisciplinary approach delves into the foundations of human control modelling from both a biomechanical and biomechatronics engineering perspective in an effort to improve cycling safety and reduce falls.@en

With the resurgence in bicycle ridership in the last decade and the continuous increase of electric bicycles in the streets a better understanding of bicycle rider behaviour is imperative to improve bicycle safety. Unfortunately, these studies are dangerous for the rider, given that the bicycle is a laterally unstable vehicle and most of the time in need for rider balance control. Moreover, the bicycle rider is very vulnerable and not easily protected against impact injuries. A bicycle simulator, on which the rider can balance and manoeuvre a bicycle within a simulated environment and interact with other simulated road users, would solve most of these issues. In this paper, we present a description of a recently build bicycle simulator at TU Delft, were mechanical and mechatronics aspects are discussed in detail.

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A common limitation in human factors research is that vehicle simulators often lack perceptual fidelity. Video games, on the other hand, are becoming increasingly realistic and may be a promising tool for simulator-based human factors research. In this work, we explored whether an off-the-shelf video game is suitable for research purposes. We used Grand Theft Auto (GTA) V combined with a Smart Eye DR120 eye tracker to measure eye movements of participants cycling in hazardous traffic situations. Twenty-seven participants encountered various situations representative of urban cycling, such as intersection crossings, a car leaving a parking spot in front of the cyclist, and the opening of a car door in front of the cyclist. Data of participants’ gaze on the computer monitor as recorded by the eye tracker were translated into 3D coordinates in the virtual world, as well as into semantic information regarding the object where the participant was focusing on. We conclude that GTA V allows for the collection of useful data for human factors research.@en

The bicycle, being unstable at low speed and marginally stable at high speed, is sensitive to lateral perturbations. One of the major lateral perturbations is crosswind, which can lead to accidents and fatalities. Here we investigate the effect of crosswind on the lateral dynamics and control of the bicycle in a wide range of forward speeds and various crosswinds, by means of computer model analysis and simulation. A low dimensional bicycle model is used together with experimentally identified rider control parameters. The crosswind forces are obtained from a recent experimental study. Analysis and simulation show that crosswind decreases the stability of the bicycle and is clearly a safety issue. @en

Since the 1800s, the design of bicycles involves a mechanical linkage between the handlebar and the fork assembly. Herein, we propose an innovation, where the traditional mechanical connection between the handlebar and fork is decoupled and replaced with sensors, servomo-tors and a microcontroller allowing artificial manipulation of the bicycle and steering dynamics. The purpose of our steer-by-wire bicycle is to investigate the influence of handlebar torque feedback on rider control in order to understand rider control on a bicycle. In addition, steer-by-wire bicycles have the potential to be used as stability-enhancing support systems which can improve cycling safety. We demonstrate the design and performance of the steer-by-wire bicycle in computer simulations as well as real-life tests. Preliminary rider tests showed a per-ceived near-to-identical behaviour of the steer-by-wire system to a mechanical connection at steering frequencies below 3 Hz.@en

Recent years have seen an increase in cycling as a transport mode in urban centers. This has spurred an interest in the use of bicycle simulators to study cyclist behavior [1, 2, 3, 4]. However, few implement a model based approach that couples the bicycle roll and steer in a realistic manner [5]. Balancing is a key task in cycling and we aimed to develop a simulator that allows us to study the effect of balance on the rider’s higher level cognitive decisions.@en