Up to now, not much is known about how humans control bicycles, especially when subject to large perturbations. In order to learn more about the extent to which these perturbations can be handled, a new experimental setup is required, which can deliver large perturbations to cyclists and bring them to fall. This thesis describes the detailed design and evaluation of such a setup. Several requirements are formulated regarding different experiment aspects that the setup must adhere to. The proposed design consists of a treadmill on which a subject rides a bicycle. Ropes are guided from the ends of the bicycle’s handlebar toward the front and back of the setup, where they are attached to four motor units of a robotic rope-pulling system. Based on a feed-forward conversion added with PI force feedback control, a shared controller commands the motors to maintain a tracking force or perturb the cyclist by applying a net torque on the handlebar for a short time. An active safety harness is the main feature that prevents the subject from harm. Meanwhile, motion capture recordings of strategically placed passive markers and data from inertial measurement units on the bicycle are collected. With appropriate processing, the angles and angular velocities that describe the dynamics and control of the bicycle-rider system can be obtained from these measurements. The force data is also collected, by the controller. Interesting results that can be obtained with this setup include the probabilities to fall after perturbations of variable forces and the data required to evaluate the equations of motions of the bicycle-rider system during and shortly after a perturbation. This can be used to provide a baseline against which future bicycles can be compared and it is useful for validating rider models. The experiment shows consistent performance and generates high quality measurements. Neither the 12 pilot participants nor the 26 subjects who participated in follow-up experiments encountered any safety issues. The experiment could even be improved by resolving issues regarding the motor behaviour and CPU overloads. The workload of the experiment operators could be decreased if intervention of the safety harness was trained on cycling and coupled to deactivation of the treadmill. A next step would be to automate the data processing by developing a classifier that distinguishes recoveries from falls.

Bicycles connected to the internet present an opportunity for integrated accident detection and geolocation. Such a system can reduce the time it takes for help to arrive by automatically alerting predefined contacts with the location of the accident. I developed a systematic method for the practical implementation of bicycle accident detection in connected bicycles and present the performance of a prototype system. The method uses accelerometer and gyroscopic measurements as well as localization and velocity estimations. Supplementing existing research, a bicycle accident detection system is validated on normal cycling, edge cases, and three types of single bicycle accidents with constraints set by a bicycle manufacturer. Edge cases are movements of a bicycle that occur during regular usage, but can not be described by normal cycling. This method uses a data¬driven approach. For the prototype system, the input signals are collected during 71 different simulated accidents and 54 hours of normal cycling and edge cases. A three¬layer detection algorithm determines if an accident has occurred and sends the last known location to a set of predefined contacts. Multiple combinations of thresholds and classification algorithms are compared. This resulted in a prototype system with a K¬Nearest Neighbours classifier which detects 75% of accidents. Normal cycling and edge cases are correctly detected 99.997% of the time. From all warnings send, 85.7% are true accidents. The prototype system proves that the proposed method can be used to integrate reliable accident detection in connected bicycles. Bicycles with such a system automatically inform emergency contacts with a message containing the location of the accident, in a time where every second counts.

Introduction During Bicycle Motocross races (BMX SX), the start has been proven to be crucial for good overall performance [1]. Riders reaching the bottom of the eight meter high starting ramp in front of the pack, have a favorable position to perform the first jump and can pick the most ideal line through the first corner. The chances of getting involved in collisions with other riders are also highly reduced. Since riders start behind a gate, the anticipation and timing with respect to this gate movement are most important [2]. Most scientific research regarding the BMX SX gate start is focused on defining the performance indicators for a fast start [2] [3] [4] or using in-field experiments
to evaluate the effects of minor changes to the bicycle design [5] [6]. However, using the results of these studies to actually improve the start performance would require extensive training using these new conditions. Using predictive simulations, these adaptations can be evaluated without practicing and can thus have a huge contribution to enhancing the gate start technique. However, before these simulation models can have any impact, they must be thoroughly analyzed to prove their validity.
Objective The main goal for this study was to construct a biomechanical model for the BMX SX gate start which could reproduce experimental data. The model must be able to track kinematic data with an accuracy of less than 5% while also match the main kinetic characteristics without tracking those. The kinetic profiles should show the same peak pattern as is commonly seen in cycling and must not differ more than 10% with experimental data. When these goals are reached, this model could serve as a framework for future applications within BMX SX gate start research or other cycling disciplines.
Method A nine degree-of-freedom biomechanical planar model was created within the open-source software package OpenSim [7] [8]. The model consists out of the ground surface, the gate, the BMX SX bicycle, and the rider. The latter two are connected using kinematic constraints on the feet and pedals. The upper body is connected to the frame by a single arm. The model is driven by eight optimal torque actuators located at the hip, knee, ankle, shoulder, and elbow joints. The contact dynamics of the wheels to the ground and the gate are included using the Hunt-Crossley model [9]. Moco [10], a direct collocation package for OpenSim, was used to solve the kinematic tracking optimization problem. The kinematic data was taken from a prior study by Melle van Dilgt [11] who captured three-dimensional kinematics of an elite female BMX SX athlete of the Dutch National team using an Xsens suit (Xsens Technologies, Enschede, The Netherlands). This IMU data was projected on the planar model using OpenSense, a tool within OpenSim that converts experimental IMU data into the model’s generalized coordinates. Simulation outcomes were compared to kinetic data collected by Hylke van Grieken [4], who used a fully instrumented bicycle including special cranks (Axis2D, Swift Performance, Brisbane, Australia) to capture the pedal forces executed during in-field experiments with a sample rate of 100 Hz. These experiments used the same elite participant but were taken on a different day using a different bicycle.
Results The optimized tracking simulation showed close agreement with experimental kinematic data, showing an average root mean squared error (RMSE) of 0.337° or 0.52% for the six leg joints. For the tracking of the crank angle and the horizontal displacement of the bicycle similar results were found (RMSEs of 0.079% and 0.6% respectively). Simulated crank torque peak values were off by 4.4%, 7.7%, and 5.1% for the first, second and third torque peak respectively. Overall the crank torque was reproduced with an RMSE of 18%.
Conclusion This work shows the suitability of the designed model for future applications in predictive simulation of the BMX SX gate start. The model can be used to study a wide range of "what-if" scenarios and could lead to the improvement of gate start performance. The way the model is constructed, the main building blocks can be adjusted to more accurate, but also more complex, components if desired.

Bicycle simulator research has been the subject of considerable research, however, few of these attempts have integrated direct balance control and enough freedom of motion to deliver a real-world kinematic cycling experience. In this study, the B.I.K.E. (Bicycle Intrinsic Kinematics Emulator) system, a kinematic bicycle simulator, is developed with the purpose of letting its users experience realistic kinematic motion, which are: steer, roll, yaw and sway motions. This study validates the developed simulator by performing a kinematic comparison of bicycle motion among 15 participants of varying age and mass, and performs an initial subjective study to investigate effects common to indoor vehicle simulation. Manoeuvres performed by the participants are straight-line cycling, at low (5 km/h) to high (40 km/h) velocities, as well as performing a zig-zagging motion. The results show that users can successfully rely on existing bicycle skills to use the simulator. They also show that, in the kinematic sense, the simulator performs similarly to an outdoor bicycle, particularly at velocities below 35 km/h, but more work is needed in improving the vehicle model and control algorithm to accurately cover low to high-velocity cycling. Subjectively speaking, the simulator performs better than existing static solutions, but more work will be required to make the riding experience feel like real outdoor cycling.

Minimum-time optimisation has been used extensively in motorsports, such as Formula One racing. Using minimum-time optimisation, the ideal racing line as well as control strategies such as braking strategies can be found. This is interesting, as Reijne et al have shown that cyclists apply diverse strategies, specifically during a descent [1]. With minimum-time optimisation, it is possible to compare a riders performance to the theoretically optimal performance. The results from such optimisations can be used to help with training, as well as improve and test equipment design.

This work describes a free-trajectory steady motion control optimisation for the descent of elite cyclists. The prediction of the individual descent performance was formulated as an optimal control problem and solved with a direct approach to finding optimal cornering and braking strategies that yield the shortest descent time. While the state equations were kept simple (3 variables only), more elaborated performance limits were represented by g-g diagrams. Such diagrams represent the longitudinal, lateral, and combined acceleration limits for cyclists. A method to numerically derive g-g diagrams for cyclists driving on 3D tracks was designed. In this method, a tire model, power limit, and steady motion equations for a cyclist are used to determine the control space. The bicycle and cyclist are modeled as a single rigid body, the tire friction model is simplified as a friction circle, and the wind speed is considered to be zero at all times. As for the 3D road geometry effects, all possible effects are considered in the method, except lateral road curvature. The resulting method
provides g-g diagrams as a function of 8 local geometry and state variables.

The optimisation model was tested against the velocity and trajectory output data measured on Team Sunweb professional cyclists at the L218 descent in Germany. The resulting trajectory was similar to the trajectory ridden by elite cyclists. The velocity profile showed large differences, which are a result of a combination of inaccurate track data, differences in friction coefficient estimation, and safety margins applied by the cyclists. The results show that descent performance can be improved, as even when adhering to safety margins harder braking is possible. Overall, the model responds as expected to changes in track, environment, and bicycle/rider parameters.

Steps can be made towards better implementation of the g-g diagrams in the minimum-time optimisation. Furthermore, a more accurate tire model and power model can improve the model and extend its applications. The presented model can be used for qualitative descent analyses, and facilitate the training of elite cyclists.

[1] A.L. Schwab, M.M. Reijne, D.J.J. Bregman, Measuring and comparing descend in elite race cycling with a perspective on real-time feedback for improving individual performance. In Multidisciplinary Digital Publishing Institute Proceedings, volume 2, page 262, 2018.

Statistics show that cycling accidents have the biggest (and increasing) contribution to the overall number of hospital visits related to traffic accidents in the Netherlands. In the majority of these cycling accidents, no other road users are involved. Because the majority of the cycling accidents are so-called single vehicle accidents, understanding the control behaviour of the cyclist can spark new insight in to effective preventive measures. This thesis aims to achieve that by reviewing the current state-of-the-art in bicycle-rider control research and subsequently proposing a new rider control model that is developed using system identification techniques. The results of a literature review are used to propose a novel bicycle-rider control model structure that includes realistic human neural and cognitive characteristics to predict control behaviour for stabilizing a bicycle. Sensory integration is modelled with a Kalman filter, and human control and prediction capabilities are mimicked with a Linear-Quadratic-Regulator (LQR) and Tapped-Delay-Line predictor, respectively. Human neuromuscular dynamics are included in the model structure in the form of a second order filter and the bicycle dynamics are modelled with the linear Whipple bicycle model. Two different experimental data sets during which cyclists are laterally (roll) perturbed on instrumented bicycles are used: one collected at the UC Davis on both a horse treadmill and in a sports pavilion and the other collected at the TU Delft on a public cycling path (without other road users). The human steer response to the perturbation is separated from other effects caused by unknown disturbances and noise with a non-parametric Finite-Impulse-Response model. A structured system identification approach is used to determine the final free parameter set that approximates the non-parametric model in the best way possible. The data sets are split in a train set and a test set. The model structure is fitted to the train set. The predictive performance is verified by applying the resulting model to the test set. For the UC Davis data, the resulting model has one rider dependent parameter that describes human bicycle-balancing control behaviour for the entire evaluated forward velocity range (2-8 m/s). This parameter is the weight placed on the roll angle in the LQR control algorithm. The single-run training performance in terms of Variance-Accounted-For (VAF) with the non-parametric model reaches up to 97 %. Test performance incurred a VAF drop, on average, of around 10 %. The steer responses of the TU Delft experiment can be predicted with a model that has two rider dependent parameters: the weights placed on the roll angle and roll rate in LQR control algorithm. Training performance reaches up till 83 % and test performance incurred a VAF drop, on average, of around 7%. Promising future directions are the inclusion of a passive rider model to further increase the fidelity of the model. The investigation of the stability margins of the proposed bicycle-rider controller and their sensitivity to bicycle design and/or human sensory and cognitive decline can lead to tailored measures to reduce the injury rate among cyclists.

Part of the goal of Europe’s Strategy Vision Zero is to eliminate all severe cycling accidents in Europe by 2030. The majority of cycling accidents are single vehicle accidents; this term indicates the absence of collisions with other road participants and implies a fall of the cyclist. Research has shown that mainly elderly cyclists are victim to those accidents. An untested hypothesis is that their slowed motor responses are one of the main reasons behind this. This study aims to address this hypothesis by studying the influence of neural time delay on the lateral stability of bicycle-rider systems. In this study, the slowed motor responses are represented by single neural time delay values. The influence is quantified by the sizes of the identified basins of attraction of stability (BoA). The BoA contains the set of finite lateral disturbances for which stability is
retained and is acquired via numerical integration. Binary threshold criteria are used to determine the stability of the solution. The bicycle-rider system consists of two components: a bicycle model and a rider model. The bicycle is modelled using the Whipple(-Carvallo) bicycle model with the set of non-linear equations derived by Basu-Mandal [2]. The rider is modelled using an implicit experimentally validated model from literature [31]. This model consists of a PID controller with full state feedback, neuro-muscular dynamics and, in this study, is extended to include nonzero time delay. The neural time delay value of a young cyclist has been based on literature [4]. The value is doubled to model an older cyclist. The control strategy of the young cyclist is identified using system identification techniques. The basins of the young and old cyclist are compared to study the detrimental effect of time delay on lateral stability in cycling. It declined over 80% when the time delay was doubled. The human’s ability to adapt its control to circumstances has been considered by repeating the control identification process for the rider which suffers from double the time delay. With respect to the young cyclist, a decline of over 50% was observed. Therefore, the results strongly support the hypothesis. Further research should focus on increasing complexity of the rider model to include preview and prediction. In this way, the influence of slowed motor responses can be mapped more clearly.
A secondary objective of this thesis is the preliminary development of a steer assist control model to aid the elderly cyclist balance during cycling. This development builds further on a simple control model from literature [29] which uses roll angle feedback. As a result, a nonlinear velocity dependent roll rate feedback control law was developed. This control law yields a constant basin height over the commonly used velocity range of cyclists. This height indicates the maximum allowable steer rate perturbations the bicycle-steer assist system could handle and is approximately the same height as what was identified for
a young cyclist. Future research is required for improving the steer assist. This means adding maximum allowable control torque, sensorial time delays and trajectory tracking

A model for the team time trial in road cycling is devised adn optimizations are caried out to find the most optimal strategy over different terain

The objective of this research is to identify the passive response of the rider’s body to translational and rotational random perturbations. A custom made bicycle mock-up equipped with a system of sensors has been developed, capable of measuring the linear accelerations, angular velocity and the rider’s force responses in all translational axes of all bicycle interfaces. The bicycle mock-up is driven by a hexapod that generates coloured noise perturbations in the range 0–10 Hz. Twenty four healthy male adults participated in this study and gave informed consent according to the guidelines of the ethical committee of Delft University of Technology. The responses of all subjects are represented in the frequency domain by means of frequency response functions. More specific, the interaction of the rider’s body at the seat, foot pegs and handlebars are expressed in terms of apparent mass and as seat-to-sternum transmissibility functions (STS). The apparent mass and STS transfer functions for the surge and heave motion suggest a simple underlying passive response system. For surge, a clear resonance peak was found at 2 Hz for nearly all interfaces and directions, whereas, for the heave motion a clear resonance peak at 5 Hz was found for the seat and handlebars and a resonance peak at 6 Hz for the foot pegs. The apparent mass of the pitch and yaw motion also suggest, to a certain extend, simple passive dynamics after 1 Hz characterised by resonance peaks at 1.8 and 2.3 Hz, respectively. Only the corresponding yaw STS transfer function showed a resonance peak around 2.3 Hz, as well. The sway and roll motion do not suggest simple passive dynamics showing similar trends in apparent mass characterised by an ever-decreasing gain and no resonance peaks. Finally, the surge, heave, pitch and yaw apparent mass transfer functions suggest that higher body mass in general yields higher peak magnitude and lower resonance frequency. This effect was most apparent for the surge motion.

Brake squeal is a well know problem in the bicycle industry. Most of the time brake squeal occurs due to wear of the brake components and/or in certain environmental conditions (e.g. rain and dirt). Bicycle brake squeal is often solved by trial and error. Compared to automotive industry, there is not much research done on the fundamental cause of bicycle brake squeal. As a result, bicycle brands are not able to guarantee that their bicycles will not produce squeal noise over time. The goal of this graduation project is to get more insight into the fundamental cause of bicycle brake squeal and to find the crucial parameters that influence bicycle brake squeal.

A lot of research has been done on the behaviour of pneumatic tyres and this has led to various tyre models and a lot of measurement data. However, in the specific field of bicycle tyres, not so much measurement data is available. However, in 2013 Andrew Dressel received the Degree of Doctor of Philosophy in Engineering at the University of Wisconsin-Milwaukee by presenting his research: Measuring and modeling the mechanical properties of bicycle tires. In this research he did a lot of measurements with multiple bicycle tyre brands and models under different conditions. The results from these measurements are interesting to use for modelling purposes. The goal of this research is to find out if it is possible to estimate the bicycle tyre behaviour in terms of vertical stiffness, cornering stiffness and camber stiffness based on known parameters like the inflation pressure, tyre width, rim width, vertical load and the rubber compound using a tyre model. An important part of this thesis are tyre models. The measurement data will be analysed using various tyre models. The first used tyre model is the brush model. This model uses a single material parameter and it turns out that this is too less to be able to extract clear relations between the tyre behaviour and the known parameters like inflation pressure, tyre width and rim width. The second tyre model that is used is the enhanced string model. This model is an extension of the brush model. This model has three material parameters for the vertical direction and also three material parameters for the lateral direction. Investigating this model shows that there is reasonable suspicion to assume that one of the model parameters represents the inflation pressure. In order to find the material parameters for every tyre, inflation pressure and normal load combination a parameter optimisation is required. The results from this parameter optimisation show that the suspected model parameter is actually not related to the inflation pressure. When the obtained model parameters from the optimisation are put back into the tyre model interesting results are acquired, because the model output agrees fairly well with the measurement data. This is unexpected because the model parameters were differing a lot depending on how they were obtained, e.g. obtaining the parameters from cornering stiffness or from camber stiffness. The answer to the research question is no. In order to extract relations between the model parameters and the tyres behaviour depending on their measurable properties, a lot more complete measurements are needed. The whole idea was to be able to estimate tyre behaviour without the need of extensive testing. This still might be possible, but in order to to that a lot more measurements are needed first. These measurements should create a baseline of model parameters which can be used to estimate the model parameters of unmeasured tyres.

This exploration study focuses on the braking behaviour of World Tour cyclists during a descent. For this study, 8 riders descended over 6 trials using a ‘sensor bike’. As part of this particular study, a novel brake sensor is developed and validated in practice. The sensor package can be transferred between bicycles, allowing each rider to use his own bicycle. Results of the exploration study indicate that for the chosen descent, braking and cornering skills are not decisive for overall time over the descent. However, significant time differences are found for the corner which is analysed. Time difference reported over this corner are approximately one second. With a shortest cornering time of 10.14 seconds this is a significant difference. The brake behaviour of theWorld Tour cyclists could be split into two distinct braking strategies: • ’stop brake late’ ( where braking is stopped late and well into the turn). • ’stop brake early’ (where braking is stopped before or early in the turn). It was found in this study that the best brake strategy is ’stop brake late’. The peak brake forces measured during the descent are much lower than the maximum brake forces reported in literature. This implies, that performance can still be improved by increasing brake forces at the first part of the braking action, so the braking can start later. The results found in this study can contribute to optimise braking and cornering skills of riders by explaining and showing where improvements can be found. An additional result is that the brake sensor revealed unexpected brake rub at certain parts of the descent, especially when riders are accelerating. Eliminating this brake rub, can improve rider performance. The riders also shows clear signs of learning behaviour as can be observed in the obtained data. For future research it is recommended to add a speed sensor to the sensor package. Recommended small improvements for the brake sensor are identified. Using this improved sensor package, trials could be rehearsed on a steeper descent, such that pedalling actions have less influence, exploring braking and cornering strategies further.

The purpose of this project is to design and develop a set of force sensors to measure steering forces applied by an athlete down the ice track. Currently, there is not enough information about instrumentation in skeleton, and to maintain competitive advantages, most of the research remains private and unpublished. Athletes use their shoulders and knees to steer down the track. For this reason, four handmade piezoresistive tactile force sensors were built to measure the force applied by each joint. Each sensor has its own model to convert bits recorded into force. Results showed a difference between applied and calculated forces by each model. However, calculated results followed similar trends compared to the real values of the applied force. In addition, a graphical user interface was created to present the results to the athlete in a simple and easy way to read and understand. It is planned to use a shimmer (an inertial measurement unit) to collect information about accelerations developed on each run. Coupling both measurement systems have to be done during the processing stage. Further work has to be done regarding electronics size and testing the systems in a real run down the track.

The track bound sliding sport of Skeleton was permanently added to Winter Olympics programme in 2002. This has led to increased interest in the sport. Engineering has already proved to be a vital contributor to improved performance in the related sport of Bobsleighing. We hope that engineering can do the same for Skeleton. This report describes an attempt at developing a platform to be used as a real-time training simulator for the sport of Skeleton. For a multitude of reasons athletes are, on average limited to a total of two hours of practice and competitive on-track time in any given year. When compared with time spent practising and in competition in most sports, this is extremely low. It is hypothesized that a simulator can augment track time by providing a realistic environment to practise in, even when access to a track is not available. This work is guided by simulators that have been developed for Bobsleighing. The main components are the models to describe the dynamics of the sport, an input method and visualization of the simulation. The main considerations for the dynamic model are of the track surface, the sled and contact between sled and track surface. These models lead to a system of equations which when solved provide accelerations and contact forces. The accelerations are integrated over a fixed time interval to determine changes in velocities, position and orientation. The position and orientation obtained after the integration is passed on to a game engine which provides the user with real-time visual output of the position and orientation along a digitally recreated track surface. A video game controller was chosen to serve as the input device. It has two joysticks, which can be mapped so as to mimic the forces applied by an athlete. A number of descents were performed using this platform both at real-time speed and at a slower speed to give the user, unfamiliar with the sport, a better chance to steer the sled. We were able to consistently reach the exit of curve 2 in real-time speed and curve 4 at the slower play speed before failure of the simulation. In most cases the algorithm used here proves to take lesser time for computation than the chosen integration time step, which is a great sign for future development as we did not make any attempts to optimise its omputation
time. We made an attempt at validation using time elapsed to traverse a certain distance and the sum of magnitude of Lagrangian multipliers. We had poor results with the time elapsed comparison, with simulated runs being 15% slower than competitive descents. While the sum of Lagrangian multipliers showed good relation to expected behaviour. This first attempt was reasonably successful, and we believe that the lessons learnt from this work has brought us one step closer to realizing a training simulator that can be useful to Skeleton athletes.

Experimental data were obtained from riding a steer-by-wire bicycle on the open road while perturbing balance with impulsive forces at the seat post (lateral pertubations) as well as perturbing balance with impulsive torques at the steering assembly (steering pertubations). The experiments were conducted at 2.6–5.6 m/s covering both the stable and the unstable forward speed range. For the lateral pertubation experiments two conditions were explored; normal steering and reduced torque feedback steering. Three metrics are used to assess the effect of torque feedback on rider steer control and balance. Results failed to indicate any statistically significant difference between experimental conditions. Bicycle and rider mechanics have been modeled using the Whipple bicycle model extended with the rider inertia. A rider control model is developed that incorporates all of human's sensory pathways and includes a strategy to compensate for sensory dead time. The identified rider control parameters, stabilize the system and mimic realistic rider control behavior. From the results the importance of the torque feedback pathway is strongly indicated. Finally for the steering pertubations the rider control model is modified to account for the cocontraction mechanism. The model manages to approximate the rider measured response and simultaneously captures the significance of the intrinsic response. A high level of intersubject variability is exhibited. The hypothesis that this variability is in fact due to the modulation of admittance in the shoulder joint is strongly suggested.

In Bicycle Motocross (BMX) racing, a fast gate start is crucial for overall race performance (Rylands2014). The goal of this study was to (1) provide a better understanding of how cyclists effectively propel the bicycle during BMX gate start, and (2) identify pedalling variables which are good predictors of a fast start."

Research in the motorcycle industry is lagging behind research in the automotive industry. Especially with respect to safety, more research is needed, since motorcycles are overrepresented in the number of road casualties and injuries. Important tools in vehicle research are vehicle simulators. The use of motorcycle simulators enables manufacturers to develop new motorcycle technologies and could make motorcycles safer. Unfortunately, few motorcycle simulators are available, and even fewer are used in the development of new motorcycles and motorcycle safety systems.
This thesis evaluates the Cruden’s six Degrees of Freedom (DoF) motorcycle simulator and shows that it can be used in motorcycle research. To back up this claim, it is showed that a 15-DoF multibody dynamics motorcycle model is used and that the motion platform is capable of having the rider experience dynamics associated with this dynamics model. Furthermore, a human research approach shows that participants experience the same speed perception corresponding as in real-life and that the motion platform is necessary to achieve the highest performance form the rider with respect to lane deviation. Also workload and presence in the virtual environment were significantly better with platform motion. The influence of body tracking has also been investigated but has not demonstrated significant results with respect to the rider’s performance.

On all levels of rowing, a general rule is that you have to row together. Rowing together has no clear-cut definition. However, it is known that each rower has his or her own style, which can be registered in movement patterns and force curves. The big question is how to combine these individual styles such that the crew works together in the best way. The Dutch Rowing Federation showed interest in this topic, wanting to know how to adjust the rigging dimensions of the boat to allow the best racing performance. The goal of this thesis is to provide advice on what features of the rowing stroke should be synchronized and whether and how this could be promoted by individualized rigging.

The theoretical foundation for this study was a literature study about the current knowledge on the rowing stroke and differences within and between individuals and crews. Current used measures on performance and synchronization of rowers were described, and finally a proposal was done for which methods to use in the ongoing of the study.

Data was obtained from five female athletes of elite level, doing trials in a quadruple sculls of approximately 30 seconds at 30 SPM and 32 SPM in four different combinations. The strokes were identified and analyzed, based on performance and synchronization measures. Performance measured as Average Speed, Work per Stroke, Blade Losses, Velocity Fluctuation Losses and their respective and combined efficiencies. Synchronization measures were defined as Mean Standard Deviation of the Phase, Standard Deviation of the Time to Half Impulse and Standard Deviation of the Time to Half Work.

The chosen synchronization measures were not completely independent. Standard deviations of time to half impulse and half work were found to be highly similar (r = 0.970). An opposite effect was found between kinematic synchronization and the other two, Mean Standard deviation of the Phase was not in line with the empirical rule that better synchronization leads to better performance. The kinetic and energetic measures did show this effect: Lower standard deviations of time to half impulse and time to half work meant higher average speed (r = −0.193) and higher Work per Stroke (r = −0.574).

The best performing synchronization measure was time to half impulse synchrony. A drawback on this measure was that the sampling period was long, compared to the interpolated time differences. Athletes were found to achieve their half impulse moments in a consistent order.

To find out whether it is possible to promote synchronization and thus performance by individualizing rigging, the oar angles at the time to half impulse were analyzed. This new measure correlated moderately (r = 0.624), meaning it quantifies more or less the same effect. The kinetic similarity actually worked better (r = −0.292 with Average Speed and r = −0.748 with Work per Stroke) than the synchronization measure.

Similarity of half impulse angles enables the coach to adjust the rigging such that the timing should improve too. However, this should be tested in a follow-up study.

In this research the influence of the rower behavior and rigging setup on the boat performance is investigated in a data-driven model. There are different rowing styles and techniques between rowers. Making rowers row in synchrony, while important for the boat performance, is not easy. Rowers have their own signature rowing curve, of which only few aspects can be changed. The signature rowing curve can be based on the oar angle or the relative displacement of the rower. The latter is assumed to be constant for changes in the rigging setup and therefore preferred.
The data used in this study comes from a woman’s double, the rowers of which are members of the KNRB. In the boat measurements are done on the gate and foot forces, as well as the oar angles, the seat displacement and boat accelerations.
From the free body diagrams of the different parts of the system, a one-dimensional rowing model is derived. The model is driven with the measured forces on the rower and the oar angles. It can be validated with the measured boat accelerations. The distribution of the masses in the system are slightly changed. All drag force on the system is assumed to be viscous and is assumed to be proportional to the square of the boat velocity. The lateral forces on the blade and the oar deformation are neglected.
The relative motions of the rower are best predicted with the forces acting directly on the rower, after a compensation of the measured foot force. The best fit for the boat accelerations are found by combining the system acceleration with the relative accelerations of the rowers.
With the assumption that the rower can be modeled as a force constraint model, the rigging setup of the modeled boat is changed. The blade forces have a leading role on the resulting boat motions when changing the rigging parameters. However the blade forces might not be realistically modeled. Changing the lever ratio of the oar, by increasing the inboard length leads to a bigger covered oar angle and a higher boat velocity, but a lower work per stroke applied on the handle by the rower. Moving the footstretcher towards the bow of the boat shifts the oar angle and leads to a higher boat velocity and lower handle work per stroke as well. Changing individual rigging parameters did not result in big differences between the rowers.
No indications of improved synchronization between the rowers are found and the energy balance of the system is disrupted. The model simplifications of the blade forces may not be justified. After implementation of a more complex modeling of the blade forces indications of the synchronization might be found.