The favorite way of transport for commuters is still by cars, which are designed too heavy and too wide for the average amount of passengers. Accidents without other traffic users make up a large proportion of crashes for free-tilting bicycles. Tricycles have a chance of rollover while cornering fast.Therefore, new human-powered commuter vehicles are needed that have optimized handling performance and are safer. This alternative can be the narrow tilting tricycle, with the combined advantages of bicycles and tricycles. Faster cornering can be performed than with a tricycle, and better balance and more traction can be obtained than with a bicycle. No method exists to evaluate the handling performance of a narrow tilting tricycle that gives a combined conclusion about the handling performance for multiple velocities and aspects of handling.This study evaluated the optimized handling performance for commuting for a prototype tilting tricycle. The tricycle is designed by Andrew Dressel and built by DEMO at TU Delft. The tilt mechanism incorporates tie rods that connect A-arms to the bell crank at adjustable connection points. This coordinates the tilt behaviour which changes with different connections from the tie rods to the bell crank. I created a novel handling evaluation method for commuter vehicles in a quantitative within-subjects study. I selected a moderate-speed slalom manoeuvre and a low-speed line-following manoeuvre as test manoeuvres. I have measured the maximum yaw factor, the mean absolute steer angle, and the time delay between the roll rate and steer as handling metrics using two Shimmer3 IMUs. The first metric is evaluated for the slalom manoeuvre and the second and third metrics are evaluated for the low-speed line-following manoeuvre. I scaled the metrics and combined the results into a single score. The selected metrics are able to discriminate between the performance of conventional bicycles and prototypes of tilting tricycles. For highly similar designs, it is important to add trials until statistical significance can be reached. The analysis of the data showed the optimal handling performance of the Dressel tilting tricycle for tie rod angles halfway between free-tilting and self-stable when stationary. For commuter vehicles in city traffic, the tie rods can be fixed at 50%. Increased low-speed balance is proven for increased tie rod angles, without finding reduced performance on the moderate-speed slalom. It is not recommended to increase the tie rod angle to 75%. Uncontrollable performance has been observed in this configuration.A tie rod angle of 100% can provide complete rigidity while standing still. The tilt limit has been hit with increased tie rod angles and this limit is increased with a Matlab optimization. For the optimal configuration with tie rods connected halfway in, the bell crank should be designed 380 mm wide and connected 235 mm high from the ground. The tilt mechanism with the optimal design parameters can make the vehicle safer because of the improved balance, without reducing the handling performance. A fixed design can make the vehicle cheaper and easier to build compared to the adaptable tilting tricycle. 

Skateboarding involves a human controlling a four wheeled vehicle that is steered by tilting the standing surface. The riding mechanics of skateboarding have been well reported [2, 3]. The sport also includes aerial maneuvers such as jumping of stairs, flying off ramps and flipping and rotating the skateboard. The most basic aerial trick is called the ollie. The athlete jumps up while pushing down on the back end of the skateboard’s tail, causing a rotation about the back axle. The upward acceleration due to the rotation together with the tail-ground impact cause the skateboard to go airborne. Midair the athlete drags the skateboard up through frictional contact and levels it out to land the trick. The most concrete performance measure of the ollie is height according to the Olympic judging criteria [4]. To reach maximum height the dynamics such as impact, dynamic response, and torque production are dependent on shape, inertia and mass, which gives reason to assume an optimal shape exists. This leads to the research question: What are the optimal geometric and inertial parameters of a skateboard for an Olympic athlete to reach maximal ollie height. The skateboard geometry is optimized through multiphase direct collocation with the objective of maximal ollie height. A parameterized model is created with scaling mass and inertia properties such that the geometry of the skateboard. Modelling the dynamics of the ollie including impact and friction are done with a point mass human controller that is kineticly and kinematicly mapped to a counter movement jump. A simplistic contact implicit impact scheme is made for a higher order optimization. The ollie height is improved by changing the mass and inertia properties of the skateboard. Multiple optimal board shapes are generated for example a skateboard with a smaller wheelbase can reach higher ollie height compared to an industry standard skateboard.

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.

The establishment of areas for safe automated driving in mixed-traffic settings is one major barrier in the development and adoption of Autonomous Vehicles (AVs). This work investigates safety in the interactions between AVs, human-driven vehicles, and vulnerable road users such as cyclists and pedestrians in a simulated urban environment in the Dutch city of Rotterdam. Proposing new junction and pedestrian models, virtual AVs with an occlusion aware driving system are deployed to deliver cargo autonomously. Assessing the impact of various measures, including V2V, V2I, V2X communications, infrastructure modifications, and driving behavior, we show that traffic safety and network efficiency can be achieved in a living lab setting for the considered case. Our findings further suggest that V2X gets implemented, new buildings are not placed close to intersections, and the speed limit of non-arterial roads is lowered.

Bicycle disc brake noise and vibration, which usually falls in the frequency range of 0-2 kHz, is a principal braking quality attribute that has started to attract significant interest from bicycle manufacturers. Brake noise is an irritant to their customers, who see it as a symptom of a defective brake and that leads to unnecessary warranty claims. Over the years various theories (e.g. stick-slip, sprag-slip, modal coupling) have been developed that explain the noise and vibration generation mechanism in the frictional brakes. Traditionally, research groups working on this issue have conducted their investigations by combining analytical and experimental studies. Likewise, this report aims to predict the brake noise using finite element analysis where the experimental data validates the finite element model. In order to reproduce the brake noise in the laboratory setting, the brake test machine at the Koninklijke Gazelle laboratory was used. This novel test bench made it possible to run the experiments on the actual bike by providing features to control the bike speed, brake pressure, and weather conditions within the setup. The dynamic characteristics of the brake system were captured with the microphone and the laser Doppler vibrometer. % The audio frequency spectrum was generated by placing a microphone close to the sliding interface of the pads and rotor. A Laser Doppler vibrometer was used to generate the mode shapes and the vibration velocity spectrum of the brake components. It was established from the results of the brake noise audio and the vibrometer scans that the entire bike vibrated at three peak frequencies during the brake noise events. Brake noise level as loud as 95 decibels was captured. Stick-slip as one of the friction-induced instabilities was identified during the experiments. Furthermore, a detailed finite element model of the disc brake assembly was developed. Modal analysis on the components of the assembly and a pre-stressed modal analysis on the entire brake assembly was performed. The finite element results compared well with the experimental results. It was observed that there exists doublet modes and intermediate modal coupling in the system. Limiting the rotor symmetry by adding weights on the rotor ribs was shown to be effective in reducing instabilities. Other ways to counter brake noise by increasing the rotor mass and by introducing a parallel slot in the brake pad were successfully tested.

Rehabilitation robots have been shown to be effective in post-stroke gait rehabilitation. However, these devices are usually expensive and suffer from high inertia which decreases transparency. The Minimally Actuated Tendon-based exercise Environment (MATE) is a tendon-based rehabilitation device, designed to be cost-effective and minimize inertia effects. The MATE must apply minimal forces to the wearer if the gait cycle is healthy to prevent deviation into an unhealthy gait. Previously a mathematical optimization was performed on the design of the MATE. This thesis aims to make a physical realization of the MATE to investigate the minimal forces during a healthy gait cycle with two experiments. The first experiment attached the tendons to a machine to investigate forces on a non-altering gait. HTC VIVE motion trackers were used to measure the position of the tendon attachments over time. To measure the tension, in each cable inline tension sensors were added. Comparing the measured forces to velocity-based thresholds indicates that the forces applied by the MATE are too high and would cause deviation. The second experiment involved a human walking with and without the MATE. Evaluating the gait cycle trajectory when walking with and without the MATE indicates that the MATE alters a healthy gait cycle, lowering the step height and causing drift. The forces acting on this gait also exceed the thresholds. The MATE in its current design alters a healthy gait. Redesigning the MATE with the suggestions from this thesis will likely show further improvements.

The rapid adoption of e-bikes as an alternative mode of transportation to automobiles gives rise to new methods of safety regulations for cyclists. Modern e-bikes feature Internet of Things (IoT) modules capable of collecting and sending cycling data that can be used for traffic safety analysis. This study explores the potential of using cycling data to detect dangerous intersections and then implement local low-speed areas using geofencing. A natural cycling experiment with 10 participants is conducted, where data is collected similar to the capabilities of e-bike IoT modules (GNSS, power and IMU data) and participants are asked to cycle through Delft, The Netherlands. The data is combined with a traffic accident dataset from the Dutch government, where intersections with accidents are labelled dangerous. The cycling data is separated into separate intersection approaches, based on positional data. Metrics based on power and cadence data show the most significant statistical difference (p-values <0.02) and the largest effect size (Cohen's d >0.80) at dangerous intersections. A binary classification model is trained on the dataset, which can correctly predict whether an intersection is dangerous or safe with an accuracy of 68,2%, a specificity of 50,0%, and a sensitivity of 24,2%. This prediction is based on the metrics of a single intersection approach. To investigate the viability of using geofencing to implement low-speed areas at designated dangerous intersections, a simulation is carried out to determine the minimum size of a geofence that effectively slows down e-bike cyclists. The minimal effective geofence size to limit a cyclist's speed at an intersection is determined by simulating cyclists approaching a geofence for several geofence perimeters, incline levels, and wind speeds. The e-bike's motor stops supporting when the geofence is entered and the cyclist is cycling above a target speed. The minimal effective geofence size ranges from 50 to 300+ m and depends on the target speed, wind speed, and road incline. This study shows that cycling data can be used to identify dangerous intersections. Enforcing a slower speed on intersections with local geofencing is not feasible, as the geofences have to be extremely large, showing a lot of overlap on other intersections in cities due to high intersection density. Future work can be done on the intersection risk estimation method and the feasibility of speed-limiting geofences that employ active braking.

The cycling industry is influenced by the approval of the tire pressure control system in competitive cycling. This system allows real-time adjustments to the tire-road interaction during races. The total rolling losses is the resistance resulting from tire-road interaction, incorporating resistance due to tire deformation and the dissipation of vibrational energy within the rider-bicycle system. This research investigates the influence of tire parameters on the total rolling losses during road cycling through three key measurements: ink print test, drum test, and rolling losses measurement. The ink print test captures the contact area between the tire and road surface under specified loads, revealing significant impacts of tire type, width, inflation pressure and vertical load on the contact patch shape. In addition, this study shows that an increase in contact patch measures is related to an increase in the rolling resistance coefficient (𝐶𝑟𝑟). The drum test extracts 𝐶𝑟𝑟 values related to pure rolling resistance by measuring the power needed to maintain constant velocity of a rotating drum when in contact with a loaded tire. Results indicate a significant influence of tire type, width, inflation pressure, vertical load and velocity on 𝐶𝑟𝑟 estimates. Combining 𝐶𝑟𝑟 obtain with drum testing with 𝐶𝑟𝑟 determined with total rolling losses measurements, provides insights into the contribution of vibrational losses to the total rolling losses. The study employs a novel bike trailer measurement technique to estimate total rolling losses, measuring the cyclist’s power while cycling at constant speed with elimination of aerodynamic drag. Despite some limitations, the bike trailer method successfully identifies optimal tire parameters for minimizing rolling losses on different road surfaces at varying speeds.

Commissioned for Team DSM, a computational model for professional road cycling races is developed to answer the question: ``What is the optimal cycling wheel-tire combination, available to Team DSM in order to ride different road cycling races as fast as possible?''. This model is used to make an approximation of the wind that the cyclist experiences, using race data from Team DSM. Using this wind approximation, race times for different wheel-tire combinations are compared. A sensitivity analysis of the model for the coefficient of rolling resistance, coefficient of drag multiplied with the frontal area, mass and rotational inertia is performed. Taking the error in the measurements of parameters into account, the sensitivity analysis and race time results both point to the ``C60 tubeless'' wheel-tire combination to be the fastest combination out of the available wheel-tire combinations to Team DSM. If the weight of a C36 wheel-set was reduced, this wheel set could outperform the C60 wheel-set on mountainous race courses.

Existing wind load simulators such as wind tunnels and fans have multiple disadvantages, especially when used in a scaled-down environment. This paper proposes to simulate wind loads by using an admittance-controlled industrial robot arm rigidly attached to a research object. Admittance control should make it possible to simulate wind loads and a specific amount of inertia that is higher than the inertia of the original research object. The goal is to verify whether an admittance-controlled industrial robot arm is suitable for wind load and inertia simulations and what the limitations of this simulation method are. The scope of this research is limited to three Degrees of Freedom. First, the admittance controller is tested on a computer simulation model before execution on a Hardware-in-the-loop setup. It is found that an admittance-controlled robot arm is well capable of simulating both wind loads and a specific amount of inertia. However, there are some limitations. The motion controller of the industrial robot should be able to change the end-effector position within a frequency of 50 Hz. Frequencies above 333 Hz result in the most accurate simulations. The upper range of inertia that can be simulated is restricted by the maximum joint torques the robot can apply. The lower range is restricted by the inertia of the real object, the applied wind loads, and the sampling frequency of the admittance control loop.

Bicycle safety is quickly becoming an increasingly important field as the number of electric bicycles on the streets grows faster each year. E-bikes are able to accelerate quicker and travel at faster speeds than conventional bicycles, increasing the severity of injuries in case of an accident. There are a number of ways to improve safety, such as building better infrastructure, implementing active safety systems, improving bicycling skills, or better protective gear. In this thesis, a controller based on Model Predictive Control has been designed to explore whether it could be used as a haptic guidance system that would improve motor learning of a cycling task, and whether it could assist the cyclist during cycling manoeuvres. The cycling task of lane change manoeuvres performed at a constant forward velocity was investigated. The controller was implemented on a desktop PC, which wirelessly controlled the TU Delft's Steer-by-Wire bicycle -- a bicycle where the steering is enabled by the use of electric motors instead of mechanical coupling between the front fork and the handlebars. To test the controller, ten participants took part in a pilot study. The study was designed following a counterbalanced measures design and the participants were split into two groups that experienced the controller's haptic guidance in different order. During the study, the participants were asked to ride the bicycle on a treadmill and hit virtual targets, shown on a display mounted in front of the treadmill, by carrying out lane change manoeuvres. The hypothesis stated that the controller improves performance while it is assisting the participants. It was found that the controller did not significantly improve immediate performance and this result is likely caused by too low of the task difficulty. However, it is likely that the controller was more effective at improving motor learning of lower skilled participants compared to higher skilled participants, but a small number of lower skilled participants limited the analysis. A short post-hoc no-hands riding test of the same cycling task was carried out to investigate whether the controller is able to carry out lane change manoeuvres with minimal rider input. A significant performance improvement was found during the no-hands test. In conclusion, due to limitations of the study, no performance or motor learning improvement caused by the controller was found. Yet the controller showed promising results in a no-hands riding test, which suggests that the controller could be used as a starting point for advanced safety systems for bicycles.

Cycling is an increasingly attractive transportation mode, thanks to its health and environmental benefits. Personalized travel assistance services can help make cycling more appealing by providing speed or route advices that can reduce travel time and increase safety while taking into account the personal preferences of cyclists. Due to its ability to learn agents' reward function, Inverse Reinforcement Learning is a suitable algorithm for learning cycling preferences from data. This thesis aims to describe cycling styles as a set of cycling preferences encoded as a reward function composed of a weighted sum of features. The weights associated to the features composing the reward function represent the importance given to each cycling preference and express the trade-off between different goals of a cyclist. Continuous-time Inverse Reinforcement Learning extracts the weights from empirical cyclists' trajectories collected during an experiment performed in Delft. During the experiment, cyclists were asked to cycle according to three different cycling styles: cautious, normal and aggressive. Differences between weight sets extracted for each cycling styles were analyzed by means of the Kruskar-Wallis statistical test and K-Means clustering algorithm, and the averaged weights for each cycling style were used to simulate a set of test trajectories. It is shown by simulations that the reward function identified for a specific cycling style leads to an improvement in terms of similarity to test trajectories with the same cycling style with respect to the reward functions corresponding to other cycling styles. The statistical analysis shows that the weights of cautious and aggressive cycling styles show statistical differences and define separate clusters.

The DelFly Nimble is a type of tailless flapping-wing micro air vehicles (FWMAVs) that has received an increasing amount of attention. FWMAVs show efficient and agile flight possibilities at small scale. The aerodynamics and dynamics of these flapping vehicles are challenging and not fully understood. In this work, a strategy to implement a 3D dynamic model and a trajectory control algorithm is proposed for the DelFly Nimble by the use of a quasi-steady state framework. The design of a suitable tracking control algorithm is the essence of this task. A globally defined smooth nonlinear geometric framework of the flapping-wing vehicle’s rigid body dynamics is introduced as a basis for the analysis. This grants an unambiguous coordinate-free dynamic model in which problem of singularities are avoided. The Nimble has four inputs used to control the six translational and rotational degrees of freedom. A nonlinear tracking controller is chosen on the special Euclidean group 푆퐸(3) for the underactuated aerial vehicle, where position and yaw trajectory tracking are achieved. The full system is classified into the coupled attitude and position subsystems. Using the Lyapunov Stability theorem, the nonlinear controller is shown to achieve almost global asymptotic tracking of the attitude error dynamics of the Nimble and almost global asymptotic tracking of the position error dynamics of the center of mass of the Nimble, enabling sufficient tracking of aggressive maneuvers. Finally, the dynamic model and the controller are examined with numeric simulations. From the results can be concluded that the nonlinear control design allows for aggressive aerobatic maneuvers while maintaining stability of the closed-loop system, provided that the control inputs and damping forces remain moderate.

The main purpose of this report is to investigate flaws within Cornelis Tromp 25T lemniscate crane upper arm joint. This is done in order to figure out why the joint structure is experiencing significant crack propagation and what potentially could have led to a structural joint failure and death of an operator within a crane of the same model. Assessment is performed by simulating stress distribution within the problematic joint structure and assessing high-cycle fatigue damage accumulation around its welds. Loading conditions affecting crane upper arm are established through multi-body dynamic simulations, which are meant to replicate operation of a lemniscate crane. Multi-body dynamic model is verified for its accuracy using available crane operation measurement data. Loads are acquired within the time domain and include temporal effects of luffing, slewing and hoisting operations as well as pontoon motion. Fatigue analysis is performed to evaluate damage accumulation within the tubular joint structure of the crane upper arm. A detailed shell finite element model is established to acquire time-dependent stress responses. During stress evaluation stage - a particularly large stress concentration has been observed at the joint brace saddle position. To assess which method best simulate damage accumulation in the joint structure - three specific fatigue assessment approaches are tested: nominal stress approach, hot-spot stress approach and multi-axial fatigue approach. Nominal and hot-spot stress approaches are evaluated and compared to determine how inclusion of stress concentration effects into fatigue assessment influence damage accumulation results. Result comparison has shown a large disparity in results with hot-spot stress approach, indicating that the method capable of determining locations of dangerous stress accumulation, in relation to what has been observed in the real structure. Evaluation is performed to determine whether multi-axial fatigue assessment is needed to improve calculation results of fatigue damage accumulation. Based on stress direction properties within the analysed structure - most favorable multi-axial fatigue assessment approach (capable of analysing proportional stress responses) is used. Multi-axial fatigue assessment method results are then compared with results of conventional hot-spot stress approach to evaluate the differences in damage accumulation rate. Analysis results have shown that both methods are capable of determining locations of critical points with present disparity within magnitude of damage accumulation. This indicates that hot-spot stress fatigue approach, which uses Von Mises stress, is more conservative out of two methods. Fatigue analysis has also presented that original joint structure is inherently flawed, as its stress concentration locations are not easily accessible without crane disassembly and its structural capacity has been underestimated during design stage. Finally methods for extending operational life of crane upper arm structure are evaluated. Three methods for reducing stress within the structure are assessed: increase of structural capacity, stress redistribution and load reduction. Increase of structural capacity is performed by adjusting thickness of relevant joint elements, with optimal thickness being established using a sensitivity analysis algorithm, which simultaneously acquires combined thickness setup for multiple joint elements - making the joint capable of surviving predetermined fatigue life. Stress redistribution approach is implemented by producing an alternative upper arm joint design, which could be exchanged with the problematic original joint during crane refurbishment. Load reduction approach is performed to investigate whether it would be possible to increase fatigue life of the original joint structure without affecting work efficiency, by only adjusting crane motion profile within multi-body dynamic simulation environment. All three methods are quantified and compared through fatigue damage factor results acquired using multi-axial fatigue assessment method. Result comparison has shown that joint redesign is the most preferred approach due to its ability to efficiently improve fatigue life of the structure without significant structural weight increase, while exposing any potential points for crack initiation to locations easily accessible for inspection and repair.

This study investigated the relationship between Equivalent Fall Height (EFH) and peak Ground Reaction Force (GRF) in freestyle ski jumping. An experiment was conducted in which a semi-professional freestyle skier was instrumented with Inertial Measurement Units (IMUs) and a position sensor. The skier performed jumps off ‘kickers’ in snow parks in four different ski resorts in Northern Italy. The gathered sensor data was utilized to calculate the EFH and GRF of every jump. The data reveals convincing evidence that a positive correlation between these two parameters exists. However, the coefficient of determination, R2, indicates only a moderate correlation. The results suggest that alternating landing strategies might have affected the measured GRF as well. This indicates that a higher correlation between EFH and GRF might exist than shown in this research. Further research should focus on how individual parameters, such as EFH and landing strategy, affect the GRF. This should develop a more comprehensive understanding of how to enhance the safety and enjoyment of freestyle ski jumps for a broader audience.

Bicycles have been studied extensively over the past 200 years, with mathematical models providing valuable insights into various aspects of bicycle dynamics and rider control. However, the lack of a common framework for creating and sharing bicycle-rider models hinders the development of advanced models, research reproducibility, and dissemination. This thesis addresses this gap by introducing BRiM: an open-source modular and extensible framework for creating Bicycle-Rider Models. The modular setup of BRiM relies on a systematic approach to define a model and form the analytical equations of motion. For the involved analytical computations BRiM utilizes SymPy, a Computer Algebra System. The systematic approach consists of four stages. The first stage defines the objects in the system, such as symbols and bodies. Secondly, the kinematic relationships between the objects, such as angular velocities between reference frames, are established. The third and the fourth stages, which are order-independent, specify the loads and constraints acting upon the system. The decoupling BRiM required to achieve modularity is enabled through this systematic approach, because computations within a stage are mostly order-independent. The core of BRiM employs the systematic approach within a unified framework for modeling mechanical systems in general. It describes a model using a tree representation, in which a model is defined as an aggregation of smaller submodels. The relationships between submodels are established by parent models, using interchangeable connections to accommodate complex relations, such as tyre models between the ground and a wheel. This application of submodels enables swapping and adding submodels, making the overarching model both modular and extensible. Actuation within BRiM can either be specified by attaching prespecified groups of loads to models and connections, or by utilizing the interface provided by the mechanics module in SymPy, which offers the flexibility to even manipulate equations in detail. BRiM applies this generalized framework to create modular bicycle-rider models. Both a stationary bicycle and a modular bicycle based on Moore's convention of the Carvallo-Whipple bicycle have been constructed. These bicycle models are extensible to bicycle-rider models by including an upper and/or lower body. Within the rider models each joint can be actuated by a linear torsional spring-damper. BRiM integrates parametrization of models, which provides mappings between symbolic quantities used in equations and experimentally determined values, using the existing open-source BicycleParameters library. Additionally, SymMePlot, a visualization package for symbolically defined mechanical systems, has been developed and integrated within BRiM to visualize the created bicycle-rider models. The effectiveness of BRiM is demonstrated through optimization and simulation tasks. Firstly, a real-time forward simulation of a torque-driven upper body bicycle-rider is performed. Secondly, an optimization problem is solved, involving the tracking of a rolling disc along a sinusoidal trajectory while minimizing the control torques. These demonstrations highlight the seamless integration of BRiM with other scientific tools and BRiM's potential for practical applications. In conclusion, BRiM fills the gap in bicycle dynamics research by providing a modular and extensible framework for creating and sharing bicycle-rider models. Its systematic approach, unified framework, and integration capabilities enable efficient model development, research reproducibility, and further advancement in bicycle research.

Training with bodyweight support (BWS) systems can improve the likelihood of regaining normal locomotor abilities for neurologically impaired patients. It is known that people alter their gait parameters when walking with BWS. However, it is unclear whether 2D (vertical and lateral support) and 3D (only vertical support) BWS systems affect these gait parameters differently. In this study, participants walked overground in both a 2D and a 3D BWS system to investigate the effects of this lateral support. To compare the contribution of the vestibular system between the different BWS systems, participants received galvanic vestibular stimulation (GVS). Motion capture and force plates were used to find the coupling between the GVS stimulus and the mediolateral ground reaction forces and to calculate the gait parameters. Differences in gait parameters were observed between the 2D and the 3D system. Compared to unsupported gait, participants increased their step width variability by ~10% in the 3D system. Contrarily, participants decreased step width variability by more than 15% in the 2D system. Mean step width decreased slightly in only the 3D system. The margin of stability did not change significantly in any condition. The coupling between the GVS signal and mediolateral ground reaction forces decreased in the 2D and 3D systems compared to unsupported gait, but no significant differences were observed between different BWS conditions. These results suggest that 2D and 3D BWS systems influence gait parameters differently and that they influence the contribution of the vestibular system to balance, but no significant differences between the systems can be observed in this aspect.