Figure 1 - available via license: Creative Commons Attribution 4.0 International
Content may be subject to copyright.
Measurement system installed on a bicycle. (A) GoPro camera and mount to record rider posture; (B) GNSS antenna to measure rider's position on the road; (C) optical encoder to measure steering angle; (D) IMU to measure roll angle and data acquisition system; (E) strain gauges on brake shoe to measure brake force; (F) velocity sensor and power meter.
Source publication
Descend technique and performance vary among elite racing cyclists and it is not clear what slower riders should do to improve their performance. An observation study was performed of the descending technique of members of a World Tour cycling team and the technique of each member was compared with the fastest descender amongst them. The obtained d...
Contexts in source publication
Context 1
... participants signed an informed consent. For this study, the bicycle of each rider was equipped with the measurement system as shown in Figure 1. Each rider rode a 1.85 km descent, as shown in Figure 2, six times on his instrumented bicycle. ...
Context 2
... position of the rider on the road is measured with a Global Navigation Satellite System (GNSS) receiver. To increase accuracy, a base station was used and the GNSS antenna was mounted high above and behind the rider (see Figure 1). Even so, occlusions remained a problem on certain areas of the descent due to the environment (e.g., trees or proximity of a high cliff). ...
Context 3
... front and rear brake forces of the rider are measured using custom brake shoes on which strain gauges are installed. The lean angle of the bicycle is measured using an Inertial Measurement Unit (IMU) positioned at the bottle cage holder (see Figure 1). An optical encoder measures the steering angle. ...
Citations
... Studies of vehicle drivers show that the tangent point on the inside of a bend, beyond which one cannot see the full breadth of the road, is an observational focus [8]. In cycling, faster riders over a set course brake later at corners and use the full width of the road [9]. ...
... In the remaining sections we analyse that model, specifically with the objective to find a generic estimate of t * to minimise centripetal acceleration along routes. This is a safety-first approach to using pedalling and braking at bends, rather than minimising total time by braking as late as possible [9]. One potential issue is that for a region of large curvature, the rider may be unable to see beyond the bend, limiting t * . ...
We present a mathematical model of road cycling on arbitrary routes using the Frenet–Serret frame. The route is embedded in the coupled governing equations. We describe the mathematical model and numerical implementation. The dynamics are governed by a balance of forces of gravity, drag, and friction, along with pedalling or braking. We analyse steady-state speed and power against gradient and curvature. The centripetal acceleration is used as a control to determine transitions between pedalling and braking. In our model, the rider looks ahead at the curvature of the road by a distance dependent on the current speed. We determine such a distance (1–3 s at current speed) for safe riding and compare with the mean power. The results are based on a number of routes including flat and downhill, with variations in maximum curvature, and differing number of bends. We find the braking required to minimise centripetal acceleration occurs before the point of maximum curvature, thereby allowing acceleration by pedalling out of a bend.
... The group of Professor A. Schwab at the Delft University of Technology has done scientific research on the topic [6,7]. However, their research has been focused on the bike-rider interaction from a 'vehicle dynamics' perspective, rather than a 'sport engineering' perspective. ...
Performance in downhill road cycling is understudied. Tools that can be used to assess the cyclists’ cornering strategies ecologically and objectively are missing. A new methodology based on motion capture and mathematical modelling is presented here. A drone was used to capture the trajectory of the centre of mass of a cyclist, who was asked to complete 10 times a ~220-m-long downhill course. The motion capture and ‘optimal’ trajectories were compared in terms of displacement, speed, and heading. In each trial, the apex, the turn-in and the braking points were detected. Whilst the ‘optimal’ trajectory suggested an ‘early’ apex strategy was best, the cyclist in this study completed the corners with a ‘late’ apex strategy. This study presents a methodology that can be used to objectively assess cornering strategies in road cycling. Discrepancies between actual and ‘optimal’ trajectories are also discussed. This study brings to light concepts such as: ‘early’ or ‘late’ apex, braking and turning points, which are discussed within the context of road cycling downhill performance.
... Few studies have investigated racing trajectories in cycling, 40 whilst trajectories are well documented in racing cars, 41 where two cornering strategies can be detected: (I) steady velocity and (II) high entry and exit velocities. A cycling analogy can be made here. ...
A mathematical model of a bike-rider's longitudinal and lateral dynamics was used to study the influence of road conditions (tyre-road friction coefficient) on cycling individual time trial (ITT) performance and pacing strategy. A dynamic optimisation approach was used on different simulated 40-km-ITT courses, where environmental variables (i.e. slope and wind), the presence of corners and the tyre-road friction coefficient were varied. The objective of the optimisation was the performance time. Maximal velocity was constrained by road geometry and the tyre-road friction coefficient. The maximal deliverable power output was constrained accordingly to the critical power model. The simulation results suggest that when technical sections constitute 25% of the entire course, road conditions can meaningfully affect the final performance time and peak power required, but not the pacing strategy. In fact, the time lost in slow technical sections cannot be regained during fast straight sections, even if technical sections are used to restore anaerobic energy stores. However, more experimental research is needed to test the applicability of these predictions.
Purpose
The purpose of this research was to investigate the beliefs, attitudes, and experiences of stakeholders in youth triathlon regarding the important motor subskills that are required to be successful at the elite level of triathlon competition.
Method
Twenty-five participants were recruited from five stakeholder groups in triathlon and interviewed via video conference. A constructionist and relativist approach to thematic analysis was used to identify three first order themes and several second order themes.
Results
The first, first order theme was ‘Continuous motor skills' which consisted of the invariant features of triathlon's continuous motor skills and the parameterization of continuous motor skills. The second, first order theme was ‘Discrete Motor Skills' and consisted of discrete motor skills involved with cornering and change of direction in each discipline and transition phases in triathlon. The final first order theme was ‘Adaptability to continuous and discrete motor skills'.
Conclusion
This research provides a novel and more broad understanding of the beliefs, attitudes, and experiences of stakeholders in triathlon regarding important motor skills that are required to succeed at the elite level of the sport. This novel and broad understanding of important triathlon motor skills has theoretical implications for evaluating triathlon performance with skill acquisition as a primary focus. Additionally, this research is practically important for coaches, administrators, and athletic performance staff who design training programs and pathways for young, developing triathletes.
