Peloton

[1] Exploitation of this potential energy saving leads to complex cooperative and competitive interactions between riders and teams in race tactics.

[6] After a period of time in front, leading riders maneuver farther back in the peloton to a drafting position to recover.

Like bird flocks, peloton-like behavior that involves drafting or similar energy-saving mechanisms has been identified in a variety of biological systems.

Comparatively high power output efforts due to high-speeds on flat topography, a strong headwind or inclines (hills) tends to spread out or lengthen the formation, often into single file.

A slow pace or brisk tailwind in which cyclists' power outputs are low result in compact formations such that riders ride side-by-side, often filling roads from one side to the other.

When two or more groups of riders have reason to contest control of the peloton, several lines may form, each seeking to impose debilitating fatigue on the other teams.

Introducing riders' physiological variables including metabolic power production and time to exhausion ("supply" factors), Olds' presents an iterative algorithm for determining the mean power of each group and their relative times to exhaustion, thus determining whether the chasers will catch the breakaway.

[22] Agent-based computer models allow for any number of independent "agents" with assigned attributes to interact according to programmed rules of behavior.

[23] For their cyclist agents, Hoenigman et al.[24] assigned individual maximum-power-outputs over a heterogeneous range among peloton cyclists and individual and team cooperative attributes in which agents share the most costly front position, or defect by seeking lower-cost drafting positions within the peloton, both according to some probabality.

The authors performed experiments by varying the noted parameters over a simulated 160 kilometres (99 mi) flat road race containing 15 teams of 10 riders.

The results are realistic when compared with real-world competitive cycling and demonstrate the effectiveness of this kind of agent-based model which facilitates accurate identification and analysis of underlying principles of system (in this case, peloton) behavior.

[27] Ratamaro then applied Sayama's algorithm for cohesive and separating forces[28] to adjust agents' acceleration based on their proportionate spacing within a defined field of vision.

This algorithm produces a realistic simulation of oscillating phase behavior between compact and stretched pelotons as speeds vary throughout the course of a race.

Trenchard et al. tested the model against an actual set of MSOs for 14 cyclists who participated in a velodrome (track) race.

[33] Trenchard proposed a theoretical framework for peloton "protocooperative" behavior, a form of cooperation that emerges naturally from physical interactive principles as opposed to ones driven by human competitive, sociological or economic motivations.

Applying the PCR equation (noted above), the range of cyclists’ MSOs in the free-riding phase is equivalent to the energy savings benefit of drafting (1-d).

Trenchard extracts the following principles:[34]It is this sorting behavior that Trenchard hypothesizes to be a universal evolutionary principle among biological systems coupled by an energy-saving mechanism, which he and collaborators have developed further in relation to extinct trilobites and slime mold[8][35] While the riders at the very front encounter the greatest air resistance (and also those on the windward side when there is a significant crosswind), those behind the first few riders near the front have critical advantages.

In addition, riders are increasingly affected by the accordion effect, in which a change in speed becomes amplified as it propagates to the back of the peloton.

Teams aware of wind conditions ahead, strong enough to move to the front, well experienced in echelon riding, can gain an important time advantage in these circumstances.

It is critical for riders in contention to win a race to remain near (but not at) the front of the peloton, especially when approaching sharp turns that require braking.

Once a division occurs, if the will and collective strength of those wisely placed at the front is greater than those behind, the gap between the groups will remain (or increase) to the end of the race, because the extra air resistance for a single rider attempting to move forward to reach the front group imposes an extravagant fatigue penalty, as compared to those who remained protected in the peloton.