Peloton

In a road bicycle race, the peloton (from French, originally meaning 'platoon') is the main group or pack of riders. Riders in a group save energy by riding close (drafting, or slipstreaming) to (particularly behind) other riders. The reduction in drag is dramatic; riding in the middle of a well-developed group, drag can be reduced by as much as 95%. Exploitation of this potential energy saving leads to complex cooperative and competitive interactions between riders and teams in race tactics. The term is also used to refer to the community of professional cyclists in general.

More formally, a peloton is defined as "two or more cyclists riding in sufficiently close proximity to be located either in one of two basic positions: (1) behind cyclists in zones of reduced air pressure, referred to as ‘drafting’, or (2) in non-drafting positions where air pressure is highest. Cyclists in drafting zones expend less energy than in front positions." A peloton has similarly been defined "as a group of cyclists that are coupled together through the mutual energy benefits of drafting, whereby cyclists follow others in zones of reduced air resistance." A peloton is a complex system, which means that collective behavior emerges from simple rules of cyclists' interactions.

Pelotons are typically observed during bicycle races in which drafting is permitted, although pelotons also form from cyclist commuter traffic. Pelotons travel as an integrated unit in which each rider makes positional adjustments in response to the movements of adjacent riders and those ahead. Riders at the front are fully exposed to wind resistance, hence they experience higher fatigue loads than riders in drafting positions. After a period of time in front, leading riders maneuver farther back in the peloton to a drafting position to recover. Thus the peloton is in fluid motion as a continuous rotation of riders push from the back through to the leading edge, then falling away. Like bird flocks, peloton-like behavior that involves drafting or similar energy-saving mechanisms has been identified in a variety of biological systems.

The shape or formation of the peloton changes according to multiple factors. 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. Fatigue is a decisive factor in the outcome of every race. Cyclists' range of peripheral vision is a significant factor in peloton formation.

Thus these formations comprise two main phases of behavior: a compact, low-speed formation, and a single-file, high-speed formation. Peloton phases are indicated by thresholds in collective output that can be modeled mathematically and computationally. The principles of phase behavior identified by Trenchard et al. have been applied to optimize engineering problems.

Similarly, these thresholds in peloton formations define transitions between peloton cooperative behavior and free-riding behavior. Cooperation and free-riding in pelotons have been studied using game theory and as a social dilemma, and have also been considered in terms of equivalencies to aspects of economic theory.

Basic peloton behaviors have also been modelled with robots, and principles of peloton behavior have also been considered in relation to the future of collective robot behavior.

Olds' analysis involved peloton breakaway and chasing groups. He identified the factors involved in determining the likelihood that a breakaway group would succeed in reaching the finish ahead of chasing groups. He identified the following critical factors: distance remaining in the race, the speed of the breakaway group, the number of riders in both the breakaway and chasing groups, how closely riders draft each other, course gradient and roughness, and headwinds and crosswinds (referred to as "demand" factors). 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.