(Image: Doug Pensinger/Getty Images)

Cyclists school like fish. The physics of how a group of individuals stays together may be the same whether they are athletes or animals.

Pelotons are groups of cyclists that form during mass-start races like the Tour de France. Cyclists ride behind each other to take advantage of reduced drag, a strategy known as drafting. Emerging from the peloton allows riders to pass each other, but also exposes them to much greater drag and slows them down.


It turns out that these physical principles guide behaviour in a peloton more than cyclists’ individual wills, says Hugh Trenchard, a former competitive cyclist and self-taught physicist. He has developed a model that describes the peloton and which biologists say may also apply to migrating birds and shoaling fish.

Trenchard videoed races around the oval track of a velodrome and looked up statistics on cyclists’ speed and physical attributes. He used this information to create computer simulations of various pelotons.

Energy savers

He found that the shape of the peloton changes from a roughly circular structure to a single-file line depending on the front rider’s speed: as the front rider speeds up, the cyclists stretch out and ride single file; as the front rider slows down, the group comes back together.

This means slower cyclists can still keep up the pace, because of the energy boost they get from drafting. Only when the peloton speed exceeds their top speed combined with the boost they gain from slipstreaming will they fall out of the group.

“Because there is an energy-saving mechanism, it allows weaker members to sustain the speeds of other members and keep the group cohesive,” he says.

Any cyclist has seen these phases in action, but modelling them unveils the basic principles that explain how pelotons work, Trenchard says. First, the energy-saving benefit of drafting drives cyclists to stay close together. Next, the shape of the peloton is determined by each cyclist’s individual speed. Finally, the entire group is limited by individual cyclists’ inherent maximum abilities.

These principles apply regardless of team strategies, rider fatigue and other human aspects of cycling, he says. He calls this “protocooperative behaviour,” because it emerges when individuals work together unintentionally.

Best placed

In pelotons as in animal groups, some individuals stand to gain more than others depending on their positions, says James Herbert-Read of Uppsala University in Sweden, who studies collective animal behaviour.

“Some individuals could ‘cheat’ by occupying positions at the back of the group and not moving into forward positions,” he says. “The questions asked in this paper could indeed be applied to moving animal groups, although measuring these processes is more difficult.”

Trenchard is now working with Shaun Killen at the University of Glasgow, UK, to study whether his model applies to schools of fish fleeing predators.

“From our perspective, it does provide a useful framework for testing predictions,” Killen says. “It’s not something that is often thought about in an ecological context, where it gets assumed that a group of fish is a group of fish. But there might actually be some physiological structure there.”

Journal reference: Applied Mathematics and Computation, DOI: 10.1016/j.amc.2015.08.006