source of food, they will also return to the nest bringing food and reinforcing the pheromone trail, increasing the probability of recruiting more ants. Once the food source is exhausted, ants stop reinforcing the pheromone trail, which evaporates with time to prevent more ants from going to an empty source. Once a new source of food is found by exploring ants, new pheromone trails are formed. This communication via the environment is also known as “stigmergy” [123]. Functionally, the cognition of insect colonies mediated by stigmergy is analogous to neural cognition [55]. The self-organizing method proposed for regulating public transportation headways is also stigmergic. However, instead of using pheromones, it uses “antipheromones”. Pheromones are placed by insects and evaporate with time, thus reducing their concentration. An- tipheromones are virtual markers that increase their concentration with time, while they are erased by passing vehicles. A simple algorithm determines how much time each vehicle should spend at each station depending on the amount of passengers waiting at the station, the antipheromone concentration (which is directly proportional to the time since the vehicle ahead departed), and the distance to the vehicle behind [57]. This algorithm enables each vehicle to adapt to the demand at each station, preventing idling that occurs when equal headways are maintained, and allows enough robustness to prevent the platooning of vehicles and flexibility to recover from platooned configurations. Discrete computer simulations were performed to compare the self-organizing method with a “default” method, which does not restrict any waiting time and always leads to equal headway instability, and an “adaptive maximum” method [66], where there is a minimum waiting time at stations for vehicles and a maximum waiting time is modified depending on the global passenger demand and headways are always maintained, but not recovered. In the simulations, vehicles have a maximum passenger capacity and move discretely one space unit per time step, unless there is another vehicle ahead, passengers are boarding or descending at stations, or there is another restriction, such as waiting times at stations. Passengers arrive randomly at stations with a Poisson distribution on average every λ time steps. When a 21