Poor travel-time reliability, meaning that travel times for the same journey are highly variable and unpredictable, gives rise to similar negative impacts on the environment and the economy as does traffic congestion. Moreover, being able to offer a high degree of travel-time reliability will facilitate the uptake of sustainable road transportation including future public, shared, and on-demand mobility services, and on-time delivery of freight. Unpredictability arises partly from poor coordination between vehicles.
Swarm intelligence refers to a set of techniques, inspired by nature, that allow collections of agents to coordinate and collaborate to achieve their common goals through mutual interactions either directly or via their environment. Examples of swarm intelligence techniques include ant colony optimization and particle swarm optimization. This project will explore the use of swarm intelligence techniques, possibly as an enhancement of reinforcement learning, to enable automated vehicles to coordinate their behaviours so as to harmonize traffic flow with the specific goal of offering highly predicable travel times.