Bridging the Gap Between 1D Car-Following and 2D Swarming

Multi-agent systems in multiple dimensions occur in many contexts like human traffic, flocks of birds, and schools of fish. These systems can produce complex emergent phenomena which are not immediately apparent from the individual agents’ law of motion and objectives. In many cases, the emergent behaviors are beneficial like: protection from predators, greater social interactions, and more efficient movement in the environment. One-dimensional traffic flow also exhibits emergent structures; but these are frequently undesirable, like phantom jams and traffic waves. In this talk we present ideas for models that draw from both traffic models and swarming models to produce new models for multi-agent dynamics in 2D and 3D that exhibit agent-following behavior like cars and thus can develop dynamic instabilities. These models may describe swarming with leader effects and driving in the absence of roadways, more accurately than classical swarming models. We showcase via simulations and some analytical results, how the new models can produce very different emergent swarm behavior than existing swarming models.