Modelling Pedestrian Behavior

I describe a discrete choice approach to microscopic agent modelling pedestrian behaviour. Crossed nested logit models are used by agents to make utility maximising choices in a dynamic and individual-based discretization of speed and direction. Each agent has a first-order theory-of-mind, basing their choices on predictions about the behaviour of other agent in the next time step. In contrast to most existing pedestrian models I introduce individual differences in agent parameters and present simulations of how groups of pedestrians interact in a range of scenarios requiring them to achieve a set of movement goals. If time allows I will present preliminary results on estimating agent parameters.