Neither Dumb nor Optimal: Plausible Wayfinding in Pedestrian Agent-Based Models

Pedestrians are not robots: although observations show that they consider congestion when planning, there are evidences that their decisions are not optimal, even in normal situations. We present a model improving consolidated results mitigating the optimization effects of congestion aware path planning by making commonsense estimations of the effects of perceivable congestion, also embedding an imitation mechanism stimulating changes in planned decisions whenever another nearby pedestrian did the same.