We propose and validate a model for pedestrian walking behavior, based ondiscrete choice modeling. Two main types of behavior are identified: unconstrained and constrained. By unconstrained, we refer to behavior patternswhich are independent from other individuals. The constrained patterns are captured by a leader follower model and by a collision avoidance model. The spatial correlation between the alternatives is captured by a cross nested logit model. The model is estimated by maximum likelihood estimation on a real data set of pedestrian trajectories, manually tracked from videosequences. The model is successfully validated using a bi-directional flow data set, collected in controlled experimental conditions at Delft university. (A) Reprinted with permission from Elsevier.
Abstract