A continuous distance model (CDM) for the single-file pedestrian movement considering step frequency and length

A good evacuation model should be good to predict actual macroscopic and microscopic characteristics of pedestrian movement. In order to explore pedestrian movement behavior, we conducted controlled experiments of the single-file pedestrian movement, extracted the motion data by using a mean-shift digital image processing algorithm and analyzed the movement characteristics of pedestrians. It is found that both the pedestrian step length and frequency decreases with the increasing global pedestrian density. Furthermore, there is linear relationship between the step frequency and the distance headway of a pedestrian. Based on the characteristics observed from our experiments, we built a continuous distance model (CDM) for the single-file pedestrian movement. Two new insights were taken into account in the movement algorithm. The first one is that, the continuous step length is adopted to avoid unreasonable results caused by the simplification of the step length in traditional discrete models. The second one is that the dependency between the transition probability and the distance headway is introduced for the reason that the transition probability is correlated with the actual step frequency. Simulation results indicated that there is a close agreement on the flow-density and velocity–density relations between the experiments and modeling. Moreover, it is found that the CDM model is capable of reproducing microscopic features for the scenario with high density.