Can Walking Behavior be Predicted?: Analysis of Calibration and Fit of Pedestrian Models

Abstract

Several models for simulation of pedestrian movement have been proposed in recent decades. These models are primarily used in the planning and evaluation of large pedestrian infrastructures, such as transportation hubs, with a focus to increase comfort and safety for pedestrians. Although the number of proposed simulation models is increasing at a fast pace, not much is known about the properties of calibration procedures or the transferability of the models estimated in one setting to other settings. This paper compares three calibration methods for a slightly adapted social force model. The main emphasis lies in the characteristics of the data-generation process and the information contained in the data sets. The sensitivity of the model parameters of the calibrated model were investigated, and the transferability of the model to different scenarios was tested. Results revealed that the quality of the data had a strong effect on the suitability of different calibration strategies and that the information content in the scene under investigation limited the transferability of the results to other scenarios. These results suggest that several data sets with different characteristics do not need to be included in the calibration process to achieve a model that performs well in a wider variety of settings.