Sahaleh, S., Bierlaire, M., Farooq, B., Danalet, A., and Hänseler, F. (2012)

Scenario Analysis of Pedestrian Flow in Public Spaces

12th Swiss Transport Research Conference, Monte Verit�, Ascona, Switzerland

Several modeling approaches in both microscopic and macroscopic scales have been already put forward into the pedestrian modeling literature. The most operational one of these models is the social force model, where forces are first defined by physical concepts (Newton’s equation) and then have been applied to pedestrian behaviors. On the contrary, there are also models based on discrete choice modeling concept that go deeper in behavioral aspects of pedestrians’ reactions rather than physical forces. In this paper, first we go through the literature in pedestrian modeling domain. Subsequently a real pedestrian simulation experiment conducted in the SV building at EPFL (Ecole Polytechnique Fédérale de Lausanne) is explored. In this building, at a medium sized entrance hall people’s walking behaviors become extremely interesting at certain periods of the day since they take different entrances and exits depending on various destinations that they can reach by passing this hall. We have put a strong emphasis on model calibration. The simulator we used for calibration and simulation is called VISSIM. The VISSWALK add-on of the software (intended exclusively for pedestrians) has been mainly exploited which is based on the social force model. Another dataset is currently collected at a train station which experiences interesting passenger behaviors. The train station is a highly frequent multi-modal transportation hub. This second dataset can be of a high interest for more development in pedestrian modeling especially in the model calibration and validation. Basically, the SV building project is a part of a bigger project concerning pedestrian flow simulation/optimization in a transportation hub where the same methodology and calibration method tested for the SV building are going to be exploited. For the SV building experiment various forecasting (demand change) and optimization (supply change) scenarios are also built and simulated. The analysis of the results from these scenarios is presented.