This paper discusses basic findings on crowd movement and their application to simulation models. This includes empirical and experimental results concerning group behavior, pedestrian motion, and emergency egress. Next to a literature review, we will present own empirical investigations on walking speed distribution and the dependency of walking speed on group size. The second part of the paper relates these findings to modelling and simulation of crowd movement. This comprises the representation of behavior, calibration and verification and the connection to many particle systems. Finally, we will present an extension of the current microscopic theory (basically underlying all the "individual" models used for real world applications). This includes route-choice behavior and links microscopic and macroscopic behavior..

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The modeling of pedestrian movement has received growing interest over the last decades. This is due to the potential applications in facility design and especially evacuation simulation as well as the fascination of its fundamental properties. Empirical data plays a particular role with respect to both aspects. The key challenge in modeling and simulating crowd movement is to validate the model assumptions on the one hand and to verify the simulation results on the other hand. In this paper we present empirical data on an evacuation exercise in a primary school. About two hundred pupils (and their teachers) took part in the drill. Three drills were carried out. The premises are divided into two separate buildings, the larger one containing 6 classrooms with about 120 pupils. The results of the exercise are reported. Additionally, the time measured is compared to the time gained from a simulation. It took about 85 s to evacuate the whole school. It has to be noted that the result for the exercise is not a statistical one and no standard deviation can be given. The simulation estimated 160 s with parameter settings representing an average population. This deviation is mainly due to the fact that the students to not fit into this population demographics. We therefore adapted the parameters accordingly and got a result closer to the empirical one: (¤ ¦ ¥ § ¥ © ) s for the egress time (500 simulation runs), e.g., the empirical results is about " ! $ # & % ( ' ) 0.