Crowd modelling is essential to the understanding of pedestrian logistics and prevention of crowd disasters. Agent-based approaches can realistically predict crowd behaviour. The social force model as proposed by Helbing and Mólnar in 1995[1] is a widely used agent-based approach. This is a physical model for psychological behaviour that relies strongly on its various parameter values. To investigate the underlying thought of the social force model the physical consequences of the effects and parameters are reviewed in this thesis. Next to this, an adjustment onHelbing andMólnar’s model is made by treating agents as particleswith a hard kernel, requiring a walkover- and ghost-prevention functionality. In addition, it is suggested to set the agent interaction magnitude to U0 ®¯ Æ 21 m2/s2. Subsequently, the adjusted model is validated to empirical research done by Seyfried et al.[2] and to simulations done by Helbing andMólnar[1]. For validation a cluster analysis method is developed to give a quantitative measure of the number of lanes.