Compared with vehicular traffic, pedestrian flow operations are very complex. This is why vehicular flow simulation modeling approaches are generally not applicable to the description of pedestrian flows. Gaining insights into pedestrian flow operations is important in, for instance, the planning and geometric design of pedestrian infrastructural facilities. Additionally, management of pedestrian flows requires knowledge of pedestrian flow behavior. Motivated by the need for accurate pedestrian flow models, a microscopic pedestrian flow model is presented. The model is characterized by pedestrian interaction behavior, based on stimulus-response mechanisms. Moreover, local route-choice behavior is included, which describes how pedestrians choose their direction on the basis of, among other things, their destination and local pedestrian flow conditions. The choice behavior is based on the concept of subjective utility maximization. Moreover, the model features parallel updating, comparable with recently developed cellular automata models for pedestrian flows. However, contrary to these models, pedestrian locations are not bounded to discrete cells. The model can therefore easily describe multidirectional pedestrian flows (e.g., unidirectional, bidirectional, and crossing). Application of the model to a simple hallway is discussed. Besides speed-density relations, self-organizing phenomena are studied in pedestrian flows (dynamic lane formation and clustering) from the microscopic pedestrian flow model.