A model of pedestrian movement in a comfortable environment is presented. "Comfortable" and "relaxed" here mean that traffic flow is not overly restricted by environment or congestion and in addition is not related to safety measures, such as evacuation. The algorithmic model uses a layered approach to model human movement in which rules and behaviors are created to simulate group interactions. Learning and memory are modeled so that simulated pedestrians are like humans in ways that have an effect on congestion, and software has been developed that implements the model. The model was calibrated by using widely accepted data and validated against observed data in a shopping mall. Results from the simulator show that the model produces reliable results for situations in which the modeled behavior is typical. Proof-of-concept software implementation shows the utility of the model and how it can be used to ease and improve design of pedestrian areas.