Interactive crowd dynamics are crucial for achieving high-fidelity pedestrian behavior in virtual built environments. This study presents IntCrowd, a novel framework for enhancing interactive crowd simulation within immersive virtual environments. The framework comprises a BIM-driven navigational graph, a macro—micro integrated crowd simulation model comprising multidirectional potential fields and modified social force model, and a human—agent information fusion system. Simulation experiments show IntCrowd is more efficient than agent-based models, achieving an 85.6% reduction in additional computational time for generating more agents. A human-in-the-loop experiment conducted on a CAVE platform further demonstrates that IntCrowd can produce realistic pedestrian behavior closely aligned with real-world characteristics on the pedestrian fundamental diagram. The experiment also indicates IntCrowd significantly increases pedestrians’ perceived presence. The findings underscore the importance of high-fidelity and interactive crowd simulation for experiencing virtual built environments. Moreover, IntCrowd offers a more reliable testbed for studying pedestrian behavior in virtual built environments. • Simulating interactive crowd dynamics in virtual built environments • Reducing per-agent computational cost by 85.6% through macro–micro integrated modeling • Construction of the navigational graph using BIM-based geometries and semantics • Enabling low-latency interactions through a human–agent information fusion system • Demonstrate the effectiveness of IntCrowd through a controlled CAVE experiment
Liang et al. (Fri,) studied this question.