Modeling pedestrian dynamics and their implementation in a computer are challenging and
important issues in the knowledge areas of transportation and computer simulation. The aim …

The real‐time simulation of human crowds has many applications. Simulating how the
people in a crowd move through an environment is an active and ever‐growing research …

We present a new local method for collision avoidance that is based on collision prediction.
In our model, each pedestrian predicts possible future collisions with other pedestrians and …

As a collective and highly dynamic social group, the human crowd is a fascinating
phenomenon that has been frequently studied by experts from various areas. Recently …

We present Menge, a cross-platform, extensible, modular framework for simulating
pedestrian movement in a crowd. Menge's architecture is inspired by an implicit …

We present an information-theoretic method to measure the similarity between a given set of
observed, real-world data and visual simulation technique for aggregate crowd motions of a …

Local collision avoidance algorithms in crowd simulation often ignore agents beyond a
neighborhood of a certain size. This cutoff can result in sharp changes in trajectory when …

To simulate the low-level ('microscopic') behavior of human crowds, a local navigation
algorithm computes how a single person ('agent') should move based on its surroundings …

The ever‐increasing applicability of interactive virtual worlds in industry and academia has
given rise to the need for robust, versatile autonomous virtual humans to inject life into these …

Data-driven crowd modeling has now become a popular and effective approach for
generating realistic crowd simulation and has been applied to a range of applications, such …