Robot navigation in crowded public spaces is a complex task that requires addressing a
variety of engineering and human factors challenges. These challenges have motivated a …

Understanding the behavior of human crowds is a key step toward a safer society and more
livable cities. Despite the individual variability and will of single individuals, human crowds …

Robots that navigate through human crowds need to be able to plan safe, efficient, and
human predictable trajectories. This is a particularly challenging problem as it requires the …

Pedestrian trajectory prediction is an essentially connecting link to understanding human
behavior. Recent works achieve state-of-the-art performance gained from the hand …

Pedestrian trajectory prediction is an extremely challenging problem because of the
crowdedness and clutter of the scenes. Previous deep learning LSTM-based approaches …

Predicting pedestrian movement is critical for human behavior analysis and also for safe and
efficient human-agent interactions. However, despite significant advancements, it is still …

In this paper, we describe the PALM model system 6.0. PALM (formerly an abbreviation for
Parallelized Large-eddy Simulation Model and now an independent name) is a Fortran …

In crowd scenarios, predicting trajectories of pedestrians is a complex and challenging task
depending on many external factors. The topology of the scene and the interactions …

Bacteria are among the oldest and most abundant species on Earth. Bacteria successfully
colonize diverse habitats and play a significant role in the oxygen, carbon, and nitrogen …

The first part of our paper presents a general survey on the modeling, analytic problems, and
applications of the dynamics of human crowds, where the specific features of living systems …