With growing numbers of intelligent autonomous systems in human environments, the ability
of such systems to perceive, understand, and anticipate human behavior becomes …

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 …

Collecting pedestrian behaviour data is vital to understand pedestrian behaviour. This
systematic review of 147 studies aims to determine the capability of contemporary data …

Currently, pedestrian simulation models are used to predict where, when and why
hazardous high density crowd movements arise. However, it is questionable whether …

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 …

Crowd simulation has emerged in the last decade as a widely used method of visual effects,
computer games, and urban planning, etc. The improvement of hardware performance and …

Large dense crowds show aggregate behavior with reduced individual freedom of
movement. We present a novel, scalable approach for simulating such crowds, using a dual …

In the everyday exercise of controlling their locomotion, humans rely on their optic flow of the
perceived environment to achieve collision-free navigation. In crowds, in spite of the …

We present a new local collision avoidance algorithm between multiple agents for real-time
simulations. Our approach extends the notion of velocity obstacles from robotics and …

The human-robot interaction community has developed many methods for robots to navigate
safely and socially alongside humans. However, experimental procedures to evaluate these …