Introduction The safety of humans in crowded environments has been recognised as an
important and rapidly growing research area with significant implications for urban planning …

This article presents a review of the use of optimisation models for pedestrian evacuation
and design problems. The articles are classified according to the problem type that is …

Demystifying the interactions among multiple agents from their past trajectories is
fundamental to precise and interpretable trajectory prediction. However, previous works only …

Human trajectory prediction is challenging and critical in various applications (eg,
autonomous vehicles and social robots). Because of the continuity and foresight of the …

Since the past few decades, human trajectory forecasting has been a field of active research
owing to its numerous real-world applications: evacuation situation analysis, deployment of …

Understanding human motion behavior is critical for autonomous moving platforms (like self-
driving cars and social robots) if they are to navigate human-centric environments. This is …

Mobility in an effective and socially-compliant manner is an essential yet challenging task for
robots operating in crowded spaces. Recent works have shown the power of deep …

Humans navigate complex crowded environments based on social conventions: they
respect personal space, yielding right-of-way and avoid collisions. In our work, we propose a …

Humans navigate crowded spaces such as a university campus by following common sense
rules based on social etiquette. In this paper, we argue that in order to enable the design of …

Pedestrian trajectory prediction is a challenging task because of the complex nature of
humans. In this paper, we tackle the problem within a deep learning framework by …