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

As mobile robots are increasingly introduced into our daily lives, it grows ever more
imperative that these robots navigate with and among people in a safe and socially …

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 …

The maritime Internet of Things (IoT) has recently emerged as a revolutionary
communication paradigm where a large number of moving vessels are closely …

Pedestrian trajectory prediction is an essential component in a wide range of AI applications
such as autonomous driving and robotics. Existing methods usually assume the training and …

Capturing high-dimensional social interactions and feasible futures is essential for
predicting trajectories. To address this complex nature, several attempts have been devoted …

Social interaction is an important topic in human trajectory prediction to generate plausible
paths. In this paper, we present a novel insight of group-based social interaction model to …

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 …

The recent progress in autonomous vehicle research and development has led to
increasingly widespread testing of fully autonomous vehicles on public roads, where …

We present a novel approach for traffic forecasting in urban traffic scenarios using a
combination of spectral graph analysis and deep learning. We predict both the low-level …