Pedestrian motion modeling in mixed traffic scenarios is crucial to the development of
autonomous systems in transportation related applications. This work investigated how …

This work d deals with the problem of navigating a robot in a constrained human-like
environment. We provide a method to generate a control strategy that enables the robot to …

Autonomous navigation in structured urban environments amongst pedestrians is a
challenging and less explored problem. In this work, we propose to use a deep …

We consider the problem of mapless collision-avoidance navigation where humans are
present using 2D laser scans. Our proposed method uses ego-safety to measure collision …

While motion planning techniques for automated vehicles in a reactive and anticipatory
manner have already been widely presented, cooperative motion planning has only been …

This paper focuses on the detection of pedestrian crossing intention to improve the situation
awareness for autonomous driving in urban environments. A new definition of pedestrian …

Recent developments in vehicle automation require simulations of human-robot interactions
in the road traffic context, which can be achieved by computational models of human …

Behavior prediction of traffic actors is an essential component of any real-world self-driving
system. Actors' long-term behaviors tend to be governed by their interactions with other …

One of the major challenges that autonomous vehicles (AVs) face in an urban setting is
communicating with other road users such as pedestrians. In this work, we investigated with …

Accurate prediction of pedestrian and bicyclist paths is integral to the development of
reliable autonomous vehicles in dense urban environments. The interactions between …