Mobile robots capable of navigating seamlessly and safely in pedestrian rich environments
promise to bring robotic assistance closer to our daily lives. In this paper we draw on insights …

Driving in urban traffic requires making quick and safe decisions while interacting with
multiple pedestrians and other road users. Early anticipation of others' intentions is …

In order to generate favorable trajectories, road users need to cope with interaction among
them, especially in dense traffic. Thus, for autonomous cars, the intention of involved …

Humans, as both pedestrians and drivers, generally skillfully navigate traffic intersections.
Despite the uncertainty, danger, and the non-verbal nature of communication commonly …

Creating rational driving options and designing the decision process to select the best
solution in a traffic situation with multiple participants present is a challenging problem …

Predicting object motion behaviour is a challenging but crucial task for safe decision making
and path planning for an autonomous vehicle. It is challenging in large part due to the …

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

This paper presents our research platform Safe VRU for the interaction of self-driving
vehicles with Vulnerable Road Users (VRUs, ie, pedestrians and cyclists). The paper details …

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

With autonomous cars being released into the wild, the question is how they integrate with
conventional participants in traffic, such as pedestrians. For accident-free traffic, it is …