A situation-aware collision avoidance strategy for car-following

Uncertainty-Aware Reinforcement Learning for Collision Avoidance

Reinforcement learning can enable complex, adaptive behavior to be learned automatically for autonomous robotic platforms. However, practical deployment of reinforcement learning methods must contend with the fact that the training process itself can be unsafe for the robot. In this paper, we consider the specific case of a mobile robot learning to navigate an a priori unknown environment while...

Cooperative Situation Awareness for a Railway Collision Avoidance System (RCAS)

This paper introduces a new approach addressing the problem of colliding trains. As opposed to ”traditional” technical train safety systems, the approach does not require any technology in the infrastructure, i.e. along the railway track, but entirely relies on pervasive information and communication technology in the trains. The approach combines three core technologies: a direct train-to-trai...

Automatic lateral emergency collision avoidance for a passenger car

A Context-Aware Framework for Intersection Collision Avoidance

Leader-Following Formation Navigation for Multiple Robots with Collision Avoidance

This paper deals with a collision avoidance problem in leader-following formation navigation for multiple mobile robots. Because followers should move along a leader’s trajectory, we first try to avoid collisions by adjusting their velocities on the trajectory. This strategy causes delays of the followers from the leader, which is often problematic because we cannot predict how late the followe...