The large-scale deployment of automated vehicles on public roads has the potential to
vastly change the transportation modalities of today's society. Although this pursuit has been …

We provide a review of recent work on formal methods for autonomous driving. Formal
methods have been traditionally used to specify and verify the behavior of computer …

Ensuring that autonomous vehicles do not cause accidents remains a challenge. We
present a formal verification technique for guaranteeing legal safety in arbitrary urban traffic …

Provably safe motion planning for automated road vehicles must ensure that planned
motions do not result in a collision with other traffic participants. This is a major challenge in …

The computational effort of trajectory planning for automated vehicles often increases with
the complexity of the traffic situation. This is particularly problematic in safety-critical …

In modern autonomy stacks, prediction modules are paramount to planning motions in the
presence of other mobile agents. However, failures in prediction modules can mislead the …

In autonomous vehicles (AVs), early warning systems rely on collision prediction to ensure
occupant safety. However, state-of-the-art methods using deep convolutional networks …

This article is focused on bibliographic analysis and collaboration pattern analysis of the text
papers published in the IEEE Transactions on Intelligent Vehicles (TIV) from January 2019 …

This paper presents a hierarchical three-layer trajectory planning framework to realize real-
time collision avoidance under complex driving conditions. This is mainly ascribed to the …

The behavior prediction of the surrounding vehicles is crucial when planning a minimal-risk
path when realizing a collision-avoidance system. Herein, we propose a multiple model …