As more and more autonomous vehicles (AVs) are being deployed on public roads,
designing socially compatible behaviors for them is becoming increasingly important. In …

Autonomous vehicles (AVs) need to reason about the multimodal behavior of neighboring
agents while planning their own motion. Many existing trajectory planners seek a single …

Typically, autonomous cars optimize for a combination of safety, efficiency, and driving
quality. But as we get better at this optimization, we start seeing behavior go from too …

Autonomous vehicles need to handle various traffic conditions and make safe and efficient
decisions and maneuvers. However, on the one hand, a single optimization/sampling-based …

Recently significant progress has been made in vehicle prediction and planning algorithms
for autonomous driving. However, it remains quite challenging for an autonomous vehicle to …

Decision-making in uncontrolled intersection is one of the main challenges in urban
autonomous driving. This paper proposed a new decision-making framework in uncontrolled …

Contingency planning, wherein an agent generates a set of possible plans conditioned on
the outcome of an uncertain event, is an increasingly popular way for robots to act under …

Autonomous cars have to navigate in dynamic environment which can be full of
uncertainties. The uncertainties can come either from sensor limitations such as occlusions …

Automated driving systems need to perform according to what human drivers expect in every
situation. A different behavior can be wrongly interpreted by other human drivers and cause …

Before autonomous vehicles are widely spread, they will share the roads with non-
autonomous cars. Furthermore, to ensure functional safety of the self-driving cars, the cause …