Collision avoidance at unsignalized intersections is critical to autonomous vehicle
technology. Our work addresses the challenging problem of online speed planning along a …

In this paper, we propose a decision-making framework for autonomous driving at road
intersections that determines appropriate maneuvers for an autonomous vehicle to navigate …

High confidence in the safe operation of autonomous systems remains a critical hurdle on
their path to becoming ubiquitous. Recent accidents of Uber and Google driverless cars …

In this work we put forward a predictive trajectory planning framework to help autonomous
vehicles plan future trajectories. We develop a partially observable Markov decision process …

Uncontrolled intersections are important and challenging traffic scenarios for autonomous
vehicles. Vehicles not only need to avoid collisions with dynamic vehicles instantaneously …

Safety is one of the major concerns in autonomous driving tasks, and enhancing the
collision avoidance ability of connected and autonomous vehicles (CAVs) is an effective way …

As a part of developing autonomous vehicles and better Advanced driver assistance
systems (ADAS), it is important to consider how the spatio-temporal activities of other agents …

Automated vehicles and advanced driver-assistance systems require an accurate prediction
of future traffic scene states. The tendency in recent years has been to use deep learning …

As autonomous driving technology progresses, the need for precise trajectory prediction
models becomes paramount. This paper introduces an innovative model that infuses …

Autonomous driving in an urban environment with surrounding agents remains challenging.
One of the key challenges is to accurately predict the traversability map that probabilistically …