Trajectory prediction is a crucial step in the pipeline for autonomous driving because it not
only improves the planning of future routes, but also ensures vehicle safety. On the basis of …

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 …

The past few years have been witness to an increase in autonomous vehicle (AV)
development and testing. However, even with a fully developed and comprehensively tested …

Autonomous robots that can perform common tasks like driving, surveillance, and chores
have the biggest potential for impact due to frequency of usage, and the biggest potential for …

Abstract Internet of Vehicles (IoV) is a rapidly evolving technology that attracts interest from
active research communities such as Internet of things, data security and Artificial …

For a long period, autonomous vehicles (AVs) and human-driven vehicles (HDVs) need to
share roads in mixed traffic flow, where the cut-ins of the HDVs towards the AVs can …

In this study, a novel traffic risk assessment framework of mega-events that integrate risk
field and deep learning is proposed. Considering the inherent difference of different traffic …

Abstract Machine learning-based techniques have shown great promises in perception,
prediction, planning, and general decision-making for improving task performance of …

Learning-based motion prediction and planning algorithms can efficiently extract and
effectively represent the agent-map relationships in high-dimensional space. Generally, the …

The connected and automated vehicle (CAV) technology in recent years has demonstrated
its potential in improving efficiency in transportation systems. Prediction, as a key component …