Policy networks have great potential to learn sophisticated driving policy under complicated
interaction between human drivers. However, it is hard for policy networks to satisfy safety …

Collaborative motion planning for multi-agent systems is a challenging problem because of
the existence of highly nonlinear and nonconvex constraints. Such difficulties also lead to …

This letter proposes an adaptive high-order control barrier function-based iterative linear
quadratic regulator (AHOCBF-ILQR) algorithm for real time safety-critical motion planning …

In order to solve the accuracy problem of trajectory tracking control method based on data-
driven model, an intelligent vehicle trajectory tracking control method based on physics …

Advanced driver assistance systems have gained popularity as a safe technology that helps
people avoid traffic accidents. To improve system reliability, a lot of research on driving …

Humans use tools to complete impact-aware tasks such as hammering a nail or playing
tennis. The postures adopted to use these tools can significantly influence the performance …

We propose a new framework to design controllers for high-dimensional nonlinear systems.
The control is designed through the iterative linear quadratic regulator (ILQR), an algorithm …

Autonomous driving planning is a challenging problem when the environment is
complicated. It is difficult for the planner to find a good trajectory that navigates autonomous …

With the development of science and technology, self-driving technology is gradually being
applied to automobile semi-trailer trains. Aiming at the problem that it is challenging to plan …

Autonomous vehicles have limited computational resources; hence, their control systems
must be efficient. The cost and size of sensors have limited the development of self-driving …