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 …

This paper studies the codesign optimization approach to determine how to optimally adapt
automatic control of an intelligent electric vehicle to driving styles. A cyber-physical system …

Graph neural networks (GNNs) have been extensively used in a wide variety of domains in
recent years. Owing to their power in analyzing graph-structured data, they have become …

In this paper, an improved Model Predictive Control (MPC) controller based on fuzzy
adaptive weight control is proposed to solve the problem of autonomous vehicle in the …

During the last decade, sampling-based algorithms for path planning have gained
considerable attention. The RRT*, a variant of RRT (rapidly-exploring random trees), is of …

This paper focuses on the lane-changing trajectory planning (LTP) process in the automatic
driving technologies. Existing studies on the LTP algorithms are primarily the static planning …

A motion planning method for autonomous vehicles confronting emergency situations where
collision is inevitable, generating a path to mitigate the crash as much as possible, is …

Autonomous vehicles (AVs) have now drawn significant attentions in academic and
industrial research because of various advantages such as safety improvement, lower …

The recent progress in autonomous vehicle research and development has led to
increasingly widespread testing of fully autonomous vehicles on public roads, where …

Parametric modeling uncertainties and unknown external disturbance are major concerns in
the development of advanced lateral motion controller for autonomous vehicle at the limits of …