The behavior prediction of the surrounding vehicles is crucial when planning a minimal-risk
path when realizing a collision-avoidance system. Herein, we propose a multiple model …

In this study, to improve the accuracy of path tracking in intelligent vehicles, we propose an
intelligent vehicle path-tracking control method based on improved model predictive control …

Machine Learning (ML) has replaced traditional handcrafted methods for perception and
prediction in autonomous vehicles. Yet for the equally important planning task, the adoption …

High-performance path tracking is a key technology for autonomous vehicles. Feedforward-
feedback control architectures are suitable for accurate path tracking with adequate margins …

Autonomous vehicles have received considerable attention, yet high-speed path following
control remains a critical and challenging issue. At high speeds, achieving perfect control …

Vehicle chassis coordinated control always has been an appealing topic in academia and
industry because of the increasing number of chassis electronic actuators with the rapid …

To further enhance the precision and the adaptability of path tracking control, and
considering that most of the research is focused on front-wheel steering, an adaptive …

Intelligent vehicle trajectory tracking exhibits problems such as low adaptability, low tracking
accuracy, and poor robustness in complex driving environments with uncertain road …

Supervised deep learning methods using image data as input have shown promising results
in the context of vehicle control. However, these supervised methods have two main …

The Stanley controller is a proven approach for path tracking control in automated vehicles.
If time delays occur, for example, in signal processing and steering angle control, precision …