Thanks to their road safety potential, automated vehicles are rapidly becoming a reality. In
the last decade, automated driving has been the focus of intensive automotive engineering …

Model Predictive Control (MPC) algorithms typically use the classical L 2 cost function,
which minimises squared differences of predicted control errors. Such an approach has …

This work has two objectives. Firstly, it describes a novel physics-informed hybrid neural
network (PIHNN) model based on the long short-term memory (LSTM) neural network. The …

Background: The growth of the number of vehicles in traffic has led to an exponential
increase in the number of road accidents with many negative consequences, such as loss of …

This study aims to solve the problems of poor exploration ability, single strategy, and high
training cost in autonomous underwater vehicle (AUV) motion planning tasks and to …

Traffic waves in traffic flow significantly impact road throughput and fuel consumption and
may even lead to severe safety issues. Currently, in connected and autonomous …

This paper proposes a Linear Parameter Varying (LPV) based steering control design
method, which contains data aided control elements, eg, learning-based agents. The …