Precise vehicle state and the surrounding traffic information are essential for decision-
making and dynamic control of intelligent connected vehicles. Tremendous research efforts …

Accurate knowledge about the motion state of preceding vehicles (PVs) contributes to the
optimization of planning and decision making of autonomous vehicles, which in turn further …

Motion control of lane-change maneuvers under high-speed scenarios creates a great
challenge for autonomous vehicles. However, a novel framework of lane-change trajectory …

Intelligent connected vehicles can perform better decision making and path planning tasks
when they obtain the accurate motion state of preceding vehicles. In this article, an event …

Accurate information on tire road friction coefficient (TRFC) is essential to autonomous
driving systems. In this paper, a fault-tolerant estimation scheme is proposed to estimate …

As one of the most significant states to represent lateral stability, vehicle sideslip angle holds
significant importance in vehicle dynamic control systems. Nevertheless, few previous …

The premise of vehicle intelligent decision making is to obtain vehicle motion state
parameters accurately and in real-time. Several state parameters cannot be measured …

Estimation of the tire–road friction coefficient (TRFC) has always been a hotspot in the field
of vehicle control. This problem is also significant in electric vehicles (EVs) with four-wheel …

Accurate prediction of the motion state of the connected vehicles, especially the preceding
vehicle (PV), would effectively improve the decision-making and path planning of intelligent …

An H∞ control strategy based on the phase plane method (phase plane H∞ controller)
tracking two degrees of freedom (DOF) ideal vehicle trajectory scheme is designed for …