Connected Cruise and Traffic Control for Pairs of Connected Automated Vehicles

Guo, Sicong; Orosz, Gábor; Molnár, Tamás G.

doi:10.1109/tits.2023.3285852

Cited by 3 publications

(1 citation statement)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…and realizing safety, intelligence, comfort, and energy saving in the process of automobile driving. Therefore, AGVs have a broad application prospect in the Intelligent Transportation System [1][2][3][4][5][6]. And as an important part of intelligent connected vehicle technology, trajectory tracking technology involves how to steer the vehicle to make the vehicle travel along the reference path under the premise of ensuring the safety and comfort of the driver.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Terminal Sliding Mode Trajectory Tracking Control for Autonomous Vehicles Considering Completely Unknown Parameters and Unknown Perturbation Conditions

Feng,

Shen,

Wang

et al. 2024

Machines

View full text Add to dashboard Cite

In the actual implementation of autonomous vehicle controller and related applications, it is difficult to obtain all the actual parameters of the vehicle. Considering factors such as uneven pavement and different pavement conditions, it is difficult to accurately establish the vehicle dynamic system model. Based on the non-singular terminal sliding mode and adaptive control theory, this paper establishes a trajectory tracking control strategy for an autonomous vehicle with unknown parameters and unknown disturbances. Firstly, the complex trajectory tracking problem is decoupled from the position and heading angle tracking problem, and the preview error equation is established. Secondly, a non-singular terminal sliding mode (NTSM) controller is established to stabilize the trajectory tracking error to the origin in a finite time, and adaptive laws are proposed to estimate the unknown vehicle parameters to adapt to environmental changes. Through the CarSim–Matlab platform, typical working conditions are implemented to verify the proposed controller. Our experimental outcomes affirm that the NTSM controller effectively guarantees the autonomous vehicle’s accurate following of the reference path, ensuring smooth control inputs throughout the entire process.

show abstract