A survey on attack detection and resilience for connected and automated vehicles: From vehicle dynamics and control perspective

Z Ju, H Zhang, X Li, X Chen, J Han… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
Recent advances in attack/anomaly detection and resilience strategies for connected and
automated vehicles (CAVs) are reviewed from vehicle dynamics and control perspective …

[HTML][HTML] A review of model predictive controls applied to advanced driver-assistance systems

A Musa, M Pipicelli, M Spano, F Tufano, F De Nola… - Energies, 2021‏ - mdpi.com
Advanced Driver-Assistance Systems (ADASs) are currently gaining particular attention in
the automotive field, as enablers for vehicle energy consumption, safety, and comfort …

Distributed dynamic event-triggered secure model predictive control of vehicle platoon against DoS attacks

J Chen, H Zhang, G Yin - IEEE Transactions on Vehicular …, 2022‏ - ieeexplore.ieee.org
This paper studies the distributed dynamic event-triggered model predictive control (MPC) of
vehicle platoon systems subject to denial-of-service (DoS) attacks and external …

Data-driven modeling and distributed predictive control of mixed vehicle platoons

J Zhan, Z Ma, L Zhang - IEEE Transactions on Intelligent …, 2022‏ - ieeexplore.ieee.org
With the development of automatic driving technology and the internet of vehicles,
platooning based on control of connected autonomous vehicles has become one of the most …

Disturbance observer-based cooperative control of vehicle platoons subject to mismatched disturbance

M Hu, X Wang, Y Bian, D Cao… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
The connected and automated vehicle (CAV) technique is a critical application of intelligent
vehicles (IV) and is gaining widespread attention for its prospects of increasing driving …

[HTML][HTML] Traffic expertise meets residual RL: Knowledge-informed model-based residual reinforcement learning for CAV trajectory control

Z Sheng, Z Huang, S Chen - Communications in Transportation Research, 2024‏ - Elsevier
Abstract Model-based reinforcement learning (RL) is anticipated to exhibit higher sample
efficiency than model-free RL by utilizing a virtual environment model. However, obtaining …

Mixed cloud control testbed: Validating vehicle-road-cloud integration via mixed digital twin

J Dong, Q Xu, J Wang, C Yang, M Cai… - IEEE Transactions …, 2023‏ - ieeexplore.ieee.org
Reliable and efficient validation technologies are critical for the recent development of multi-
vehicle cooperation and vehicle-road-cloud integration. In this paper, we introduce our …

Robust min-max model predictive vehicle platooning with causal disturbance feedback

J Zhou, D Tian, Z Sheng, X Duan, G Qu… - IEEE Transactions …, 2022‏ - ieeexplore.ieee.org
Platoon-based vehicular cyber-physical systems have gained increasing attention due to
their potentials in improving traffic efficiency, capacity, and saving energy. However, external …

Data-driven robust predictive control for mixed vehicle platoons using noisy measurement

J Lan, D Zhao, D Tian - IEEE Transactions on Intelligent …, 2021‏ - ieeexplore.ieee.org
This paper investigates cooperative adaptive cruise control (CACC) for mixed platoons
consisting of both human-driven vehicles (HVs) and automated vehicles (AVs). This …

Robust MPC-based trajectory tracking of autonomous underwater vehicles with model uncertainty

Z Yan, J Yan, S Cai, Y Yu, Y Wu - Ocean Engineering, 2023‏ - Elsevier
A robust model predictive control (MPC) method with dual closed-loops is presented to
handle trajectory tracking of autonomous underwater vehicle (AUV) with uncertain model …