Control of connected and automated vehicles: State of the art and future challenges
Autonomous driving technology pledges safety, convenience, and energy efficiency. Its
challenges include the unknown intentions of other road users: communication between …
challenges include the unknown intentions of other road users: communication between …
Review and comparison of path tracking based on model predictive control
G Bai, Y Meng, L Liu, W Luo, Q Gu, L Liu - Electronics, 2019 - mdpi.com
Recently, model predictive control (MPC) is increasingly applied to path tracking of mobile
devices, such as mobile robots. The characteristics of these MPC-based controllers are not …
devices, such as mobile robots. The characteristics of these MPC-based controllers are not …
A survey of motion planning and control techniques for self-driving urban vehicles
Self-driving vehicles are a maturing technology with the potential to reshape mobility by
enhancing the safety, accessibility, efficiency, and convenience of automotive transportation …
enhancing the safety, accessibility, efficiency, and convenience of automotive transportation …
The kinematic bicycle model: A consistent model for planning feasible trajectories for autonomous vehicles?
Most autonomous driving architectures separate planning and control phases in different
layers, even though both problems are intrinsically related. Due to limitations on the …
layers, even though both problems are intrinsically related. Due to limitations on the …
From linear to nonlinear MPC: bridging the gap via the real-time iteration
Linear model predictive control (MPC) can be currently deployed at outstanding speeds,
thanks to recent progress in algorithms for solving online the underlying structured quadratic …
thanks to recent progress in algorithms for solving online the underlying structured quadratic …
Lateral vehicle trajectory optimization using constrained linear time-varying MPC
B Gutjahr, L Gröll, M Werling - IEEE Transactions on Intelligent …, 2016 - ieeexplore.ieee.org
In this paper, a trajectory optimization algorithm is proposed, which formulates the lateral
vehicle guidance task along a reference curve as a constrained optimal control problem …
vehicle guidance task along a reference curve as a constrained optimal control problem …
[HTML][HTML] Impact of battery cell imbalance on electric vehicle range
Due to manufacturing variation, battery cells often possess heterogeneous characteristics,
leading to battery state-of-charge variation in real-time. Since the lowest cell state-of-charge …
leading to battery state-of-charge variation in real-time. Since the lowest cell state-of-charge …
Stochastic model predictive control—how does it work?
Stochastic model predictive control (SMPC) provides a probabilistic framework for MPC of
systems with stochastic uncertainty. A key feature of SMPC is the inclusion of chance …
systems with stochastic uncertainty. A key feature of SMPC is the inclusion of chance …
Event-triggered model predictive control for autonomous vehicle path tracking: Validation using CARLA simulator
Z Zhou, C Rother, J Chen - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
Model predictive control (MPC) has been widely researched for automotive control.
However, the real-world application of MPC for autonomous vehicles (AV) is still limited due …
However, the real-world application of MPC for autonomous vehicles (AV) is still limited due …
Active safety control of automated electric vehicles at driving limits: A tube-based MPC approach
To enhance the active safety performance for automated electric vehicles (AEVs) at driving
limits, the collaborative control of four-wheel steering (4WS) and direct yaw-moment control …
limits, the collaborative control of four-wheel steering (4WS) and direct yaw-moment control …