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Road friction virtual sensing: A review of estimation techniques with emphasis on low excitation approaches
In this paper, a review on road friction virtual sensing approaches is provided. In particular,
this work attempts to address whether the road grip potential can be estimated accurately …
this work attempts to address whether the road grip potential can be estimated accurately …
Dynamic drifting control for general path tracking of autonomous vehicles
G Chen, X Zhao, Z Gao, M Hua - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Taking full advantage of tire saturation in high sideslip drifting maneuvers can substantially
improve the handling limits of autonomous vehicles. However, most singular motion control …
improve the handling limits of autonomous vehicles. However, most singular motion control …
Virtual tyre force sensors: An overview of tyre model-based and tyre model-less state estimation techniques
M Acosta, S Kanarachos… - Proceedings of the …, 2018 - journals.sagepub.com
This paper presents a comprehensive literature review on tyre force estimation and road grip
recognition approaches. With the development of modern automotive control systems, a …
recognition approaches. With the development of modern automotive control systems, a …
Beyond the stable handling limits: nonlinear model predictive control for highly transient autonomous drifting
Autonomous vehicles that can reliably operate outside the stable handling limits would have
access to a wider range of maneuvers in emergencies, improving overall safety. To that end …
access to a wider range of maneuvers in emergencies, improving overall safety. To that end …
Toward automated vehicle control beyond the stability limits: drifting along a general path
JY Goh, T Goel… - Journal of …, 2020 - asmedigitalcollection.asme.org
Professional drivers in drifting competitions demonstrate accurate control over a car's
position and sideslip while operating in an open-loop unstable region of state-space. Could …
position and sideslip while operating in an open-loop unstable region of state-space. Could …
High-speed autonomous drifting with deep reinforcement learning
Drifting is a complicated task for autonomous vehicle control. Most traditional methods in this
area are based on motion equations derived by the understanding of vehicle dynamics …
area are based on motion equations derived by the understanding of vehicle dynamics …
An adaptive backstep** sliding mode controller to improve vehicle maneuverability and stability via torque vectoring control
L Zhang, H Ding, J Shi, Y Huang… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
To improve the maneuverability and stability of a vehicle and fully leverage the advantages
of torque vectoring technology in vehicle dynamics control, a finite-time yaw rate and …
of torque vectoring technology in vehicle dynamics control, a finite-time yaw rate and …
A real-time nonlinear model predictive control strategy for stabilization of an electric vehicle at the limits of handling
In this paper, we propose a real-time nonlinear model predictive control (NMPC) strategy for
stabilization of a vehicle near the limit of lateral acceleration using the rear axle electric …
stabilization of a vehicle near the limit of lateral acceleration using the rear axle electric …
Modeling and control for dynamic drifting trajectories
TP Weber, JC Gerdes - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
Drifting, or cornering with rear tires that exceed slip limits, represents a trade-off of stability
for controllability while operating at the limits of friction. Recent work has demonstrated …
for controllability while operating at the limits of friction. Recent work has demonstrated …
Search-based task and motion planning for hybrid systems: Agile autonomous vehicles
To achieve optimal robot behavior in dynamic scenarios we need to consider complex
dynamics in a predictive manner. In the vehicle dynamics community, it is well know that to …
dynamics in a predictive manner. In the vehicle dynamics community, it is well know that to …