A survey of deep learning applications to autonomous vehicle control
Designing a controller for autonomous vehicles capable of providing adequate performance
in all driving scenarios is challenging due to the highly complex environment and inability to …
in all driving scenarios is challenging due to the highly complex environment and inability to …
Design of a reinforcement learning-based lane keeping planning agent for automated vehicles
Featured Application The presented method can be used as a real-time trajectory following
algorithm for autonomous vehicles using prediction based on lookahead information …
algorithm for autonomous vehicles using prediction based on lookahead information …
Speed tracking control using online reinforcement learning in a real car
L Puccetti, F Köpf, C Rathgeber… - 2020 6th International …, 2020 - ieeexplore.ieee.org
Reinforcement learning has the potential to improve classical control design methods in
numerous applications. However, tracking control is still a challenge. Varying the target over …
numerous applications. However, tracking control is still a challenge. Varying the target over …
Safe car-following strategy with multi-constraints based on deep reinforcement learning for autonomous driving vehicles
Y Zhang, R Yan - 2022 IEEE International Conference on …, 2022 - ieeexplore.ieee.org
Car-following control, based on deep reinforcement learning (DRL), is suitable for achieving
multi-objective optimization and capturing complex system features. However, how to …
multi-objective optimization and capturing complex system features. However, how to …
Adaptive cruise control via adaptive dynamic programming with experience replay
The adaptive cruise control (ACC) problem can be transformed to an optimal tracking control
problem for complex nonlinear systems. In this paper, a novel highly efficient model-free …
problem for complex nonlinear systems. In this paper, a novel highly efficient model-free …
A Testing and Verification Approach to Tune Control Parameters of Cooperative Driving Automation Under False Data Injection Attacks
JC Holland, F Javidi-Niroumand, A Ala'J… - IEEE …, 2024 - ieeexplore.ieee.org
Control systems are used in safety-critical applications where tuning the system parameters
is required to ensure safe and secure operation. The process of tuning these parameters …
is required to ensure safe and secure operation. The process of tuning these parameters …
Dynamics model and design for adaptive cruise control vehicles
Adaptive Cruise Control (ACC) is the function of advanced driver assistance system in the
longitudinal vehicle dynamics to maintain the desired distance and the safe speed from the …
longitudinal vehicle dynamics to maintain the desired distance and the safe speed from the …
[PDF][PDF] Reinforcement learning based approach for multi-vehicle platooning problem with nonlinear dynamic behavior
A Farag, OM AbdelAziz, A Hussein… - Proc. 34th Conf. Neural …, 2020 - researchgate.net
One of the most recent research directions in the field of Cooperative Intelligent
Transportation System is vehicle platooning. Researchers focused on various ways of …
Transportation System is vehicle platooning. Researchers focused on various ways of …
[PDF][PDF] End-to-end deep learning control for autonomous vehicles
SJ Kuutti - 2022 - openresearch.surrey.ac.uk
The next generation of autonomous vehicles will provide major improvements in traffic flow,
fuel efficiency, and vehicle safety. Several challenges currently prevent the deployment of …
fuel efficiency, and vehicle safety. Several challenges currently prevent the deployment of …