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Found 4 papers, 1 papers with code
Learning to drive via Apprenticeship Learning and Deep Reinforcement Learning
Therefore, we propose an apprenticeship learning in combination with deep reinforcement learning approach that allows the agent to learn the driving and stopping behaviors with continuous actions.
Robotics
Real-Time Forecasting of Driver-Vehicle Dynamics on 3D Roads: a Deep-Learning Framework Leveraging Bayesian Optimisation
This represents a particularly useful problem, for instance in autonomous driving, but it does not cover a spectrum of applications in control and simulation that require information on vehicle dynamics features other than pose and orientation.
Trajectory Forecasting
Robotics
I.2.9
Design and Simulation-Based Testing of Connected Traffic Light Guidance Systems
The establishment of fast and reliable communication technologies, such as 5G, is enabling the evolution of a new generation of connected ADAS.
Model Predictive Control Strategies for Electric Endurance Race Cars Accounting for Competitors Interactions
This paper presents model predictive control strategies for battery electric endurance race cars accounting for interactions with the competitors.
