Track based offline policy learning for overtaking maneuvers with autonomous racecars
The rising popularity of driver-less cars has led to the research and development in the field
of autonomous racing, and overtaking in autonomous racing is a challenging task. Vehicles …
of autonomous racing, and overtaking in autonomous racing is a challenging task. Vehicles …
Towards Optimal Head-to-head Autonomous Racing with Curriculum Reinforcement Learning
Head-to-head autonomous racing is a challenging problem, as the vehicle needs to operate
at the friction or handling limits in order to achieve minimum lap times while also actively …
at the friction or handling limits in order to achieve minimum lap times while also actively …
Gaussian process-based stochastic model predictive control for overtaking in autonomous racing
A fundamental aspect of racing is overtaking other race cars. Whereas previous research on
autonomous racing has majorly focused on lap-time optimization, here, we propose a …
autonomous racing has majorly focused on lap-time optimization, here, we propose a …
Autonomous overtaking in gran turismo sport using curriculum reinforcement learning
Professional race-car drivers can execute extreme overtaking maneuvers. However, existing
algorithms for autonomous overtaking either rely on simplified assumptions about the …
algorithms for autonomous overtaking either rely on simplified assumptions about the …
Deriving spatial policies for overtaking maneuvers with autonomous vehicles
Planning an accurate and safe trajectory is a crucial element in autonomous driving. To
execute complex driving maneuvers like overtaking, motion planning requires an enhanced …
execute complex driving maneuvers like overtaking, motion planning requires an enhanced …
Formula rl: Deep reinforcement learning for autonomous racing using telemetry data
This paper explores the use of reinforcement learning (RL) models for autonomous racing.
In contrast to passenger cars, where safety is the top priority, a racing car aims to minimize …
In contrast to passenger cars, where safety is the top priority, a racing car aims to minimize …
Overtaking maneuvers in simulated highway driving using deep reinforcement learning
Most methods that attempt to tackle the problem of Autonomous Driving and overtaking
usually try to either directly minimize an objective function or iteratively in a Reinforcement …
usually try to either directly minimize an objective function or iteratively in a Reinforcement …
Game-theoretic model predictive control with data-driven identification of vehicle model for head-to-head autonomous racing
Resolving edge-cases in autonomous driving, head-to-head autonomous racing is getting a
lot of attention from the industry and academia. In this study, we propose a game-theoretic …
lot of attention from the industry and academia. In this study, we propose a game-theoretic …
An autonomous system for head-to-head race: Design, implementation and analysis; team kaist at the indy autonomous challenge
While the majority of autonomous driving research has concentrated on everyday driving
scenarios, further safety and performance improvements of autonomous vehicles require a …
scenarios, further safety and performance improvements of autonomous vehicles require a …
Residual policy learning for vehicle control of autonomous racing cars
R Trumpp, D Hoornaert… - 2023 IEEE Intelligent …, 2023 - ieeexplore.ieee.org
The development of vehicle controllers for autonomous racing is challenging because
racing cars operate at their physical driving limit. Prompted by the demand for improved …
racing cars operate at their physical driving limit. Prompted by the demand for improved …