On the public citation graph
A Benchmark Comparison of Imitation Learning-based Control Policies for Autonomous Racing
0 signed · 42 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-01234-2_36openalex-snapshot
CIRL: Controllable Imitative Reinforcement Learning for Vision-Based Self-driving
inferredcites →https://doi.org/10.1007/978-3-662-64550-5_10openalex-snapshot
Indy Autonomous Challenge - Autonomous Race Cars at the Handling Limits
inferredcites →https://doi.org/10.1007/s10514-021-10006-9openalex-snapshot
Expert Intervention Learning
inferredcites →https://doi.org/10.1016/b978-0-08-047865-4.50016-8openalex-snapshot
FEATURE EXTRACTION AND LINEAR MAPPING FOR CLASSIFICATION
inferredcites →https://doi.org/10.1016/j.artint.2021.103500openalex-snapshot
A survey of inverse reinforcement learning: Challenges, methods and progress
inferredcites →https://doi.org/10.1016/j.ifacol.2020.12.1669openalex-snapshot
Design and Simulation of a Machine-learning and Model Predictive Control Approach to Autonomous Race Driving for the F1/10 Platform
inferredcites →https://doi.org/10.1016/j.robot.2008.10.024openalex-snapshot
A survey of robot learning from demonstration
inferredcites →https://doi.org/10.1109/ccdc49329.2020.9164410openalex-snapshot
An end-to-end learning of driving strategies based on DDPG and imitation learning
inferredcites →https://doi.org/10.1109/icra.2019.8793698openalex-snapshot
HG-DAgger: Interactive Imitation Learning with Human Experts
inferredcites →https://doi.org/10.1109/icra48506.2021.9562079openalex-snapshot
Learning from Simulation, Racing in Reality
inferredcites →https://doi.org/10.1109/lra.2021.3097345openalex-snapshot
Vision-Based Autonomous Car Racing Using Deep Imitative Reinforcement Learning
inferredcites →https://doi.org/10.1109/ojits.2022.3181510openalex-snapshot
Autonomous Vehicles on the Edge: A Survey on Autonomous Vehicle Racing
inferredcites →https://doi.org/10.1109/tits.2022.3144867openalex-snapshot
A Survey on Imitation Learning Techniques for End-to-End Autonomous Vehicles
inferredcites →https://doi.org/10.1184/r1/6550949openalex-snapshot
A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning
inferredcites →https://doi.org/10.1184/r1/6603146openalex-snapshot
ALVINN, an autonomous land vehicle in a neural network
inferredcites →https://doi.org/10.15607/rss.2018.xiv.056openalex-snapshot
Agile Autonomous Driving using End-to-End Deep Imitation Learning
inferredcites →https://doi.org/10.15607/rss.2020.xvi.055openalex-snapshot
Learning from Interventions: Human-robot interaction as both explicit and implicit feedback
inferredcites →https://doi.org/10.3217/978-3-85125-524-9-10openalex-snapshot
Design of an Autonomous Race Car for the Formula Student Driverless (FSD)
inferredcites →https://doi.org/10.4230/oasics.dx.2024.16openalex-snapshot
Diagnosing Non-Intermittent Anomalies in Reinforcement Learning Policy Executions (Short Paper)
inferredcites →https://doi.org/10.48550/arxiv.1605.06450openalex-snapshot
Query-Efficient Imitation Learning for End-to-End Autonomous Driving
inferredcites →https://doi.org/10.48550/arxiv.1707.08817openalex-snapshot
Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards
inferredcites →https://doi.org/10.48550/arxiv.2109.08273openalex-snapshot
ThriftyDAgger: Budget-Aware Novelty and Risk Gating for Interactive Imitation Learning
inferredcites →https://doi.org/10.48550/arxiv.2209.11181openalex-snapshot
Teaching Autonomous Systems Hands-On: Leveraging Modular Small-Scale Hardware in the Robotics Classroom
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1016/j.cogr.2023.04.002openalex-snapshot
Safe reinforcement learning for high-speed autonomous racing
inferred← citeshttps://doi.org/10.1109/airc64931.2025.11077489openalex-snapshot
Goaltargetnet: Goal Prediction and Tracking for F1tenth Autonomous Sim Racing League With Convolutional Neural Networks
inferred← citeshttps://doi.org/10.1109/ascc70886.2026.11701764openalex-snapshot
Reinforcement Learning-Guided MPC for Autonomous Racing
inferred← citeshttps://doi.org/10.1109/cdc49753.2023.10384075openalex-snapshot
Safe Perception-Based Control Under Stochastic Sensor Uncertainty Using Conformal Prediction
inferred← citeshttps://doi.org/10.1109/compas60761.2024.10796663openalex-snapshot
Creating Multi-level AI Racing Agents Using a Combination of Imitation and Reinforcement Learning and Analyzing Similarity Using Cross-Correlation
inferred← citeshttps://doi.org/10.1109/icmcce63640.2024.11163406openalex-snapshot
Trajectory Tracking Using Frenet Coordinates with Deep Deterministic Policy Gradient
inferred← citeshttps://doi.org/10.1109/iros58592.2024.10801430openalex-snapshot
TinyLidarNet: 2D LiDAR-based End-to-End Deep Learning Model for F1TENTH Autonomous Racing
inferred← citeshttps://doi.org/10.1109/itsc58415.2024.11414064openalex-snapshot
MEGA-DAgger: Imitation Learning with Multiple Imperfect Experts
inferred← citeshttps://doi.org/10.1109/iv55156.2024.10588611openalex-snapshot
AV4EV: Open-Source Modular Autonomous Electric Vehicle Platform for Making Mobility Research Accessible
inferred← citeshttps://doi.org/10.1109/lra.2023.3295252openalex-snapshot
High-Speed Autonomous Racing Using Trajectory-Aided Deep Reinforcement Learning
inferred← citeshttps://doi.org/10.1109/metms70800.2026.11706566openalex-snapshot
End-to-End Steering Regression with a Fixed Vision Transformer Backbone for Input Preprocessing and Bilateral Fusion
inferred← citeshttps://doi.org/10.1109/tase.2025.3541409openalex-snapshot
A Lyapunov-Based Framework for Trajectory Planning of Wheeled Vehicle Using Imitation Learning
inferred← citeshttps://doi.org/10.1109/tiv.2024.3351131openalex-snapshot
A Survey of Vehicle Dynamics Modeling Methods for Autonomous Racing: Theoretical Models, Physical/Virtual Platforms, and Perspectives
inferred← citeshttps://doi.org/10.1109/tiv.2024.3495227openalex-snapshot
F1TENTH: Enhancing Autonomous Systems Education Through Hands-On Learning and Competition
inferred← citeshttps://doi.org/10.23919/acc60939.2024.10644200openalex-snapshot
Safe Control Synthesis for Hybrid Systems through Local Control Barrier Functions
inferred← citeshttps://doi.org/10.23919/acc63710.2025.11107738openalex-snapshot
End-to-end Reinforcement Learning for Autonomous Racing: Bridging the sim-to-real gap
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.