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Exploring Applications of Deep Reinforcement Learning for Real-world Autonomous Driving Systems
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-319-25808-9_4openalex-snapshot
An Experimental Review of Reinforcement Learning Algorithms for Adaptive Traffic Signal Control
inferredcites →https://doi.org/10.1007/978-3-319-58347-1_10openalex-snapshot
Domain-Adversarial Training of Neural Networks
inferredcites →https://doi.org/10.1007/978-3-319-67361-5_40openalex-snapshot
AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles
inferredcites →https://doi.org/10.1007/978-3-319-71589-6_36openalex-snapshot
Survival-Oriented Reinforcement Learning Model: An Effcient and Robust Deep Reinforcement Learning Algorithm for Autonomous Driving Problem
inferredcites →https://doi.org/10.1007/springerreference_302487openalex-snapshot
Robot Learning from Demonstration
inferredcites →https://doi.org/10.1016/b978-1-55860-141-3.50030-4openalex-snapshot
Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dynamic Programming
inferredcites →https://doi.org/10.1023/a:1022140919877openalex-snapshot
Recent Advances in Hierarchical Reinforcement Learning
inferredcites →https://doi.org/10.1038/nature16961openalex-snapshot
Mastering the game of Go with deep neural networks and tree search
inferredcites →https://doi.org/10.1109/cvpr.2012.6248074openalex-snapshot
Are we ready for autonomous driving? The KITTI vision benchmark suite
inferredcites →https://doi.org/10.1109/cvpr.2017.18openalex-snapshot
Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks
inferredcites →https://doi.org/10.1109/cvpr.2017.233openalex-snapshot
DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agents
inferredcites →https://doi.org/10.1109/cvpr.2017.376openalex-snapshot
End-to-End Learning of Driving Models from Large-Scale Video Datasets
inferredcites →https://doi.org/10.1109/cvpr.2018.00803openalex-snapshot
Toward Driving Scene Understanding: A Dataset for Learning Driver Behavior and Causal Reasoning
inferredcites →https://doi.org/10.1109/icra.2015.7139555openalex-snapshot
Learning driving styles for autonomous vehicles from demonstration
inferredcites →https://doi.org/10.1109/icra.2018.8460875openalex-snapshot
Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping
inferredcites →https://doi.org/10.1109/ijcnn.1992.287172openalex-snapshot
Meta-neural networks that learn by learning
inferredcites →https://doi.org/10.1109/iros.2004.1389727openalex-snapshot
Design and use paradigms for gazebo, an open-source multi-robot simulator
inferredcites →https://doi.org/10.1109/iros.2009.5354147openalex-snapshot
Planning-based prediction for pedestrians
inferredcites →https://doi.org/10.1109/itsc.2017.8317735openalex-snapshot
Formulation of deep reinforcement learning architecture toward autonomous driving for on-ramp merge
inferredcites →https://doi.org/10.1109/ivs.2018.8500368openalex-snapshot
Deep Hierarchical Reinforcement Learning for Autonomous Driving with Distinct Behaviors
inferredcites →https://doi.org/10.1109/tits.2011.2106158openalex-snapshot
A Multiple-Goal Reinforcement Learning Method for Complex Vehicle Overtaking Maneuvers
inferredcites →https://doi.org/10.1109/tiv.2016.2578706openalex-snapshot
A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles
inferredcites →https://doi.org/10.1109/tnn.2004.842673openalex-snapshot
Reinforcement Learning: An Introduction
inferredcites →https://doi.org/10.1109/wacv45572.2020.9093332openalex-snapshot
Uncertainty-aware Short-term Motion Prediction of Traffic Actors for Autonomous Driving
inferredcites →https://doi.org/10.1145/1015330.1015430openalex-snapshot
Apprenticeship learning via inverse reinforcement learning
inferredcites →https://doi.org/10.1145/1102351.1102352openalex-snapshot
Exploration and apprenticeship learning in reinforcement learning
inferredcites →https://doi.org/10.1145/1390156.1390278openalex-snapshot
Sample-based learning and search with permanent and transient memories
inferredcites →https://doi.org/10.1146/annurev-control-060117-105157openalex-snapshot
Planning and Decision-Making for Autonomous Vehicles
inferredcites →https://doi.org/10.1184/r1/6554699openalex-snapshot
Efficient Reductions for Imitation Learning
inferredcites →https://doi.org/10.1184/r1/6555512openalex-snapshot
Maximum Entropy Inverse Reinforcement Learning
inferredcites →https://doi.org/10.1609/aaai.v30i1.10295openalex-snapshot
Deep Reinforcement Learning with Double Q-Learning
inferredcites →https://doi.org/10.1609/aaai.v31i1.10857openalex-snapshot
Query-Efficient Imitation Learning for End-to-End Simulated Driving
inferredcites →https://doi.org/10.1609/aaai.v32i1.11757openalex-snapshot
Deep Q-learning From Demonstrations
inferredcites →https://doi.org/10.21236/ada440280openalex-snapshot
Intrinsically Motivated Reinforcement Learning
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.1312.5602openalex-snapshot
Playing Atari with Deep Reinforcement Learning
inferredcites →https://doi.org/10.48550/arxiv.1502.05477openalex-snapshot
Trust Region Policy Optimization
inferredcites →https://doi.org/10.48550/arxiv.1509.02971openalex-snapshot
Continuous control with deep reinforcement learning
inferredcites →https://doi.org/10.48550/arxiv.1603.00448openalex-snapshot
Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization
inferredcites →https://doi.org/10.48550/arxiv.1604.07316openalex-snapshot
End to End Learning for Self-Driving Cars
inferredcites →https://doi.org/10.48550/arxiv.1610.03295openalex-snapshot
Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving
inferredcites →https://doi.org/10.48550/arxiv.1611.02779openalex-snapshot
RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning
inferredcites →https://doi.org/10.48550/arxiv.1611.05763openalex-snapshot
Learning to reinforcement learn
inferredcites →https://doi.org/10.48550/arxiv.1612.00147openalex-snapshot
Combining Deep Reinforcement Learning and Safety Based Control for Autonomous Driving
inferredcites →https://doi.org/10.48550/arxiv.1612.03653openalex-snapshot
Learning to Drive using Inverse Reinforcement Learning and Deep Q-Networks
inferredcites →https://doi.org/10.48550/arxiv.1612.04340openalex-snapshot
End-to-End Deep Reinforcement Learning for Lane Keeping Assist
inferredcites →https://doi.org/10.48550/arxiv.1703.03400openalex-snapshot
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
inferredcites →https://doi.org/10.48550/arxiv.1705.10422openalex-snapshot
Learning End-to-end Multimodal Sensor Policies for Autonomous Navigation
inferredcites →https://doi.org/10.48550/arxiv.1709.06560openalex-snapshot
Deep Reinforcement Learning that Matters
inferredcites →https://doi.org/10.48550/arxiv.1710.03641openalex-snapshot
Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
inferredcites →https://doi.org/10.48550/arxiv.1711.01503openalex-snapshot
Composing Meta-Policies for Autonomous Driving Using Hierarchical Deep Reinforcement Learning
inferredcites →https://doi.org/10.48550/arxiv.1803.00590openalex-snapshot
Hierarchical Imitation and Reinforcement Learning
inferredcites →https://doi.org/10.48550/arxiv.1803.02999openalex-snapshot
On First-Order Meta-Learning Algorithms
inferredcites →https://doi.org/10.48550/arxiv.1803.07055openalex-snapshot
Simple random search provides a competitive approach to reinforcement learning
inferredcites →https://doi.org/10.48550/arxiv.1804.07871openalex-snapshot
A Reinforcement Learning Based Approach for Automated Lane Change Maneuvers
inferredcites →https://doi.org/10.48550/arxiv.1808.04355openalex-snapshot
Large-Scale Study of Curiosity-Driven Learning
inferredcites →https://doi.org/10.48550/arxiv.1809.01999openalex-snapshot
Recurrent World Models Facilitate Policy Evolution
inferredcites →https://doi.org/10.5244/c.31.11openalex-snapshot
Virtual to Real Reinforcement Learning for Autonomous Driving
inferredcites →https://doi.org/10.5555/1577069.1755839openalex-snapshot
Transfer Learning for Reinforcement Learning Domains: A Survey
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Variance Reduction in Actor Critic Methods (ACM)
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Social Navigation with Human Empowerment Driven Deep Reinforcement Learning
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Dynamic Simulation and Kinematic Control for Autonomous Driving in Automobile Robots
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Managing Deep Learning Uncertainty for Unmanned Systems
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Reinforcement Learning Based Advanced Driver Assistance System for Unmarked Road Scenarios
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Trojan playground: a reinforcement learning framework for hardware Trojan insertion and detection
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Deep Reinforcement Learning Techniques in Diversified Domains: A Survey
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A survey of deep reinforcement learning application in 5G and beyond network slicing and virtualization
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Driving policies of V2X autonomous vehicles based on reinforcement learning methods
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Decentralized cooperative driving automation: a reinforcement learning framework using genetic fuzzy systems
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Detecting Human Driver Inattentive and Aggressive Driving Behavior Using Deep Learning: Recent Advances, Requirements and Open Challenges
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RL_QOptimizer: A Reinforcement Learning Based Query Optimizer
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Two-timescale Mechanism-and-Data-Driven Control for Aggressive Driving of Autonomous Cars
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Revolutionizing Transportation Using Deep Reinforcement Learning: A Comprehensive Review
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Deep Reinforcement Learning for Autonomous Internet of Things: Model, Applications and Challenges
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Safe and Reliable Training of Learning-Based Aerospace Controllers
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DynaPredict: Alternating Predictive and Real Iteration for Efficient Deep Reinforcement Learning Training
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Bidirectional Guided Policy Search for Aircraft Maneuver
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NeurAll: Towards a Unified Visual Perception Model for Automated Driving
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Meta Reinforcement Learning-Based Lane Change Strategy for Autonomous Vehicles
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A Survey of Deep Reinforcement Learning Algorithms for Motion Planning and Control of Autonomous Vehicles
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Deep hierarchical reinforcement learning in a markov game applied to fishery management decision making
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Variance-Reduced Deep Actor–Critic With an Optimally Subsampled Actor Recursion
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Deep Reinforcement Learning for Autonomous Driving: A Survey
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Unsupervised Reinforcement Learning for Multi-Task Autonomous Driving: Expanding Skills and Cultivating Curiosity
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Deep Reinforcement Learning: A Survey
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Review of Learning-Based Longitudinal Motion Planning for Autonomous Vehicles: Research Gaps Between Self-Driving and Traffic Congestion
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Recurrent Neural Network Controllers Synthesis with Stability Guarantees for Partially Observed Systems
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Traffic Signal Control for a Single Intersection-Based Intelligent Transportation System
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Real-Time Financial and Traffic for Marketing Management Through Deep Learning for IoT-Integrated Autonomous Vehicle System
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On the computation of counterfactual explanations -- A survey
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Deep Reinforcement Learning and Transportation Research: A Comprehensive Review
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A Survey of Deep Reinforcement Learning Algorithms for Motion Planning and Control of Autonomous Vehicles
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Apprentissage continu : S'attaquer à l'oubli foudroyant des réseaux de neurones profonds grâce aux méthodes à rejeu de données
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