mlsanityData to 7 Oct 2026

Reinforcement Learning for Autonomous Driving with Latent State Inference and Spatial-Temporal Relationships

arXiv 2011.04251 ↗First posted 9 Nov 2020cs.LGcited by 36

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Abstract (arXiv)

Deep reinforcement learning (DRL) provides a promising way for learning navigation in complex autonomous driving scenarios. However, identifying the subtle cues that can indicate drastically different outcomes remains an open problem with designing autonomous systems that operate in human environments. In this work, we show that explicitly inferring the latent state and encoding spatial-temporal relationships in a reinforcement learning framework can help address this difficulty. We encode prior knowledge on the latent states of other drivers through a framework that combines the reinforcement learner with a supervised learner. In addition, we model the influence passing between different vehicles through graph neural networks (GNNs). The proposed framework significantly improves performance in the context of navigating T-intersections compared with state-of-the-art baseline approaches.

Key facts. Cited by 36 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Nov 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 8; 2022: 4; 2023: 7; 2024: 8; 2025: 8; 2026: 1.

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  1. 2022A Review of Safe Reinforcement Learning: Methods, Theory and Applicationscited by 169
  2. 2023Rank2Tell: A Multimodal Driving Dataset for Joint Importance Ranking and Reasoningcited by 63
  3. 2021Spectral Temporal Graph Neural Network for Trajectory Predictioncited by 36
  4. 2021RAIN: Reinforced Hybrid Attention Inference Network for Motion Forecastingcited by 36
  5. 2021Spatio-Temporal Graph Dual-Attention Network for Multi-Agent Prediction and Trackingcited by 35
  6. 2021Autonomous Driving Strategies at Intersections: Scenarios, State-of-the-Art, and Future Outlookscited by 15
  7. 2022Statistical Deep Learning for Spatial and Spatio-Temporal Datacited by 15
  8. 2023Towards Socially Responsive Autonomous Vehicles: A Reinforcement Learning Framework with Driving Priors and Coordination Awarenesscited by 12
  9. 2022Spatiotemporal Costmap Inference for MPC via Deep Inverse Reinforcement Learningcited by 10
  10. 2023Interactive Autonomous Navigation with Internal State Inference and Interactivity Estimationcited by 10
  11. 2021Learning to Navigate Intersections with Unsupervised Driver Trait Inferencecited by 8
  12. 2024HEIGHT: Heterogeneous Interaction Graph Transformer for Robot Navigation in Crowded and Constrained Environmentscited by 6
24 more
  1. 2025RoaD: Rollouts as Demonstrations for Closed-Loop Supervised Fine-Tuning of Autonomous Driving Policiescited by 6
  2. 2021Vision Transformer for Learning Driving Policies in Complex Multi-Agent Environmentscited by 5
  3. 2023Robust Driving Policy Learning with Guided Meta Reinforcement Learningcited by 5
  4. 2025Human Implicit Preference-Based Policy Fine-tuning for Multi-Agent Reinforcement Learning in USV Swarmcited by 5
  5. 2025Towards Generalizable Safety in Crowd Navigation via Conformal Uncertainty Handlingcited by 5
  6. 2021Towards Learning Generalizable Driving Policies from Restricted Latent Representationscited by 4
  7. 2023PeRP: Personalized Residual Policies For Congestion Mitigation Through Co-operative Advisory Systemscited by 4
  8. 2024Enhance Planning with Physics-informed Safety Controller for End-to-end Autonomous Drivingcited by 4
  9. 2022Don't Watch Me: A Spatio-Temporal Trojan Attack on Deep-Reinforcement-Learning-Augment Autonomous Drivingcited by 3
  10. 2024Importance Sampling-Guided Meta-Training for Intelligent Agents in Highly Interactive Environmentscited by 3
  11. 2023Provably Efficient Algorithm for Nonstationary Low-Rank MDPscited by 2
  12. 2024Learning Interpretable Policies in Hindsight-Observable POMDPs through Partially Supervised Reinforcement Learningcited by 2
  13. 2024Learning to Model Diverse Driving Behaviors in Highly Interactive Autonomous Driving Scenarios with Multi-Agent Reinforcement Learningcited by 2
  14. 2024Towards Flexible Visual Relationship Segmentationcited by 2
  15. 2024Act Better by Timing: A timing-Aware Reinforcement Learning for Autonomous Drivingcited by 1
  16. 2025SPoRt -- Safe Policy Ratio: Certified Training and Deployment of Task Policies in Model-Free RLcited by 1
  17. 2021Dynamic Inferencecited by 0
  18. 2023SCPO: Safe Reinforcement Learning with Safety Critic Policy Optimizationcited by 0
  19. 2024Delay-Aware Reinforcement Learning for Highway On-Ramp Merging under Stochastic Communication Latencycited by 0
  20. 2025Dynamically Local-Enhancement Planner for Large-Scale Autonomous Drivingcited by 0
  21. 2025Socially-Aware Autonomous Driving: Inferring Yielding Intentions for Safer Interactionscited by 0
  22. 2025Frenet Corridor Planner: An Optimal Local Path Planning Framework for Autonomous Drivingcited by 0
  23. 2025Graph Neural Networks, Deep Reinforcement Learning and Probabilistic Topic Modeling for Strategic Multiagent Settingscited by 0
  24. 2026DriveSafe: A Framework for Risk Detection and Safety Suggestions in Driving Scenarioscited by 0