mlsanityData to 7 Oct 2026

Robustness and Adaptability of Reinforcement Learning based Cooperative Autonomous Driving in Mixed-autonomy Traffic

arXiv 2202.00881 ↗First posted 2 Feb 2022cs.RO cs.LGcited by 15

On the map: End-to-end autonomous driving → Cooperative and V2X driving

Abstract (arXiv)

Building autonomous vehicles (AVs) is a complex problem, but enabling them to operate in the real world where they will be surrounded by human-driven vehicles (HVs) is extremely challenging. Prior works have shown the possibilities of creating inter-agent cooperation between a group of AVs that follow a social utility. Such altruistic AVs can form alliances and affect the behavior of HVs to achieve socially desirable outcomes. We identify two major challenges in the co-existence of AVs and HVs. First, social preferences and individual traits of a given human driver, e.g., selflessness and aggressiveness are unknown to an AV, and it is almost impossible to infer them in real-time during a short AV-HV interaction. Second, contrary to AVs that are expected to follow a policy, HVs do not necessarily follow a stationary policy and therefore are extremely hard to predict. To alleviate the above-mentioned challenges, we formulate the mixed-autonomy problem as a multi-agent reinforcement learning (MARL) problem and propose a decentralized framework and reward function for training cooperative AVs. Our approach enables AVs to learn the decision-making of HVs implicitly from experience, optimizes for a social utility while prioritizing safety and allowing adaptability; robustifying altruistic AVs to different human behaviors and constraining them to a safe action space. Finally, we investigate the robustness, safety and sensitivity of AVs to various HVs behavioral traits and present the settings in which the AVs can learn cooperative policies that are adaptable to different situations.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Placed in Cooperative and V2X driving, one of 9 directions in End-to-end autonomous driving. Builds on 44 of its 64 references that are in the map. First posted on arXiv 2 Feb 2022.

Builds on

44 of 64 references.

Closest ancestors · 2

Same direction, newest first

  1. 2021Altruistic Maneuver Planning for Cooperative Autonomous Vehicles Using Multi-agent Advantage Actor-Critic12 Jul
  2. 2021Social Coordination and Altruism in Autonomous Driving1 Jul

Other references · 42

  1. 2015Deep Reinforcement Learning with Double Q-learningcited by 1,704
  2. 2017Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environmentscited by 1,519
  3. 2015Prioritized Experience Replaycited by 1,070
  4. 2017Counterfactual Multi-Agent Policy Gradientscited by 733
  5. 2016Cooperative Inverse Reinforcement Learningcited by 298
  6. 2019Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal Controlcited by 159
  7. 2019A Review of Cooperative Multi-Agent Deep Reinforcement Learningcited by 147
  8. 2017Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observabilitycited by 143
  9. 2017A Survey of Learning in Multiagent Environments: Dealing with Non-Stationaritycited by 93
  10. 2020Learning Latent Representations to Influence Multi-Agent Interactioncited by 92
  11. 2019Combining Planning and Deep Reinforcement Learning in Tactical Decision Making for Autonomous Drivingcited by 52
  12. 2021Deep Multi-agent Reinforcement Learning for Highway On-Ramp Merging in Mixed Trafficcited by 38
30 more
  1. 2021On the Critical Role of Conventions in Adaptive Human-AI Collaborationcited by 26
  2. 2018Generative Modeling of Multimodal Multi-Human Behaviorcited by 24
  3. 2019Lane Change Decision-making through Deep Reinforcement Learning with Rule-based Constraintscited by 24
  4. 2021A learning agent that acquires social norms from public sanctions in decentralized multi-agent settingscited by 24
  5. 2019Autonomous Highway Driving using Deep Reinforcement Learningcited by 22
  6. 2020CMetric: A Driving Behavior Measure Using Centrality Functionscited by 19
  7. 2017Towards Full Automated Drive in Urban Environments: A Demonstration in GoMentum Station, Californiacited by 17
  8. 2021Cooperative Autonomous Vehicles that Sympathize with Human Driverscited by 17
  9. 2019Controlling Steering Angle for Cooperative Self-driving Vehicles utilizing CNN and LSTM-based Deep Networkscited by 15
  10. 2019Deep Local Trajectory Replanning and Control for Robot Navigationcited by 15
  11. 2020Cooperative Perception with Deep Reinforcement Learning for Connected Vehiclescited by 14
  12. 2019Learning How to Dynamically Route Autonomous Vehicles on Shared Roadscited by 12
  13. 2021Emergent Prosociality in Multi-Agent Games Through Giftingcited by 12
  14. 2019Approximate Robust Control of Uncertain Dynamical Systemscited by 9
  15. 2019Spatio-temporal Dynamics of Cellular V2X Communication in Dense Vehicular Networkscited by 8
  16. 2020A Maneuver-based Urban Driving Dataset and Model for Cooperative Vehicle Applicationscited by 8
  17. 2018Multiple Access in Cellular V2X: Performance Analysis in Highly Congested Vehicular Networkscited by 7
  18. 2018Altruistic Autonomy: Beating Congestion on Shared Roadscited by 7
  19. 2019Real-Time Hardware-In-the-Loop Emulation Framework for DSRC-based Connected Vehicle Applicationscited by 7
  20. 2019V2X System Architecture Utilizing Hybrid Gaussian Process-based Model Structurescited by 6
  21. 2021Reinforcement Learning Based Safe Decision Making for Highway Autonomous Drivingcited by 5
  22. 2017A Stochastic Hybrid Framework for Driver Behavior Modeling Based on Hierarchical Dirichlet Processcited by 4
  23. 2018A Driver Behavior Modeling Structure Based on Non-parametric Bayesian Stochastic Hybrid Architecturecited by 4
  24. 2019Analysis of Distributed Congestion Control in Cellular Vehicle-to-everything Networkscited by 4
  25. 2020Representing Realistic Human Driver Behaviors using a Finite Size Gaussian Process Kernel Bankcited by 4
  26. 2020Performance Analysis of Cellular-V2X with Adaptive and Selective Power Controlcited by 4
  27. 2021Impact of Communication Loss on MPC based Cooperative Adaptive Cruise Control and Platooningcited by 4
  28. 2021Towards Learning Generalizable Driving Policies from Restricted Latent Representationscited by 4
  29. 2020Optimizing Mixed Autonomy Traffic Flow With Decentralized Autonomous Vehicles and Multi-Agent RLcited by 3
  30. 2021RVE-CV2X: A Scalable Emulation Framework for Real-Time Evaluation of CV2X-Based Connected Vehicle Applicationscited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 3; 2023: 2; 2024: 3; 2025: 4; 2026: 3.

15 papers.

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By area:

  1. 2023HM-ViT: Hetero-modal Vehicle-to-Vehicle Cooperative perception with vision transformercited by 70
  2. 2022Bridging the Domain Gap for Multi-Agent Perceptioncited by 60
  3. 2025Fully Autonomous AI Agents Should Not be Developedcited by 43
  4. 2024Comprehensive Overview of Reward Engineering and Shaping in Advancing Reinforcement Learning Applicationscited by 34
  5. 2022V2XP-ASG: Generating Adversarial Scenes for Vehicle-to-Everything Perceptioncited by 28
  6. 2024CoMAL: Collaborative Multi-Agent Large Language Models for Mixed-Autonomy Trafficcited by 22
  7. 2023FusionPlanner: A Multi-task Motion Planner for Mining Trucks via Multi-sensor Fusioncited by 7
  8. 2022Prediction-aware and Reinforcement Learning based Altruistic Cooperative Drivingcited by 6
  9. 2025Enhancing Cooperative Multi-Agent Reinforcement Learning with State Modelling and Adversarial Explorationcited by 3
  10. 2025A Survey of Reinforcement Learning-Based Motion Planning for Autonomous Driving: Lessons Learned from a Driving Task Perspectivecited by 2
  11. 2025A New Perspective On AI Safety Through Control Theory Methodologiescited by 1
  12. 2024Shared learning of powertrain control policies for vehicle fleetscited by 0
3 more
  1. 2026A Collaborative Safety Shield for Safe and Efficient CAV Lane Changes in Congested On-Ramp Mergingcited by 0
  2. 2026CRRL: A Causality-Based Reinforcement Learning Framework for Autonomous System Recoverycited by 0
  3. 2026Think When It Matters: Conditional VLM Reasoning for Social Navigation with RL Policiescited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2022Learning-based social coordination to improve safety and robustness of cooperative autonomous vehicles in mixed traffic
  2. 2023Towards Socially Responsive Autonomous Vehicles: A Reinforcement Learning Framework with Driving Priors and Coordination Awareness
  3. 2023Multi-Agent Deep Reinforcement Learning for Cooperative and Competitive Autonomous Vehicles using AutoDRIVE Ecosystem
  4. 2023Development and Assessment of Autonomous Vehicles in Both Fully Automated and Mixed Traffic Conditions
  5. 2025Impact of Collective Behaviors of Autonomous Vehicles on Urban Traffic Dynamics: A Multi-Agent Reinforcement Learning Approach
  6. 2021Multi-agent Reinforcement Learning for Cooperative Lane Changing of Connected and Autonomous Vehicles in Mixed Traffic
  7. 2020A Survey on Autonomous Vehicle Control in the Era of Mixed-Autonomy: From Physics-Based to AI-Guided Driving Policy Learning
  8. 2024Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey