mlsanityData to 14 Oct 2026

Toward Safety-First Human-Like Decision Making for Autonomous Vehicles in Time-Varying Traffic Flow

arXiv 2506.14502 ↗First posted 17 Jun 2025cs.AIcited by 0

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

Abstract (arXiv)

Despite the recent advancements in artificial intelligence technologies have shown great potential in improving transport efficiency and safety, autonomous vehicles(AVs) still face great challenge of driving in time-varying traffic flow, especially in dense and interactive situations. Meanwhile, human have free wills and usually do not make the same decisions even situate in the exactly same scenarios, leading to the data-driven methods suffer from poor migratability and high search cost problems, decreasing the efficiency and effectiveness of the behavior policy. In this research, we propose a safety-first human-like decision-making framework(SF-HLDM) for AVs to drive safely, comfortably, and social compatiblely in effiency. The framework integrates a hierarchical progressive framework, which combines a spatial-temporal attention (S-TA) mechanism for other road users' intention inference, a social compliance estimation module for behavior regulation, and a Deep Evolutionary Reinforcement Learning(DERL) model for expanding the search space efficiently and effectively to make avoidance of falling into the local optimal trap and reduce the risk of overfitting, thus make human-like decisions with interpretability and flexibility. The SF-HLDM framework enables autonomous driving AI agents dynamically adjusts decision parameters to maintain safety margins and adhering to contextually appropriate driving behaviors at the same time.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Cooperative and V2X driving, one of 9 directions in End-to-end autonomous driving. Builds on 15 of its 75 references that are in the map. First posted on arXiv 17 Jun 2025.

Builds on

15 of 75 references.

Closest ancestors · 1

Same direction, newest first

  1. 2021Social Coordination and Altruism in Autonomous Driving1 Jul

Other references · 14

  1. 2019A Survey on Distributed Machine Learningcited by 188
  2. 2021Embodied Intelligence via Learning and Evolutioncited by 163
  3. 2022Behavioral Intention Prediction in Driving Scenes: A Surveycited by 30
  4. 2021Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Surveycited by 28
  5. 2021Cooperative Autonomous Vehicles that Sympathize with Human Driverscited by 18
  6. 2018Automated vehicle's behavior decision making using deep reinforcement learning and high-fidelity simulation environmentcited by 16
  7. 2023Social Interaction-Aware Dynamical Models and Decision Making for Autonomous Vehiclescited by 13
  8. 2022FBLNet: FeedBack Loop Network for Driver Attention Predictioncited by 12
  9. 2022Safe, Learning-Based MPC for Highway Driving under Lane-Change Uncertainty: A Distributionally Robust Approachcited by 4
  10. 2022Modeling road user response timing in naturalistic settings: a surprise-based frameworkcited by 4
  11. 2023Multiobjective Evolutionary Pruning of Deep Neural Networks with Transfer Learning for improving their Performance and Robustnesscited by 4
  12. 2021High performing ensemble of convolutional neural networks for insect pest image detectioncited by 3
2 more
  1. 2024Self-Supervised Interpretable End-to-End Learning via Latent Functional Modularitycited by 3
  2. 2023A Fast and Map-Free Model for Trajectory Prediction in Trafficscited by 2

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Close in wording, no citation either way

  1. 2023Towards Socially Responsive Autonomous Vehicles: A Reinforcement Learning Framework with Driving Priors and Coordination Awareness
  2. 2025Socially-Aware Autonomous Driving: Inferring Yielding Intentions for Safer Interactions
  3. 2023Bringing Diversity to Autonomous Vehicles: An Interpretable Multi-vehicle Decision-making and Planning Framework
  4. 2023Human-Like Implicit Intention Expression for Autonomous Driving Motion Planning: A Method Based on Learning Human Intention Priors
  5. 2021Calibration of Human Driving Behavior and Preference Using Naturalistic Traffic Data
  6. 2025An Intention-driven Lane Change Framework Considering Heterogeneous Dynamic Cooperation in Mixed-traffic Environment ↗
  7. 2024HAIM-DRL: Enhanced Human-in-the-loop Reinforcement Learning for Safe and Efficient Autonomous Driving
  8. 2024DDM-Lag : A Diffusion-based Decision-making Model for Autonomous Vehicles with Lagrangian Safety Enhancement