# Towards Socially Responsive Autonomous Vehicles: A Reinforcement Learning Framework with Driving Priors and Coordination Awareness arXiv: https://arxiv.org/abs/2309.09726 ยท HTML: https://mlsanity.com/paper/2309.09726/ ## Key facts - Cited by 12 papers in the map (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 49 references that are in the map. - First posted on arXiv 18 Sep 2023. ## Placed in - End-to-end autonomous driving / [Cooperative and V2X driving](https://mlsanity.com/driving/cooperative-and-v2x-driving/) ## Builds on (most cited first, 15 of 15) - [Proximal Policy Optimization Algorithms](https://mlsanity.com/paper/1707.06347/) (2017) - [Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation](https://mlsanity.com/paper/1406.1078/) (2014) - [Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveys](https://mlsanity.com/paper/2303.17220/) (2023) - [Multimodal Probabilistic Model-Based Planning for Human-Robot Interaction](https://mlsanity.com/paper/1710.09483/) (2017) - [Social Attention for Autonomous Decision-Making in Dense Traffic](https://mlsanity.com/paper/1911.12250/) (2019) - [MTD-GPT: A Multi-Task Decision-Making GPT Model for Autonomous Driving at Unsignalized Intersections](https://mlsanity.com/paper/2307.16118/) (2023) - [Reinforcement Learning for Autonomous Driving with Latent State Inference and Spatial-Temporal Relationships](https://mlsanity.com/paper/2011.04251/) (2020) - [Driving in Dense Traffic with Model-Free Reinforcement Learning](https://mlsanity.com/paper/1909.06710/) (2019) - [Social Coordination and Altruism in Autonomous Driving](https://mlsanity.com/paper/2107.00200/) (2021) - [Socially-Compatible Behavior Design of Autonomous Vehicles with Verification on Real Human Data](https://mlsanity.com/paper/2010.14712/) (2020) - [Simultaneous Policy Learning and Latent State Inference for Imitating Driver Behavior](https://mlsanity.com/paper/1704.05566/) (2017) - [Alternating Direction Method of Multipliers for Constrained Iterative LQR in Autonomous Driving](https://mlsanity.com/paper/2011.00462/) (2020) - [Decentralized iLQR for Cooperative Trajectory Planning of Connected Autonomous Vehicles via Dual Consensus ADMM](https://mlsanity.com/paper/2301.04386/) (2023) - [Decision Making for Connected Automated Vehicles at Urban Intersections Considering Social and Individual Benefits](https://mlsanity.com/paper/2201.01428/) (2022) - [A Reinforcement Learning Benchmark for Autonomous Driving in Intersection Scenarios](https://mlsanity.com/paper/2109.10557/) (2021) ## Built on by (most cited first, 12 of 12) - [Towards Interactive and Learnable Cooperative Driving Automation: a Large Language Model-Driven Decision-Making Framework](https://mlsanity.com/paper/2409.12812/) (2024) - [DDM-Lag : A Diffusion-based Decision-making Model for Autonomous Vehicles with Lagrangian Safety Enhancement](https://mlsanity.com/paper/2401.03629/) (2024) - [A Knowledge-Driven Diffusion Policy for End-to-End Autonomous Driving Based on Expert Routing](https://mlsanity.com/paper/2509.04853/) (2025) - [CoDriveVLM: VLM-Enhanced Urban Cooperative Dispatching and Motion Planning for Future Autonomous Mobility on Demand Systems](https://mlsanity.com/paper/2501.06132/) (2025) - [Towards Safe and Robust Autonomous Vehicle Platooning: A Self-Organizing Cooperative Control Framework](https://mlsanity.com/paper/2408.09468/) (2024) - [Game-Theoretic Modeling of Vehicle Unprotected Left Turns Considering Drivers' Bounded Rationality](https://mlsanity.com/paper/2507.03002/) (2025) - [Autonomous Vehicle Decision-Making Framework for Considering Malicious Behavior at Unsignalized Intersections](https://mlsanity.com/paper/2409.17162/) (2024) - [GITSR: Graph Interaction Transformer-based Scene Representation for Multi Vehicle Collaborative Decision-making](https://mlsanity.com/paper/2411.01608/) (2024) - [Towards Developing Socially Compliant Automated Vehicles: Advances, Expert Insights, and A Conceptual Framework](https://mlsanity.com/paper/2501.06089/) (2025) - [Sky-Drive: A Distributed Multi-Agent Simulation Platform for Human-AI Collaborative and Socially-Aware Future Transportation](https://mlsanity.com/paper/2504.18010/) (2025) - [Learn2Drive: A neural network-based framework for socially compliant automated vehicle control](https://mlsanity.com/paper/2510.21736/) (2025) - [A Survey on End-to-End Autonomous Driving Training from the Perspectives of Data, Strategy, and Platform](https://mlsanity.com/paper/2610.00926/) (2026) ## Abstract (arXiv) The advent of autonomous vehicles (AVs) alongside human-driven vehicles (HVs) has ushered in an era of mixed traffic flow, presenting a significant challenge: the intricate interaction between these entities within complex driving environments. AVs are expected to have human-like driving behavior to seamlessly integrate into human-dominated traffic systems. To address this issue, we propose a reinforcement learning framework that considers driving priors and Social Coordination Awareness (SCA) to optimize the behavior of AVs. The framework integrates a driving prior learning (DPL) model based on a variational autoencoder to infer the driver's driving priors from human drivers' trajectories. A policy network based on a multi-head attention mechanism is designed to effectively capture the interactive dependencies between AVs and other traffic participants to improve decision-making quality. The introduction of SCA into the autonomous driving decision-making system, and the use of Coordination Tendency (CT) to quantify the willingness of AVs to coordinate the traffic system is explored. Simulation results show that the proposed framework can not only improve the decision-making quality of AVs but also motivate them to produce social behaviors, with potential benefits for the safety and traffic efficiency of the entire transportation system.