# Social Coordination and Altruism in Autonomous Driving

arXiv: https://arxiv.org/abs/2107.00200 · HTML: https://mlsanity.com/paper/2107.00200/

## Key facts

- Cited by 28 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 30 of its 56 references that are in the map.
- First posted on arXiv 1 Jul 2021.

## Placed in

- End-to-end autonomous driving / [Cooperative and V2X driving](https://mlsanity.com/driving/cooperative-and-v2x-driving/)

## Builds on (most cited first, 30 of 30)

- [Playing Atari with Deep Reinforcement Learning](https://mlsanity.com/paper/1312.5602/) (2013)
- [Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments](https://mlsanity.com/paper/1706.02275/) (2017)
- [Counterfactual Multi-Agent Policy Gradients](https://mlsanity.com/paper/1705.08926/) (2017)
- [Learning with Opponent-Learning Awareness](https://mlsanity.com/paper/1709.04326/) (2017)
- [Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability](https://mlsanity.com/paper/1703.06182/) (2017)
- [Socially Aware Motion Planning with Deep Reinforcement Learning](https://mlsanity.com/paper/1703.08862/) (2017)
- [Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning](https://mlsanity.com/paper/1702.08887/) (2017)
- [A Survey of Learning in Multiagent Environments: Dealing with Non-Stationarity](https://mlsanity.com/paper/1707.09183/) (2017)
- [Imitating Driver Behavior with Generative Adversarial Networks](https://mlsanity.com/paper/1701.06699/) (2017)
- [Learning Latent Representations to Influence Multi-Agent Interaction](https://mlsanity.com/paper/2011.06619/) (2020)
- [Multi-Agent Connected Autonomous Driving using Deep Reinforcement Learning](https://mlsanity.com/paper/1911.04175/) (2019)
- [Multimodal Probabilistic Model-Based Planning for Human-Robot Interaction](https://mlsanity.com/paper/1710.09483/) (2017)
- [Efficient Model Learning for Human-Robot Collaborative Tasks](https://mlsanity.com/paper/1405.6341/) (2014)
- [On the Critical Role of Conventions in Adaptive Human-AI Collaboration](https://mlsanity.com/paper/2104.02871/) (2021)
- [SEAN: Social Environment for Autonomous Navigation](https://mlsanity.com/paper/2009.04300/) (2020)
- [Controlling Steering Angle for Cooperative Self-driving Vehicles utilizing CNN and LSTM-based Deep Networks](https://mlsanity.com/paper/1904.04375/) (2019)
- [Learning How to Dynamically Route Autonomous Vehicles on Shared Roads](https://mlsanity.com/paper/1909.03664/) (2019)
- [Emergent Prosociality in Multi-Agent Games Through Gifting](https://mlsanity.com/paper/2105.06593/) (2021)
- [Approximate Robust Control of Uncertain Dynamical Systems](https://mlsanity.com/paper/1903.00220/) (2019)
- [Spatio-temporal Dynamics of Cellular V2X Communication in Dense Vehicular Networks](https://mlsanity.com/paper/1906.08634/) (2019)
- [A Maneuver-based Urban Driving Dataset and Model for Cooperative Vehicle Applications](https://mlsanity.com/paper/2005.13781/) (2020)
- [Multiple Access in Cellular V2X: Performance Analysis in Highly Congested Vehicular Networks](https://mlsanity.com/paper/1809.02678/) (2018)
- [Altruistic Autonomy: Beating Congestion on Shared Roads](https://mlsanity.com/paper/1810.11978/) (2018)
- [Real-Time Hardware-In-the-Loop Emulation Framework for DSRC-based Connected Vehicle Applications](https://mlsanity.com/paper/1905.09267/) (2019)
- [V2X System Architecture Utilizing Hybrid Gaussian Process-based Model Structures](https://mlsanity.com/paper/1903.01576/) (2019)
- [Feature Sharing and Integration for Cooperative Cognition and Perception with Volumetric Sensors](https://mlsanity.com/paper/2011.08317/) (2020)
- [A Stochastic Hybrid Framework for Driver Behavior Modeling Based on Hierarchical Dirichlet Process](https://mlsanity.com/paper/1711.05655/) (2017)
- [A Driver Behavior Modeling Structure Based on Non-parametric Bayesian Stochastic Hybrid Architecture](https://mlsanity.com/paper/1807.03919/) (2018)
- [Analysis of Distributed Congestion Control in Cellular Vehicle-to-everything Networks](https://mlsanity.com/paper/1904.00071/) (2019)
- [Performance Analysis of Cellular-V2X with Adaptive and Selective Power Control](https://mlsanity.com/paper/2008.03453/) (2020)

## Built on by (most cited first, 28 of 28)

- [Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey](https://mlsanity.com/paper/2408.09675/) (2024)
- [BAT: Behavior-Aware Human-Like Trajectory Prediction for Autonomous Driving](https://mlsanity.com/paper/2312.06371/) (2023)
- [Robustness and Adaptability of Reinforcement Learning based Cooperative Autonomous Driving in Mixed-autonomy Traffic](https://mlsanity.com/paper/2202.00881/) (2022)
- [Active Uncertainty Reduction for Safe and Efficient Interaction Planning: A Shielding-Aware Dual Control Approach](https://mlsanity.com/paper/2302.00171/) (2023)
- [Towards Socially Responsive Autonomous Vehicles: A Reinforcement Learning Framework with Driving Priors and Coordination Awareness](https://mlsanity.com/paper/2309.09726/) (2023)
- [MFTraj: Map-Free, Behavior-Driven Trajectory Prediction for Autonomous Driving](https://mlsanity.com/paper/2405.01266/) (2024)
- [Altruistic Maneuver Planning for Cooperative Autonomous Vehicles Using Multi-agent Advantage Actor-Critic](https://mlsanity.com/paper/2107.05664/) (2021)
- [Prediction-aware and Reinforcement Learning based Altruistic Cooperative Driving](https://mlsanity.com/paper/2211.10585/) (2022)
- [Towards Learning Generalizable Driving Policies from Restricted Latent Representations](https://mlsanity.com/paper/2111.03688/) (2021)
- [Learning responsibility allocations for multi-agent interactions: A differentiable optimization approach with control barrier functions](https://mlsanity.com/paper/2410.07409/) (2024)
- [Intent-Aware Autonomous Driving: A Case Study on Highway Merging Scenarios](https://mlsanity.com/paper/2309.13206/) (2023)
- [Towards Safe and Robust Autonomous Vehicle Platooning: A Self-Organizing Cooperative Control Framework](https://mlsanity.com/paper/2408.09468/) (2024)
- [Active Altruism Learning and Information Sufficiency for Autonomous Driving](https://mlsanity.com/paper/2110.04580/) (2021)
- [How Bad is Selfish Driving? Bounding the Inefficiency of Equilibria in Urban Driving Games](https://mlsanity.com/paper/2210.13064/) (2022)
- [Learning-based social coordination to improve safety and robustness of cooperative autonomous vehicles in mixed traffic](https://mlsanity.com/paper/2211.11963/) (2022)
- [Learning in Cooperative Multiagent Systems Using Cognitive and Machine Models](https://mlsanity.com/paper/2308.09219/) (2023)
- [A Two-stage Based Social Preference Recognition in Multi-Agent Autonomous Driving System](https://mlsanity.com/paper/2310.03303/) (2023)
- [Learning Probabilistic Responsibility Allocations for Multi-Agent Interactions](https://mlsanity.com/paper/2604.13128/) (2026)
- [Context-Aware Target Classification with Hybrid Gaussian Process prediction for Cooperative Vehicle Safety systems](https://mlsanity.com/paper/2212.12819/) (2022)
- [Studying the Impact of Semi-Cooperative Drivers on Overall Highway Flow](https://mlsanity.com/paper/2304.11693/) (2023)
- [Zero-shot Transfer Learning of Driving Policy via Socially Adversarial Traffic Flow](https://mlsanity.com/paper/2304.12821/) (2023)
- [Human-Like Implicit Intention Expression for Autonomous Driving Motion Planning: A Method Based on Learning Human Intention Priors](https://mlsanity.com/paper/2307.15950/) (2023)
- [S4TP: Social-Suitable and Safety-Sensitive Trajectory Planning for Autonomous Vehicles](https://mlsanity.com/paper/2404.11946/) (2024)
- [Towards Developing Socially Compliant Automated Vehicles: Advances, Expert Insights, and A Conceptual Framework](https://mlsanity.com/paper/2501.06089/) (2025)
- [Toward Safety-First Human-Like Decision Making for Autonomous Vehicles in Time-Varying Traffic Flow](https://mlsanity.com/paper/2506.14502/) (2025)
- [Intrinsic-Motivation Multi-Robot Social Formation Navigation with Coordinated Exploration](https://mlsanity.com/paper/2512.13293/) (2025)
- [Personalized Autonomous Driving via Optimal Control with Clearance Constraints from Questionnaires](https://mlsanity.com/paper/2602.08326/) (2026)
- [COIN: Collaborative Interaction-Aware Multi-Agent Reinforcement Learning for Self-Driving Systems](https://mlsanity.com/paper/2603.24931/) (2026)

## Abstract (arXiv)

Despite the advances in the autonomous driving domain, autonomous vehicles (AVs) are still inefficient and limited in terms of cooperating with each other or coordinating with vehicles operated by humans. A group of autonomous and human-driven vehicles (HVs) which work together to optimize an altruistic social utility -- as opposed to the egoistic individual utility -- can co-exist seamlessly and assure safety and efficiency on the road. Achieving this mission without explicit coordination among agents is challenging, mainly due to the difficulty of predicting the behavior of humans with heterogeneous preferences in mixed-autonomy environments. Formally, we model an AV's maneuver planning in mixed-autonomy traffic as a partially-observable stochastic game and attempt to derive optimal policies that lead to socially-desirable outcomes using a multi-agent reinforcement learning framework. We introduce a quantitative representation of the AVs' social preferences and design a distributed reward structure that induces altruism into their decision making process. Our altruistic AVs are able to form alliances, guide the traffic, and affect the behavior of the HVs to handle competitive driving scenarios. As a case study, we compare egoistic AVs to our altruistic autonomous agents in a highway merging setting and demonstrate the emerging behaviors that lead to a noticeable improvement in the number of successful merges as well as the overall traffic flow and safety.