# Resolving space-sharing conflicts in road user interactions through uncertainty reduction: An active inference-based computational model

arXiv: https://arxiv.org/abs/2604.19838 · HTML: https://mlsanity.com/paper/2604.19838/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 62 references that are in the map.
- First posted on arXiv 21 Apr 2026.

## Builds on (most cited first, 11 of 11)

- [The Waymo Open Sim Agents Challenge](https://mlsanity.com/paper/2305.12032/) (2023)
- [Hierarchical Game-Theoretic Planning for Autonomous Vehicles](https://mlsanity.com/paper/1810.05766/) (2018)
- [Formal Scenario-Based Testing of Autonomous Vehicles: From Simulation to the Real World](https://mlsanity.com/paper/2003.07739/) (2020)
- [Pedestrian Models for Autonomous Driving Part II: High-Level Models of Human Behavior](https://mlsanity.com/paper/2003.11959/) (2020)
- [A World unto Itself: Human Communication as Active Inference](https://mlsanity.com/paper/1906.10538/) (2019)
- [Interactive inference: a multi-agent model of cooperative joint actions](https://mlsanity.com/paper/2210.13113/) (2022)
- [Resolving uncertainty on the fly: Modeling adaptive driving behavior as active inference](https://mlsanity.com/paper/2311.06417/) (2023)
- [Active inference as a unified model of collision avoidance behavior in human drivers](https://mlsanity.com/paper/2506.02215/) (2025)
- [A model of communication-enabled traffic interactions](https://mlsanity.com/paper/2304.06604/) (2023)
- [A Model of the Sidewalk Salsa](https://mlsanity.com/paper/2412.04023/) (2024)
- [Being good (at driving): Characterizing behavioral expectations on automated and human driven vehicles](https://mlsanity.com/paper/2502.08121/) (2025)

## Built on by (most cited first, 1 of 1)

- [Emotion in an active inference model of human driving](https://mlsanity.com/paper/2608.07480/) (2026)

## Abstract (arXiv)

Understanding how road users resolve space-sharing conflicts is important both for traffic safety and the safe deployment of autonomous vehicles. While existing models have captured specific aspects of such interactions (e.g., explicit communication), a theoretically-grounded computational framework has been lacking. In this paper, we extend a previously developed active inference-based driver behavior model to simulate interactive behavior of two agents. Our model captures three complementary mechanisms for uncertainty reduction in interaction: (i) implicit communication via direct behavioral coupling, (ii) reliance on normative expectations (stop signs, priority rules, etc.), and (iii) explicit communication. In a simplified intersection scenario, we show that normative and explicit communication cues can increase the likelihood of a successful conflict resolution. However, this relies on agents acting as expected. In situations where another agent (intentionally or unintentionally) violates normative expectations or communicates misleading information, reliance on these cues may induce collisions. These findings illustrate how active inference can provide a novel framework for modeling road user interactions which is also applicable in other fields.