# Developing Situational Awareness for Joint Action with Autonomous Vehicles

arXiv: https://arxiv.org/abs/2404.11800 · HTML: https://mlsanity.com/paper/2404.11800/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 69 references that are in the map.
- First posted on arXiv 17 Apr 2024.

## Builds on (most cited first, 5 of 5)

- [Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey](https://mlsanity.com/paper/2006.11371/) (2020)
- [Explainable Artificial Intelligence for Autonomous Driving: A Comprehensive Overview and Field Guide for Future Research Directions](https://mlsanity.com/paper/2112.11561/) (2021)
- [Building Trust in Autonomous Vehicles: Role of Virtual Reality Driving Simulators in HMI Design](https://mlsanity.com/paper/2007.13371/) (2020)
- [Modeling Dispositional and Initial learned Trust in Automated Vehicles with Predictability and Explainability](https://mlsanity.com/paper/2012.13603/) (2020)
- [Explainable AI And Visual Reasoning: Insights From Radiology](https://mlsanity.com/paper/2304.03318/) (2023)

## Built on by (most cited first, 2 of 2)

- [What Did My Car Say? Impact of Autonomous Vehicle Explanation Errors and Driving Context On Comfort, Reliance, Satisfaction, and Driving Confidence](https://mlsanity.com/paper/2409.05731/) (2024)
- [Predicting Trust In Autonomous Vehicles: Modeling Young Adult Psychosocial Traits, Risk-Benefit Attitudes, And Driving Factors With Machine Learning](https://mlsanity.com/paper/2409.08980/) (2024)

## Abstract (arXiv)

Unanswered questions about how human-AV interaction designers can support rider's informational needs hinders Autonomous Vehicles (AV) adoption. To achieve joint human-AV action goals - such as safe transportation, trust, or learning from an AV - sufficient situational awareness must be held by the human, AV, and human-AV system collectively. We present a systems-level framework that integrates cognitive theories of joint action and situational awareness as a means to tailor communications that meet the criteria necessary for goal success. This framework is based on four components of the shared situation: AV traits, action goals, subject-specific traits and states, and the situated driving context. AV communications should be tailored to these factors and be sensitive when they change. This framework can be useful for understanding individual, shared, and distributed human-AV situational awareness and designing for future AV communications that meet the informational needs and goals of diverse groups and in diverse driving contexts.