# Driving Towards Inclusion: A Systematic Review of AI-powered Accessibility Enhancements for People with Disability in Autonomous Vehicles

arXiv: https://arxiv.org/abs/2401.14571 · HTML: https://mlsanity.com/paper/2401.14571/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 212 references that are in the map.
- First posted on arXiv 26 Jan 2024.

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

- [Audio-driven Talking Face Video Generation with Learning-based Personalized Head Pose](https://mlsanity.com/paper/2002.10137/) (2020)
- [3DAvatarGAN: Bridging Domains for Personalized Editable Avatars](https://mlsanity.com/paper/2301.02700/) (2023)
- [A comprehensive survey of research towards AI-enabled unmanned aerial systems in pre-, active-, and post-wildfire management](https://mlsanity.com/paper/2401.02456/) (2024)
- [MAVERIC: A Data-Driven Approach to Personalized Autonomous Driving](https://mlsanity.com/paper/2301.08595/) (2023)
- [Governing autonomous vehicles: emerging responses for safety, liability, privacy, cybersecurity, and industry risks](https://mlsanity.com/paper/1807.05720/) (2018)
- [Deep Learning Serves Traffic Safety Analysis: A Forward-looking Review](https://mlsanity.com/paper/2203.10939/) (2022)
- [Building Trust in Autonomous Vehicles: Role of Virtual Reality Driving Simulators in HMI Design](https://mlsanity.com/paper/2007.13371/) (2020)
- [ProtoSound: A Personalized and Scalable Sound Recognition System for Deaf and Hard-of-Hearing Users](https://mlsanity.com/paper/2202.11134/) (2022)
- [LLM-based Smart Reply (LSR): Enhancing Collaborative Performance with ChatGPT-mediated Smart Reply System](https://mlsanity.com/paper/2306.11980/) (2023)
- [Effects of Multimodal Explanations for Autonomous Driving on Driving Performance, Cognitive Load, Expertise, Confidence, and Trust](https://mlsanity.com/paper/2401.04206/) (2024)
- [The Effect of Robo-taxi User Experience on User Acceptance: Field Test Data Analysis](https://mlsanity.com/paper/2006.16870/) (2020)

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

- [When Stopping Fails: Rethinking Minimal Risk Conditions through Human-Interactive Autonomous Driving for Safe Transportation Systems](https://mlsanity.com/paper/2606.29115/) (2026)

## Abstract (arXiv)

This paper provides a comprehensive and, to our knowledge, the first review of inclusive human-computer interaction (HCI) within autonomous vehicles (AVs) and human-driven cars with partial autonomy, emphasizing accessibility and user-centered design principles. We explore the current technologies and HCI systems designed to enhance passenger experience, particularly for individuals with accessibility needs. Key technologies discussed include brain-computer interfaces, anthropomorphic interaction, virtual reality, augmented reality, mode adaptation, voice-activated interfaces, haptic feedback, etc. Each technology is evaluated for its role in creating an inclusive in-vehicle environment. Furthermore, we highlight recent interface designs by leading companies and review emerging concepts and prototypes under development or testing, which show significant potential to address diverse accessibility requirements. Safety considerations, ethical concerns, and adoption of AVs are other major issues that require thorough investigation. Building on these findings, we propose an end-to-end design framework that addresses accessibility requirements across diverse user demographics, including older adults and individuals with physical or cognitive impairments. This work provides actionable insights for designers, researchers, and policymakers aiming to create safer and more comfortable environments in autonomous and regular vehicles accessible to all users.