Building Trust in Autonomous Vehicles: Role of Virtual Reality Driving Simulators in HMI Design
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Abstract (arXiv)
The investigation of factors contributing at making humans trust Autonomous Vehicles (AVs) will play a fundamental role in the adoption of such technology. The user's ability to form a mental model of the AV, which is crucial to establish trust, depends on effective user-vehicle communication; thus, the importance of Human-Machine Interaction (HMI) is poised to increase. In this work, we propose a methodology to validate the user experience in AVs based on continuous, objective information gathered from physiological signals, while the user is immersed in a Virtual Reality-based driving simulation. We applied this methodology to the design of a head-up display interface delivering visual cues about the vehicle' sensory and planning systems. Through this approach, we obtained qualitative and quantitative evidence that a complete picture of the vehicle's surrounding, despite the higher cognitive load, is conducive to a less stressful experience. Moreover, after having been exposed to a more informative interface, users involved in the study were also more willing to test a real AV. The proposed methodology could be extended by adjusting the simulation environment, the HMI and/or the vehicle's Artificial Intelligence modules to dig into other aspects of the user experience.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Jul 2020.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 3; 2024: 4; 2025: 1; 2026: 1.
10 papers.
- 2024Advancing Explainable Autonomous Vehicle Systems: A Comprehensive Review and Research Roadmapcited by 6
- 2024Effects of Multimodal Explanations for Autonomous Driving on Driving Performance, Cognitive Load, Expertise, Confidence, and Trustcited by 3
- 2021Comparing State-of-the-Art and Emerging Augmented Reality Interfaces for Autonomous Vehicle-to-Pedestrian Communicationcited by 2
- 2023Pedestrian and Passenger Interaction with Autonomous Vehicles: Field Study in a Crosswalk Scenariocited by 2
- 2024Developing Situational Awareness for Joint Action with Autonomous Vehiclescited by 2
- 2023Converging Measures and an Emergent Model: A Meta-Analysis of Human-Automation Trust Questionnairescited by 1
- 2024Driving Towards Inclusion: A Systematic Review of AI-powered Accessibility Enhancements for People with Disability in Autonomous Vehiclescited by 1
- 2023Analyze Drivers' Intervention Behavior During Autonomous Driving -- A VR-incorporated Approachcited by 0
- 2025Green Robotic Mixed Reality with Gaussian Splattingcited by 0
- 2026Seeing What the Vehicle Sees: Video-Augmented Virtual Reality for Physical Autonomous Vehiclescited by 0
- 2026Seeing What the Vehicle Sees: Video-Augmented Virtual Reality for Physical Autonomous Vehicles31 Aug 2026
- 2025Green Robotic Mixed Reality with Gaussian Splatting18 Apr 2025
- 2024Developing Situational Awareness for Joint Action with Autonomous Vehicles17 Apr 2024
- 2024Advancing Explainable Autonomous Vehicle Systems: A Comprehensive Review and Research Roadmap19 Mar 2024
- 2024Driving Towards Inclusion: A Systematic Review of AI-powered Accessibility Enhancements for People with Disability in Autonomous Vehicles26 Jan 2024
- 2024Effects of Multimodal Explanations for Autonomous Driving on Driving Performance, Cognitive Load, Expertise, Confidence, and Trust8 Jan 2024
- 2023Pedestrian and Passenger Interaction with Autonomous Vehicles: Field Study in a Crosswalk Scenario11 Dec 2023
- 2023Analyze Drivers' Intervention Behavior During Autonomous Driving -- A VR-incorporated Approach4 Dec 2023
- 2023Converging Measures and an Emergent Model: A Meta-Analysis of Human-Automation Trust Questionnaires24 Mar 2023
- 2021Comparing State-of-the-Art and Emerging Augmented Reality Interfaces for Autonomous Vehicle-to-Pedestrian Communication4 Feb 2021