Short answer
Focus design efforts on demonstrating and communicating the system's reliable performance to users, as this is the strongest driver of trust in automated driving.
- Field
- Human Factors
- Source
- DepositOnce (2019)
- Method
- User studies in both real-world driving and simulated environments.
- Sample
- 90 participants (28 in study 1, 72 in study 2)
- Evidence
- Strong effect
Trust in highly automated driving systems is primarily driven by the user's perception of the system's performance, rather than inherent personality traits or general technology attitudes. This human factors research insight is drawn from a 2019 study published in DepositOnce. Using User studies in both real-world driving and simulated environments. with 90 participants (28 in study 1, 72 in study 2), researchers explored how this design variable affects real-world outcomes. The key design takeaway: Focus design efforts on demonstrating and communicating the system's reliable performance to users, as this is the strongest driver of trust in automated driving.
Perceived System Performance is Key to Building Trust in Automated Driving
Trust in highly automated driving systems is primarily driven by the user's perception of the system's performance, rather than inherent personality traits or general technology attitudes.
DepositOnce · 2019
Key Findings
- 01Perceived performance of the automated driving system is the most important factor for building trust.
- 02Personality characteristics (desire for control) and general attitude towards technology can influence trust, but to a lesser extent than perceived performance.
- 03The type of system limit experienced significantly impacts trust, with non-detection of relevant events being particularly detrimental.
Application
Design takeaway
Focus design efforts on demonstrating and communicating the system's reliable performance to users, as this is the strongest driver of trust in automated driving.
How to apply
When designing interfaces for automated systems, ensure that the system's operational status, its successes, and its limitations are clearly and consistently communicated to the user.
Project actions
- 01When designing a system that takes over tasks, make sure its performance is obvious and reliable.
- 02Consider how you will show the user that the system is doing a good job, especially in critical situations.
Method & Evidence
Variables
Strengths & Limitations
Strengths
- +Utilized both real-world driving and simulation for a comprehensive approach.
- +Investigated multiple potential factors influencing trust.
Limitations
The complexity of real-world driving and the range of human personalities can be difficult to fully replicate in a controlled experiment.
Reliability & validity
The use of multiple studies and varied methodologies (real-world vs. simulation) enhances the study's validity. Reliability would depend on the consistency of trust ratings across similar participants and conditions.
Think critically
How can designers proactively build trust in systems that are inherently complex and may experience occasional failures, beyond simply ensuring high performance?
Design Principles
"Trust in automated systems is built on perceived competence and transparent communication of system capabilities and limitations."
For designers of automated driving systems, understanding that perceived performance is the most critical factor for user trust is paramount. This insight guides design efforts towards ensuring the system is not only functional but also demonstrably reliable and effective in real-world scenarios.
What This Means for Your Design
People trust self-driving cars more when they see them working well, not just because they like technology or want to give up control.
How to use in your project
- 1.Reference this study when discussing the importance of system reliability and user perception in your design project's justification or evaluation sections.
Add to My Project
Quick Cite
Paragraph starter
Research indicates that perceived system performance is the most significant factor in building user trust for highly automated driving systems (Stephan, 2019). Therefore, design efforts should prioritize demonstrating the system's reliability and effectiveness to foster user confidence.
Source
Questions About This Research
- What does the research say about perceived system performance is key to building trust in automated driving?
- Focus design efforts on demonstrating and communicating the system's reliable performance to users, as this is the strongest driver of trust in automated driving. Evidence: DepositOnce (2019).
- Why does "Perceived System Performance is Key to Building Trust in Automated Driving" matter for design?
- For designers of automated driving systems, understanding that perceived performance is the most critical factor for user trust is paramount. This insight guides design efforts towards ensuring the system is not only functional but also demonstrably reliable and effective in real-world scenarios.
- How can designers apply this research?
- Focus design efforts on demonstrating and communicating the system's reliable performance to users, as this is the strongest driver of trust in automated driving.
- What were the main findings?
- Perceived performance of the automated driving system is the most important factor for building trust.. Personality characteristics (desire for control) and general attitude towards technology can influence trust, but to a lesser extent than perceived performance.. The type of system limit experienced significantly impacts trust, with non-detection of relevant events being particularly detrimental.
- What research method was used?
- User studies in both real-world driving and simulated environments. with 90 participants (28 in study 1, 72 in study 2).
- How strong is the evidence?
- Evidence strength is rated Strong effect, based on a 2019 journal from DepositOnce.
- What should I do differently in my next project?
- When designing interfaces for automated systems, ensure that the system's operational status, its successes, and its limitations are clearly and consistently communicated to the user.
- What are the limitations?
- The studies may not fully capture long-term trust development or the impact of diverse driving conditions and user demographics. The specific HMI concepts tested are not fully detailed.