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Acceptance and Trust: Drivers' First Contact with Released Automated Vehicles in Naturalistic Traffic
- Source :
- IEEE Transactions on Intelligent Transportation Systems ( Early Access ) (2024) 1-10
- Publication Year :
- 2023
-
Abstract
- This study investigates the impact of initial contact of drivers with an SAE Level 3 Automated Driving System (ADS) under real traffic conditions, focusing on the Mercedes-Benz Drive Pilot in the EQS. It examines Acceptance, Trust, Usability, and User Experience. Although previous studies in simulated environments provided insights into human-automation interaction, real-world experiences can differ significantly. The research was conducted on a segment of German interstate with 30 participants lacking familiarity with Level 3 ADS. Pre- and post-driving questionnaires were used to assess changes in acceptance and confidence. Supplementary metrics included post-driving ratings for usability and user experience. Findings reveal a significant increase in acceptance and trust following the first contact, confirming results from prior simulator studies. Factors such as Performance Expectancy, Effort Expectancy, Facilitating Condition, Self-Efficacy, and Behavioral Intention to use the vehicle were rated higher after initial contact with the ADS. However, inadequate communication from the ADS to the human driver was detected, highlighting the need for improved communication to prevent misuse or confusion about the operating mode. Contrary to prior research, we found no significant impact of general attitudes towards technological innovation on acceptance and trust. However, it's worth noting that most participants already had a high affinity for technology. Although overall reception was positive and showed an upward trend post first contact, the ADS was also perceived as demanding as manual driving. Future research should focus on a more diverse participant sample and include longer or multiple real-traffic trips to understand behavioral adaptations over time.
- Subjects :
- Computer Science - Human-Computer Interaction
Computer Science - Robotics
Subjects
Details
- Database :
- arXiv
- Journal :
- IEEE Transactions on Intelligent Transportation Systems ( Early Access ) (2024) 1-10
- Publication Type :
- Report
- Accession number :
- edsarx.2312.08957
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.1109/TITS.2024.3443927