Creating Appropriate Trust for Autonomous Vehicle Systems: A Framework for HMI Design
Paper in proceeding, 2016

While autonomous vehicle technology progresses, potentially leading to a safer and more efficient traffic environment, many challenges remain within the area of human factors, such as user trust for Autonomous Driving (AD) vehicle systems. The aim of this paper is to investigate how an appropriate level of user trust for AD vehicle systems can be created via human-machine interaction (HMI). A guiding framework for implementing trust-related factors into the HMI interface is presented. This trust-based framework incorporates usage phases, AD events, trust-affecting factors, and levels explaining each event from a trust perspective. Based on the research findings, the authors recommend that HMI designers and autonomous vehicle manufacturers take a more holistic perspective on trust rather than focusing on single, “isolated” events, for example understanding that trust formation is a dynamic process that starts long before a user’s first contact with the system, and continues long thereafter. Furthermore, factors affecting trust change, both during user interactions with the system and over time; thus HMI concepts need to be able to adapt. Future work should be dedicated to understanding how trust-related factors interact, as well as validating and testing the trust-based framework.

Framework

User

Human-Machine Interaction (HMI)

Trust

Autonomous Vehicles/Systems

Author

Fredrick Ekman

Chalmers, Product and Production Development, Design and Human Factors

Mikael Johansson

Chalmers, Product and Production Development, Design and Human Factors

Jana Sochor

Chalmers, Product and Production Development, Design and Human Factors

Proceedings of the 95th Annual Meeting of the Transportation Research Board, Washington, D.C. January 10-14, 2016

Areas of Advance

Transport

Subject Categories

Transport Systems and Logistics

Other Social Sciences not elsewhere specified

More information

Created

10/8/2017