Autonomous Vehicle Human-Machine Interface


Persons with visual disabilities like blindness and low vision often face significant obstacles to gainful employment and social inclusion due to limited personal mobility.

Proponents of fully autonomous or “self-driving” vehicles argue that the emergence of this technology may address this issue. Advocates for the approximately 8 million people with visual disabilities in the United States, however, are concerned that their needs are not being adequately considered in the design of this technology.

There is concern that the self-driving vehicles of the near future are being designed around the driver of the present who, in all cases, is sighted as opposed to the user/operator of the future who need not necessarily be. As a result, it is argued, self-driving technologies are being developed that will ultimately prove inaccessible to persons who are significantly visually impaired, ultimately undermining the potential mobility benefits of the technology.

There is therefore a critical need to determine a model of interaction that will support efficient use of this technology by visually impaired persons.

Therefore, the goals of this research are to i) gain a deeper understanding of the needs and challenges of visually impaired persons in terms of their interaction with self-driving vehicles, ii) develop tools to address these needs, and iii) test the usefulness of these tools in laboratory and field studies.
We specifically seek to:

1) Develop a self-driving vehicle interaction model tailored for the visually impaired user.

2) Develop novel user interfaces and interaction techniques, based on our interaction model so that visually impaired users can locate in space, interact with, and direct a self-driving vehicle. Our focus in this context is on SAE Level 4 and 5 autonomous vehicles that control all aspects of the driving task without human intervention.

3) Determine the efficacy of our interaction model and tools (e.g. user interfaces) in assisting visually impaired users in effectively interacting with and directing self-driving vehicles. Our evaluations will include testing using a real or simulated self-driving vehicle in controlled laboratory conditions, private parking facilities, private roadways and public road courses.

Basic info

Project Date: Jan. 30, 2017 - Present
Sponsors: internal
Keywords: autonomous vehicles, self-driving vehicles, accessibility

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