Self-driving vehicles are the latest innovation in improving personal mobility and road safety by removing arguably error-prone humans from driving-related tasks. Such advances can prove especially beneficial for people who are blind or have low vision who cannot legally operate conventional motor vehicles. Missing from the related literature, we argue, are studies that describe strategies for vehicle design for these persons. We present a case study of the participatory design of a prototype for a self-driving vehicle human-machine interface (HMI) for a graduate-level course on inclusive design and accessible technology. We reflect on the process of working alongside a co-designer, a person with a visual disability, to identify user needs, define design ideas, and produce a low-fidelity prototype for the HMI. This paper may benefit researchers interested in using a similar approach for designing accessible autonomous vehicle technology.
INTRODUCTION
The rise of autonomous vehicles (AVs) may prove to be one of the most significant innovations in personal mobility of the past century. Advances in automated vehicle technology and advanced driver assistance systems (ADAS) specifically, may have a significant impact on road safety and a reduction in vehicle accidents (Brinkley et al., 2017; Dearen, 2018). According to the Department of Transportation (DoT), automated vehicles could help reduce road accidents caused by human error by as much as 94% (SAE International, n.d.).
In addition to reducing traffic accidents and saving lives and property, autonomous vehicles may also prove to be of significant value to persons who cannot otherwise operate conventional motor vehicles. AVs may provide the necessary mobility, for instance, to help create new employment opportunities for nearly 40 million Americans with disabilities (Claypool et al., 2017; Guiding Eyes for the Blind, 2019), for instance. Advocates for the visually impaired specifically have expressed how “transformative” this technology can be for those who are blind or have significant low vision (Winter, 2015); persons who cannot otherwise legally operate a motor vehicle.
While autonomous vehicles have the potential to break down transportation
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L3 Vehicles are becoming a Reality: Important Human Factors Consideration for the Viability of Conditional Automation
As of early 2023, only a limited number of Society of Automotive Engineers (SAE) Level 3 (L3) automated driving systems are available on the market, and they are primarily offered by luxury vehicle brands. SAE L3 automated driving systems are classified as conditional automation (CA), meaning that the vehicle can undertake some well-defined driving tasks under specific conditions, but the driver must be ready to assume control of the vehicle when prompted by the system. It is anticipated that an increasing number of L3 CA systems will be introduced on public roads in the next few years. However, L3 systems pose unique Human Factors (HF) challenges that require thoughtful consideration to ensure that production systems are feasible without compromising driver or road safety. This panel discussion brings together HF researchers and practitioners with expertise in human behavior and usability design for automotive applications to discuss and delineate key issues specifically related to L3 systems, as well as potential approaches to tackle these issues.
more » « less- Award ID(s):
- 2239642
- PAR ID:
- 10528531
- Publisher / Repository:
- SAGE Publications
- Date Published:
- Journal Name:
- Proceedings of the Human Factors and Ergonomics Society Annual Meeting
- Volume:
- 67
- Issue:
- 1
- ISSN:
- 1071-1813
- Page Range / eLocation ID:
- 1285 to 1288
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1177/21695067231192644
