Combating Anti-Patterns in Autonomous Vehicle Design

What Are Autonomous Vehicles?

Autonomous vehicles (AVs) have been described as one of the most significant advances in personal mobility of the past century. The most advanced of this technology, fully autonomous or “self-driving” vehicles [1], [2] have been described as potentially improving traffic safety considerably by minimizing the role of arguably error - prone human beings in the driving process [3].

The resulting technology will see the human occupant act less as an active driver tasked with manipulating safety critical controls (e.g. steering, braking, acceleration, etc.) while acting more as an operator working in conjunction with an artificial intelligence (AI).

Despite the reimagined role of the human occupant there are emerging concerns about the human- machine interaction with this technology that has, as of yet, not become commercially available. Of specific focus are issues of the technology’s accessibility for persons with disabilities and older adults [4], [5].

There are concerns specifically that the design of this technology is focused on the needs of the driver of the present, who in all cases is sighted and has sufficient physical and cognitive abilities to manipulate a vehicle’s manual controls.

This stands in contrast to design which ideally would focus on the needs of the user/operator of the future who may be blind or have other physical or cognitive impairments which would likely render it impossible to operate a conventional motor vehicle.

We argue that within the current paradigm, absent concrete guidance that dictates what constitutes accessibility within the self-driving vehicle context [6], this emerging technology is being designed in a common manner with common characteristics of inaccessibility that supports and even encourages the proliferation of inaccessibility. Borrowing the language of object-oriented programming, we argue that these commonalities essentially amount to anti patterns [7], [8] in AV design. These antipatterns are common approaches to design that are ineffective and counterproductive.

We believe that new tools and thinking are needed to further accessible and inclusive autonomous vehicle design. If you wish to learn how to learn more about how we might help your company innovate please reach out.

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References

1. SAE International, “SAE J3016 automated-driving graphic,” Society of Automotive Engineers, 2019. https://www.sae.org/news/2019/01/sae-updates-j3016-automated-driving-graphic (accessed Jul. 15, 2019).
2. SAE International, “J3016B: Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles.” https://www.sae.org/standards/content/j3016_201806/ (accessed Nov. 01, 2019).
3. B. Crew, “Driverless Cars Could Reduce Traffic Fatalities by Up to 90%, Says Report,” ScienceAlert, 2015. https://www.sciencealert.com/driverless-cars-could-reduce-traffic-fatalities-by-up-to-90-says-report (accessed Apr. 26, 2019).
4. J. Brinkley, B. Posadas, J. Woodward, and J. E. Gilbert, “Opinions and Preferences of Blind and Low Vision Consumers Regarding Self-Driving Vehicles: Results of Focus Group Discussions,” in Proceedings of the 19th International ACM SIGACCESS Conference on Computers and Accessibility, Baltimore Maryland USA, Oct. 2017, pp. 290–299. doi: 10.1145/3132525.3132532.
5. A. Gluck, K. Boateng, E. W. Huff Jr., and J. Brinkley, “Putting Older Adults in the Driver Seat: Using User Enactment to Explore the Design of a Shared Autonomous Vehicle,” in 12th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, Virtual Event DC USA, Sep. 2020, pp. 291–300. doi: 10.1145/3409120.3410645.
6. J. Brinkley, S. B. Daily, and J. E. Gilbert, “A Policy Proposal to Support Self-Driving Vehicle Accessibility,” J. Technol. Pers. Disabil., pp. 35–43, 2019.
7. W. H. Brown, R. C. Malveau, H. W. McCormick, and T. J. Mowbray, AntiPatterns: refactoring software, architectures, and projects in crisis. John Wiley & Sons, Inc., 1998.
8. P. Wolfgang, “Design patterns for object-oriented software development,” Read. Mass, vol. 15, 1994.