UW Graduate Design Thesis 2020–2021
This post is part of a series of design papers on the theme of ‘New Interface Design for the Semi-autonomous Car’.
Hello! I’m Solji, a 2nd-year MDes at the University of Washington. I majored and majoring in industrial design, and now I work as a UX designer based in Seattle.
As Tesla's stock change shows, which have risen nearly 800 percent in the past year, the public’s interest in self-driving cars is worldwide hot. Self-driving cars make us dream of our calm mornings and peaceful journeys sitting behind the driver's seat freed from driving and traffic jams. But you will look at self-driving cars from a slightly critical perspective after reading these posts.
My dad bought a car having Adaptive Cruise Control, called semi-autonomous mode, a year ago. He enjoyed using this driving aid feature, which automatically controls lanes and speeds. And last August, the car hit the car next to it which was trying to change the lane.
It was not a fast speed (about 25 mi/h) and the vehicle vision was not obscured by external factors like harsh weather. It was a too obvious accident for human sight. Why autonomous function was not able to prevent this accident? Is the fully autonomous car will become true in the near future as we expected? My design paper began with a question that originated from the autonomous car accident.
1) What are the main causes of self-driving car accidents?
2) How can design help drive safe self-driving cars?
First of all, I analyzed the fatalities of self-driving cars to find out the main cause of accidents in self-driving cars. It has been difficult to find the accurate cause of the accident. Because there are not yet enough policy or law on AV(autonomous vehicle) accident, accident data recorded in the black box were frequently damaged by the crash, and self-driving car companies didn’t like to announce the failure of AV to the public. However, the data collected from various media were able to divide the cause of the accident into two main causes.
1) Automotive vision sensor failure
The second case among the five cases in the above table is a relatively well-known accident. It caused by the failure of vision sensors to distinguish the white side of a trailer from the bright sky behind the car. Other accidents have also been caused by the vision sensors’ failure to achieve the recognition of accurate objects with a sense of distance/depth. The car combines three to four different vision sensors to obtain a similar level of visual information that the human eye gets. (The next post will cover this topic in more detail.)
2) Driver’s carelessness while driving
As above, the level of automation of self-driving cars is at the level of driving assistance systems, but the level of automation we expect from the word “semi-autonomous driving” is more than that. That cognitive difference causes the driver to lose engagement in driving and leads to a very ridiculous accident. Contrary to our expectations, AV experts expected to take at least 25 years to complete self-driving.
To sum up, the machine driver is not yet sufficiently delicate in the sensing surrounding environment.
Human drivers do not fully understand the limitations of self-driving cars and become careless in driving by that over-reliance.
The goal of my design thesis is to find a design solution that will bridge the gap between humans and self-driving cars.
If you have any question or advice, please do not hesitate to email soljilee@uw.edu — I’m happy to talk to you :)
