On a clear spring morning in Taichung, Taiwan I rode with a team of researchers and
scientists in a 20-seat bus through the campus streets of the world-renowned Industrial
Technology Research Institute of Taiwan. As a gold sedan suddenly merged into our lane, the
bus came to a jolting stop to allow for a safe right-of-way passage, and I was reminded of the
myriad of people who had anticipated this exact moment. Urban planners, designers, sci-fi
enthusiasts, journalists, mechanics, and scientists have all awaited the era where a driverless
vehicle will successfully react, in real-time, to the seemingly unpredictable high-speed ballet of
cars, motorbikes, and pedestrians that all lay claim to the road.
Two days later and more than 11,000 km away, a driverless car fatally struck a pedestrian
in Phoenix, Arizona. And while the incident did not mark the first death in the world of
autonomous vehicles, the pedestrian became the initial casualty in the new frontier of “off-track”
driverless cars. When I learned of the event from an innocuous ping on my iPhone while
commuting from Hong Kong to Taipei, my response was similar to predictions made by the New
York Times less than six months prior. Was this “the one catastrophic accident that could imperil
the whole experiment?”[1]
Given the recent headlines, designing trust in autonomous vehicles has become all the
more salient. Riders will need to be reassured beyond statistical data, which reveals that human-controlled vehicles pose a much greater risk to the public than driverless cars. But the question remains, how does trust become automatic, especially in the aftermath of a tragedy? And how can the ownership models pursued by the automotive industry be of benefit?
The autonomous, mid-sized bus I rode in Taichung, Taiwan was not considered a Level 5
Automated Vehicle, which is defined as a “full-time performance by an Automated Driving
System for all aspects of the dynamic driving task under all roadway and environmental
conditions.” In other words, an automated vehicle with no human driver. The bus I rode in still had a nervous graduate student perched behind the wheel. Anticipating a manual override of any “mistakes” that the artificial intelligence system may have made, human feet were always within inches of the pedals, and other researchers were constantly monitoring the several screens positioned within the body of the bus. It felt like a beta-version of the future, hopefully with less cables.
Though I had previously ridden in a Level 5 autonomous car in Masdar City, Abu Dhabi,
the scale of vehicle currently in development in Taiwan (mid-sized buses used for public
transportation) re-frames the degrees to which vehicles should be considered autonomous. In
fact, accepting vehicles as a type of urban infrastructure positions autonomous public
transportation as a shared platform that could provide the same level of accessibility as a private
car.
Development in Taiwan encourages a shift in scale: no longer should the highest level of
autonomous vehicles be designated solely by the sophistication of the artificial intelligence
commanding the vehicle. The top benchmark of driverless vehicles should instead be classified
by type and not by degrees of autonomy. In other words, vehicles designated for public transit, which have the capacity to reduce the number of private cars on the road and increase urban densification, should be granted the highest accolades. Perhaps a Level 6 should now be designated for completely autonomous vehicles that can transport more than 10 people per trip. Designing trust in the technology will come from re-framing the types of autonomous vehicles developed, rather than the degree of autonomy it performs. As Marshall Brown, founder of the Driverless City Project forecasts, because “society is cultural, and political, and aesthetic, and about desires — [autonomous developers] are going to need more than just software engineers working on it.” [2]