The development and spread of advanced ‘semi-automated’ features among personal vehicles has been bold. The fact that non-premium consumers now have access to a feature which allows their car to steer itself into a parking space is nothing short of a triumph. But notwithstanding this achievement, the market for semi-automated and autonomous vehicles—either personal or through mobility services—has yet to be proven viable with actual consumers.
Only a narrow segment of consumers are interested in features that leverage self-driving technology; and most remain wary of automated driving features. In a situation exacerbated by the poor user experience (UX) of existing semi-automated features, such as park assist and automated highway driving systems, in addition to high-profile crashes and fatalities involving self-driving test vehicles, automakers have done little to nothing to address this problem thus far.
To drive consumer demand, it is not enough for semi-automated and autonomous vehicles just to be safe; they must also be practical and desirable.
Consumer interest is beginning to fracture
The broader consumer market outside of the premium segment has been slow to warm to semi-automated driving features in large numbers, primarily due to a lack of trust in the technology. Research by Strategy Analytics showed that after a pronounced decrease in 2016, interest in semi-automated and autonomous driving features rebounded in 2017, despite mixed levels of reported satisfaction.
However, after several years of uniform increases and decreases, interest in these varied features has now begun to fracture, especially in the US and China. Semi-automated driving functions no longer tick the right boxes for the premium class; consumers are now providing feedback on their usefulness and what we are learning is that not all features are equal. While interest in park assist is growing, particularly in the US, interest in traffic jam assist is dropping, particularly in Europe.
Usefulness and usability are critical to gain trust
Investigating further, Strategy Analytics found that there are two underlying reasons for the fracturing of interest in certain features, and the lack of trust many consumers have with them—especially in personal vehicles.
Firstly, the usefulness of these features remains questionable, particularly for systems such as traffic jam assist which require the user to ‘check in’ once every ten seconds. Such systems add no value to the enjoyment of the driving experience, and questionable value in terms of perceived safety. Secondly, the interface design and usability
of these features remains abysmal, as system status and handoff/takeover methods are confusing not just to drivers—as Strategy Analytics’ extensive benchmarking of these systems has proven—but to dealers as well, who cannot fully explain their functions or benefits.
These systems are also hindered by the lack of standardisation in how they are activated, how they behave, and even what they are called. A recent study by the American Automobile Association (AAA) found that semi-automated and other ADAS features have too many different names, which confuses consumers.
Practical usefulness also hinders automated shared transport
Furthermore, consumer attitudes toward automated shared transport, such as taxis and buses, are no different. Consumer interest worldwide is extremely narrow because the practical usefulness of such services has yet to be proven to consumers beyond the early-adopter segment. In addition to not having a use for automated taxi or bus services, sceptical consumers do not yet trust automated transport technology. Consumers in China also show strong concern for the quality of the vehicles which might be utilised for such a service.
In August 2018, a number of Arizona locals noted their frustration in sharing the road with autonomous test vehicles from Waymo’s self-driving taxi pilot. As such negative public feedback would illustrate, it is not enough to simply build an automated transport programme, roll out a charm offensive and expect consumers to ‘flock’ to a service. Supply will not create its own demand, and any service offered must be usable and practical for local use cases. Moreover, just as Strategy Analytics has found with reactions to semi-automated driving systems, consumer scepticism toward automated transport in general remains unresolved.
Scepticism is more than an issue of trust
But consumer scepticism is not only confined to trust. Strategy Analytics previously identified four major factors that consumers use to determine how to transport themselves: monetary cost, usability (as a function of availability, simplicity, and convenience), time or length of journey, and comfort.
The importance of each individual factor can vary based on weather, cargo, the perceived safety of the environment, the urgency of the trip, and so forth. But those overall decision factors are resilient. Plus, if a mobility service is too expensive for the use case, not available when or where it is needed, or is complex or unreliable to use, consumers are less likely to be satisfied, and unlikely to become loyal users. This is wholly the case with autonomous mobility services and personal autonomous vehicles: if consumers cannot see the value of each of these elements in autonomous vehicles, then there is no basis for consumer demand.
Trust remains the elephant in the room preventing widespread consumer demand. In order to get consumers on board with fully automated driving and hasten the profitability of these services, providers need patronage from not just early adopters and willing beta testers, but from some portion of the large percentage of consumer base who are currently distrustful of the technology.
Large swathes of consumers, especially in the US and Western Europe, are still actively avoiding automated parking and driving technology. Among these segments, a lack of trust is far and away the most prominent rationale for avoidance. An extensive human factors related overhaul of existing systems, and even pilot test systems at the human-machine interface (HMI) level, would go a long way toward addressing these issues.
This article appeared in the Q2 2019 issue of M:bility | Magazine. Follow this link to download the full issue.