September 14, 2017 | Written by: Jen Clark and Ben Stanley
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On Thursday September 14th Ben Stanley, Automotive Research Lead from IBM’s Institute for Business Value, spoke at IAA 2017 about the changing ways consumers will engage with their vehicles.
Ben explored the promise of self-enabling cars, the power of cognitive technology to offer a connected experience and the willingness of consumers to embrace these new capabilities. The following post is a whistle-stop tour of some of the points he made in his presentation.
Ben Stanley presenting at IAA 2017
Consumer perspectives on mobility are shifting
Last year, the IBV published a paper entitled ‘A new relationship – people and cars’, which explored how consumers around the world envisage that cars should fit their lives. The paper’s authors analysed the reactions of 16,000 participants to understand what people want from transportation.
The breakdown of the respondents’ answers uncovered some interesting trends that are expected to present themselves over the next ten years. Among them are anticipated:
- A 5% reduction in personal car usage;
- 15% increase in ride sharing;
- 19% reduction in public transport use;
- 30% increase in other modes of transport.
The figures are interesting because they indicate changing attitudes toward personal mobility. For many consumers, transportation will no longer be simply a case of getting from A to B. Instead, we see expectations that modes of individual transport will serve as platforms for entertainment and information, hubs for retail and even health monitors.
Above all, these vehicles will be able to look after themselves. They will perform engine diagnostic checks to identify when maintenance needs to be carried out, book themselves into a garage and drive themselves there for servicing – all without human input. In other words, they will be self-enabling.
Self-enabling vehicles are cognitive computing’s big promise to the automotive industry. Not only will they look after themselves; they’ll also look after the interests of their occupants.
For example, a self-enabling car will be able to drive itself (and its occupants) to work, allow them to make in-vehicle purchases (like toll-paying and parking charges) and keep them updated about current affairs, the weather and flow of traffic as needed.
In a snapshot, a self-enabling vehicle is:
- Self-integrating: supporting seamless and secure digital integration;
- Self-configuring: customizing itself to its environment and personalising its services to appeal to those on board;
- Self-learning: cognitively optimizing its performance;
- Self-healing: undertaking analytics and prognostics for service and maintenance;
- Self-socializing: performing ancillary tasks and accessing social networks;
- Self-driving: managing automated and autonomous mobility.
A vehicle like this acts like a PA to its occupants, offering them a rich and varied mobility experience. Some anticipated in-vehicle services include:
- Weather and traffic information
- Commerce (payment for tolls, parking)
- Health (measuring the occupants’ heart rate and blood pressure)
- Concierge (recommending hotels, theatre and dining experiences)
- Education (offering training materials and video)
- Marketing (making special offers to occupants based on their location or preferences)
Cognitive computing: making it happen
At the crux of these tempting possibilities is cognitive computing. Cognitive systems can assist us in ways that were previously unimaginable because they mimic the way that human beings engage with and make use of information. Like us, cognitive systems can understand imagery, interpret language and handle other unstructured data – i.e., anything that doesn’t fit neatly on a spreadsheet.
By drawing on existing knowledge, these systems can reason, come up with hypotheses and select the most likely outcome based on their interaction with new data points. They can develop and sharpen their expertise with each new experience, and communicate those experiences with those around them.
Are we ready for this level of integration?
In this way, self-enabling vehicles supported by cognitive technology possess a level of autonomy that was previously impossible. But are people ready to accept them?
Naturally, vehicles that offer such a complex roster of services and capabilities may be met with skepticism, and not all consumers are on board with the vision of enriched mobility experiences. Some early adopters will lead the way, while others only belatedly accept new technology. The paper, ‘A new relationship – people and cars’, identified four broad groups:
- – The pacemakers (16%) – early adopters, eager to try new technology;
- – Fast followers (32%) – close behind the pacemakers;
- – The pack (38%) – view technology conservatively, but are eventually open to it;
- – Spectators (14%) – happy with the status quo, inflexible with new mobility solutions.
The challenge for the automotive industry will be to communicate the value of this new proposition to consumers who are naturally reticent and slow to embrace new technology.
In the industry, however, automotive executives are generally ready to embrace cognitive computing. Hopes are high – and so are expectations. Seven in 10 automotive executives believe cognitive computing will have a significant impact on the in-vehicle personal experience, while the same proportion believes it will significantly impact mobility services.
If you are interested in the future of self-enabling vehicles, you might find these resources useful: