Hi there! I'm Elizabeth, a Product Design Leader based in NYC.
Photo credit: Flickr user fittzer (Creative Commons)
“The focus has been on safety and convenience to date. From emergency calling to listening to Pandora or Spotify in your car, the opportunity is to start thinking about how to use information from the vehicle to transform the relationship with the customer, or to improve operational efficiency.”
The Assignment Brief
The Internet of Things means that large amounts of sensor data can move from one product service system to another, becoming available to new industries. In this nine-week project, we will conceive of and new design services that leverage data from cars, drivers, and passengers. The modern automobile contains multiple computer systems that in many cases, are decoupled, insecure, and outdated. Our new service designs will explore how to offer bundled services in the car to benefit drivers, passengers, and society at large.
Online Research
We conducted online research in both articles and academic papers on topics ranging from car safety, insurance, cabin comfort, and traffic. This research helped us better understand the system as a whole, the technical features of cars and their sensors, as well as identify opportunity gaps in the market. The most obvious gap that bubbled up to the surface was a more detailed and dynamic traffic and weather data display.
Other online research included exploring areas around big data, voice activation, and steps the government is taking to prepare for connected cars. We found that there were numerous stake holders we hadn't initially considered.
Driving Survey
We created a survey for drivers with 43 participants that covered a range of topics including driving habits, phone usage, and safety & maintenance.
Respondents reported that the most annoying aspects of driving are other drivers and traffic. The most enjoyable parts are independence and driving while listening to their favorite music. We found is that almost all participants multitask to some degree while driving, including using navigation, changing the music, and checking texts or emails.
About 70% of respondents had been in accident of some sort, the most common reasons being that it was another driver’s fault, weather conditions and drunk drivers.
Interviews
The participants we interviewed didn’t drive much and similarly didn’t enjoy it much due to the annoyance of other drivers, however they saw driving as a way to get to places otherwise inaccessible by public transport. A couple of unique findings were the struggles around maintenance after an accident. For instance, the problems and costs associated with trying to maintain a car after it had been damaged.
Common themes found were of high insurance, maintenance and repair costs, as well as accidents and damage that were not due to hitting another moving car, but either hitting or being hit while one car was parked.
“I hate finding directions: when to go where, my attention is split between looking at navigation and driving.”
Final Concept Model
Our initial research fueled much of our conceptual model of how car sensors currently work. We decided to group the various sensors of the car into 4 distinct categories: Comfort, Performance, Safety and Location. From there we tried to identify the major breakdowns in these various areas. I created the final model in Adobe Illustrator.
Identifying Market Opportunities
Our team used our initial research as a spring board and whiteboarded ideas for services, sketching out the Stakeholders, Goals, Technology, Value Proposition and Use Case for each. We landed upon 4 very different ideas:
- Car maintenance via sensors
- Adjustable car settings
- Mood settings with context-awareness
- Good driver insurance and on-vehicle tutoring
Storyboard Speed Dating
Speed dating is a user research method for rapidly testing ideas by creating lo-fi A/B versions of an idea and running it by potential customers, while having them share feedback. We created 6 storyboards to illustrate possible use cases of the various ideas.
Key finding: Most people hated the idea of having their information reported to insurance. Everyone wanted to learn how to be a better driver, but they didn't want to be "told what to do."
Modeling The Service
During our initial research we found that people hate other drivers, but they also didn't like being alerted about bad drivers as they thought it would be annoying or unactionable. However, drivers responded particularly positively to our storyboardthat offered tips related to road conditions, especially due to weather. So we needed to make a major pivot away from our earlier initial service models.
We decided to model a new service where the car's sensors could be leveraged to share road conditions and minute-to-minute weather reports. This data would create a value to both drivers as well as weather and traffic reporting, and to municipalities who may use it to better deploy their salt and plow trucks.
From these white board sketches I created digitized versions of the service using Adobe Illustrator.
Model created by John DeGore
Model created by John DeGore
Reimagining what driving will look like
I created the final customer journey map with the idea of mapping both a past and future interaction when problems occur on the road as well as the customer's emotional reaction to them.
User Enactments
We verified our final service in a user enactment in which we put the user in the front seat of the car with a PS3 steering wheel controller and pedals.They had a dashboard that was displayed to them on an iPad. From there we had a driver set out on a pre-prescribed route while another member of our team sat in the back seat with a laptop and an iPhone. At designated landmarks, we used a Wizard of Oz technique to deliver audio, visual and haptic feedback to the user in a random order. Haptic, or vibration, was simulated through placing an iPhone under the steering wheel and texting the phone to make it vibrate. We collected the user's input from the game controllers to update their dash display according to when they took action.
We set out to find what modalities (haptic, visual and audio) were most effective and salient in grabbing attention. Overwhelmingly people liked the service and felt like the visual and audio combination was most effective, most people couldn't feel the haptic either because it wasn't a strong enough signal or because Pittsburgh has so many pot holes it's difficult to tell what is vibrating. Check out video of the enactments.
“I’m used to listening to voices for map directions so I would take the same cues from that... typically I don’t have the phone right in front of my face... but I would look down at the screen to confirm what I think the voice said.”
Final Analysis
We feel there is a place in the market for an integrated navigation system that crowd sources weather information using the embedded sensors in vehicles. The result of this data could be sold to municipalities, navigation system makers, and car manufacturers. The data would also feed into driver's navigation and traffic systems as well as instruct the driver to take evasive action when needed. Such a service could integrate with existing players in car navigation to enhance the service rather than replace it.