“In an autonomous driving world, drivers will regain, on average, 26 minutes of free time. What will people do with these 26 minutes? How do we demonstrate what content to promote to drivers in autonomous mode?” Volvo partnered with Ericsson to address these problem statements for their vision of the future of long distance driving. Assuming that cars will be driving themselves, our team addressed how the required network connections and content delivery could provide a seamless, entertainment-focused, autonomous trip. Over the course of the twelve-month engagement, Snacks produced marketing guidelines for “Business Builders” at CES, MWC Barcelona, MWC Shanghai, and NAB trade shows, designed and developed supportive demonstrations around “The Chair” from Volvo that took center stage on the trade show floors. For different exhibits, “short” (1 minute) and “long” (5 minutes) demonstrations were prepared for various attendees and media outlets.

What initially began as an IoT dashboard meant to harness the power of machine learning, analytics, and the large number of accessible connected devices that rely on timely data analytics to deliver seamless user experience, the software our team designed and developed served as the underpinning for the company’s later solution offering, “Predictive Mobility”.

Ericsson Predictive Mobility used analytics and machine learning to combine knowledge about users, different connected devices, and different networks along a route to proactively guarantee a seamless and productive user experience. For example, in-car services such as onsite fueling and maintenance can only be enabled if we can predict with confidence different locations, approximate duration of stops, and current network KPIs.

Our trip simulator incorporated real data derived from our team’s actual driving history. In order to set a baseline for our data, we developed a simple tracking Android application, loaded it on three burner phones, and kept the phones in our car glove boxes.

Over the course of a few weeks we had sufficient data to plot actual trips and establish real-life use cases. Monthly business trips to Santa Clara from Boston meant we had data from two very different regions as well. Volvo believed that self-driving automobiles would return, on average, 26 minutes to the driver. By freeing-up this time normally spent commuting, our simulated drivers were encouraged to do other things like make calls, check email, watch television, or even video chat. All imagined use cases from the manufacturer were dependent on a very strong and reliable connection to a cell network. In order to realize the vision of a continuously connected individual inside a continuously connected automobile, we needed to explain how this might all work.

The data picked up from our burner phones highlighted every minute detail of our driving, including every radio tower we encountered with timestamps. Scheduled pings from the app allowed us to select from dozens of different trips linked back to different drivers on our team. Different driving patterns and personas were developed based on our unique driving data. In-car services could only be enabled if we could reasonably predict locations, stops, and network availability along a route.

In order to illuminate our case studies at different trade shows, our team created three personas to assist sales people in delivering effective presentations and generate interest with different types of audiences, despite differing backgrounds and levels of technical expertise. Our design interfaces for the back-end dashboard measured driver activities, network bandwidth, predictive analytics, and content delivery during extended trips.

Our exhibition design simulated scenarios using real data we collected in addition to data we collected and anonymized from the T-Mobile network managed by Ericsson. In the end, visitors to the Ericsson booth left with a greater understanding of the network demands of a future that features autonomous vehicles.