Retail Predictions
3 MIN READ | 5G

For Connected Vehicles, Seeing the Future Pays Dividends

Tim Brooks
Feb. 26 2019

How much would you pay to know the future? Believe it or not, this isn’t a hypothetical question.

OK, we can’t show you tomorrow’s winning lottery numbers. But we can predict your in-vehicle cellular performance, minutes or hours down the road, with extraordinary accuracy. 
These insights can make a huge difference to the applications you use while driving. They can make your time on the road safer and less frustrating. It’s no stretch to envision this predictive intelligence even fueling brand-new commercial ecosystems. 

Connectivity Matters

Industry analysts forecast the global connected vehicle market will triple over the next six years, reaching more than $219 billion by 2025. That connectivity brings a world of new applications and experiences: autonomous driving, smart vehicle telemetry and maintenance services, advanced driver assistance systems (ADAS), and much more. But it also means heavier reliance on cellular networks—and more serious consequences when connectivity fails. 

Today, variable performance and coverage gaps amount to little more than an inconvenience. My GPS won’t update. My phone cut out in the middle of a call. My kids’ Netflix movie won’t load and they’re being really annoying. In the future though, poor connectivity will be a serious problem. 

If your vehicle fleet relies on real-time logistics and telemetry, for example, or if you’re the company providing those services, losing connectivity can mean significant financial losses. Enter the realm of autonomous vehicles and connected ADAS safety features, and poor connections could even make drivers less safe. 

In-Vehicle ESP

What if you could know ahead of time how your connection’s throughput and latency will fluctuate throughout your trip, and even predict coverage gaps? Infovista’s TEMS for Auto solution makes it possible. 

A software client in the vehicle or a telematics control unit (TCU) provides detailed information about expected throughput, latency, and availability. That can be for the route you’re traveling based on a GPS destination, or just based on the direction the vehicle is moving. 
The client passively monitors radio parameters and network signaling, so it doesn’t consume wireless bandwidth. And it uploads the data to a cloud database, where it enables detailed geodata maps of cellular performance—and granular predictions that applications can use. 

Insights in Action

With predictive intelligence, in-vehicle applications can be alerted to upcoming coverage gaps or connectivity issues and proactively take action to mitigate them. That could include:

  • A streaming video app increasing buffering to ensure no disruption to the viewer
  • A GPS app pre-downloading maps in advance of coverage gaps
  • ADAS systems adapting to changing conditions (for example, a hands-free cruise control system increasing the distance between vehicles to account for increased latency)
  • Ability to advise users that their call may drop soon

Drivers also get a better experience just knowing there is reduced functionality ahead. For example, if you’re plotting a family road trip and see a stretch with major data performance issues, you could choose an alternate route. Or, seeing you’re about to hit a coverage gap, you could wait 10 minutes before placing an important call. 

Driving New Value

As a driver, how much would you pay for that kind of predictive intelligence? What if you’re an automotive manufacturer launching a new suite of in-vehicle services ahead of the competition? What if you’re developing the next generation of in-vehicle IoT applications? 
In these early days of the connected car revolution, the future of these business models and ecosystems is not yet written. But there’s one thing we can predict: the ability to anticipate cellular performance will be extremely valuable to multiple connected vehicle stakeholders. 
Want to discuss how your business could capitalize on these insights? Contact Infovista today. 

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