The Road Ahead

How data in context extends the range of connected vehicle sensors

By | 2 minute read | September 29, 2020

Overhead view of car driving in very rain conditions

Connected cars have been around for a long time. General Motors launched Onstar, the first built-in telematics and crash notification system, in 1996.  Fast forward to today and not only are vehicles connected, but with Advanced Driver Assisted Systems (ADAS), the driving experience is safer and more enjoyable.

ADAS uses sensors and analytics to understand the environment directly around the vehicle.  Scenarios like Adaptive Cruise, Collision Avoidance and Lane Assist all function by using this kind of data.

But data collected from vehicles has tended to be limited. Most Original Equipment Manufacturers (OEM) don’t gather a lot of information beyond the immediate vehicle environment. Nor do they use “data in context” (e.g., driving in snow).

What typically happens with a vehicle system is that the immediate data is analyzed, and the context around the vehicle is considered after the fact. For example, OEMs may assess diagnostics information and discover certain problems that only occur in cold regions.

ADAS + traffic + weather = safer driving

So how can data in context help? You may know your GPS location, but do you know the weather or traffic or road conditions in that location? The information adds important context to the GPS data and can enhance the vehicle system.

Consider an Advanced Adaptive Cruise scenario, where a vehicle automatically passes another car. It is safer when the ADAS can also understand the traffic, position of other cars, weather ahead and so on.

As the next generation of systems is deployed, it will be critically important to understand the environment beyond the range of vehicle sensors. It means not just collecting data but using and acting on it in context — not after the fact, but in real time. These scenarios can help ADAS and the industry build an even better driving experience.

How IBM can enhance driver systems today

New technologies like cellular vehicle-to-everything (C-V2X), 5G and Edge computing will ultimately assist these scenarios in the next three to five years. But standards organizations and slow deployments will keep them from fully aiding the industry now. IBM is helping OEMs today with IoT Connected Vehicle Insights, a SaaS solution that brings data in context to connected cars.

Connected Vehicle Insights is more than an automotive IoT platform. It integrates with content and map providers in the cloud to not just collect data from a vehicle, but to add context around it and enable systems to act on it in real time. Connected Vehicle Insights manages the vehicle data, driver data and environment data — in memory — to provide response times as fast as 10 milliseconds, and with less network overhead.

What’s next

In the future, IBM will work with 5G and Edge technologies to get network latency even lower for driving scenarios that require it. In the meantime, IBM is leveraging today’s systems and the cloud to help OEMs see further down the road.