Verizon and Nissan have collaborated to research and test how connected cars can communicate with their surrounding infrastructure to improve safety.
The tests have been carried out in California and the new technology can help notify drivers of detected pedestrians or other vehicles emerging from behind visual barriers.
The technology leverages Verizon 5G Edge, 4G LTE, and a Nissan proprietary telematics test platform to process sensor data from vehicles and infrastructure into urgent notifications.
The Contra Costa Transportation Authority (CCTA) is now in the process of validating the technology for its Automated Driving Systems Grant Program, which includes controlled deployment in select public locations in Contra Costa County, California.
TJ Fox, senior vice president of industrial IoT and Automotive, Verizon Business, said: “Communication between vehicles and the environment around them, or C-V2X, will be one of the most important transportation innovations of the connected and autonomous future of driving.
“This proof of concept shows that edge computing with Verizon’s cellular network can help take the resource-intensive compute burden off vehicles and public infrastructure -- housing their software platforms and crunching their sensor data for them -- and can communicate data outward to prompt potentially lifesaving safety alerts or autonomous driving features in the car, all essentially in real time.”
How the trials worked
The trials focused on testing a variety of vehicle-based and infrastructure-based sensor configurations to create a multi-viewpoint picture of potential safety hazards beyond vehicle and driver line-of-sight.
Using Verizon 5G Edge with AWS Wavelength, the sensor data from Nissan vehicles and infrastructure was processed at the edge of Verizon’s wireless network and communicated back via the cellular network to vehicles in near real time, prompting Nissan’s platform to initiate driver notifications.
This process helped notify drivers of detected pedestrians entering roadways from behind other cars or of oncoming vehicles obscured behind larger vehicles, as can occur during left turns with oncoming traffic.