How 5G and Edge Computing are Changing the Personal Transportation Industry
Growing up, my generation associated the future with a singular technological advancement – the development of a flying car. I had no doubts that by the year 2020, my life would very much resemble that of Jetsons especially when it came to transportation. If you are to look outside your window, the lack of flying cars will be painfully obvious. Our dream did not become a reality for many reasons. It may still happen one day, but what the greatest minds in the transportation industry realized is that we need not flying cars, but rather self-driving ones.
Can Driverless Cars be a Solution?
Unlike flying cars, driverless cars stand to solve real problems, like traffic delays and traffic collisions caused by driver error just to name a few. There many other applications of autonomous vehicles. Retail, food services, shipping, and healthcare industries are already testing them to see how they can take advantage of that technology.
Early versions of driverless cars focused on the approach of having a multitude of sensors within a vehicle and an on-board AI processing system that is crunching data and making decisions. That proved to be somewhat challenging. A recent Uber crash in Arizona was caused due to the system being overwhelmed with the number of incoming data points and delay that it took to process all of the data and make a decision.
The solution lies in vehicle processing being supplemented by its ability to communicate with other vehicles, remote servers, and external devices sending signals via reliable and fast communication methods. It will also require a significant amount of bandwidth. One vehicle generates more data in a day than all of Twitter activity in a world in the same day. This is where 5G network and edge computing come in as a key required infrastructure component for the future of autonomous vehicles.
What is 5G and Edge Computing?
When people talk about 5G today, they focus primarily on much higher bandwidth and download speeds that will be available to consumer devices such as smartphones. What is not getting as much coverage is a requirement for low latency when communicating using a 5G network. Latency is the time that it takes for a round trip of data, meaning how long after sending a signal you will get response data back. Current 4G networks have latency of about 50 milliseconds and 5G will be able to lower it to about 10-20 milliseconds. However, when the vehicle is moving at 60 mph and needs to brake because the traffic light is turning red, even a 10-millisecond latency could be deadly. This is where edge computing comes in. In current Verizon lab prototypes, latency using 5G and Edge computing has been reduced to just one millisecond.
Cloud computing has delivered a multitude of business capabilities and benefits. It enabled business to outsource infrastructure management and more importantly accelerated mobile revolution by allowing enterprise applications residing in the cloud to be accessed from virtually anywhere with internet access. One unfortunate thing about cloud is that it consists of data centers that were built in places with the cheapest prices on land and electricity. Those areas tend to be remote with higher latency accessing them. That latency is negligible when you are reading emails or updating your Facebook status, however for a real-time application, it becomes a critical factor.
The Problem Edge Computing Addresses
Edge computing is a network architecture paradigm where you bring resources necessary to process the problem closer to where data is generated. As Forrester highlights in a 2018 report, edge computing arose to address a number of cloud-related challenges, including:
An increasing need for low latency and high reliability
The rapid expansion of the IoT
An increasingly mobile and distributed workforce
Bandwidth and connectivity limitations
The high cost of data transit and storage
Evolving data privacy requirements
Verizon has recently deployed and tested a full 5G and edge computing solution. It was used for AI-powered facial recognition. The speed of recognition was much faster compared to the previous cloud-powered solution.
With 5G rollouts finally becoming a reality, automotive manufacturers are starting to recognize that it needs to be an important component of their overall approach to autonomous vehicles. Besides the need for vehicle-to-vehicle (V2V) and vehicle-to-everything (V2X) communication, one other important safety feature will be made possible through 5G and edge computing.
When road conditions prove too difficult for a computing system to deal with, autopilot feature hands the reins over to the driver. However, if a rider is disabled or elderly, they may not be able to take control. Some companies have been experimenting with remote drivers sitting at a simulator taking over vehicle controls. To be able to do that low latency and fast speed provided by 5G and edge computing would be required.
Hyundai was one of the pioneers in testing autonomous vehicles with 5G communication. It is still being done in a controlled environment and those solutions are at least three to four years away from being available to consumers. What is interesting is that Hyundai also used 5G technology to navigate its autonomous passenger flying drones. Is it possible after all that by 2025 we will get not only autonomous vehicles but also flying cars? I will remain hopeful.