The Impact of Autonomous Cars on Data Centers

By: Ernest Sampera on August 11, 2020

Few tech innovations of the 21st century have garnered as many headlines or drawn as much public attention as autonomous cars. For the better part of the last decade, various auto manufacturers and tech companies have been locked in a fierce competition to get the first viable self-driving vehicle to market. While there have been many notable successes and real-world, “on-the-road” testing has been underway for quite some time, the self-driving revolution keeps running into various delays and unforeseen obstacles.

But the figure isn’t here yet. To understand why autonomous cars aren’t yet a fixture of every neighborhood in the US, it’s important to look at the challenges associated with self-driving technology and the limitations that researchers and manufacturers continue to face.

So...Where Are All the Self-Driving Cars?

Despite rather optimistic projections by many media outlets and tech companies, the widespread rollout of self-driving vehicles has yet to occur. In fact, a recent report by researchers at MIT found that it could be another ten years before fully autonomous vehicles arrive in substantial numbers. While most skeptical evaluations focus on technological and social barriers, the study identified cost as one of the most significant obstacles.

Apart from the self-driving software itself, autonomous vehicles will require tremendous investments in IT infrastructure and usher in a whole new era of regulatory oversight that has yet to be fully defined. Without the high-speed connectivity and low latency of 5G wireless networks, for example, it will be difficult to deploy self-driving cars in significant numbers.

Data Demands of Autonomous Cars

Thanks to the wide range of sensors equipped on these vehicles, each autonomous car is expected to generate massive quantities of data. Rather than focusing on the raw data totals (about 4,000 GB of data generated per hour of driving), it’s helpful to think about that total comparatively. Each vehicle will generate the same amount of data as 3,000 people, so rolling deploying just one million self-driving cars would be like adding three billion people’s worth of data.

A million autonomous vehicles may sound like a lot, but a recent Statista report estimates that one in ten cars in the US will be fully automated by 2030. Considering that there were 273.6 million vehicles registered in the US in 2018, that estimate suddenly doesn’t seem so conservative.

Data Centers, Vehicular Edge Computing, and IoT Cars

Managing all of this data will be an incredible challenge, both for the makers of autonomous cars and the people managing the infrastructure that supports them. Traditional centralized networks will be insufficient to the data management needs of the self-driving future. In a world where vehicles will need to be communicating continuously with each other while also transmitting and gathering information about their surroundings, traffic patterns, weather conditions, and operational status, there simply isn’t enough time to wait for vital data to be processed.

That’s why a combination of vehicular edge computing and Internet of Things (IoT) technology will be absolutely critical to making self-driving vehicles a viable reality. In many ways, autonomous cars will be the ultimate IoT device, generating and collecting data while processing information to make split-second decisions that could save lives. Machine to machine (M2M) communication will be a vital part of this process, as vehicles will need to take in and analyze data from other vehicles to gain a more complete picture of their operational environment.

Much of the data being gathered will be unstructured and noisy, with little impact on immediate decision making. However, it could also contain important performance insights that can help manufacturers improve their products and perform vital preventative maintenance functions. A network of edge data centers positioned in key locations will form an important backbone of nationwide autonomous vehicle infrastructure.

Thanks to edge data centers, high-powered analytics platforms will be able to process unstructured data gathered by autonomous vehicles with minimal latency. These facilities can relay some data to more distant hyperscale data centers, but they can also provide extra processing power for localized networks.

Why Driverless Car Technology Needs Smart Infrastructure

Self-driving vehicles aren’t going to get very far without a smart city infrastructure in place to support them. Urban areas are already rolling out innovative IoT-enabled technology that will help them to transform the way they leverage data to improve services for their residents. As 5G technology rolls out, the available bandwidth and computing power available to autonomous vehicles will increase tremendously, opening up a wide range of possibilities.

Data centers are already playing a key role in enabling this transformation. Between edge data center locations in emerging growth markets and the use of modular micro data centers to extend connectivity wherever it’s needed, smart cities are finding new ways to expand and improve data center services to enable dynamic business growth.

Steering Towards the Future with vXchnge

With multiple data centers located in high-potential markets across the country, vXchnge is excited to be in a position to empower digital transformation when it comes to autonomous vehicles and smart city infrastructure. Our data centers are engineered for perfection, allowing us to deliver the superior uptime reliability that will be necessary to support vehicular edge computing. And thanks to our low-latency connectivity, vXchnge data centers can help IoT networks better manage the massive amounts of data flowing in from fleets of autonomous vehicles.

To learn more about how vXchnge colocation services are redefining edge computing networks, talk to one of our data center experts today.

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