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Self-driving cars will rely on cloud computing to communicate with other devices.
Self-driving cars will rely on cloud computing to communicate with other devices.
( Source: gemeinfrei / Pexels)

CLOUD COMPUTING The role of cloud computing in autonomous driving

Author / Editor: Jamie Thomson / Isabell Page

Cloud computing is a network of remote servers that are hosted on the internet to store, manage, and process data. It’s a disruptive technology that has had a significant impact on many sectors, including the automotive industry.

Data generated from in-car sensors and other embedded smart devices can be processed using cloud platforms to enhance the efficiency, safety and security of self-driving vehicles.

Perhaps the most well-known example of automakers using cloud computing is Tesla’s Model S, where a digital interface acts as the car’s dashboard. By using the cloud to process vehicle data, Tesla can assist drivers in real-time and fix any issues remotely using software-over-the-air updates. The model S also supports third-party apps, which enhance the car’s operation. Similarly, Ford’s partnership with Microsoft Azure enables the automaker to effectively manage the data generated by its electric vehicles and to provide automated updates to models like the Mustang Mach-E. More recently, the two companies announced that they were exploring how quantum algorithms can help improve urban traffic congestion and develop a more balanced routing system.

Cloud computing in today’s connected cars

Until we have a more advanced infrastructure to support autonomous vehicles on public roads, cloud computing will remain an underused resource in the transport and automotive industries. Currently, it’s primary use is in GPS and car infotainment systems, although some manufacturers are beginning to use the cloud in more complex ways.

Tesla, for example, was the first car company to apply software-over-the-air updates to its Model S vehicle, enabling features like cruise control to be added remotely. Soon after, Mercedes started updating its SL roadster using over-the-air updates with non-critical features like mirrored apps.

Recently, Audi has started using cloud computing to carry out real-world testing for its simulations. By partnering with Microsoft Azure, Audi has all the processing power and storage space it needs to test its new features. The Audi A8, for example, uses several cameras to capture its surroundings and monitor driving behaviour. It also has radar sensors that are used in its land departure warning system, braking assist and adaptive cruise control.

The cloud and self-driving cars

Autonomous vehicles will rely heavily on cloud computing to enable them to communicate with other vehicles and devices. The amount of data that will be gathered, managed and processed by self-driving cars will require a huge amount of secure storage space that only the cloud can provide.

Through cloud computing, self-driving cars will be able to communicate with one another to make public roads safer, update traffic conditions and produce up-to-date road maps. Passengers will arrive at their destinations quicker through positioning and navigation technologies, all the while, connected to the cloud. As software-over-the-air updates become standard, the need for vehicles to physically visit the showroom for upgrades will be eliminated. Maintenance checks could be carried out remotely with sensors providing performance data and alerting the owner when it’s time to schedule upgrades.

Improving road safety

Cloud computing will provide autonomous vehicles with real-time access to data that can be used to make rapid decisions that will make our roads safer. When used in combination with artificial intelligence, vehicles will be able to react quickly to road conditions, adjusting their speed and braking distance. They’ll also be able to re-route when obstacles cause congestion. In order process this data, autonomous vehicles will need a reliable infrastructure with low latency and instant access - all of which can be provided by cloud platforms.

Volvo, for example, is using cloud technology for many of its connected car safety features. Its forthcoming highway pilot feature uses the cloud in combination with LiDAR sensors, which will enable the company to carry out software-over-the-air updates for autonomous highway driving. The cloud will also be used to gather data from its driver monitoring cameras, which will allow the car to intervene when an intoxicated or distracted driver takes the wheel. Volvo has also recently partnered with Ericsson’s Connected Vehicle Cloud platform to develop its connected car digital services. The partnership sees Volvo advancing services like automation, telematics, fleet management and navigation, all of which contribute to safer public roads.

Addressing security concerns

Large amount of data inevitably create concerns over security. With cloud computing acting as an enabler for many connected technologies, platforms will need to be reliable and secure. For example, if a safety feature such as a speed cap was to fail on a vehicle due to an unreliable cloud, the consequences could be life-threatening.

And with greater connectivity comes greater risk. Cloud platforms that host huge amounts of data could become the target of cyber attacks, which could impact an entire autonomous infrastructure. In short, cloud infrastructures need to be built with security as the number one priority.

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