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The biggest challenge car makers face in delivering data-driven UX

  • September 18, 2017 /
  • by Claudio M. Camacho

“Big data processing in a fast and seamless way is one of the main challenges for car makers when building the cars of the future.”

Unlike the past 100 years, cars of today have become gadgets. People are starting to choose a vehicle for its software features and services, instead of physical or mechanical features like horsepower and design. It’s the software inside that’s shaping the future of driver and passenger user experience. One of the most discussed “features” of modern cars that immensely affects the user experience is autonomous driving.

The aim of autonomous driving is to make the passengers’ life much easier. But what exactly does that mean? It boils down to minimizing human-machine interactions, setting passengers free to do whatever they like during the travel time. Despite this fundamental understanding, car manufacturers, Tier-1 suppliers, and software providers are still struggling to create a great user experience that is both seamless and meaningful for passengers. So what’s the root of the problem?

The data challenge

Autonomous cars must know the conditions outside the car as well as inside. In fact, they need deep understanding to make intelligent decisions based not only on traffic conditions, but also on passenger preferences, such as seat configurations, interior lightning, temperature, music, notifications, and more. In order for the car to do all that – and genuinely enhance the user experience – the car needs artificial intelligence (AI) capabilities and machine learning (ML). These capabilities allow the car to learn from and adapt to different passenger reactions and changing situations from day to day.

AI and ML require extremely efficient computing, and it’s no wonder why those tasks are often performed on a cloud server instead of on phones or other small devices. In addition to computing resources, AI and ML require vast amounts of data to draw conclusions and build smarter decision-making mechanisms. Big data processing in a fast and seamless way is one of the main challenges for car makers when building the cars of the future.

If data-driven AI and ML are the key to powering the best user experiences of future cars, why can’t cars simply use cloud computing services and serve passengers already today? The main problem here is bandwidth. A fully autonomous car can generate up to 80 TB of data every day. That means over 3 TB of data every hour, or 1 GB every second. On the connectivity side, state-of-the-art technologies such as 5G are promising 100 MB to 1 GB/s in extremely ideal conditions. And ideal conditions means that the device is in a well-connected city and not moving at all. However, as we know, cars are constantly moving and statistically speaking, outside city limits for most of the time. Under these conditions, the best internet speeds drop to well below 10 MB per second.

The numbers above show that a car could only upload and download about 10% of its collected data, and that’s in the hypothetical case that 5G was fully deployed and conditions were nearly perfect. In the real world, it means fully autonomous cars can’t rely on the cloud for all their functions until higher performance technologies are in place.

Cars need reliable edge storage

That’s why all car manufacturers are heavily relying on edge storage – hardware and software built into the car, sitting between the car sensors and the cloud, that stores all the necessary data to enable the car to make smart decisions.

We are at an unprecedented moment in the history of cars, when the machine will relieve humans of the effort associated with driving, making journeys easier and more enjoyable. Yet, there are huge challenges (and opportunities) in processing the data required to build better user experiences and human-machine interactions. Solving these challenges brings enormous business potential for companies working around data, AI, and machine learning.

By 2030, the entire market cap around data for vehicles could be at $1.5 trillion. That figure demonstrates the level of importance for recording and processing all the data from the sensors properly, with the ultimate goal of bringing state-of-the-art user experience to passengers.

Final thoughts

If you thought the cloud was here to solve every connected problem, you might have to wait a long time to see fully autonomous cars benefiting from it. Instead, edge storage has become a critical component that all car makers are investing in. By putting resources into reliable data storage, car makers can ensure the user experience will be both seamless and meaningful.


Car makers and Tier-1 suppliers – see how we can make your edge data handling and storage faster, more secure, and more reliable.

Tuxera automotive solutions

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Claudio M. Camacho
Claudio is Head of Marketing at Tuxera. He has over 8 years of experience leading international teams responsible for business development and strategic marketing at technology-centric companies. Claudio loves working in the global tech industry, specially with software products, and he's extremely determined and results-driven. His motto: "if you don't measure it, you can't improve it."