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Google dominates design, testing for self-driving tech

Posted: 17 Nov 2015     Print Version  Bookmark and Share

Keywords:IHS  neural network  AI  machine learning  machine vision 

According to the latest report from IHS Inc., autonomous driving remains to be one of the most prevalent research and development activities within the global automotive industry. This comes as both carmakers and technology companies struggle to put advancements into production and implement them for on-road testing and approvals, stated the market research firm.

IHS revealed that companies such as Google and others are working toward solutions in the autonomous vehicle space, while "car- as-a-service (CaaS)" organisations such as Uber, Lyft and others are set to create disruption and add operational expertise that will significantly influence autonomous vehicle development and consumer consideration in the next decade.

It's well known that self-driving and driverless cars are inevitable. It is only a question of time in bringing various options to market for consumers, and gaining their acceptance.

Evolutionary and revolutionary; diverging paths to autonomy

Two primary research and development strategies to achieve self-driving vehicles are in place today, evolutionary and revolutionary. Most traditional automotive manufacturers are on the evolutionary track with their R&D efforts, continuing along the current path of improving advanced driver assistance systems (ADAS) to partial self-driving, and eventual full self-driving vehicles.

On the other hand, Google leads the revolutionary approach and will have a major impact in the coming years. Uber is also beginning to implement some of its own R&D in this arena, as it works toward solutions for the next stage of its disruptive transportation strategy.

Software is key; Google leads

The key to self-driving cars is a software that can interpret all of a vehicles' sensors and learn to mimic the driving skills and experiences of the very best drivers. Google is the current technology leader in this arena, according to IHS Automotive estimates, which suggest the technology company has invested nearly $60 million so far in autonomous vehicle R&D, at a run rate of nearly $30 million per year.

Unlike traditional vehicle manufacturers, Google also has the ability to leverage adjacent technologies and learnings from its other projects and investments, including robotics, drones and related technologies that help automotive operations, such as neural networks, artificial intelligence (AI), machine learning and machine vision. This provides Google researchers additional expertise not available directly to traditional OEMs.

"No other company has as much relevant technology to advance autonomous driving software," said Egil Juliussen, PhD., senior research director at IHS Automotive and author of the report. Toyota

s early November announcement of a $1 billion, five-year investment in AI, driverless cars and robotics is likely partly due to Google's rapid technology advances.

From this perspective, Google's self-driving car software is performing better than nearly all drivers in the vast majority of traditional driving situations, at least in good weather, according to IHS analysis. However, as it continues its development, Google still must discover and teach its software the "once in a million" events, such as performing under diverse weather conditions, unique roadwork, specific traffic situations and other non-traditional driving situations.

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