Data Science Drives the Future of Autonomous Cars

Posted 2017-05-04T Posted by Tom

Artificial Intelligence has seen a rapid advancement of use in a host of industries, not least the automotive field, where the benefits of autonomous cars continue to soar in the quest to convert humans from drivers to passengers. The Analyst company, Gartner, has predicted a mammoth increase in internet connected cars in the next few years and suggests that there will be at least 250 million such vehicles on the road by 2020 and that production of these models will increase from 21 million in 2017 to 61 million by 2020. In order to do this, manufacturers will demand the skills of data scientists to develop the technologies for automated driving, telematics and mobility needs. Data scientists have been key to unleashing the potential and incrementing the successful marriage between AI and the automotive industry. With a strong likelihood of the eradication of driving tests thanks to the introduction of truly autonomous cars in the near future, data scientists can be credited with one of the most innovative technological advancements of the modern age.

Exciting new developments in technology allow computers to effectively teach themselves and this will enhance the potential of AI as well as the rate at which it is introduced to daily living, in particular, in the ways in which we drive. The Huffington Post recently offered further insight into AI developments in automotives through an interview with subject expert, author Vivek Wadhwa, who explained:

“Advances in a new form of AI called machine learning, are allowing the software to program itself. The computer is taught what to learn and how to learn and makes its own decisions. These are modeling the human mind itself using techniques similar to our learning processes. Before, it could take millions of lines of computer code to perform tasks such image recognition—which is needed for self driving cars. Now it can be done in hundreds of lines. All that is required is a large number of examples so that the computer can teach itself”

A Brief history of AI in Automotives

The progression of AI development in automation has been relatively steady until now, though rapid progression is not easy to see as recently reported by Wired, “Ford recently tripled its investment in its autonomous vehicle fleet”. The world’s largest car names are more eager than ever to utilise AI and machine learning in order to bring autonomous driving to mainstream travel as swiftly as possible.

Autonomous cars may seem like a futuristic prospect but these developments have long been in the pipeline. In 1977, Tsukuba Mechanical Engineering developed an autonomous passenger vehicle that was capable of understanding road markings whilst travelling at almost 20mph, largely thanks to the two attached vehicle-mounted cameras. Just ten years later, the German engineer Ernst Dickmanns, designed “dynamic vision,” which allowed the innovative camera technology to filter out unnecessary sounds focus on the relevant information and objects only and up to impressive speeds of 60mph. This technology is used in modern designs to help identify potential hazards and their whereabouts.

For the last two decades, the advancement of AI technology in automation has been most apparent in drone technology. One of the most famous examples, General Atomics’ Predator, is an autonomous plane that has travelled over worldwide hotspots for up to 14 hours at a time and has done so for 20 years. The technologies used in these models have been and continue to be adapted for use in cars to ensure the safety and availability of autonomous travel at all times, including radars that can navigate through smoke and thermal imaging cameras that allow for night travel.

In 2015, The University of Michigan opened MCity, its 32-acre Mobility Transformation Center. With leading minds interested in autonomous cars, including private industries, global governments and academic minds, the future of automation is likely to arrive swiftly. In a recent article, AI expert, Andrew NG, explained that the innovative new vehicles “will join human drivers on our roads sooner than most people think.”

Benefits of AI in Automation

With human incompetence being blamed for a number of road accidents, the necessity for self-driven vehicles becomes more apparent and although we may be a long way from eradicating human control over driving, we inch ever closer. The Independent recently reported that “US government research predicts that driverless vehicles will lead to an 80 per cent decline in the number of car crashes by 2035” and coupled with congestion solutions, pollution reduction and personal safety considerations, driverless cars bring a wealth of benefits to the future of travel.

Speaking with the Huffington Post, Vivek Wadhwa is keen to outline the numerous benefits of AI in automotives, arguing that:

“We will be far more productive, distance will no longer be a barrier—so we can live 150 miles away and still get to work in time, and accidents will largely be a thing of the past. Also the disabled will no longer struggle to find transportation, mothers will be able to send their children to school without worrying about them reaching safely, and everyone will be able to afford to be mobile—because of the reliability, safety, and lower costs of these technologies. Also, women and children will never worry about getting a cab ride late at night”.
It’s hard to disagree with Wadhwa’s viewpoint, there are an array of benefits to autonomous driving. Once the technology is accessible and fully developed and based on the current investment and backing of major manufacturers, autonomous cars are the future and are set to dictate the way we travel, infrastructure design, safety awareness and the imperativeness of data science in daily economic and domestic life.

The Involvement of Data Scientists in Present Autonomous Driving Developments

Huge advancements are being made across the automotive sector, driven by high profile new entrants to the market and the talent and expertise that they bring with them such as Tesla and Baidu. The rapid developments in this sector, coupled with the impressive minds of leading data scientists is encouraging automotive giants to partner up with tech firms in order to establish a share of the successes and be part of the revolution.

A partnership with Microsoft and Toyota which sees the Japanese car manufacturer authorised to use the computing powerhouses’ new patent licensing program in connected vehicles is one of the most exciting in this field. Data scientists are at the backbone of these advancements, as considered by ZDNet “All these technologies would help anticipate when cars need maintenance, connect drivers to roadside assistance, and power tomorrow's infotainment systems”. Microsoft, along with giants such as Google and Intel are at the forefront of autonomous driving developments through their own creation of technologies to support internet-connected vehicles.

Although there may be no definitive date for this technological ambition, as highlighted by Idalab “examples for data science applications are manifold and the more success stories emerge, the more will companies be willing to invest time and money to pursue those opportunities”. There are still several years between us and fully autonomous cars, in excess of a decade according to Gartner Hype Cycle, and the only way that this goal will be realised is through utilising the talent of data scientists. The scientists have the capability to help engineer and code machine learning technology that will cement the final successes in autonomous travel.

Where are the Developments heading?

It seems clear that the direction of car design and manufacturer is geared up towards a fully autonomous future. With government backing, the utilisation of some of the world’s leading data science talent and interest and funding from manufacturing names, driverless cars seem to be the inevitable outcome. The Independent recently reported a joint venture between the German engineering firm Bosch and leading car manufacturer Daimler who aim to introduce autonomous vehicles to city roads by 2020. The companies plan to develop a taxi like fleet of vehicles which can be ordered by customers for single journeys, as opposed to owned by households for constant use. That said, this huge leap into autonomous driving is certain to breed further interest and support for driverless travel.

With Germany and the US hungry to embrace the most modern automotive evolutions, the UK has taken steps to maintain their position at the forefront of the future. The Telegraph further reports that in 2016, the Chancellor, “Mr Osborne scrapped rules that prevented autonomous driving on motorways in an attempt to make the UK a global leader in a market that could be worth £900bn worldwide by 2025, while around £100m in funding has already been set aside for research into the area”. Trials of driverless cars were also carried out by Nissan on London roads in March this year, the first such trials to be conducted outside of America, further cementing the UK’s commitment and support of fully autonomous cars. For those who can, namely world leading countries and manufacturing and design powerhouses, not being involved in this rapidly progressive arena seems inexplicable.

So enthralled are the masses by driverless cars that suggestions have been made regarding F1 driving. Recognised as one of the world’s most dangerous sports for competitors, Which recently reported that Roborace, a driverless racing offering, holds the potential to become one of the most exhilarating and groundbreaking sports. They detail that “The concept is a racing competition in the style of Formula E with a fleet of identical driverless cars designed by futuristic automotive designer, Daniel Simon. Hardware includes cameras, radars, and a Nvidia Drive PX2 “brain” sitting alongside the electric motors and ‘regular’ formula E mechanics. The software, however, is an open AI platform. The intention is a race with a field of the identical Robocars with separate data analytics, data science and engineering teams determining the AI algorithms for each car”. Exciting as this all sounds and undeniably revolutionary as this may be, whether autonomous driving is embraced by F1 fans is less likely. The human element of sport is readily recognised as the crucial inclusion - fans find it much easier to champion a person than they do a computer. If we look at Roborace as a separate entity, there’s arguably a platform for a highly successful, captivating and exciting sport but the likelihood of Roborace replacing F1 and autonomous cars replacing driver controlled models is nominal at best.

The Wrap Up

The future of travel seems to be heading towards fully autonomous cars, backed by some of the leading industries and minds across the globe and propelled by data scientists. There have been rapid and exciting advances made in this field and the pace at which progression continues is astonishing. That said, despite mammoth developments in automated cars, we’re still in the early stages and we’ve barely scratched the surface of introducing AI to vehicles. The pace of evolution in this area and the joining of names such as Toyota and Daimler promises further and fast developments in automated inclusions and AI control. With greater opportunities for data scientists to develop their career and encouraging and hungry demand for their skills, this is an industry that guarantees to flourish.

Thanks to trailblazers such as Tesla, Faraday Futures, Baidu and a variety of tech start-ups, the futuristic automated cars that have been so eagerly anticipated are now a realistic and impending reality. The realisation of autonomous driving can also largely be credited to data scientists and their ability to test boundaries, overcome obstacles and work with exciting commitment to the future of technology. Although the car industry is in the early stages of AI, the growth is rapid and exciting and means that the data scientist talent pools need to be quickly refilled to accommodate the demand. With leading automotive tech companies poaching data scientists and expanding their data science teams so quickly, the call for new minds is increasingly loud, offering huge opportunities to many. In order to maintain the pace, successes and cement the future of AI in cars, the industry relies on data scientists to drive us into the future.

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