For the past decade, manufacturers and governments all over the world have been preparing for the adoption of self-driving cars—with the promise of transformative economic development.
As autonomous vehicles become more of a looming certainty, what will be the wider impacts of this monumental transition?
Which Countries are Ready?
Today’s interactive visual from Aquinov Mathappan ranks countries on their preparedness to adopt self-driving cars, while also exploring the range of challenges they will face in achieving complete automation.
The Five Levels of Automation
The graphic above uses the Autonomous Vehicles Readiness Index, which details the five levels of automation. Level 0 vehicles place the responsibility for all menial tasks with the driver, including steering, braking, and acceleration. In contrast, level 5 vehicles demand nothing of the driver and can operate entirely without their presence.
Today, most cars sit between levels 1 and 3, typically with few or limited automated functions. There are some exceptions to the rule, such as certain Tesla models and Google’s Waymo. Both feature a full range of self-driving capabilities—enabling the car to steer, accelerate and brake on behalf of the driver.
The Journey to Personal Driving Freedom
There are three main challenges that come with achieving a fully-automated level 5 status:
- Data Storage
Effectively storing data and translating it into actionable insights is difficult when 4TB of raw data is generated every day—the equivalent of the data generated by 3,000 internet users in 24 hours.
- Data Transportation
Autonomous vehicles need to communicate with each other and transport data with the use of consistently high-speed internet, highlighting the need for large-scale adoption of 5G.
- Verifying Deep Neural Networks
The safety of these vehicles will be dictated by their ability to distinguish between a vehicle and a person, but they currently rely on algorithms which are not yet fully understood.
Which Countries are Leading the Charge?
The 20 countries were selected for the report based on economic size, and their automation progress was ranked using four key metrics: technology and innovation, infrastructure, policy and legislation, and consumer acceptance.
The United States leads the way on technology and innovation, with 163 company headquarters, and more than 50% of cities currently preparing their streets for self-driving vehicles. The Netherlands and Singapore rank in the top three for infrastructure, legislation, and consumer acceptance. Singapore is currently testing a fleet of autonomous buses created by Volvo, which will join the existing public transit fleet in 2022.
India, Mexico, and Russia lag behind on all fronts—despite enthusiasm for self-driving cars, these countries require legislative changes and improvements in the existing quality of roads. Mexico also lacks industrial activity and clear regulations around autonomous vehicles, but close proximity to the U.S. has already garnered interest from companies like Intel for manufacturing autonomous vehicles south of the border.
How Autonomous Vehicles Impact the Economy
Once successfully adopted, autonomous vehicles will save the U.S. economy $1.3 trillion per year, which will come from a variety of sources including:
- $563 billion: Reduction in accidents
- $422 billion: Productivity gains
- $158 billion: Decline in fuel costs
- $138 billion: Fuel savings from congestion avoidance
- $11 billion: Improved traffic flow and reduction of energy use
Transportation will be safer, potentially reducing the number of accidents over time. Insurance companies are already rolling out usage-based insurance policies (UBIs), which charge customers based on how many miles they drive and how safe their driving habits are.
Long distance traveling in autonomous vehicles provides a painless alternative to train and air travel. The vehicles are designed for comfort, making it possible to sleep overnight easily—which could also impact the hotel industry significantly.
- Real Estate
An increase in effortless travel could lead to increased urban sprawl, as people prioritize the convenience of proximity to city centers less and less.
With the adoption of autonomous vehicles projected to reduce private car ownership in the U.S. to 43% by 2030, it’s disrupting many other industries in the process.
How Self-Driving Cars “See” the World
This video breaks down the complex technology allowing a new generation of self-driving cars to view the world around them.
How Self-Driving Cars “See” the World
Modern cars bear little resemblance to their early ancestors, but the basic action of steering a vehicle has always remained the same. Whether you’re behind the wheel of a Tesla or a vintage Model T, turning the wheel dictates the direction of movement. This simple premise, which places humans at the center of control, may be ripe for disruption as tech giants and car companies race toward a future that would render human-controlled vehicles obsolete.
How does this next generation of self-driving cars “see” the road? Today’s video from TED-Ed explains one of the mind-bending innovations making autonomous vehicles a reality.
Eye of the Laser
Safely getting a vehicle and its passengers from point A to B is no simple matter.
First, weather and time of day can create a wide variety of challenging situations, affecting things like visibility, braking distances, or speed. Next, other vehicles, bikes, and pedestrians are constantly moving through the transportation network, sometimes in unpredictable ways. To further complicate matters, the road network is rarely in optimum form. Road lines fade and construction can throw ambiguous detours into the mix.
Sensing and analyzing the world at a granular level is crucial in making self-driving cars a viable transportation option. To solve this problem, new generations of autonomous vehicles are using photonic integrated circuits, as well as light detection and ranging (LiDAR) to generate an extremely nuanced picture of the road ahead.
How self-driving cars see the world. (Source: Hesai)
LiDAR – which is related to RADAR – uses short laser pulses to sense the depth and shape of objects. Essentially, scattered bursts reflect off objects around the vehicle, painting a detailed 3D picture of its surroundings. LiDAR’s depth resolution is so accurate that it could eventually see details at the millimeter scale.
A Dissenting Opinion
While most companies in the autonomous vehicle space have fully embraced LiDAR, Tesla has a divergent point of view. The company employs a combination of GPS, cameras, and other sensors to help its cars visualize the world.
LiDAR is a fool’s errand. Anyone relying on LiDAR is doomed.
– Elon Musk
Society and Self-Driving Cars
While companies like Uber and Waymo determine the functional mechanics of self-driving cars, the rest of society is left to ponder how this new technology will affect employment, privacy, and personal autonomy.
In the U.S., more than 70% of goods are moved by truck, and over 80% of commuters take a private vehicle to work on any given day. Even partial automation of the nation’s transportation network will have wide-sweeping impacts on the economy.
As AI-powered cars and trucks hit the streets at scale, how cars see the road will be a detail most of us will overlook. The bigger question will be whether we are ready for a society where we’re no longer in the driver’s seat.
The Outlook for Automation and Manufacturing Jobs in Seven Charts
How will technologies such as automation and artificial intelligence end up impacting jobs and the workforce? Here are seven charts that tell the story.
The Outlook for Automation and Manufacturing in Seven Charts
View the high resolution version of today’s graphic by clicking here.
Over the last decade, the prospect of mass automation has seemingly shifted from a vague possibility to an inescapable reality.
While it’s still incredibly difficult to estimate the ultimate impact of automation and AI on the economy, the picture is starting to become a bit clearer as projections begin to converge.
Today’s infographic comes to us from Raconteur, and it highlights seven different charts that show us how automation is shaping the world – and in particular, the future outlook for manufacturing jobs.
The Age of Automation
The precise details are up to debate, but here are a few key areas that many experts agree on with respect to the coming age of automation:
Half of manufacturing hours worked today are spent on manual jobs.
- In an analysis of North American and European manufacturing jobs, it was found that roughly 48% of hours primarily relied on the use of manual or physical labor.
- By the year 2030, it’s estimated that only 35% of time will be spent on such routine work.
Automation’s impact will be felt by the mid-2020s.
- According to a recent report from PwC, the impact on OECD jobs will start to be felt in the mid-2020s.
- By 2025, for example, it’s projected that 10-15% of jobs in three sectors (manufacturing, transportation and storage, and wholesales and retail trade) will have high potential for automation.
- By 2035, the range of jobs with high automation potential will be closer to 35-50% for those sectors.
Industrial robot prices are decreasing.
- Industrial robot sales are sky high, mainly the result of falling industry costs.
- This trend is expected to continue, with the cost of robots falling by 65% between 2015 and 2025.
- With the cost of labor generally rising, this makes it more difficult to keep low-skilled jobs.
Technology simultaneously creates jobs, but how many?
- One bright spot is that automation and AI will also create jobs, likely in functions that are difficult for us to conceive of today.
- Historically, technology has created more jobs than it has destroyed.
- AI alone is expected to have an economic impact of $15.7 trillion by 2030.
Unfortunately, although experts agree that jobs will be created by these technologies, they disagree considerably on how many. This important discrepancy is likely the biggest x-factor in determining the ultimate impact that these technologies will have in the coming years, especially on the workforce.
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