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What Is Self Driving Car?: Driverless

Driverless Car

A driverless car (sometimes called a self-driving car, an automated car or an autonomous vehicle) is a robotic vehicle that is design to travel between destinations without a human operator. To qualify as fully autonomous, a vehicle must be able to navigate without human intervention to a predetermined destination over roads that have not been adapted for its use.

Companies developing and/or testing driverless cars include Audi, BMW, Ford, Google, General Motors, Volkswagen, and Volvo. Google’s test involved a fleet of self-driving cars — six Toyota Prii and an Audi TT — navigating over 140,000 miles of California streets and highways. A single accident occurred during one of the infrequent occasions when a human was driving. Another test of over 1000 miles was complete successfully with no human intervention.

Here’s how Google’s cars work:

  • The “driver” sets a destination. The car’s software calculates a route and starts the car on its way.
  • A rotating, roof-mounted LIDAR (Light Detection and Ranging – a technology similar to radar) sensor monitors a 60-meter range around the car and creates a dynamic 3-D map of the car’s current environment.
  • A sensor on the left rear wheel monitors sideways movement to detect the car’s position relative to the 3-D map.
  • Radar systems in the front and rear bumpers calculate distances to obstacles.
  • Artificial intelligence (AI) software in the car is connected to all the sensors and has input from Google Street View and video cameras inside the car.
  • The AI simulates human perceptual and decision-making processes and controls actions in driver-control systems such as steering and brakes.
  • The car’s software consults Google Maps for advance notice of things like landmarks and traffic signs and lights.
  • An override function is available to allow a human to take control of the vehicle.

Self-Driving Cars Explained

Self-driving vehicles are cars or trucks in which human drivers are never require to take control to safely operate the vehicle. Also known as autonomous or “driverless” cars, they combine sensors and software to control, navigate, and drive the vehicle.

Currently, there are no legally operating, fully-autonomous vehicles in the United States. There are, however, partially-autonomous vehicles—cars and trucks with varying amounts of self-automation, from conventional cars with brake and lane assistance to highly-independent, self-driving prototypes.


How they work

Various self-driving technologies are developed by Google, Uber, Tesla, Nissan, and other major automakers, researchers, and technology companies.

While design details vary, most self-driving systems create and maintain an internal map of their surroundings, based on a wide array of sensors, like radar. Uber’s self-driving prototypes use sixty-four laser beams, along with other sensors, to construct their internal map; Google’s prototypes have, at various stages, used lasers, radar, high-powered cameras, and sonar.

The software then processes those inputs, plots a path, and sends instructions to the vehicle’s “actuators,” which control acceleration, braking, and steering. Hard-coded rules, obstacle avoidance algorithms, predictive modeling, and “smart” object discrimination (ie, knowing the difference between a bicycle and a motorcycle) help the software follow traffic rules and navigate obstacles.

Partially-autonomous vehicles may require a human driver to intervene if the system encounters uncertainty; fully-autonomous vehicles may not even offer a steering wheel.

Self-driving cars can be further distinguished as being “connected” or not, indicating whether they can communicate with other vehicles and/or infrastructure, such as next-generation traffic lights. Most prototypes do not currently have this capability.


The costs and benefits of self-driving cars are still largely hypothetical. More information is require to fully assess how they’ll impact drivers, the economy, equity, and environmental and public health.

Safety is an overarching concern. Many thousands of people die in motor vehicle crashes every year in the United States (more than 30,000 in 2015); self-driving vehicles could, hypothetically, reduce that number—software could prove to be less error-prone than humans—but cybersecurity is still a chief concern.

Equity is another major consideration. Self-driving technology could help mobilize individuals who are unable to drive themselves, such as the elderly or disabled. But the widespread adoption of autonomous vehicles could also displace millions of Americans employed as drivers, negatively impact public transportation funding. And perpetuate the current transportation system’s injustices.

Environmental impacts are a serious concern and a major uncertainty. Accessible, affordable.And convenient self-driving cars could increase the total number of miles driven each year. If those vehicles are powered by gasoline, then transportation-related climate emissions could skyrocket. If, however, the vehicles are electrified—and paired with a clean electricity grid—then transportation emissions could drop, perhaps significantly.

To the extent that electrified self-driving cars enable more shared rides. (for example, through services such as Lyft or Uber), emissions could drop even further.

The Union of Concerned Scientists has worked on transportation-related policy issues for decades,  and infrastructure. In February 2017 we released a policy brief that outlines the challenges and benefits of self-driving technology. And that includes seven principles for policymakers, companies, and other stakeholders to use as guides.

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