If you’ve been following the latest technology news, then you’ve definitely heard of self-driving cars and all of the companies investing in the development of self-driving technology. On the one hand, they are an example of the robot revolution taking over the world. On the other, they are a phenomenon in their own right.
To put it simply, self-driving vehicles are either cars or trucks which have a degree of autonomy in their operations. Fully self-driving cars, which may soon be with us, won’t even need a driver to take control at any point and will therefore completely do away with steering wheels and pedals.
AS we speak, there aren’t any fully-autonomous, legally operating vehicles in the United States. All we have are partially self-driving vehicles. They range from cars most of us have driven with cruise control and lane assistance, to prototypes for independent self-driving vehicles being developed by tech companies.
The technology is still very young, learning to manoeuvre through the wilderness of engineering, regulatory, and political problems facing it. However, even as the field learns to crawl, walk, and eventually run, it is becoming more and more common and promises to disrupt our transportation industry and, by extension, the entire economy.
“Technology experts estimate that in about a decade, we should have level 4 autonomous vehicles being offered at retail prices and filling our roads,” says George Jayden, a technology writer at easy essay.
But let’s not get ahead of ourselves; let’s talk about the different layers of autonomy.
Different Levels of Autonomy
One of the most important features of self-driving cars is the level of autonomy that they have achieved. Different autonomous vehicles are capable of different levels of autonomy, graded on a scale of 0-5.
Level 0 Autonomy
A level 0 vehicle is one in which all of the major systems of the vehicle are controlled by a human being. This is your normal everyday car of the early 2000s and earlier. Most cars with a manual gearbox fall under this category.
Level 1 Autonomy
A level 1 vehicle is one in which certain systems are controlled by the car. The caveat is that they are not controlled simultaneously. For example, a level 1 vehicle can either engage cruise control or assisted braking at a time, but not both at the same time. Most production cars today fall under level 1 autonomy.
Level 2 Autonomy
A level 2 vehicle is one in which at least 2 major functions are controlled by the car simultaneously. This is the key difference between a level 2 vehicle and a level 1 vehicle. For example, a level 2 vehicle can take control of both steering and acceleration at the same time, with no assistance from a human. Tesla’s Autopilot enabled vehicles are level 2 vehicles.
Level 3 Autonomy
A level 3 autonomous vehicle can manage all critical driving functions under certain special conditions. They will, however, expect the driver to step in and take control when alerted. Audi A8’s Traffic Jam Pilot is an example of level 3 autonomy. The technology allows your Audi to take over in traffic. However, it will alert you to take control in most other situations.
Level 4 Autonomy
A level 4 vehicle is fully autonomous in most situations except the most extreme. It is really a continuation of the versatility and adaptability achieved at level 3. Such vehicles should be able to handle the most complex driving tasks in just about any situation. However, the human will be required to take over in the most extreme situations, such as extreme weather. Google’s Waymo is an example of such a vehicle.
Level 5 Autonomy
A level 5 vehicle is one which is fully automated. It does not require human intervention and probably won’t even include a steering wheel and pedals. It can carry out all driving tasks, no matter what the complexity or environment. There are currently no vehicles that have achieved this level of autonomy.
To learn more about each of these levels and the technology that makes them possible, you can read essays about self-driving cars at Best Essay.
How do Self Driving Vehicles work?
Because of the fact that the technology is still young, many different approaches to the engineering challenges involved have been formulated. There are many different players in the niche, including Tesla, Uber, Google, and other large companies, as well as a slew of startups capitalizing on different aspects of the ecosystem.
The different implementations vary, but many of the ideas are the same at the core. For example, all self-driving vehicles seek to create a map of their surroundings and store it internally, using it to navigate the external world. They collect data on their surroundings using a wide array of external sensors. Google’s prototype, for example, uses cameras, radar, and lidar (like radar, except with light instead of radio waves). Uber’s prototypes use 64 laser beams coupled with sensors of other types to build the internal map. Tesla’s vehicles use only high-resolution cameras.
There is wide debate about what the perfect set of sensors should be and what technologies are best. There are tradeoffs for each of radar and lidar, for example. While radar is better for greater distances and in more extreme weather, lidar is better at resolution. Cameras are better than both but suffer visibility issues in extreme environments, just like the human eye. Another challenge is how expensive these sensors are. Lidar, for example, costs about $75k a unit, which makes mass production of self-driving vehicles unfeasible. For now, tech companies are finding the perfect mix of sensors and finding ways to make them cost-effective.
Once the data is in, it is handled by software, primarily machine learning algorithms that use that data to determine what lies outside and around the vehicle. A path will then be plotted and instructions will be sent to the actuators that control such things as steering, braking, and acceleration.
Another distinction in self-driving vehicles is how ‘connected’ they are. This is a reference to their ability to communicate with infrastructure, other vehicles, and even human beings on the road. Allowing for connectivity can drastically improve the ability of self-driving cars to navigate their surroundings with ease. 5G technology is one of the technologies that promise to make this kind of connectivity possible.
Do they really work? Challenges and important questions
- The challenge of safety – Safety is perhaps the greatest challenge with self-driving cars. Fully automated vehicles will arguably be safer than human-driven ones. After all, machines are much better at following rules than humans, and less likely to commit errors. However, the vehicles we have today are far from fully automated and adoption depends on trust. Any accidents caused by self-driving vehicles will undermine that trust. Due to their reliance on software, cybersecurity is another safety concern.
- The challenge of equity – Self-driving vehicles will make it easier to transport people who cannot drive. However, they could also put a lot of drivers out of a job.
- The question of the environment – Self-driving vehicles coupled with gasoline are not good for the environment. However, if they are fully electric and the electricity grid is clean, they could cause a significant drop in transport emission.
Self-driving vehicles really are the future. However, before that future is realized, it is important that the technologies involved mature and the challenges posed are sufficiently explored and solved. Till then, we will be excited to see where the technology goes.
Michael Gorman is a highly skilled freelance writer and proofreader from the UK who currently works as an essay writer at a dissertation service. He not only writes educational and insightful essays but is also an essay reviewer who seeks to help people improve their writing skills. Feel free to contact him via Facebook or check his Twitter.