‘Self-driving’ cars are still a long way off. Here are three reasons why
The recent crash of a Tesla car in the United States, in which two people died, has reignited debate about the capabilities and safety of today’s “self-driving” technologies.
Tesla cars include an “autopilot” feature which monitors surrounding traffic and lane markings, and the company is currently rolling out a more advanced “full self-driving” system which promises automatic navigation, stopping at traffic lights, and more.
Investigators say it appears nobody was in the driver’s seat of the vehicle when it crashed. Tesla chief executive Elon Musk has said no self-driving features were in use at the time.
Nonetheless, the tragic incident has raised questions over self-driving technology: how safe is it, and how much attention does it require from
What do we mean by ‘self-driving’?
Experts talk about six levels of autonomous vehicle technology, ranging from level 0 (a traditional vehicle with no automation) to level 5 (a vehicle that can independently do anything a human driver can).
Most automated driving solutions available on the market today require human intervention. This puts them at level 1 (driver assistance, such as keeping a car in a lane or managing its speed) or level 2 (partial automation, such as steering and speed control).
These capabilities are intended for use with a fully attentive driver prepared to take control at any moment.
Level 3 vehicles have more autonomy and can make some decisions on their own, but the driver must still remain alert and take control if the system is unable to drive.
In the past few years, several fatal crashes involving level 2 and level 3 vehicles have occurred. These crashes were largely attributed to human error, and to mistaking these levels of automation for full self-driving capabilities.
Vehicle manufacturers and regulators have been criticized for not doing enough to make these systems more resilient to misuse by inattentive drivers.
The path towards higher levels of automation
For higher levels of automation, a human driver won’t necessarily be involved in the driving task. The driver would effectively be replaced by the AI self-driving software.
Level 4 is a “self-driving” vehicle that has a bounded scope of where and when it will drive. The best example of a level 4 vehicle is Google’s Waymo robotaxi project. Other companies are also making significant progress in developing level 4 vehicles, but these vehicles are not commercially available to the public.
Level 5 represents a truly autonomous vehicle that can go anywhere and at any time, similar to what a human driver can do. The transition from level 4 to level 5, however, is orders of magnitude harder than transitions between other levels, and may take years to achieve.
While the technologies required to enable higher levels of automation are advancing rapidly, producing a vehicle that can complete a journey safely and legally without human input remains a big challenge.
Three key barriers must be overcome before they can be safely introduced to the market: technology, regulations and public acceptance.
Machine learning and self-driving software
The self-driving software is a key differentiating feature of highly automated vehicles. The software is based on machine learning algorithms and deep learning neural networks that include millions of virtual neurons that mimic the human brain.
The neural nets do not include any explicit “if X happens, then do Y” programming. Rather, they are trained to recognize and classify objects using examples of millions of videos and images from real-world driving conditions.
The more diverse and representative the data, the better they get at recognizing and responding to different situations. Training neural nets is something like holding a child’s hand when crossing the road and teaching them to learn through constant experience, replication and patience.