Driverless cars not coming anytime soon – Experts verdict

The dream of having self-driving or driverless cars in showrooms and on major roads of the world including Africa may not materialise anytime soon going by latest developments in the auto industry.

Last month, Tesla CEO Elon Musk wrote in a tweet, stated, “Generalised self-driving is a hard problem, as it requires solving a large part of real-world AI. Didn’t expect it to be so hard, but the difficulty is obvious in retrospect.”

Musk is definitely singing a new tone compared to his earlier comment that by 2020, there would be “over a million cars with full self-driving software everything.”

To his surprise, achieving fully autonomous driving is a lot more complicated than one might think. Apart from the countless technological obstacles, other issues that need to be considered are cybersecurity, regulatory restrictions and wider-scale infrastructural necessities, according to a Tuesday August 24 analysis by an online journal, Just Auto.

A professor of urban mobility, Hussein Dia, in an article he contributed to Conversation, an international magazine, notes that self-driving cars are still a long way to come and recalls a recent crash of a Tesla car in the United States, in which two people died, as igniting the debate about the safety of self-driving technologies.

The crash was said to have occurred despite special features in Tesla cars such as autopilot meant for monitoring surrounding traffic and lane markings.

Experts point out that the technology required for fully autonomous vehicles that do not need any human supervision is still not mature enough.

Self-driving or autonomous vehicles are said to require processing power orders of magnitude greater than what is usually found in modern vehicles, banks of expensive sensors with multiple points of redundancy, and an infallible software system that handles the driving task while ensuring the safety of occupants and pedestrians.

Dia talks 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 require human intervention and 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).

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 were largely attributed to human error. Vehicle manufacturers and regulators have thus been criticised for not doing enough to make these systems more resilient to misuse by inattentive drivers.

For higher levels of automation, a human driver will not be involved. 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. But like those being produced ny others, it is 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.

Experts note that the transition from level 4 to level 5, however, is harder than transitions between other levels, and may take years to achieve.

While the technologies required for higher levels of automation are advancing rapidly, producing a vehicle that can complete a journey safely and legally without human input appears to remain a big challenge.

One of the challenges is the self-driving software, which is based on artificial intelligence (AI) and deep learning neural networks that include millions of virtual neurons that mimic the human brain. This is the area in which current science is still lacking.

This process involves the collection of a massive amount of raw data.

Experts note that training neural nets is something like holding a child’s hand when crossing the road and teaching the child to learn through constant experience, replication and patience. The focus will thus lie on developing more brain-like AI.

Chief Technology Officer at Dell, Charles Sevior, says the world is still 10 years away from level 5 autonomy.

Thomas Dannemann, director of product marketing at Qualcomm, appears more optimistic as he predicts that fully autonomous vehicles will hit the road in “the second half of this decade”.

Dia lists three key barriers to be overcome before they can be safely introduced to the market as technology, regulations and public acceptance.

He says in his conclusion, “While it is necessary to test the performance of self-driving software under real-world conditions, this should only happen after comprehensive safety testing and evaluation. Regulators should come up with a set of standard tests and make companies benchmark their algorithms on standard data sets before their vehicles are allowed on open roads.”

He also says, “The public must be involved in decisions regarding self-driving vehicle deployment and adoption. There is a real risk of undermining public trust if self-driving technologies are not regulated to ensure public safety. A lack of trust will affect not only those who want to use the technology, but also those who share the road with them.

“Finally, this incident should serve as a catalyst to bring regulators and industry to establish a strong and robust safety culture to guide innovations in self-driving technologies.”

Autonomous cars are no doubt tomorrow’s transport luxury, but analysts are unanimous in their view that it will take some time before people can have a pleasurable cruise in a self-driving vehicle.

At the moment, human drivers are found to be better than robot drivers. At least people are able to rapidly view the world around them to make the right decisions about the prevailing circumstances. That is not the case with the AI.

“While emergent technology can easily and accurately detect and classify objects, it still can’t mimic the intricate complexities of driving. Autonomous vehicles not only need to detect and recognise humans and other objects but must also interact with, understand and react to how these things behave.

According to a report by verdict.co.uk, while emergent technology can easily and accurately detect and classify objects, it still can’t mimic the intricate complexities of driving.

It adds that autonomous vehicles not only need to detect and recognise humans and other objects but must also interact with, understand and react to how these things behave.