Autonomous racing has long captured the public imagination, and voices clamoring for self-driving cars have been strident for well over a decade. The Technology Innovation Institute is all set to participate in the upcoming edition of the Indy Autonomous Challenge at CES 2023 this week, and it is an exciting time for us as our colleagues from the region join other teams of an elite league at the Las Vegas Motor Speedway for the second year. The racing itself is exciting, but how does this technology translate to the real world?
While not fully autonomous yet, today's vehicles are very sophisticated, containing features like adaptive cruise control, automatic transmission, and self-parking modes. We may be a few years behind level three autonomy, but these technology-enabled vehicles significantly reduce concerns about road safety, speeding, and comfort.
For those who think self-driving cars only exist in a Sci-Fi world, think again. By 2025, researchers forecast that we will see approximately eight million autonomous or semi-autonomous vehicles on the road. Ambitious target? According to the American Society of Engineers, we are still at level two of a possible six levels of autonomy. Even with level two, we experience a great deal of comfort and peace of mind driving along high-speed roads, thanks to the lasers, radars, and intelligent sensors in our vehicles.
Artificial Intelligence (AI), of course, plays a major role in the advances of autonomous systems. With so many of today's newer cars featuring an AI-powered advanced driver assist system, we can today say goodbye to parking woes – such cars support parallel parking.
What’s more, there are different types of ADAS like automatic braking, driver drowsiness detection, and lane departure warning. Advances like 360-degree cameras will soon be able to zoom in on specific spots, outside, and even underneath cars. The same cameras will eventually be used along with Machine Learning vision algorithms to enable autonomous navigation and obstacle avoidance in full autonomous modes.
White-label software is set to add a conversational voice and intelligence capabilities to tech products in industries like automotive, video conferencing, health, and air travel. Again, the earliest prototypes are a few years away from commercialization. There are those who would argue that such systems are likely to cause more accidents than they prevent – but such technologies as well as vehicle-to-vehicle communication capabilities - will become crucial in allowing urban transportation management systems to make informed decisions and optimize sustainable mobility.
With AI and machine learning making huge inroads in the automotive sector, the writing is certainly on the wall – full autonomy is only a matter of time – give or take a few races.