Autonomous Cars

When it comes to AI, one of the most far-reaching areas is autonomous cars. Interestingly enough, this category is not really new. Yes, it’s been a hallmark of lots of science fiction stories for many decades! But for some time, there have been many real-life examples of innovation, like the following:

• Stanford Cart: Its development started in the early 1960s, and the original goal was to create a remote-controlled vehicle for moon missions. But the researchers eventually changed their focus and developed a basic autonomous vehicle, which used cameras and AI for navigation. While it was a standout achievement for the era, it was not practical as it required more than 10 minutes to plan for any move!
• Ernst Dickmanns: A brilliant German aerospace engineer, he would turn his attention to the idea of converting a Mercedes van into an autonomous vehicle…in the mid-1980s. He wired together cameras, sensors, and computers. He also was creative in how he used software, such as by only focusing the graphics processing on important visual details to save on power. By doing all this, he was able to develop a system that would control a car’s steering, gas pedal, and brakes. He tested the Mercedes on a Paris highway—in 1994—and it went over 600 miles, with a speed up to 81 MPH.⁵ Nevertheless, the research funding was pulled because it was far from clear if there could be commercialization in a timely manner. It also did not help that AI was entering another winter.

But the inflection point for autonomous cars came in 2004. The main catalyst was the Iraq War, which was taking a horrible toll on American soldiers. For DARPA, the belief was that autonomous vehicles could be a solution.

But the agency faced many tough challenges. This is why it set up a contest, dubbed the DARPA Grand Challenge, in 2004, which had a $1 million grand prize to encourage wider innovation. The event involved a 150-mile race in the Mojave Desert, and unfortunately, it was not encouraging as the cars performed miserably. None of them finished the race!

But this only spurred even more innovation. By the next year, five cars finished the race. Then in 2007, the cars were so advanced that they were able to take actions like U-turns and merging.

Through this process, DARPA was able to allow for the creation of the key components for autonomous vehicles:

• Sensors: These include radar and ultrasonic systems that can detect vehicles and other obstacles, such as curbs.
• Video Cameras: These can detect road signs, traffic lights, and pedestrians.
• Lidar (Light Detection and Ranging): This device—which is usually at the top of an autonomous car—shoots laser beams to measure the surroundings. The data is then integrated into existing maps.
• Computer: This helps with the control of the car, including the steering, acceleration, and braking. The system leverages AI to learn but also has built-in rules for avoiding objects, obeying the laws, and so on.

Now when it comes to autonomous cars, there is lots of confusion of what “autonomous” really means. Is it when a car drives itself completely alone—or must there be a human driver?

To understand the nuances, there are five levels of autonomy:

• Level 0: This is where a human controls all the systems.
• Level 1: With this, computers control limited functions like cruise control or braking—but only one at a time.
• Level 2: This type of car can automate two functions.
• Level 3: This is where a car automates all the safety functions. But the driver can intervene if something goes wrong.
• Level 4: The car can generally drive itself. But there are cases in which a human must participate.
• Level 5: This is the Holy Grail, in which the car is completely autonomous.

The auto industry is one of the biggest markets, and AI is likely to unleash wrenching changes. Consider that transportation is the second largest household expenditure, behind housing, and twice as large as healthcare. Something else to keep in mind: The typical car is used only about 5% of the time as it is usually parked somewhere.⁶

In light of the enormous opportunity for improvement, it should be no surprise that the autonomous car industry has seen massive amounts of investment. This has not only been about venture capitalists investing in a myriad of startups but also innovation from traditional automakers like Ford, GM, and BMW.

Then when might we see this industry become mainstream? The estimates vary widely. But according to a study from Allied Market Research, the market is forecasted to hit $556.67 billion by 2026, which would represent a compound annual growth rate of 39.47%.⁷

But there is still much to work out. “At best, we are still years away from a car that doesn’t require a steering wheel,” said Scott Painter, who is the CEO and founder of Fair. “Cars will still need to be insured, repaired, and maintained, even if you came back from the future in a Delorean and brought the manual for how to make these cars fully autonomous. We make 100 million cars-per-year, of which 16 million-a-year are in the U.S. And, supposing you wanted the whole supply to have these artificial intelligence features, it would still take 20 years until we had more cars on the road including all the different levels of A.I. versus the number of cars that didn’t have those technologies.”⁸

But there are many other factors to keep in mind. After all, the fact remains that driving is complex, especially in urban and suburban areas. What if a traffic sign is changed or even manipulated? How about if an autonomous car must deal with a dilemma like having to decide to crash into an oncoming car or plunging into a curb, which may have pedestrians? All these are extremely difficult.

Evening seemingly simple tasks can be tough to pull off. John Krafcik, who is the CEO of Google’s Waymo, points out that parking lots are a prime example.⁹ They require finding available spots, avoiding other cars and pedestrians (that can be unpredictable), and moving into the space.

But technology is just one of the challenges with autonomous vehicles. Here are some others to consider:

• Infrastructure: Our cities and towns are built for traditional cars. But by mixing autonomous vehicles, there will probably be many logistical issues. How does a car anticipate the actions of human drivers? Actually, there may be a need to install sensors alongside roads. Or another option is to have separate roads for autonomous vehicles. Governments also will probably need to change driver’s ed, providing guidance on how to interact with autonomous vehicles while on the road.
• Regulation: This is a big wild card. For the most part, this may be the biggest impediment as governments tend to work slowly and are resistant to change. The United States is also a highly litigious country—which may be another factor that could curb development.
• Adoption: Autonomous vehicles will probably not be cheap, as systems like Lidar are costly. This will certainly be a limiting factor. But at the same time, there are indications of skepticism from the general public. According to a survey from AAA, about 71% of the respondents said they are afraid of riding in an autonomous vehicle.¹⁰

Given all this, the initial phase of autonomous vehicles will probably be for controlled situations, say for trucking, mining, or shuttles. A case of this is Suncor Energy, which uses autonomous trucks for excavating various sites in Canada.

Ride-sharing networks—like Uber and Lyft—may be another starting point. These services are fairly structured and understandable to the public.

Keep in mind that Waymo has been testing a self-driving taxi service in Phoenix (this is similar to a ride-sharing system like Uber, but the cars have autonomous systems). Here’s how a blog post from the company explains it:

We’ll start by giving riders access to our app. They can use it to call our self-driving vehicles 24 hours a day, 7 days a week. They can ride across several cities in the Metro Phoenix area, including Chandler, Tempe, Mesa, and Gilbert. Whether it’s for a fun night out or just to get a break from driving, our riders get the same clean vehicles every time and our Waymo driver with over 10 million miles of experience on public roads. Riders will see price estimates before they accept the trip based on factors like the time and distance to their destination.¹¹

Waymo has found that a key is education because the riders have lots of questions. To deal with this, the company has built in a chat system in the app to contact a support person. The dashboard of the car also has a screen that provides details of the ride.

According to the blog post, “Feedback from riders will continue to be vital every step of the way.”¹²