Should Self-Driving Cars Have Razzle Dazzle To Make Them Standout Or Maybe That’s A Bad Idea

Dr. Lance Eliot, AI Insider

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[Ed. Note: For reader’s interested in Dr. Eliot’s ongoing business analyses about the advent of self-driving cars, see his online Forbes column:]

We generally think of camouflage as a means to blend into the surroundings.

There’s another form of camouflage that we don’t often consider, namely the kind that is known as motion dazzle, also sometimes called razzle-dazzle, or perhaps more easily understood by the name disruptive camouflage.

In this instance, the desire is to actually stand out and be readily seen.

Background About Disruptive Camouflage

This idea of using disruptive camouflage was extensively undertaken during World War I and also somewhat during World War II.

We tend to think of navy ships as always being painted a rather dull monotone grey color.

This would seem to be a wise choice.

At sea, the navy ships would tend to blend into the background of a grayish sky and a blue sea. Presumably, whales and dolphins use a similar colorization to try to blend into their surroundings. Here in Southern California, you can wander to San Diego and see lots of United States Navy ships docked in the harbor as it is a major west coast naval center. Many visitors often say to me that they didn’t even notice the big ships, in spite of the fact that there are many dozens of them all readily seen. Must be the grey monotone.

In a controversial manner, upon the onset of World War I, there were some that suggested it would be better to use a disruptive camouflage pattern for navy ships rather than a monotone grey.

Various complex patterns involving striking geometric shapes were devised and painted onto navy ships of the time period. Thousands of such motion dazzle depictions were used. The colors and shapes are intersecting each other and interrupting each other.

There are zoological theories that suggest the zebra, jaguar, and giraffe are examples of a razzle-dazzle form of camouflage.

There is much contention whether those animals are indeed going the razzle-dazzle route or whether there is some other reason for the patterns and colors on their skin.

In terms of the navy use of disruptive camouflage, numerous scientific studies have tried to determine whether the razzle-dazzle is really more effective than the monotone grey. It would seem that most studies ultimately are unable to control sufficiently the numerous factors involved and it is a muddied picture as to whether the razzle-dazzle is truly an effective defensive technique.

Razzle-dazzle And AI Autonomous Cars

What does this have to do with AI self-driving driverless autonomous cars?

At the Cybernetic AI Self-Driving Car Institute, we are developing AI software for self-driving cars. One aspect that is going to be crucial for the ultimate success of self-driving cars will be whether pedestrians are safe when around AI self-driving cars.

In theory, the AI self-driving car is supposed to be good enough at the driving task to be able to detect pedestrians.

Imagine that an AI self-driving car is driving down a street at the legally posted speed. Suppose it is 45 miles per hour, which is about 66 feet per second. A pedestrian is standing behind a pole that is adjacent to the road and right at the curb. Neither an AI self-driving car sees the pedestrian, and nor could a human driven car see the person that’s standing behind that pole. The pedestrian decides to step out into the street just as the AI self-driving car gets within a few feet of the pole (or, if you like, pretend it was a human driver — the same end result is going to occur).

By what magic is the AI self-driving car not going to hit that pedestrian?

I ask the question because the answer is rather plain and simple, the law of physics is going to take over and the AI self-driving car is going to ram into that pedestrian.

Obscured From View

I’m not sure where you drive, but I assure you that in the downtown Los Angeles area that I drive, it happens all the time that pedestrians are obscured from view.

In short, either a human driven car or an AI self-driving car can end-up hitting and possibly killing a pedestrian, doing so for sure in the circumstance wherein the pedestrian opts to enter into the street when there is no viable means of avoiding the pedestrian, either by braking or swerving the car.

You might be thinking that shouldn’t the AI self-driving car do a better job on this than a human driven car?

I suppose you could say that an AI self-driving car might do a better job in that the AI is presumably not distracted as a human driver might get distracted. A human driver might be looking at the other side of the street and noticing a new barbershop that’s opened up, and thus fail to notice the pedestrian to their right that suddenly steps into the street.

If there is a chance to avoid striking the pedestrian, by-and-large you might say that the AI will perhaps be more likely to do so, since it lacks the distraction factor that could beset a human driver. The AI is presumably continually scanning the surroundings, on all sides, and not going to allow itself to become preoccupied with one particular thing, such as the new barbershop.

If a pedestrian is on the sidewalk and running, and they are veering toward the street, the AI is intended to make a prediction that the pedestrian might logically end-up in the street, and if intersecting with the path of the self-driving car, the AI should direct the AI self-driving car to avoid striking the pedestrian, once they (possibly) enter into the street.

Imperfect Machines

Please keep in mind that the AI and the self-driving car are not considered perfect machines.

Is there a chance that a pedestrian might not be detected in spite of the array of sensors on the self-driving car?

Yes, absolutely.

Can the sensors themselves at times fail or falter?

Yes, absolutely.

Could the AI system end-up making a wrong choice about whether there is a pedestrian nearby and whether the pedestrian might be intending to get into harm’s way?

Yes, absolutely.

Let’s then assume that the AI self-driving car is going to do what it can to avoid hitting pedestrians, but that it is not a perfect system and there are still substantive chances of hitting pedestrians, especially when a pedestrian does something erratic or rash.

One aspect is to try to grab the attention of the pedestrian so that they are less likely to blindly step into the path of an AI self-driving car.

Making A Self-Driving Car Standout

I now present to you a somewhat provocative notion.

Should an AI self-driving car be readily noticed as an AI self-driving car?

Some would say that yes, it is important for pedestrians to realize that an AI self-driving car is coming along on the street.

If they realize it is an AI self-driving car, perhaps the pedestrians will be more cautious than they otherwise might be. This could be especially important if we are conceding that in many respects the AI self-driving car might not be as good as a human driver in terms of dealing with pedestrians. By realizing that there is an AI self-driving car, the pedestrians are essentially forewarned.

And this brings us to the topic of razzle-dazzle!

Right now, most of the automakers and tech firms are taking a conventional looking car and outfitting it to be an AI self-driving car.

The shape and colorization of the AI self-driving car is pretty much the same as any other car on the roadways today. There are some future concept cars that have designs of a rather new look, but those aren’t particularly aimed to be on our roadways soon.

We already accept the notion that a cab or taxi is often yellow in color and has an indicator on the roof. We accept the notion that police cars have a certain pattern and color scheme. Would it make sense to consider that all AI self-driving cars would need to abide by some special designated “razzle-dazzle” combination of shapes and colors?

The rather obvious downside to this idea is that perhaps the public might not like the razzle-dazzle look. If you are an auto maker pouring tons of money into AI self-driving cars, you probably don’t want to risk having people not be willing to buy an AI self-driving car because of how it looks. Remember before that some expressed that the razzle-dazzle looking navy ships are freakish in appearance? I doubt that we want the public to perceive AI self-driving cars in a freakish manner.

There might be a fine line then between purposely coming up with a common or standard scheme of shapes or colors that could make an AI self-driving car become readily apparent to humans, and especially pedestrians, and yet also not be overly garish. A kind of softer disruptive camouflage, as it were.

Unlike the normal kind of disruptive camouflage that intends to deceive about speed and direction, we’d of course want the razzle-dazzle to make those factors actually more apparent, rather than less so. Also, the traditional disruptive camouflage for navy ships is distinct per ship so that the class of ships cannot be revealed, while in this case we would want something that was consistent across all instances. In that sense, please use this analogy to the disruptive camouflage concept in a thoughtful manner and not a stricter aspect-for-aspect manner.

Presumably, each automaker would want to be able to still provide their own look-and-feel to the AI self-driving car, allowing them to be differentiated in the marketplace.


If we don’t do something to make AI self-driving cars appear distinctive, it essentially means that they will be using traditional “camouflage” in that they will blend into the surroundings consisting of other conventional cars.

You won’t be able to readily notice whether those cars nearby are human driven or AI self-driving cars. As a society, do we believe that AI self-driving cars should be required to appear distinctive, or are we fine with them blending in?

Razzle-dazzle, or just the norm.

Time will tell.

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Copyright © 2019 Dr. Lance B. Eliot

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Dr. Lance B. Eliot is a renowned global expert on AI, Stanford Fellow at Stanford University, was a professor at USC, headed an AI Lab, top exec at a major VC.

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