Getting Ready For The Full-Blown Autonomous Vehicular Cloud  

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The vehicular cloud is a form of a cloud that consists of a combination of the mobile cloud, the conventional cloud, and vehicles. (Credit: Getty Images) 

By Lance Eliot, the AI Trends Insider   

Any farmer will tell you that sometimes a planted seed takes a while to grow. In the field of autonomous vehicles (AVs), there has been ongoing talk about the advent of the vehicular cloud. Someday, mark my words, the vehicular cloud will be a mighty redwood tree, and we’ll likely look back at the amazing aspect that it all began in such modest ways.   

Let’s take a deep dive into the expanding ways of how this specialized form of cloud computing is arising.    

As I’ve previously indicated in my columns, the use of cloud computing and the inclusion of the cloud as integrated into the emergence of autonomous vehicles portends a quite vital match. When I refer to autonomous vehicles, perhaps a more commonly used vernacular would be to mention self-driving vehicles (note that today’s headlines usually refer to self-driving rather than using the somewhat formalized and academic-sounding AV moniker). For purposes of this discussion, consider that the notion of self-driving and the notion of autonomous vehicles are generally the same. 

There will be self-driving cars, self-driving trucks, self-driving motorcycles, self-driving drones, self-driving submersibles, self-driving planes, self-driving ships, and so on. These are everyday forms of transportation that will entail an AI-based driving or piloting system that is at the wheel of the craft. The basis for garnering the acclaimed banner of being autonomous will be because the vehicle will be entirely operated by machine and without the need for any human-guided effort.   

An especially notable intertwining of self-driving vehicles in conjunction with the cloud entails the capability of using OTA (Over-The-Air) electronic communications. The vehicle will have various onboard computer processors and hard drives or similar electronic-oriented memory technology, along with sensors for detecting the outside world, and will be equipped with communication devices for connecting with the cloud.   

The OTA will allow for software updates to be downloaded into the vehicle, providing a remote updating facility. In addition, data collected by the vehicle can be uploaded into the cloud. There is continuing debate about how much data should be kept in the vehicle versus pushed up into the cloud, along with strong viewpoints about the implications of having these “roving eyes” amid the plethora of data that will be collectible.   

Okay, so there are these self-driving vehicles, and they are going to be leveraging the use of the cloud.   

The cloud can provide a place to store data that was first obtained via self-driving vehicles. Also, the cloud can make use of vast and powerful computing resources that are otherwise not readily encompassed within the vehicles themselves. The computational processing capabilities within the vehicle are focused on the self-driving activity, plus they are not of the outsized supercomputing realm that can be found within the cloud. 

A typical high-tech cloud-based setup for autonomous vehicles involves taking conventional cloud computing and marrying the access to and use of self-driving vehicles into the normal elements of the cloud. Various customized components are likely needed to ensure that the conventional cloud aspects are tailored to the specifics of autonomous vehicles. 

You might be leaping ahead mentally and perhaps be assuming at this juncture of the discussion that this conventional cloud is therefore a presumed vehicular cloud because it has been honed toward the nature of autonomous vehicles. 

Sorry, that’s not quite accurate and there is still a bit more to the story. Please continue reading. 

First, be aware that there is another variant of the cloud that not many people generally are aware of, something referred to as the mobile cloud.   

The mobile cloud is kind of a reverse version of what you might normally associate with traditional cloud computing. I’m betting that you think of conventional cloud computing as computer resources that are available online and are variously collected together as though somehow centralized in their configuration.   

Well, here’s a bit of a twist for you. 

Imagine that the mobile devices that we carry around are miniature variants of available computing resources. Your smartphone is handy for texting with others and can store all your favorite vacation pictures and those spectacular selfies that you’ve taken. That smartphone in your pocket is a computing device that has computational capabilities and also can store data.   

Suppose that you asked a friend to keep some of your photos on their smartphone, perhaps due to your smartphone getting low on available memory. You could send those prized photos to your friend, and they would (hopefully) dutifully keep them on their smartphone. At some later time, you might ask your friend to send them back over to you.   

This is essentially the underpinnings of a mobile cloud.   

You could ask all of your many friends to do likewise with each other, in the sense of every one of them sharing their computational resources with one another (via their respective smartphones). These are mobile devices. They are being treated as though they are part of a larger collective or cloud. As such, the appropriate name for this phenomenon would be to call it a mobile cloud. 

Alright, there is the conventional cloud and there is also the potential for a mobile cloud. Two types of clouds. 

Some mistakenly think that these are perhaps bitter enemies, as though they are competing for the royal crown of being the true cloud. That’s nonsense. These are appropriate variations of the “cloud” and they are perfectly able to coexist and work hand-in-hand. No bickering cats and dogs, as it were.   

Trying to successfully pull off a mobile cloud is a tougher row to hoe. 

Consider even the simplest case of you sharing your photos with your friend, and they now have a responsibility of making sure that they don’t inadvertently delete those photos or perhaps let someone else see them. The mobile cloud can have a semblance of the wild west associated with it. This is partially why you don’t see that much heralding the advent of the mobile cloud.   

In any case, we have now established the basis for bringing up the vehicular cloud.   

Are you ready? 

Those emerging autonomous vehicles that are self-driving cars, self-driving trucks, and the like, can be characterized as computers-on-wheels. This makes sense, because to bring about autonomous or AI-based driving requires an impressive amount of computing capabilities. When a human does the driving, you don’t necessarily need gobs of computers on-board. For an AI-based driving system, you have to put into the vehicle a cavalcade of computing capabilities. 

Self-driving or autonomous vehicles are inherently mobile. That’s what they do. We use them to get around and traverse from point A to point B. In that manner of thinking, you could say that self-driving vehicles are mobile devices. Just as your mobile smartphone gets carried around from place to place, an autonomous vehicle carries you around from place to place.   

The significance of this realization is that potentially we could leverage the computers within the vehicles for purposes beyond that of driving the vehicle. This seems like a mental stretch for some people.  Perhaps this will help. You likely store in the trunk of your car some goodies, such as spare bottles of water, a jacket, some camping gear, and so on. In that manner, you are using the vehicle as a storage medium. 

Autonomous vehicles will have a lot of computer memory onboard. You could potentially store your photos in that onboard computer memory. When you need to retrieve the photos, you merely connect with the vehicle via electronic means and grab those photos that you had stored there. This is somewhat similar to the mobile cloud notion that was described earlier. 

With all of that in mind, the definition of the vehicular cloud is a form of a cloud that consists of a combination of the mobile cloud, the conventional cloud, and vehicles.   

Simply stated: Vehicular cloud = Conventional cloud + Mobile cloud + Vehicles 

The reference to vehicles is usually intended to be autonomous vehicles. The reason for defaulting to autonomous vehicles is that they are chock-full of computing. That being said, there is certainly room in this realm to include semi-autonomous vehicles too (they also have extensive computing resources). 

We’ll clarify that: Vehicles = Autonomous vehicles + semi-autonomous vehicles   

In case you are wondering what constitutes autonomous versus semi-autonomous, a quick indication about the levels of autonomy associated with self-driving cars might help to provide needed clarity. 

For my framework about AI autonomous cars, see the link here: https://aitrends.com/ai-insider/framework-ai-self-driving-driverless-cars-big-picture/   

Why this is a moonshot effort, see my explanation here: https://aitrends.com/ai-insider/self-driving-car-mother-ai-projects-moonshot/   

For more about the levels as a type of Richter scale, see my discussion here: https://aitrends.com/ai-insider/richter-scale-levels-self-driving-cars/ 

For the argument about bifurcating the levels, see my explanation here: https://aitrends.com/ai-insider/reframing-ai-levels-for-self-driving-cars-bifurcation-of-autonomy/ 

Understanding The Levels Of Self-Driving   

As a clarification, true self-driving cars are ones where the AI drives the car entirely on its own and no human assists during the driving task. 

These driverless vehicles are considered Level 4 and Level 5, while a car that requires a human driver to co-share the driving effort is usually considered at Level 2 or Level 3. The cars that co-share the driving task are described as being semi-autonomous, and typically contain a variety of automated add-on’s that are referred to as ADAS (Advanced Driver-Assistance Systems).   

There is not yet a true self-driving car at Level 5, which we don’t yet even know if this will be possible to achieve, and nor how long it will take to get there.   

Meanwhile, the Level 4 efforts are gradually trying to get some traction by undergoing very narrow and selective public roadway trials, though there is controversy over whether this testing should be allowed per se (we are all life-or-death guinea pigs in an experiment taking place on our highways and byways, some contend). 

Since semi-autonomous cars require a human driver, the adoption of those types of cars won’t be markedly different from driving conventional vehicles, so there’s not much new per se to cover about them on this topic (though, as you’ll see in a moment, the points next made are generally applicable).  

For semi-autonomous cars, it is important that the public needs to be forewarned about a disturbing aspect that’s been arising lately, namely that despite those human drivers that keep posting videos of themselves falling asleep at the wheel of a Level 2 or Level 3 car, we all need to avoid being misled into believing that the driver can take away their attention from the driving task while driving a semi-autonomous car. 

You are the responsible party for the driving actions of the vehicle, regardless of how much automation might be tossed into a Level 2 or Level 3.   

For Level 4 and Level 5 true self-driving vehicles, there won’t be a human driver involved in the driving task. All occupants will be passengers. The AI is doing the driving. 

For why remote piloting or operating of self-driving cars is generally eschewed, see my explanation here: https://aitrends.com/ai-insider/remote-piloting-is-a-self-driving-car-crutch/

To be wary of fake news about self-driving cars, see my tips here: https://aitrends.com/ai-insider/ai-fake-news-about-self-driving-cars/ 

The ethical implications of AI driving systems are significant, see my indication here: https://aitrends.com/selfdrivingcars/ethically-ambiguous-self-driving-cars/   

Be aware of the pitfalls of normalization of deviance when it comes to self-driving cars, here’s my call to arms: https://aitrends.com/ai-insider/normalization-of-deviance-endangers-ai-self-driving-cars/   

Delving Into Vehicular Clouds 

Returning to the points made about the vehicular cloud, there is this ingenious combining of the conventional cloud, along with the notion of a mobile cloud, along with the inclusion of vehicles that range from semi-autonomous to autonomous.   

Some wonder why in the world would you seek to make use of the computing available on the vehicles. This seems entirely counterintuitive at first glance. Just let the vehicle do its thing, performing the self-driving, and call it a day.   

One answer that is perhaps smarmy, relates to why people climb mountains, namely because the mountains are there (an old joke, for sure).   

Today’s use of cars is a rather wasted or enormously under-utilized economic and societal asset. Most cars sit around for about 95% to possibly 98% of their available usage time. You drive your car to work and park your car. It stays there unused during your eight-hour shift or longer workday. You drive home and park your car in your garage. It stays there unused during the nighttime and until used the next morning.   

As a form of transportation, your car is woefully untapped. 

Toss a slew of state-of-the-art computing resources into a vehicle. You’ve just added a resource that is not exclusively for bringing about transportation (the computers can be used for other purposes, though admittedly some of the computing is specific to the self-driving function).   

As such, a vehicle that is jam-packed with handy computing resources and if it is going to sit in a parking lot or your garage for the preponderance of its time, those are sadly wasted or underutilized computing resources that could be put to use.   

As a form of available computing, a self-driving vehicle could end up being woefully untapped.   

We could put that computing to other useful purposes. The thing is, to do so would require somehow connecting them and being able to harness that immense array of computing, doing so sensibly and systematically. Welcome to the vehicular cloud. 

Yes, that does make sense. It is economically and societally sensible to leverage the computing available in modern vehicles. 

You can straight out utilize the raw computing horsepower. The collective available computing will eventually be enormous. There are about 250 million conventional cars in the United States alone, and predictions are that those will eventually give way to self-driving cars. This won’t happen overnight. Gradually, conventional cars will be mothballed, and the prevalence of self-driving cars will increase over a decades-long period.   

We don’t yet know how many self-driving cars will be required to achieve the equivalent transportation needs availed by the existing 250 million conventional cars. Some pundits assert that we will need a lot fewer self-driving cars to cover what today is a primarily idled set of conventional cars. Other pundits anticipate that we will witness a huge surge in the use of ground transport whence self-driving cars become available, and thus it could be that we might need as many or even more self-driving cars due to the factor of induced demand.   

Besides the raw computing power is the use of the sensory devices that will be on autonomous vehicles (and, to some degree, also included on semi-autonomous too). In theory, it would be possible to tap into using the sensory devices, or at least perhaps using the data that the sensory devices provide. See my discussion about how this data can be used in a myriad of ways, including for roadway infrastructure safety, for real estate analyses, and the like.   

For more details about ODDs, see my indication at this link here: https://www.aitrends.com/ai-insider/amalgamating-of-operational-design-domains-odds-for-ai-self-driving-cars/ 

On the topic of off-road self-driving cars, here’s my details elicitation: https://www.aitrends.com/ai-insider/off-roading-as-a-challenging-use-case-for-ai-autonomous-cars/ 

I’ve urged that there must be a Chief Safety Officer at self-driving car makers, here’s the scoop: https://www.aitrends.com/ai-insider/chief-safety-officers-needed-in-ai-the-case-of-ai-self-driving-cars/ 

Expect that lawsuits are going to gradually become a significant part of the self-driving car industry, see my explanatory details here: https://aitrends.com/selfdrivingcars/self-driving-car-lawsuits-bonanza-ahead/ 

Conclusion   

There are of course challenges that come with the vehicular cloud. 

Some worry that tapping into the computing of an autonomous vehicle would cause a “distraction” during the driving or piloting task. Trying to compute the value of pi to the zillionth digit is a lot less important than making sure that the vehicle safely makes its way in the world. Those that are developing autonomous vehicles would need to ensure that the computing resources for driving are given the highest of priority, and perhaps even block-off or turn away any other requests while the vehicle is underway.   

Another concern is whether this leveraging of the computing resources in a vehicle might enable the implanting of a computer virus by a cybercriminal. One shudders to consider the implications of what an evildoer virus might achieve while inside an autonomous vehicle. 

But this is already something that has to be at the forefront of autonomous vehicle developers. Adding a vehicular cloud to the mix does not somehow imply that without the vehicular cloud, there is no risk. Via the OTA that self-driving vehicles are going to include, plenty of ways exist to try and usurp the onboard systems. The point is that the proper security provisions for autonomous vehicles need to already be included. 

There is an interesting aspect, too, about whether autonomous vehicles will have much available “extra” computing anyway.   

Here’s the logic.   

Human-driven vehicles are subject to the needs of human drivers. A human driver gets tired and must stop driving, or else they will be driving erratically and dangerously. Human drivers need breaks for food, for using the restroom, for whatever. Self-driving vehicles don’t need those kinds of breaks in the action. Presumably, a self-driving vehicle could be going 24×7, subject to the limitations of refueling and maintenance. The general assumption is that self-driving cars will be operating continuously, driving around while awaiting a passenger’s request for a ride.   

If that’s the case, we no longer need to be concerned about vehicles that are unused for the preponderance of their available time. And, the logic follows that the computing resources will also be utilized to the same extent, namely that they will be focused on the driving chores and not be available for any other purposes.   

Of course, we don’t know that this belief or assertion that self-driving vehicles will always be on the go is valid. Maybe they will be; maybe they won’t. Even if they are on the go, this does not necessarily imply that all of the computing resources are soaked up toward the driving chore. 

This all hopefully provides you with some intriguing food for thought about the future of transportation, and likewise the future of computing and the cloud. Some refer to this as the Vehicular Cloud (VC), others call it Vehicle Cloud Computing (VCC), and some prefer to use the phrasing of the Autonomous Vehicle Cloud (AVC) as the signature naming.   

Whatever you might like to call this, the odds are that it is going to be big. Just like those majestic redwood trees that grow to gargantuan sizes, the future of the vehicular cloud looks equally exalted.   

Copyright 2021 Dr. Lance Eliot http://ai-selfdriving-cars.libsyn.com/website