manhole covers reveal gaping holes for ai autonomous cars capabilities hyperedge embed
The ability of a self-driving car to detect the safety hazard of a partially ajar manhole cover is an edge case that may not yet be programmed. (Credit: Getty Images) 

By Lance Eliot, the AI Trends Insider   

Have you been asked about manhole covers in any of your recent high-tech company job interviews?   

Probably you have.   

Yes, oddly enough, manhole covers have become a common topic for job interviews in the last several years, especially when seeking a job at a high-tech firm. You might assume that the jobs in question were somehow related to producing manhole covers or possibly working on street construction crews. 

Nope.  

The matter of manhole covers was suddenly being brought up in all kinds of job interviews for nearly any kind of job at a high-tech firm. Want to be a programmer at a high-tech firm? Better be ready for those manhole questions. Want to work in finance or marketing at a high-tech firm. Manhole covers are undoubtedly going to come up.   

Here’s the deal.   

In one of those recruitment trends, bringing up the offbeat topic of manhole covers became the hot new means to somehow screen candidates, supposedly separating the creative wheat from the dullard chaff. The interview questions about manhole covers were presumably aimed at eliciting how well someone thinks out-of-the-box or thinks on the spot.   

Let’s start with one of the initial mind-bending questions that gained a lot of traction with interviewers. The interviewer looks at you with a seriously straight face and asks you to estimate how many manhole covers there are in New York City. You are given a moment or two to reflect. The interviewer is watching you closely to see how you cope with this distressingly off-the-wall issue.   

If you’ve not heard the question before, please go ahead and mull over the matter in your mind. Try not to show any outward indication of cold sweat or otherwise tip your hand that you are struggling with the keen query. It would be better for you to appear like a hipster calculating machine and that you are crafting the best possible answer for this altogether immensely fascinating question.   

Of course, you might actually be thinking that it is an esoteric or eccentric question and doesn’t have much to do with the job that you are applying for. Nonetheless, in the quirky nature of how job interviews go, you must not dare to challenge such a question and instead act like it is the best question since the making of sliced bread.   

Since I don’t want you to ever lose a potential juicy job at a high-tech firm simply because of the manhole question, I’ll happily reveal the answer to you.  

Thinking Through the Number of Manhole Covers in New York City   

You are supposed to estimate the number of manhole covers by first mentally conjuring up a vision in your head that dreamily indicates the roadway layout of New York City. In essence, avenues run in one direction (typically north-south), and the streets go in a roughly perpendicular direction (usually east-west). This is a grid-style layout, akin to a matrix. Imagine a spreadsheet that has various rows and columns. 

Next, you are seeing in your mind’s eye that perhaps there is one manhole cover per each of the intersecting points of this matrix. Thus, if you multiply the number of avenues times the number of streets, which is the number of rows and columns of this imaginary matrix, you would then multiply that calculated amount by the estimate of one manhole cover and arrive at your total estimate.   

You are welcome to get tricky and assume that there is less than one manhole cover per intersecting point, ergo multiple the rows by columns result with a fraction. Or you can go the other way and assume that there is more than one manhole cover per intersecting point. In that case, you would be multiplying the number of rows and columns by a number greater than one.   

Voila, you have the means to answer the question. 

Kind of. One big problem with this particular variant of a so-called “clever” question is that not everyone knows that New York City is arranged in a grid-style (those interviewers that do know this bit of arcane trivia are apt to assume everyone must know it). Without that piece of crucial knowledge, you are somewhat sunk on this oddball question. Even if you knew it was in a grid shape, you might not know how many avenues there are, or know how many streets there are.   

You could also certainly argue that this is a huge generalization anyway, since not all of New York City conforms to this shapely grid notion. But you’d be wise to not tilt at windmills, especially during a job interview.   

The usual rationalization for this manhole cover query is that the interviewer is not expecting an arithmetically-derived answer, and instead trying to gauge how you think on your feet. If you were able to sketch out how you would solve this sneaky problem, this was considered a sufficiently evidential way of proving that you are a thinker and a problem solver.   

The retort to that justification is that regrettably many interviewers are deplorable at doing interviews, and as such, they completely distorted the manhole cover conundrum. Some interviewers would eagerly wait for a number, and if you said anything other than providing a single number, you were marked as wrong. For those interviewees that did calculate a number, some interviewers would have the nervy gall to mark you as “wrong” if the number was not an exact match to the number of actual manhole covers in New York City.   

Things got worse from there. 

Creative Thinking Required   

Some savvy interviewees that knew the question might be potentially asked (having been tipped by others that lamentably got crushed by the question), shrewdly memorized the number of actual manhole covers (as reported by the New York City roadway infrastructure agency), and would simply proffer that number. This might allow you to skate through the question. On the other hand, some interviewers would then ask how you derived the number. If you could not tell the inspiring story of having deduced the matter via the grid method, you were sunk for not being creative in your thinking.   

Other manhole cover questions are used in interview settings. For instances, explain why manhole covers are round. 

You see, your whole life you’ve probably seen just round manhole covers and never put much thought into why they are round. Perhaps there is some really good reason for this round shape. It could also simply be a tradition that few have ever sought to overturn.   

Once again, this is a thinker or problem-solver type of question. You are expected to demonstrate that you can take a problem that you’ve not seen before, and turn it on its head, solving it in a few seconds and under the bright lights of a job interview. 

While many do not put much stock in these attempts to catch a job interviewer off-guard, it is a commonplace tactic by interviewers. Indeed, it is sometimes the lazy way to undertake an interview. Merely scrape away at the interviewee with all kinds of problem-solving queries, and you’ve used up that allotted half-hour or hour of the interview. You can write up your notes and make it seem that you really grilled the interviewee, as though that was the purpose of the interview.   

You could assert that manhole covers are round because the manholes are round holes. Duh, what else would make sense to cover them with? (Some interviewers won’t like that answer and will severely ding you for being unduly smarmy.) Or perhaps manhole covers are round so that the effort to put the cover back over the manhole is easily done and there is no struggle with the proper orientation. Round a manhole cover is also readily turned on its edge and rolled to wherever you might want to temporarily store it.   

Manhole Covers are Heavy 

You might find of overall interest that manhole covers are often made from cast iron and weigh around 250 pounds. There are plenty of variations, including manhole covers that weigh around 100 pounds and others that weigh more than 300 pounds. There are also manhole covers that are not round, though this is rare in the United States. The lip or width of a manhole cover is usually around an inch or so, sometimes less and sometimes thicker.

You probably do not give much thought daily to manhole covers. You drive over them all the time, and yet they rarely register in your noggin as something to be noticed. Sure, there might be a construction crew that has removed a manhole cover, for which the roadway is usually blocked with cones and other obstructions to keep you from going over the now-open manhole.   

In theory, you could likely straddle the open manhole with your vehicle and not suffer any damages to your car. Do not do this! A very bad idea. Plus, for all you know, there might be someone down below in the manhole. Think of the danger that a car passing over an open manhole presents to anyone that is within the manhole itself. 

I would bet that nearly all of us would certainly avoid an open manhole, even if there weren’t brightly colored cones blocking it off. The moment that you noticed up ahead that the roadway presented an open manhole, you would either come to a stop beforehand or at least maneuver into another lane to entirely avoid the gaping opening.   

Suppose though that the manhole cover was only slightly ajar.   

This presents a different situation in that you might or might not realize that the manhole cover is not fully seated in its proper spot. Also, consider the speed of your vehicle as a factor. If you are driving fast down a street and the manhole cover is ajar, perhaps you would fail to notice it out of place or spy it only at the last moment, allowing very little reaction time to cope with the unusual circumstance.   

Most of us would say that luckily we’ve never had that kind of circumstance arise. Manhole covers are nearly always sitting in their proper placement over a manhole, or the manhole cover is fully off the manhole and sitting in the street by itself or has been placed on the sidewalk. The odds of encountering a manhole cover that was neither completely implanted and nor completely removed would seem quite remote.   

It happened recently, sadly so.   

There is an unnerving video that was captured by a camera-wielding resident showcasing a recent tragic roadway incident involving a pick-up truck and a manhole cover. The video has been recently posted by the local police within the jurisdiction that the matter occurred. The dreadful incident occurred in Panorama City, California, which is in the city of Los Angeles.   

Apparently, a young man in his 20s was for as yet unknown reasons down in a covered manhole and attempted to come up by propping out and over the manhole cover. Imagine trying to push up a manhole cover from underneath it. That’s a lot of weight to try and displace.   

Just as the manhole cover begins to shift up and slightly over, a pick-up truck comes into view of the video. The pick-up truck runs directly over the manhole cover, which is now askew and no longer fitted over the manhole per se. To give you a semblance of the forces involved, the tires of the pick-up truck thud upon the manhole cover, and the surprising result is that the manhole cover goes flying, akin to a frisbee disc. Or maybe think of a gigantic and highly dangerous tiddlywink that once you press strongly on the edge, it will go flipping and flying. It is unimaginable that a hefty manhole cover could be so readily hurled into the air, but it does so with seeming ease. 

Anyway, at the same time, it appears that the young man fell back down into the manhole as the pick-up truck proceeded overhead of the partially opened manhole. As you likely know, some manholes are relatively shallow and others can be dozens of feet in depth. In any case, according to the police, the young man died at the scene due to his injuries and was retrieved by the local fire department. 

You might be wondering if the weather or roadway conditions or other factors were at play in this heartbreaking event. The video seems to indicate that the event happened on a Saturday morning around 10:30 a.m. and that there was daylight and the road was dry. This is worthwhile to consider since the matter would likely be given a different consideration if it was nighttime or perhaps the roadway was wet, and it was raining out.   

The driver of the pick-up truck kept driving and is now wanted by the police for questioning.   

In California, there is a legal requirement that a driver must immediately (as soon as practical) come to a stop at an accident scene and remain there, regardless of whether the person believes they were not at fault and even if there isn’t any apparent damages or injuries. Generally, those that do not stop and stay at the scene can be charged with a hit-and-run crime, ranging from being rated as a misdemeanor to a potential felony. In this case, there is also the grim matter of the fatality involved too.   

The driver should have remained at the scene.   

Shifting gears, besides the shocking nature of the incident, we can also consider what lessons might be learned.   

The notion of a manhole cover being pushed up in the midst of an active roadway and without any other indicators or signage to forewarn the occurrence is a seeming outlier or sometimes referred to as an edge or corner case. In the parlance of those that study occurrences of things, an edge or corner case is considered something that only has a remote chance of occurring. It can occur, but only with some semblance of rarity.   

Perhaps this tragedy will spark us all to be cognizant of manhole covers, though on a day-to-day driving basis this would seem a somewhat extreme topic to keep at top of mind. When you are driving your car to work or simply to the local grocery store, you might occasionally take a second glance at those manhole covers. If you do so, please do not become unnecessarily distracted by the manhole covers, since the attention ought to be predominantly on the overall roadway status.   

Speaking of cars, the future of cars consists of AI-based true self-driving cars.   

There isn’t a human driver involved in a true self-driving car. Keep in mind that true self-driving cars are driven via an AI driving system. There isn’t a need for a human driver at the wheel, and nor is there a provision for a human to drive the vehicle.   

Here’s an intriguing question that is worth pondering: How might an AI-based true self-driving car contend with a manhole cover that is partially out of place?   

I’d like to first clarify what I mean when referring to AI-based true self-driving cars. 

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 Cars   

As a clarification, true self-driving cars are ones where the AI drives the car entirely on its own and there isn’t any human assistance 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 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/ 

Self-Driving Cars And Manhole Covers   

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. 

One aspect to immediately discuss entails the fact that the AI involved in today’s AI driving systems is not sentient. In other words, the AI is altogether a collective of computer-based programming and algorithms, and most assuredly not able to reason in the same manner that humans can.   

Why this added emphasis about the AI not being sentient?   

Because I want to underscore that when discussing the role of the AI driving system, I am not ascribing human qualities to the AI. Please be aware that there is an ongoing and dangerous tendency these days to anthropomorphize AI. In essence, people are assigning human-like sentience to today’s AI, despite the undeniable and inarguable fact that no such AI exists as yet. 

With that clarification, you can envision that the AI driving system won’t natively somehow “know” about the facets of driving. Driving and all that it entails will need to be programmed as part of the hardware and software of the self-driving car. 

Let’s dive into the myriad aspects that come to play on this topic.   

First, it is important to realize that self-driving cars make use of various sensors to try and detect the driving scene. The types of sensors can include video cameras, radar, LIDAR, ultrasonic units, thermal imaging, and other such devices. All told, these are the eyes and ears of the AI driving system. Data is collected via the sensors and then various onboard computational analyses are made, oftentimes making use of Machine Learning (ML) and Deep Learning (DL). The driving scene is internally estimated based on the patterns found.   

One of the most important aspects to be detected is something that might seem surprising to you, namely the detection of open space that is considered drivable. Humans are so used to eyeing the nature of drivable spaces that it is essentially second nature. You look at a street and can almost instantaneously gauge where the street is, along with where the curbs are and the medians are, and overall ascertain where you can suitably drive your car. 

It seems that this is likely a learned facet. Think back to your childhood. An adult probably pointed out the street to you and told you to look both ways, explaining that cars go there and you have to be watchful of the monstrous beasts. After a while, you gradually became adept at figuring out streets, avenues, highways, etc. Your adult mind can nearly always look at an area around you and quickly identify where a car could be driven and where it could not be driven.   

Using a computer to figure this out is not so easy. The video camera provides visual images that are examined computationally to try and identify the drivable spaces. Radar and LIDAR can be used for this purpose too. Inside the AI driving system, there is a kind of virtual database or computer model being maintained to try and keep track of where the self-driving car can go and where it ought to not go.   

Why have I dragged you through that technological indication?   

Because the key to this discussion is whether or not a self-driving car could detect a manhole and a partially ajar manhole cover.   

Detecting the instance of a manhole that is covered entirely by its manhole cover is relatively straightforward. Likewise, detecting a manhole that is completely uncovered and lacking its manhole cover is somewhat uncomplicated, though this can be tricky in certain circumstances. Recall that earlier I had brought up the factor of various roadway conditions, such as whether it is raining out or nighttime. The roadway conditions could make detecting an open manhole a lot more difficult than it otherwise would normally be.   

The really tough instance is when the manhole cover is only slightly ajar.   

Suppose the visual images coming in from the video cameras are being obscured by the bright sunlight that might be coming directly into the camera lenses. Being able to get a crisp set of images of the street and the manhole could be confounded. The profile of the manhole cover is quite low to the ground and at only an inch thick is going to be hard to either directly see or have any radar or LIDAR returns providing a definitive indication of what is happening, especially as it happens in real-time.   

Another concern is whether the AI developers conceived of the matter entailing a partially ajar manhole cover.   

It could be that the programming of the AI driving system is only devised to determine whether the cover is in place or it is not in place. This might be a binary choice. Until the manhole itself is fully exposed, the internal program might be assigning a probability that the manhole cover is in place and won’t mathematically make the switchover into the manhole cover being out of place until enough imagery or other sensory data seems to turn the tide in that determination.   

You see, the developers and management might have decided that a partially ajar manhole cover is an edge or corner case that for now is not given much priority. The development team is doing all it can to just get their self-driving car to drive safely from point A to point B. Dealing with a partially open manhole is not something that they would likely consider a core part of the driving task.   

The other added twist involves what to do even if the detection takes place with ideal accuracy. 

Overall, the first crucial aspect entails identifying that such a situation exists, and the second and equally vital part of the matter involves the AI driving system computationally laying out what to do about this discovered anomaly in the roadway scene. 

Should the AI driving system have the self-driving car come to a stop? Maybe there isn’t enough time available to stop before striking the manhole cover.   

Should the AI driving system swerve into another lane? But there might be other cars there or pedestrians nearby that could get hit by the veering self-driving car. 

And so on.   

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 many more entanglements to this problem.   

Suppose the self-driving car does strike the manhole cover and takes a beating when the flying manhole cover smacks the underbody of the autonomous vehicle and perhaps rips up the tires.   

Will the AI driving system be able to detect that this has happened?   

As I’ve explained in my columns, the AI driving system only gets informed by whatever the sensors detect and might not be able to readily detect when the vehicle itself has struck something or collided with objects. Hitting and causing the manhole cover to go flying might or might not be detected by the sensors. If the sensors do detect it, the AI driving system has to be sufficiently programmed to interpret what the actions portend.   

A human driver would certainly realize they hit something. They would likely realize it had to be the manhole cover, assuming they saw it at the last moment and felt the car shudder as it banged into the manhole cover. The odds are too that the human driver at the wheel in such a case would hear the sounds of the manhole cover as it clanged back down onto the roadway.   

In short, it seems almost impossible to imagine that a human driver would not know they had struck the partially ajar manhole cover in this kind of situation.   

On the other hand, it is conceivable that an AI driving system might not detect the matter. Or that it detects the matter and has no provision for what to do and nor how to interpret the situation. That being said, all else being equal, most of the AI driving systems are programmed to try and safely come to the soonest practical stop if something untoward seems to have occurred. The AI driving system may ascertain that something unusual has happened and go into a type of failsafe mode that instructs the self-driving car to come to a stop.   

A human driver would presumably know why they are stopping the car and would comprehend the fact that they hit a loose manhole cover. An AI driving system might simply come to a stop because something happened, which is unknown to the AI driving system, and a catchall act entails coming to a prudent halt.   

Now you know quite a bit about this narrow topic.   

Various estimates suggest that there are approximately 20 million manholes in the United States. We can reasonably assume that means there are a corresponding 20 million manhole covers out on our streets too. 

You readily pass over the ubiquitous and seeming unseen manhole covers each and every day. They largely go unnoticed by human drivers. When a manhole cover is missing, it seems nearly all human drivers would tend to notice the gaping hole. Most humans would hopefully and wisely try to divert away from the opening, and possibly warn other drivers about the matter. 

Driving along and encountering a partially ajar manhole cover is something that few have likely ever witnessed, especially when the roadway wasn’t flagged or coned to highlight the dangerous setting. It seems likely you’ll never be in the driver’s seat of your car and see ahead of you a manhole cover as it is being pushed up and out of the way, but if you do, at least now you’ve thought about what to do, and I trust you will do the right thing.   

Keep your eyes open and your wits about you. In addition, as a source of relief, perhaps, I’m sure that the AI driving systems will eventually incorporate the manhole ajar use case, and we can rest easy while riding inside a self-driving car that the autonomous vehicle will do the right thing too.   

That’s an AI driving system that manages to cover all the bases.  

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

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