By Lance Eliot, the AI Trends Insider
Determining where to best drop-off a passenger can be a problematic issue.
It seems relatively common and downright unnerving that oftentimes a ridesharing service or taxi unceremoniously opts to drop you off at a spot that is poorly chosen and raft with complications.
I remember one time, while in New York City, a cab driver was taking me to my hotel after my having arrived past midnight at the airport, and for reasons I’ll never know he opted to drop me about a block away from the hotel, doing so at a darkened corner, marked with graffiti, and looking quite like a warzone.
I walked nearly a city block at nighttime, in an area that I later discovered was infamous for being dangerous, including muggings and other unsavory acts.
In one sense, when we are dropped off from a ridesharing service or its equivalent, we often tend to assume that the driver has identified a suitable place to do the drop-off.
Presumably, we expect as a minimum:
· The drop-off is near to the desired destination
· The drop-off should be relatively easy to get out of the vehicle at the drop-off spot
· The drop-off should be in a safe position to get out of the vehicle without harm
· And it is a vital part of the journey and counts as much as the initial pick-up and the drive itself.
In my experience, the drop-off often seems to be a time for the driver to get rid of a passenger and in fact the driver’s mindset is often on where their next fare will be, since they’ve now exhausted the value of the existing passenger and are seeking more revenue by thinking about their next passenger.
Of course, you can even undermine yourself when it comes to doing a drop-off.
The other day, it was reported in the news that a woman got out of her car on the 405 freeway in Los Angeles when her car had stalled, and regrettably, horrifically, another car rammed into her and her stalled vehicle. A cascading series of car crashes then occurred, closing down much of the freeway in that area and backing up traffic for miles.
In some cases, when driving a car ourselves, we make judgements about when to get out of the vehicle, and in other cases such as ridesharing or taking a taxi, we are having someone else make a judgement for us.
In the case of a ridesharing or taxi driver, I eventually figured out that as the customer I need to double-check the drop-off, along with requesting an alternative spot to be dropped off if the circumstances seem to warrant it. You usually assume that the local driver you are relying on has a better sense as to what is suitable for a drop-off, but the driver might not be thinking about the conditions you face and instead could be concentrating on other matters entirely.
Here’s a question for you, how will AI-based true self-driving driverless autonomous cars know where to drop-off human passengers?
This is actually a quite puzzling problem that though not yet seemingly very high on the priority list of AI developers for autonomous cars, ultimately the drop-off matter will rear its problematic head as something needing to be solved.
For my overall framework about autonomous cars, see this link: https://aitrends.com/ai-insider/framework-ai-self-driving-driverless-cars-big-picture/
For why achieving a true self-driving car is like a moonshot, see my explanation here: https://aitrends.com/ai-insider/self-driving-car-mother-ai-projects-moonshot/
For my indication about edge or corner cases in AI autonomous cars, see this link: https://aitrends.com/ai-insider/edge-problems-core-true-self-driving-cars-achieving-last-mile/
For dangers that await pedestrians and how AI self-driving car should respond, see my discussion here: https://aitrends.com/ai-insider/avoiding-pedestrian-roadkill-self-driving-cars/
AI Issues Of Choosing Drop-off Points
The simplistic view of how the AI should drop you off consists of the AI system merely stopping at the exact location of where you’ve requested to go, as though it is merely a mathematically specified latitude and longitude, and then it is up to you to get out of the self-driving car.
This might mean that the autonomous car is double-parked, though if this is an illegal traffic act then it goes against the belief that self-driving cars should not be breaking the law.
I’ve spoken and written extensively that it is a falsehood to think that autonomous cars will always strictly obey all traffic laws, since there are many situations in which we as humans bend or at times violate the strict letter of the traffic laws, doing so because of the necessity of the moment or even at times are allowed to do so.
In any case, my point is that the AI system in this simplistic perspective is not doing what we would overall hope or expect a human driver to do when identifying a drop-off spot, which as I mentioned earlier should have these kinds of characteristics:
· Close to the desired destination
· Stopping at a spot that allows for getting out of the car
· Ensuring the safety of the disembarking passengers
· Ensuring the safety of the car in its stopped posture
· Not marring the traffic during its stop
Imagine for a moment what the AI would need to do to derive a drop-off spot based on those kinds of salient criteria.
The sensors of the self-driving car, such as the cameras, radar, ultrasonic, LIDAR, and other devices would need to be able to collect data in real-time about the surroundings of the destination, once the self-driving car has gotten near to that point, and then the AI needs to figure out where to bring the car to a halt and allow for the disembarking of the passengers. The AI needs to assess what is close to the destination, what might be an unsafe spot to stop, what is the status of traffic that’s behind the driverless car, and so on.
Let’s also toss other variables into the mix.
Suppose it is nighttime, does the drop-off selection change versus when dropping off in daylight (often, the answer is yes). Is it raining or snowing, and if so, does that impact the drop-off choice (usually, yes)? Is there any road repair taking place near to the destination and does that impact the options for doing the drop-off (yes)?
If you are saying to yourself that the passenger ought to take fate into their own hands and tell the AI system where to drop them off, yes, some AI developers are incorporating Natural Language Processing (NLP) that can interact with the passengers for such situations, though this does not entirely solve this drop-off problem.
Because the passenger might not know what is a good place to drop-off.
I’ve had situations whereby I argued with a ridesharing driver or cabbie about where I thought I should be dropped-off, yet it turned out their local knowledge was more attuned to what was a prudent and safer place to do so.
Plus, in the case of autonomous cars, keep in mind that the passengers in the driverless car might be all children and no adults. This means that you are potentially going to have a child trying to decide what is the right place to be dropped off.
I shudder to think if we are really going to have an AI system that lacks any semblance of common-sense be taking strict orders from a young child, whereas an adult human driver would be able to counteract any naïve and dangerous choice of drop-offs (presumably, hopefully).
For the use of Natural Language Processing in socio-conversations, see my discussion here: https://aitrends.com/features/socio-behavioral-computing-for-ai-self-driving-cars/
For my explanation about why it is that AI self-driving cars will need to drive illegally, see this link: https://aitrends.com/selfdrivingcars/illegal-driving-self-driving-cars/
For the role of children as riders in AI autonomous cars, see my indication here: https://www.aitrends.com/ai-insider/children-communicating-with-an-ai-autonomous-car/
For my insights about how nighttime use of AI self-driving cars can be difficult, see this link: https://www.aitrends.com/ai-insider/nighttime-driving-and-ai-autonomous-cars/
For the role of ODD’s in autonomous cars, here’s my discussion: https://www.aitrends.com/ai-insider/amalgamating-of-operational-design-domains-odds-for-ai-self-driving-cars/
More On The Drop-off Conundrum
The drop-off topic will especially come to play for self-driving cars at a Level 4, which is the level at which an autonomous car will seek to pullover or find a “minimal risk condition” setting when the AI has reached a point that it has exhausted its allowed Operational Design Domain (ODD). We are going to have passengers inside Level 4 self-driving cars that might get stranded in places that are not prudent for them, including say young children or perhaps someone elderly and having difficulty caring for their own well-being.
It has been reported that some of the initial tryouts of self-driving cars revealed that the autonomous cars got flummoxed somewhat when approaching a drop-off at a busy schoolground, which makes sense in that even as a human driver the chaotic situation of young kids running in and around cars at a school can be unnerving.
I remember when my children were youngsters how challenging it was to wade into the morass of cars coming and going at the start of school day and at the end of the school day.
One solution apparently for the reported case of the self-driving cars involved re-programming the drop- off of its elementary school aged passengers at a corner down the street from the school, thus apparently staying out of the traffic foray.
In the case of my own children, I had considered doing something similar, but subsequently realized that it meant they had a longer distance to walk to school, providing other potential untoward aspects and that it made more sense to dig into the traffic and drop them as closely to the school entrance as I could get.
Some hope that Machine Learning and Deep Learning will gradually improve the AI driving systems as to where to drop off people, potentially learning over time where to do so, though I caution that this is not a slam-dunk notion (partially due to the lack of common-sense reasoning for AI today).
Others say that we’ll just all have to adjust to the primitive AI systems and have all restaurants, stores, and other locales all stipulate a designated drop-off zone.
This seems like an arduous logistics aspect that would be unlikely for all possible drop-off situations. Another akin approach involves using V2V (vehicle-to-vehicle) electronic communications, allowing a car that has found a drop-off spot to inform other nearing cars as to where the drop-off is. Once again, this has various trade-offs and is not a cure-all.
It might seem like a ridiculous topic to some, the idea of worrying about dropping off people from autonomous cars just smacks of being an overkill kind of matter.
Just get to the desired destination via whatever coordinates are available, and make sure the autonomous car doesn’t hit anything or anyone while getting there.
The thing is, the last step, getting out of an autonomous car, might ruin your day, or worse lose a life, and we need to consider holistically the entire passenger journey from start to finish, including where to drop-off the humans riding in self-driving driverless cars.
It will be one small step for mankind, and one giant leap for AI autonomous cars.
Copyright 2020 Dr. Lance Eliot
This content is originally posted on AI Trends.
[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: https://forbes.com/sites/lanceeliot/]
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