I had heard about this incident in Las Vegas a few weeks ago where an autonomous vehicle ran over a robot and was planning a serious missive to discuss what some of the ramifications of this is, with respect to the autonomous vehicle space. But, first I need to get the LOL out of the way. You have to admit, it is funny.
What this does is bring out one of the issues that exists in the self-driving space. The details are not all that important. But, briefly, the car was a Tesla, the robot was one of those host models that is being developed to act as a service unit in places such as museums, hotels, banks, shopping and business centers. It is the next generation of a robot that has the capability to maneuver around obstacles and move its head and arms (Danger, Will Robinson!). It also has a display to interact with people and give them information.
The accident details were, simply, a robot gone rogue. One of several, it somehow lost its bearing and headed for the street, where the Tesla, which was in self-driving mode, mowed it down. Here is what is funny. The police were called. Seriously?
Shades of Westworld and Futureworld movies. Of course, the robot (affectionately called Promobot) will be given a post mortem to see why it went rogue.
Now – the real-world implications. Unless you live under a rock you are aware that this is not the first time there has been a mishap with self-driving vehicles. While this one may have a bit of a comic relief, the others were very serious. One happened last year when an autonomous Uber vehicle killed a pedestrian. In an another incident, a Tesla vehicle was involved in a fatal accident in 2018 when the autopilot system was engaged. As well, there have been other incidents prior to those.
One of the arguments is that there are bound to be accidents involving autonomous vehicles. Why? Because, first of all, there are just too many circumstances that cannot be preemptively foreseen. The same can be said for human drivers. However, with humans, there is the element of intuition (the non-scientific term), which enables cognitive reactions to recognize, ever so slight, deviations from the norm. Such capabilities will never exist, at least not for the foreseeable future, in an autonomous vehicle.
We can come close, with tons of pre-programmed scenarios, but will that be good enough? Perhaps, when quantum computing does a Vulcan mind meld with AI, and big data algorithms are refined, the space will narrow. But for now, the reality is that there are just too many variables to be handled by current autonomous vehicle technology.
However, there are arguments that an autonomous vehicle ecosystem will be much safer than the present driver-controlled one. Amen to that, but it will not occur until we reach the tipping point where both autonomous vehicles and driver vehicles are operating under a controlled environment. As long as human judgement and free will driving is involved, errors will continue to occur at about the same rate they are, presently. Autonomous vehicles will remove the judgement errors but will introduce other errors (although they should be significantly less among autonomous vehicles).
The interesting thing here is that the Tesla hit the robot just as it would have hit a pedestrian under the same conditions. Non-human devices cannot be expected to differentiate on an emotional scale. There can be certain parameters programmed into the mechanics (such as heat sensors) to give the device more data (unless you live in Alaska or some other frozen land where everything is cold), or character (facial) recognition algorithms (if the data is coming from the front of the human) that hedges the bet. But this is not foolproof either.
One can also go in the opposite direction and simply stop the autonomous vehicle if there is any uncertainty in the scenario, But, then it will get rear-ended by the driven vehicle because the driver happens to be texting. The industry does not have that figured out quite yet.
What all this brings up is that we are a long way away from anything other than driver assist, no matter how advanced it gets. This will be the scenario for years to come. The nice thing is that driver assist will become much more intelligent and offer more options. But letting the vehicle drive itself is not one of them in the near future.
Whether it is a robot, or a human that gets nailed by an autonomous vehicle, the end result is the same in the absolute sense that it was an incident involving a driverless vehicle. That means we have quite a ways to go before we have level 5 autonomy.
My position is that we will not have a fully autonomous vehicle infrastructure until everything and everyone can be precisely identified, and communication is two-way. That is years out.
RIP Little Promobot!
Komatsu America, a heavy equipment manufacturer, has qualified to operate an autonomous haulage system (AHS) using private LTE mobile broadband technology, a first for the mining industry.
Komatsu’s FrontRunner AHS allows unmanned operation of ultra-class mining trucks, which are designed improve mine-site safety, reduce costs, and increase productivity.
The company completed a year-long qualification program on Nokia’s Future X infrastructure. The industry is moving away from less predictable wireless technologies such as Wi-Fi, and toward private LTE networks, that improve security, capacity, and overall performance within a multi-application environment, according to a Komatsu official.
In November of last year, Nokia unveiled “Future X for industries,” which is a strategy and architecture to increase productivity across industrial sectors. The strategy, which will span both advanced LTE and 5G will exploit multiple technologies including industrial internet of things (IIoT), distributed (edge) cloud, augmented intelligence, augmented and virtual reality.
Kathrin Buvac, president of Nokia Enterprise, said, “Private LTE is a key element in the Nokia Bell Labs Future X architecture to help industries such as mining create an intelligent, dynamic, high-performance network that increases the safety, productivity and efficiency of their business.”
Testing autonomous vehicles can be tricky. When its autonomous vehicle struck and killed a woman in March, Uber suspended testing in Tempe, Arizona, as well as in Pittsburgh, San Francisco and Toronto. The government in South Korea may have found a way around that problem.
Also in March, presumably, after the accident, the government brought 188 companies together, including Hyundai, Samsung and SK Telecom, to study autonomous vehicle development. What resulted was a much safer way to test these cars by building an unpopulated city.
Work on K-City was recently completed for testing autonomous vehicles using 5G networks, Yonhap News Agency recently reported. The mock urban area, located southwest of Seoul, spans 223 square miles at a cost of $11 million.
K-City has five testing environments — highway, downtown road, suburban street, parking lot and community facilities — for autonomous vehicles, according to Yonhap.
In particular, the 5G networks will allow companies, universities and research institutes to test a variety of connected car services in those different environments, the ministry said.
Samsung Electronics and the Korea Transportation Safety Authority (KOTSA) plan to build 4G LTE, 5G and V2X networks to support the testing area, according top TAAS Magazine.
Ten testing sites for automated vehicle technologies were selected in the United States early in 2017 from more than 60 applicants, according to Forbes. However, in October of this year, the Trump Administration dropped the existing federally-recognized “automated vehicle proving grounds” as it prepared a new autonomous vehicle testing initiative.
I have long taken the position that a five-nines autonomous vehicular (AV) ecosystem is a two-way street (pun intended) and smart vehicles need smart roads.
That can be accomplished in a number of ways, but, however it is done, it is absolutely critical to any kind of fully autonomous system, IMHO. The only way I might be persuaded take that back is if we can deliver a 100 percent driverless platform as a ubiquitous, fully automated transportation system. Then roads can, probably, be left out of the equation. However, I really do not see that happening any time soon.
Presently, AV technology consists, primarily, of sensors – both on the vehicle and in the environment. The number, type, and sophistication of sensors boggles the mind; however, they all have the same thing in common – they simply sense. They are designed to do that and they do it well. The missing “man” is real-time, two-way communications. If roads were integrated with sensors and wireless transceivers, this would be a slam-dunk.
Some basic wireless one-way and two-way communications do exist. So to say there are none is not a fair statement. However, they are simple and narrow in function. They involve easy to implement communications such as those between vehicles and traffic signals, or parking meters and work with a limited number of parameters. These use subsystems already in place (cellular, Wi-Fi).
For a long time, it was believed that as dedicated, short-range communications (DSRC), an IEEE backed standard, would become the de facto vehicle to everything (V2X) commo net. However, recently, cellular vehicle to everything (C-V2X), pushed by special interests (telecos and some OEMs), has emerged and is challenging DSRC’s position. There is now competition backed by the particular interests of each technology. However, whichever one, (I am betting on both) prevails, it still cannot compensate for the lack of active, interconnected surface intelligence.
There is, however, some movement in smart roads beginning to emerge. Granted it is a monumental undertaking to make all road smart, but it is an undertaking that MUST, eventually, be tackled.
Recently, a startup company called Integrated Roadways has decided to take this on. They point to the fact that nearly half of all roadways in the United States are in need of investment – from resurfacing to replacing. This is a huge cost for public agencies, which are constantly asserting their inability to pay, let alone invest in tech-infused roads to improve the driving experience.
However, there may be a silver lining on the horizon.
Integrated Roadways believes it has a solution, in the form of commercial technology embedded inside public infrastructure which can be monetized to pay for itself.
Coming down the road (pun intended) are the next generations of wireless interconnect (Internet of Everything/Everyone – IoX, 5G, the Edge). This presents a tremendous opportunity to collect and analyze data (big data, if you will). If one thinks about it, it could, potentially, be one of the biggest RoI tickets coming down the “road.” Integrated Roadways’ belief is that data generated from all parts of a smart infrastructure could be monetized to pay for public services and take the increasing burden off the taxpayer, allowing for major infrastructure upgrades, both on and off the road.
Making streets smart will be challenging, especially considering all the entities involved. But I have to believe the amount of money involved will incentivize just about all of them. If I remember correctly, that was initially a concern in laying out a fiber infrastructure. Yet, slowly but surely, it has happened.
Making roadways smart is not that big a technological challenge. Installing wireless sensors during repaving, or building them into down precast pavement is the easy part. Literally, all of them can be commercial off-the-shelf components (COTS). The difficulty lies with such things as power, RF permeability, environmental challenges (impact from the various types of traffic), security, wireless network integration, durability, weather, and more. These are formidable.
Integrated Roadways has come up with a basic concept. And has one test bed out there. Sensors, processors, antenna and other technology, are housed in a cylinder inside the slab itself while a fiber optic strain mesh, laminated to the slab’s reinforcement, acts as a trackpad able to identify vehicle tire positions. Routers inside the slabs then connect to slab neighbors and send information to data centers alongside the roadway.
There is much more to this and many more possible vectors, but one gets the picture.
As far as the costs go, Integrated Roadways says the cost of its smart slabs averages about $4 million per lane, per mile. America’s current national rate is about $2 million per lane, per mile for a comparable concrete pavement. According to them, in the past 15 years, the cost of concrete paving has doubled and is projected to double again over the next 15 years, while the cost of precast paving has fallen 90 percent. Therefore, the cost differential is expected to disappear over the next few years.
And, of course, the bottom line to all this is that the data provided by smart roads (not just traffic, but imagine the possibilities of all kinds of data being sniffed from smart vehicles, including occupant activities, number of riders, destination, etc.), is marketable.
While this is just a fundamental concept, with limited data based on one technology, the potential to develop verticals is staggering. The benefit to any number of vectors, safety, efficiency, costs, not to mention RoI, is also significant. If we start on this now and integrate it into the evolution of this infrastructure, it will offer so many more opportunities, as well as benefits, to the entire smart “X” ecosystem. Is it challenging? Of course. But so was flying.
For the most part, the various sectors of the next generations of just about everything develop at their own pace until such time that the technologies can meld and the whole becomes greater than the sum of the parts.
There are so many vectors out there that, over the next decade, will become inextricably interwoven at any number of levels. These are all complementary to one degree or another. Artificial Intelligence will, most certainly play big in 5G, the cloud, the edge, smart “x”, self-driving “x” security, and so many more. In addition, each of these will, in turn, complement other technologies as well.
So far, we have seen little cross-pollination, except for, perhaps, AI. Recently I received a stream about how a Finnish research organization, VTT Technical Research Centre, and Nokia are moving in the direction of integrating 5G and autonomous vehicles. They are examining how 5G will transmit and receive data in the autonomous driving space.
At the moment, the work is focused on sensors that can be used to acquire data such as road conditions, traffic patterns, traffic flow and more. This first step will use radar, LiDAR and camera systems to exchange data from the vehicle and the infrastructure. Concurrently, data sensed by the infrastructure (weather, traffic cameras, lights, etc.) will be collected and sent to the vehicles. The goal is to use the Internet of Everything/Everyone (IoX) and its devices to interconnect with cloud-based servers to process information and disseminate it to the autonomous vehicle network. Data will be analyzed as to the location and be forwarded to edge networks relative to the information.
The two critical elements that 5G will bring to this, and why 5G will be necessary for it, is latency and bandwidth. For autonomous vehicles to function, efficiently and safely, data will be required in about as real-time as it gets – and there will be gobs of it. There can be no bandwidth bottlenecks. Redundancy must be absolute. 5G promises to make that happen.
In 5G, latency and bandwidth are two of the parameters that elevate it beyond present technologies. However, in the end, 5G will not only add new technologies but it will be the integration of all wireless technologies in its final form.
That is a critical theme in autonomous vehicles. While latency and bandwidth will be critical for real-time functionality, they are not the only criterion and will not be available ubiquitously, at least not for many years.
With most applications of enhanced mobile broadband (eMBB), speed bumps can be tolerated. They may be an annoyance, but few will affect life-safety. Not so with autonomous vehicles. We do not, really, have a sense for how much bandwidth or latency will be required for a five-nines reliability factor for autonomous vehicle (personally I’m waiting for nine-nines). However, the number of messages that will be interchanged in this ecosystem, between vehicles and the infrastructure will easily be in the thousands per second. The trick will be to integrate other platforms, 4G, ITS G5, satellite, unlicensed, etc. to make sure the autonomous vehicle infrastructure has what it needs, wirelessly, when and where it needs it.
For example, lonely Wyoming highways will not have the same autonomous vehicle infrastructure requirements as New York or Los Angeles. Therefore, bandwidth and latency parameters may be able to be handled by technologies other than 5G.
As well, if there is a disconnect between the vehicle and the infrastructure, for whatever reason, autonomous vehicles still need to function. How that will work is still, for the most part, on the drawing boards and varies widely according to geography. Of course, in such a case, the vehicle can always fall back to level two or three, assuming that option is still available.
There are many elements that will be part of the autonomous vehicle infrastructure. The same can be said for every other infrastructure as well (as I mentioned at the beginning). We are only beginning to comprehend the various interconnect technologies and platforms will have as the various ecosystems evolve. What is encouraging is that the various industries are beginning to look beyond the 5G race hype, simply for the sake of 5G, to what the end value of 5G technologies will be.