Two Visions for Self-Driving Cars

I was at a conference last week and I talked to three different people who believe that driverless cars are going to need extremely fast broadband connections. They cite industry experts who say that the average car is going to require terabytes per day of downloaded data to be functional and that only extremely fast 5G networks are going to be able to satisfy that need. These folks talk about needing high-bandwidth and very low latency wireless networks that can tell a car when to stop when encountering an obstacle. This vision sees cars as somewhat dumb appliances with a lot of the brains in the cloud. I would guess that wireless companies are hoping for this future.\

But I also have been reading about experts that instead think that cars will become rolling data centers with a huge amount of computing capacity on board. Certainly vehicles will need to communicate with the outside world, but in this vision a self-driving car only needs updates on things like the current location and for road conditions and traffic problems ahead – but not the masses of data anticipated by the first future vision cited above.

For a number of reasons I think the second vision is a lot more likely.

  • Self-driving cars are almost here now and that means any needed network to support them would need to be in place in the near future. That’s not realistically going to happen. Most projections say that a robust 5G technology is at least a decade away. There are a dozen companies investing huge sums on self-driving car technologies and they are not going to wait that long to even investigate if controlling cars from external sources makes sense. Every company looking into self-driving technology is operating under the assumption that the brains and sensing must be in the cars – and they are the ones that will drive the development and implementation of the new car technology. It’s not practical to think that the car industry can wait for deployment of the needed networks that are not under their control or reasonably available.
  • Who’s going to make the huge investments needed to build the network necessary to support self-driving cars? The ability to deliver terabytes of data to each car would require much faster data connections than can be delivered using the normal cellular frequencies. Consider how many fast simultaneous data connections would be needed to support all of the cars on a busy multilane highways in a major city. It’s an engineering challenge that would probably require using high frequencies. And that means putting lots of cell sites close to roads – and those cell sites will have to be largely fed by fiber to keep the latency low (wireless backhaul would add significant latency). Such a network nationwide would have to cost hundreds of billions of dollars between the widespread fiber and the huge number of mini-cell sites. I can’t picture who would agree to build such a network. The total annual capital budget for all of the wireless companies combined today is only in the low tens of billion range.
  • Even if somebody was to build the expensive networks who is going to pay for it? It seems to me like every car would need an expensive monthly broadband subscription, adding significantly to the cost of owning and driving a car. Most households are not going to want a car that comes with the need for an additional $100 – $200 monthly broadband subscription. But my back-of-the envelope tells me that the fees would have to be that large to compensate for such an extensive network that was built mostly to support self-driving cars.
  • The requirement for huge numbers of cars to download terabytes of data per day is a daunting challenge. The vast majority of the country today doesn’t even have a landline based broadband connection capable of doing that.
  • There are also practical reasons not to put the brains of a car in the cloud. What happens when there are power outages or cellular outages. I don’t care how well we plan – outages happen. I’d be worried about driving in a car if there was even just a temporary glitch in the network.
  • There are also issues of physics if this network requires any connections to be made by millimeter wave spectrum, or even spectrum that is just a little lower on the frequency scale. There is a huge engineering challenge to get such signals to track a moving vehicle reliably in real-time. Higher frequencies start having doppler shifts even at walking speeds. Compound this with the requirement to always have true line-of-sight and also the issue of connecting with many cars at the same time on crowded roads. I have learned to never say that something isn’t possible, but this presents some major engineering challenges that are going to take a long time to make work – maybe decades, and maybe never.
  • Finally are all of the issues having to do with security. I’m personally more worried about cars being hacked if they are getting most of their communications from the cloud. If cars are instead only getting location and other basic information from the outside it would be a lot easier to wall of the communications stream from the operating computing process, and reduce the chances of hacking. It also seems like a risk if cars get most of their brains from the cloud for a terrorist or mischief-maker to disrupt traffic by taking out small cell sites. There would be no way to ever make such devices physically secure.

I certainly can’t say that we’ll never have a time when self-driving cars are directed by a large outdoor cloud, as often envisioned in science fiction movies. But for now the industry is developing cars that are largely self-contained data centers and that fact alone may dictate the future path of the industry. The wireless carriers see a lot of potential revenue from self-driving cars, but I can’t imagine that the car industry is going to wait for them to develop the needed infrastructure.

Lidar

Tribrid_CarThere have been a mountain of articles about self-driving cars, but little discussion about how they see the world around them. The ability of computers to understand images is still in its infancy – in 2015 there was a lot of talk about how Google was teaching an AI program how to recognize cats within videos.

But obviously a self-driving car has to do a lot better than just ‘seeing’ around it – it needs to paint a 3D picture of everything around it in order to navigate correctly and to avoid problems. It turns out that the primary tool used by self-driving cars is called “Lidar.” Lidar stands for ‘light detection and ranging’ and fits neatly between sonar and radar.

Lidar works by sending out light beams and measuring how long it takes for reflected signals to return, much the same way that a bat sees the world using sonar. Sonar would be fairly useless in a self-driving car since sound waves get distorted in air and only paint an accurate picture for perhaps a dozen feet from the transmitter. That’s great for a bat catching a moth, but not useful for seeing oncoming traffic.

And the radio waves used in radar won’t really work well for self-driving cars. Radar works great for seeing objects far away, like metallic airplanes. But the radio waves pass through many objects (like people) meaning that radar doesn’t create a total picture of the world around it. And radar has problems creating an accurate picture of anything closer than 100 feet.

And that’s where lidar comes in. A lidar device works much like a big radar dish at an airport. It rotates and sends out light signals (actually infrared light signals) and then collects and analyzes the returning echoes to create a picture of the distances to objects around it. Lidar only became practical with modern computer chips which allow the transmitter to ‘rotate’ hundreds of times a second and which possess enough computing power to make sense of the echoed light waves.

And so a self-driving car doesn’t ‘see’ at all. The cars do not rely on standard cameras that try to make sense of the reflected ambient light around the car. The first prototypes of driverless cars tried to do this and could not process or make sense of images fast enough. Instead self-driving cars send out laser light at a specific frequency and then calculates the distance the light travels in every direction to create a picture of the world.

If you want to understand more about what this looks like, consider this Radiohead music video. Most of the images in the video were created with lidar. Don’t pay too much attention to the opening headshots because those are somewhat distorted for artistic effect. But the later images of seeing streets shows you the detail of a lidar image. Unlike the normal images our eyes see, a lidar image is massively more detailed in that the distance to everything in such a picture is known. Our eyeballs basically see in 2D and we use images from two eyes to simulate 3D. But a lidar image is fully 3D and gets full perspective from one transmitter.

Lidar does have limitations. It can be ‘blinded’ by heavy snows and rains. Lidar could be jammed by somebody transmitting a bright signal using the same light frequencies. And so smart cars don’t rely 100% on lidar but also use traditional cameras and sonar using the ultrasound frequencies to complement the lidar images.

Lidar is finding other uses. It’s being used, for example, in helicopters to search for things on the ground. A lidar system can spot a fleeing criminal or a lost child in the woods far more easily than older technologies or human eyeballs. Lidar can also create amazingly detailed images of anything. Archeologists are using it to create permanent images of dig sites during various stages of excavation before objects are removed. It’s not hard to think that within a few years that many traditional surveying techniques will be obsolete and that lidar will be able to locate and plot everything on a building lot, for example, down to the millimeter.

Do We Need 10 Gbps?

wraparound-glassesWe are just now starting to see a few homes nationwide being served by a 1 Gbps data connection. But the introduction of DOCSIS 3.1 cable modems and a slow but steady increase in fiber networks will soon make these speeds available to millions of homes.

Historically we saw home Internet speeds double about every three years, dating back to the 1980s. But Google Fiber and others leapfrogged that steady technology progression with the introduction of 1 Gbps for the home.

There are not a whole lot of home uses today that require a full gigabit of speed – but there will be. Home usage of broadband is still doubling about every three years and homes will catch up to that speed easily within a few years. Cisco recently said that the average home today needs 24 Mbps speeds but by 2019 will need over 50 Mbps. It won’t take a whole lot of doublings of those numbers to mean that homes will expect a lot more speed than we are seeing today.

There is a decent chance that the need for speed is going to accelerate. Phil McKinney of CableLabs created this video that shows what a connected home might look like in the near future. The home owns a self-driving car. The video shows a mother working at home with others using a collaboration wall, with documents suspended in the air. It shows one daughter getting a holographic lecture from Albert Einstein while another daughter is talking with her distant grandmother, seemingly in a meadow somewhere. And it shows the whole family using virtual / enhanced reality goggles to engage in a delightful high-tech game.

This may seem like science fiction, but all of these technologies are already being developed. I’ve written before about how we are at the start of the perfect storm of technology innovation. Our past century was dominated by a few major new technologies and the recent forty years has been dominated by the computer chip. But there are now literally dozens of potentially transformational technologies all being developed at the same time. It’s impossible to predict which ones will have the biggest influence on daily life – but many of them will.

Most of these new technologies are going to require a lot of bandwidth. Whether it’s enhanced reality, video collaboration, robots, medical monitoring, self-driving cars or the Internet of Things, we are going to see a lot of needs for bandwidth much greater than today’s surge due to video. The impact of video, while huge today, will pale against the bandwidth needs of these new technologies – particularly when they are used together as implied in this video.

So it’s not far-fetched to think that we are going to need homes with bandwidth needs beyond the 1 Gbps data speeds we are just now starting to see. I’m always disappointed when I see ISP executives talking about how their latest technology upgrades are making them future proof. There are only two technologies that can meet the kinds of speeds envisioned in McKinney’s video – fiber and cable networks. These speeds are not going to be delivered by telephone copper or wirelessly, and to think so is to ignore the basic physics underlying each technology.

Some of the technologies shown in KcKinney’s video are going to start becoming popular within five years, and within twenty years they will all be mature technologies that are part of everyday life. We need to have policies and plans that look towards building the networks we are going to need to achieve that future. We have to stop having stupid government programs that throw away money on expanding DSL and we need to build networks that have use beyond just a few years.

McKinney’s video is more than just an entertaining glimpse into the near-future; it’s also meant to prod us into making sure that we are ready for that future. There are many companies today investing in technologies that can’t deliver gigabit speeds – and such companies will grow obsolete and disappear within a decade or two. And policies that do anything other than promote gigabit networks are a waste of time and resources.

New Technologies and the Business Office

old robotI often write about new technologies that are just over the horizon.  Today I thought it would be interesting to peek ten years into the future and see how the many new technologies we are seeing today will appear in the average business office of a small ISP. Consider the following:

Intelligent Digital Assistants. Within ten years we have highly functional digital assistants to help us. These will be successors to Apple’s Siri or Amazon’s Alexa. These assistants will become part of the normal work day. When an employee is trying to find a fact these assistants will be able to quickly retrieve the needed answer. This will be done using a plain English voice interface and employees will no longer need to through a CRM system or do a Google search to find what they need. When an employee wants a reminder of where the company last bought a certain supply or wants to know the payment history of a given customer – they will just ask, and the answer will pop up on their screen or be fed into an earbud or other listening device as appropriate.

Telepresence. It will start becoming common to have meetings by telepresence, meaning there will be fewer face-to-face meetings with vendors, suppliers or customers. Telepresence using augmented reality will allow for a near-real life conversation with a person still sitting at their own home or office.

Bot-to-Bot Communications. The way you interface with many of your customers will become fully automated. For instance, if a customer wants to know the outstanding balance on their account they will ask their own digital assistant to go find the answer. Their bot will interface with the carrier’s customer service bot and the two will work to provide the answer your customer is seeking. Since there is artificial intelligence on both sides of the transaction the customer will no longer be limited to only asking about the few facts you make available today through a customer service GUI interface.

Self-Driving Cars. At least some of your maintenance fleets will become self-driving. This will probably become mandatory as a way to control vehicle insurance costs. Self-driving vehicles will be safer and they will always take the most direct path between locations. By freeing up driving time you will also free up technicians to do other tasks like communicating with customers or preparing for the next customer site.

Drones. While you won’t use drones a lot, they are far cheaper than a truck roll when you need to deliver something locally. It will be faster and cheaper to use drones to send a piece of electronics to a field technician or to send a new modem to a customer.

3D Printing. Offices will begin to routinely print parts needed for the business. If you need a new bracket to mount a piece of electronics you will print one that will be an exact fit rather than have to order one. Eventually you will 3D print larger items like field pedestals and other gear – meaning you don’t have to keep an inventory of parts or wait for shipments.

Artificial Intelligence. Every office will begin to cede some tasks to artificial intelligence. This may start with small things like using an AI to cover late night customer service and trouble calls. But eventually offices will trust AIs to perform paperwork and other repetitive tasks. AIs will take care of things like scheduling the next day’s technician visits, preparing bank deposit slips, or notifying customers about things like outages or scheduled repairs. AIs will eventually cut down on the need for staff. You are always going to want to have a human touch, but you won’t need to use humans for paperwork and related tasks that can be done more cheaply and precisely by an AI.

Robots. It’s a stretch to foresee physical robots in a business office environment in any near-future setting. It’s more likely that you will use small robots to do things like inspect fiber optic cables in the field or to make large fiber splices. When the time comes when a robot can do everything a field technician can do, we will all be out of jobs!