Tag Archives: autonomous vehicles

New Push on Autonomous Vehicles

As I got set to write this post on Sunday night, I saw a tweet recommending that I go to bed early and get plenty of rest so I can wake up early and do my part in what may be the least productive week at least in American history, if not the world’s.

Maybe we’ll get lucky, and the contours of the results from the U.S. presidential election on Tuesday will be clear enough, quickly enough, that we’ll be able to focus on normal activities and not be distracted by legal fights and protests, but I’m not counting on it. My younger daughter, in her third year of law school in DC, got an email from the administration over the weekend recommending that she stock up on food, medicines and any other essential supplies as though she were going to be snowed in for a week. That feels about right.

With the world perhaps about to go on hold, I’ll just lob in one, quick thought in this week’s Six Things and hope I get to you before we all disappear into Twitter and cable news for however long it takes to sort out the results of the election. The thought is this: While autonomous vehicles have faded from the discussion since an Uber killed pedestrian Elaine Herzberg in March 2018, AVs are being positioned for a resurgence.

Some of the positioning is official and from the rock-solid actors in the autonomous space. Google’s Waymo unit announced last month that it will begin offering fully driverless service (as in, with no safety driver behind the wheel) to customers of its ride-hailing operation in Phoenix. General Motors said that its Cruise unit will begin operating fully driverless vehicles in San Francisco by the end of the year.

Some of the positioning is more speculative. Tesla followed Google/Waymo and GM/Cruise by announcing that it has begun rolling out to customers what it calls Full Self-Driving as part of a beta test that will lead to a general rollout perhaps by year-end. This would be enormous news, if everything goes as advertised, but Elon Musk has long claimed self-driving capabilities that go beyond what his cars can actually do. With the latest announcement, Musk is claiming that his cars will be able to operate autonomously without access to the sort of carefully calibrated maps that Waymo, Cruise and others prepare before letting their vehicles operate in an area and believe are crucial. Musk is also planning to go live even though he doesn’t seem to have done the kind of extensive on-road testing that Waymo and Cruise emphasize. Many in the industry still doubt that Tesla’s basic technology is up to the task of providing full autonomy; conventional wisdom is that autonomous vehicles require lidar — essentially, a laser-based form of radar — while Musk uses cameras but no lidar.

Some of the positioning is subtle — and this is the part that interests me the most, because I think it may have the biggest impact in the long term. In the wake of the accident that killed Herzberg 2 1/2 years ago, AV companies seemed to fall back and regroup. Now, having done far more rigorous testing, AV companies are starting to resurface with the sort of data that could sell the public on the safety of letting a car drive them around with no one sitting behind the wheel.

Waymo, as usual, led the way, with a report last week on the performance of its driverless cars from the beginning of 2019 through the third quarter of 2020 — and the data is impressive. The vehicles were extremely safe, and — importantly, for building long-term trust — Waymo got specific about its record, using National Highway Traffic Safety Administration standards and going well beyond the press release treatment that usually obscures what actually happened.

Waymo reported 6.1 million miles of automated driving, including 65,000 with no safety driver, and 47 “contact events” — consisting of 18 actual collisions and 29 incidents where a safety driver intervened to prevent a collision and where Waymo then simulated what would have happened without a safety driver. That’s one contact every 130,000 miles, in case you’re scoring at home and want to see how your experience compares with that of the Waymo cars.

Thirty of the 47 “events” resulted in no injuries (or were projected to produce none). None produced “severe” or “life-threatening” injuries (or were projected to in the simulations). While the report wasn’t specific in assigning blame, it said that “virtually all” incidents resulted from an error by a human driver in the other car or by a pedestrian/cyclist. In the eight “most severe or potentially severe” incidents — including a car running a red light at 36 mph and T-boning a Waymo vehicle — Waymo said mildly that “road rule violations” by other drivers contributed.

In the one event where blame likely would have been assigned to Waymo, because it would have rear-ended the car in front of its vehicle, the report suggests that the human driver of the other car was instigating the collision — its driver swerved in front of the Waymo car, then slammed on its brakes, the sort of behavior that is often reported about drivers showing resentment of AVs. In any case, the safety driver saw what was happening and prevented a collision, which simulation showed would have occurred at 1mph.

There’s still a long way to go on AVs, but the announcements by Waymo, Cruise and Telsa show that companies are pressing ahead, and the report by Waymo starts to lay the intellectual groundwork for what I think will be a strong claim for public trust. In any case, after 2 1/2 years of lying low, the AV companies are back to making public arguments for themselves, and the insurance industry will have to react — next week, or the week after, or the week after that, once the craziness from the election settles down.

Stay safe.

Paul

P.S. Speaking of public trust, if you haven’t voted already, please do so. We’re better as a people, as a nation, the closer we get to 100% participation by eligible voters.

P.P.S. Here are the six articles I’d like to highlight from the past week:

Property Claims: It’s Time for Innovation

Those that solve for the dynamics of the many opportunities are likely to be the future industry leaders.

Driving Into the Future of Telematics

Connected vehicles, and their shared language of data delivered through an exchange, are the future of telematics.

The Future of Underwriting

A survey finds that nearly everyone expects big changes in underwriting. But what will different look and feel like? And how ready are we?

Asia: Latest Source of Opportunities

Think of giants like Ping An; innovations such as TenCent’s Waterdrop; and ecosystem plays such as Rakuten.

State of Commercial Insurance Market

Every company today is different than it was six months ago. All risk profiles have likely changed.

Best AI Tech for P&C Personal Lines

The value rankings indicate that user interaction technologies fueled by AI are at the top of the list for personal lines insurers.

Musings on the Future of Driverless Vehicles

What might a future world look like where all transportation is via autonomous vehicles? Although we might be decades away from this vision, there are useful insights to be gained for today’s strategies in thinking through the possibilities. While I don’t personally own a crystal ball, this blog floats some ideas regarding what the future may hold.

In the meantime, SMA’s recent research report, Connected Vehicles and Insurance: Ten Strategic Considerations, provides some practical advice for insurance strategists today by identifying the potential value levers in the evolving connected vehicle area and exploring 10 strategic questions.

See also: Rapid Evolution of Autonomous Vehicles  

With that as background, here are 10 predictions for the future of transportation:

  1. Vehicle ownership by individuals will be so rare that people will need to visit theme parks for the “experience” of driving a car.
  2. People will be able to summon autonomous vehicles on demand for travel anywhere on the planet.
  3. Autonomous vehicles will be everywhere on land, on sea, in the air and underground – none will require drivers or operators. (For example, drone taxis will fill the skies.)
  4. Travel times will be significantly reduced as speed limits increase and high-speed transportation dominates. Very high-speed travel will be common via Hyperloop, supersonic aircraft or high-speed rail.
  5. The physical infrastructure for travel will be substantially different: no signs, no traffic controls and no fuel stations. The whole system of roadways will be transformed, with no need for median strips, lane markers, etc.
  6. All land-based vehicles will be powered by electricity and recharged directly from the road surface.
  7. The urban/suburban balance will change once again, with a concentration of individuals in mega-smart cities combined with new forms of living spaces and communities in rural/satellite areas. (Think about what could be done with all the garage space in residences when individuals do not own cars.)
  8. Vehicles of all types will be real-time, information-rich machines with augmented reality, virtual reality and instant access to information/entertainment content.
  9. Vehicular accidents will be virtually eliminated, but, when accidents do occur, they will be mega-accidents. (Imagine a software glitch or a freeway hack that causes pileups of hundreds of vehicles.)
  10. The variety of vehicles for transporting both people and goods will be astonishing, ranging from individual travel pods to gigantic vehicles transporting thousands of people at a time.

See also: Driverless Vehicles: Brace for Impact  

Also not to be forgotten is the complete reshaping of the industries that build vehicles, sell and service them and, of course, insure them. The journey to this future (or something like it) is highly uncertain in terms of timing and eventual outcomes; however, there is little debate that we are in the beginning of monumental transformation.

Rapid Evolution of Autonomous Vehicles

The 2008 animated Pixar movie “Wall-E” follows the refuse-based adventures of a sentient, autonomous trash compactor whose primary function was to clean an abandoned city on a now-deserted planet Earth, long ago having been abandoned by humanity. The movie highlights some of the issues that would likely occur from human beings’ over-reliance on an automated lifestyle – issues such as waste management, obesity and human environmental impact, to name a few. “Wall-E” is set hundreds of years in the future, but some of those issues ostensibly exist in the world we inhabit today.

The transportation sector around the globe is a multitrillion-dollar industry. There’s money and mistakes to be made. While we are probably a ways off from sentient automobiles, the age of vehicle autonomy is well upon us. Every week, another company releases some update, patch or application that nudges autonomous tech in a new direction.

There have been some setbacks – name me a sector that doesn’t have any – but cars that are less reliant on humans are here to stay. This is almost universally viewed as positive, with many examples given to support this position, such as:

  • Fewer accidents.
  • A move away from owned to rented vehicles, lessening the need for parking garages.
  • A productivity increase during commuting time.
  • A reduction in traffic congestion.

There are many more, but the age of connectivity comes with risks. One must exercise caution with any kind of new technology. What happens when things go wrong? Computers malfunction sometimes; we’re all familiar with Windows’ blue screen of death.

See also: Autonomous Vehicles: ‘The Trolley Problem’  

You are turning over your most precious commodity – your family – to a computer. And if that computer fails when you are trusting it not to – let’s say when it is in full autonomous mode – how will that fail affect things? In what manner will it fail? It will likely fail however the lowest-bidding subcontractor designed it to fail.

Even if it does not fail, a computer still needs to be told what to do, at least initially. Computers can learn things and eventually make better iterative decisions based on this learning, but what do you tell a computer it should do when faced with a myriad of input data?

Autonomous vehicles (ones that fly) have been around a long time. Most commercial airliners are autonomously piloted more than 90% of the time. Aircraft, along with the routes they take, are heavily regulated. They essentially all report in to the same system around the world. There is a reason all pilots around the world must communicate in English. There has to be one universal language to avoid miscommunication and errors.

Autonomous automobiles have none of that. There is no central control, no clearing house and no standardization, to the extent that even the levels of autonomy differ by manufacturer. They can, though, roughly be classified in the following manner:

Level 0 — Nothing

The baseline since Gottlieb Daimler traded horse power for horsepower. Level zero applies to all vehicles that rely solely on humans to dictate driving actions. That is my car, and almost every car that has come before it. At best it has cruise control, but it is the “dumb” version that will crash you into a wall if you let it. Example: my 2009 Honda Ridgeline truck.

Level 1 — Driver Assistance

What does this level offer us? Some automation, but not much. For level one, you are looking at adaptive cruise control or lane departure tech to come as standard on your vehicle. While the human driver still supervises everything, the vehicle is capable of some decisions on its own. Example: your eco-friendly neighbor’s 2016 Toyota Prius.

Level 2 — Partial Automation

We get a step up from driver assistance in level two. This combines multiple automated functions such as lane assist, automatic braking and adaptive cruise control to ensure they work in a smooth, coordinated fashion. Anticipating traffic signal changes, lane changes and scanning for hazards are still the domain of the driver. Example: the Audi your boss drives that has Traffic Jam Assist as standard.

Level 3 — Conditional Automation

A car running level three automation can take full control of the vehicle during certain parts of a journey under certain conditions and within certain parameters. The vehicle will, however, turn control back over to the human driver when it encounters a situation it cannot handle or when it cannot interpret input data. The onus is, therefore, on the driver to stay alert because the vehicle may prompt the driver to intervene at any moment. The incident in Tempe, AZ, in March 2018, involving a pedestrian fatality involved a vehicle running level three autonomy. Example: Tesla’s Autopilot.

Level 4 — High Automation

An auto at level four automation does not require a human to ride along during certain journeys, subject to geographic and road-type limitations. These are currently being tested, and we should see them within the next 18 months. Think Amazon last mile and pizza delivery vehicles. Example: Johnny Cab, from the original “Total Recall.”

Level 5 — Full Automation

At level five, absent inputting the destination, which will probably be done via your phone beforehand, there is no driver involvement. You will enter the vehicle, turn on your movie or laptop and that is it until you reach your destination. Example: KITT from “Knight Rider.”

Level 6 — Beyond Full Automation

Well, there is no level six – at least yet. What would level six look like if it did exist? A teleporter? Something that transports you from your bedroom, via the bathroom and kitchen, straight to the office? A flying car? We have returned to Wall-E territory. Example: The Jetsons’ Aerocar.

Technology in vehicles is designed to assist us and make us safer. For good reason, a few of the car and tech companies working on autonomous driving have said they do not want to release anything below level four. Either force people to drive, or let the machine do all of the work. Partial implementation runs the risk of scaring people away from the technology. The more reliant you are on tech, the tougher it is when you do not have it. When, in an instant, the computer turns full control back to you because its inputs are confusing, are you ready?

See also: Autonomous Vehicles: Truly Imminent?  

What does the future look like? We should expect a reduction in the frequency of accidents, but, given the complicated nature of what is now hidden under a fender, accidents will likely cost more (increased severity).

Software updates can be problematic. They do not work well on airplanes, for example. You would not release beta software for an airliner. A recent over-the-air software update by Tesla reportedly disabled the autopilot system. Too much automation in the cockpit or car, and things can go bad when the computer gets an input it does not understand.

Walt Disney promised us self-driving cars back in 1958. They are here – somewhat – but 60 years is a long time to wait in line. As a juxtaposition to that, with robotaxis already hitting our roads, the future has arrived more quickly than most people anticipated.

15 Hurdles to Scaling for Driverless (Part 3)

This is the third part of a three-part series. You can finds part 1 here and part 2 here.

Successful industrialization of driverless cars will depend on getting over many significant hurdles. Failure only requires getting tripped up by a few of them. In part two of this series, I outlined seven key hurdles to industrial-size scaling of driverless cars. Overcoming hurdles to scaling is not enough, however.

In this concluding article, I explore the challenges to broader market acceptance. I outline eight additional hurdles related to trust, market viability and managing secondary effects. All must be overcome for driverless cars to truly revolutionize transportation.

Trust. It is not enough for developers and manufacturers to believe their AVs are good enough for widespread use, they must convince others, too. To do so, they must overcome three huge hurdles:

8. Independent verification and validation. To date, developers have kept their development processes rather opaque. They’ve shared little detail about their requirements, specifications, design or testing. An independent, systematic process is needed to verify and validate developers’ claims of their AVs’ efficacy. Many are likely to demand this, including policy makers, regulators, insurers, investors, the public at large and, of course, customers. The best developers should embrace this—it would limit liability and distinguish them from laggards and lower-quality copycats.

9. Standardization and regulation. Industry standards and government regulation cover almost every aspect of cars today. Industrialization of driverless cars will require significant doses of both, too. Standards, especially those enforced by government regulation, ensure reliability, compatibility, interoperability and economies of scale. They also increase public safety and reduce provider liability.

10. Public acceptance. Most new products take hold by attracting early adopters. The lessons and resources from that initial success help developers “cross the chasm” to mainstream success. The industrialization of AVs will depend on much earlier and broader public acceptance. AVs affect not only the early-adopting customers inside them, but also every non-customer on and near the roads those AVs travel. Without widespread acceptance—including by those who would not choose to ride in the AVs—industrialization is not likely to be allowed.

See also: Where Are Driverless Cars Taking Industry?  

Market Viability. The next three hurdles deal with whether AV-enabled business models work in the short term and the long term, both in beating the competition and other opponents.

11. Business viability. Analyses of AV TaaS business models are generally optimistic about the possibility of providing service for much less than the cost of human-driven services or personal car ownership. Current cost-per-mile estimates are nowhere near long-term targets, however. Most players are also underestimating the cost to scale. It remains to be seen whether rosy market plans will survive contact with the marketplace.

12. Stakeholder resistance. As the old saying goes, one person’s savings is another’s lost revenue. The industrialization of driverless cars will require overcoming the resistance of a large host of potential losers, including regulators, car dealers, insurers, personal injury lawyers, oil companies, truck drivers and transit unions. This will not be easy, as the potential losers include some of the most influential policy shapers at federal, state and local levels.

13. Private ownership. AV TaaS services are only a waypoint on the path to transformation of the private ownership market. If AVs are to revolutionize transportation, they will have to appeal to consumers who have long preferred to own their own cars. Privately owned cars account for the vast majority of all cars and all miles driven.

Secondary Effects. Technology always bites back. The industrialization of AVs could induce huge negative secondary effects. Most will unfold slowly, but two consequences are already concerning and must be addressed as part of the industrialization process.

14. Congestion. Faster, cheaper and better transportation will deliver greater economic opportunity and quality of life—especially for those who might otherwise not have access to it, like the poor, handicapped and elderly. But, it might also cause a surge in congestion by driving up the number of vehicles and vehicle miles traveled. This happened with ride-hail services, including Uber and Lyft. According to a recent study by the San Francisco County Transportation Authority, for example, congestion in the densest parts of San Francisco increased by as much as 73% between 2010 and 2016. The ride-hail services collectively accounted for more than half of the increase in daily vehicle hours of delay.

15. Job loss. Some argue that the history of technology, including transportation technology, shows that new services will create more jobs, not less. Few argue, however, that the new jobs go to those who lost the old ones. There’s no getting around the fact that every AV Uber means one less human Uber driver—even if other jobs are created for engineers, maintainers, dispatchers, customer service reps, etc. The same holds true for AV shuttles, buses, trucks and so on. Early AV TaaS providers will operate under an intense spotlight on this issue. Providers will have to anticipate and ameliorate potential public and regulator backlash on job loss.

* * *

There’s an old saying in Silicon Valley that one should never mistake a clear view for a short distance. The revolutionary potential of AVs is clear. Yet, we are still far from the widespread adoption needed to realize their benefits.

Don’t mistake a long distance for an unattainable goal, though. As a close observer, I am enthusiastic (and pleasantly surprised) by the progress that has been made on AV technology. Leading developers like Waymo, GM Cruise, nuTonomy and their diaspora have raced to build AVs and progressed faster than many, just a few years ago, thought possible.

See also: Driverless Cars and the ’90-90 Rule’  

Industrialization is a marathon, not a sprint. It depends on overcoming many hurdles, including the 15 I’ve laid out. The challenges of doing so are great—likely greater than many current players (and their investors) perceive and are positioned to address. New strategies are needed. A shakeout is likely.

That’s how innovation and market disruption work. That is why most contenders fail and why outsized rewards go to those who succeed. Whoever thought that a phone maker or a search engine company could be worth a trillion dollars? Is it outlandish to believe, as I still do, that driverless cars would be worth multiple trillions?

15 Hurdles to Scaling for Driverless (Part 2)

Will driverless cars (AVs, for autonomous vehicles) live up to the revolutionary potential imagined by many, including me? In part one of this series, I asked whether AVs might develop like the Segway personal transporter and be relegated to narrow niche applications. To avoid going the way of the Segway, AV developers must overcome significant hurdles to scaling, trust, market viability and managing secondary effects.

In this article, I outline the challenges to scaling. Building and proving an AV is a big first step. Scaling AVs into industrial size and strength business operations delivering transportation as a service (TaaS) is an even bigger step. Here are seven giant hurdles related to scaling:

1. Mass production. Hand crafting or retrofitting a few thousand cars with AV technology is good enough for development and testing. Industrialization will require producing hundreds of thousands of cars at scale. But, as Tesla learned the hard way, building cars at scale is more complicated than it looks.

2. Electric charging infrastructure. Almost all AV efforts are being developed on top of electric vehicle (EV) platforms. Before EV fleets can operate at scale in any market, a whole new electric charging infrastructure must be built. This will take time and lots of money.

3. Mapping. The industrialization of the detailed, high-definition (HD) maps on which AVs depend limits where AVs can operate. Even though the cars are loaded with sensors, cameras and software, they need up-to-date maps to figure out where they are and what to do.

See also: Driverless Cars and the ’90-90 Rule’  

4. Fleet management and operations. Industrialization will require flawless maintenance and efficient operation of tens of thousands of AVs widely distributed across large metropolitan service areas. Doing so will entail much more than cleaning windows and vacuuming carpets. It will entail maintaining complex computers on wheels. It will require complex predictive analytics to recharge, dispatch and load balance in response to spiky customer demand. Both public safety and business viability depend on this.

5. Customer service and experience. AV TaaS services are like a hospitality business built on a fleet of mobile hotel rooms with no on-property staff. Even the shortest trip can become arbitrarily messy and unruly—especially because there will be no human supervision in the car. Acceptable service and experience will have to extend to non-customers, as well, because AVs must interact with pedestrians, cyclists, other drivers, emergency personnel, other companies’ AVs and a host of other actors outside the car.

6. Security. Computer security is a challenging issue, in general, and networked armadas of computers on wheels will be attractive hacking targets. There are physical security issues, too. Physical security involving disgruntled drivers and bystanders, pranksters, thugs and others could also create security issues for both passengers and the public at large.

7. Rapid localization. How much of what Waymo and others are learning on the well-marked, well-lit, well-laid-out and relatively polite streets of Phoenix is transferable to the not-so-polite paved cow paths and roundabouts of Boston or the congested, pedestrian-filled city centers of New York, Paris and Beijing? Much—but not all. That is why every developer tests in multiple regions, to understand the peculiarities of local infrastructure, weather, cultural norms, etc. How fast and how well such localization can be done is another hurdle to scaling.

See also: How to Adapt to Driverless Cars  

In part three of this series, I’ll explore the challenges to market acceptance. I will discuss eight industrialization hurdles that deal with trust, market viability and secondary effects.