Tag Archives: waymo

When Incumbents Downplay Disruption…

An unmanned car driven by a search engine company? We’ve seen that movie. It ends with robots harvesting our bodies for energy.

That is a line from a 2011 Chrysler car commercial mocking Google’s self-driving car project.

Another Chrysler commercial was even blunter: “Robots can take our food, our clothes and our homes. But, they will never take our cars.”

Chrysler’s early mocking of Google’s efforts exemplifies the fact that few cling to the status quo tighter than the companies that best understand it and have the most stake in preserving it. It is human nature to value what one does well and look askance at innovations that challenge the assumptions underlying current success. Sprinkle in some predictably irrational wishful thinking and you have the mindset that too quickly dismisses potentially dangerous disruptions.

Ironically, seven years later, those Google “robots” are now mostly driving Chrysler Pacifica minivans. Those robots have taken Chrysler’s cars and driven more than 10 million miles. Chrysler benefits by selling cars to Waymo, the spinoff from that Google project, but not nearly as much as it might have from building the robots themselves. Waymo is valued at $175 billion, about five times Chrysler’s market value.

History brims with other examples.

When Alexander Graham Bell offered to sell his telephone patents to Western Union, the committee evaluating the deal concluded:

Messrs. Hubbard and Bell want to install one of their ‘telephone devices’ in every city. The idea is idiotic on the face of it… This device is inherently of no use to us. We do not recommend its purchase.

Ken Olsen, who disrupted IBM’s mainframe dominance with his DEC minicomputers, mocked the usefulness of personal computers in their early days. He declared, “The personal computer will fall flat on its face in business.” Olsen was very wrong, and DEC would eventually be sold to Compaq Computer, a personal computer maker, for a fraction of its peak value.

See also: Why AI IS All It’s Cracked Up to Be  

Steve Ballmer’s initial ridicule of Apple’s iPhone is also legendary, though the words of the then-CEO of Microsoft were mild compared with the disdain on his face when asked to comment on the iPhone launch.

Years later, after he retired, Ballmer insisted that he was right about the iPhone in the context of mobile phones at the time. What he missed, he admitted, was that the strict separation of hardware, operating system and applications that drove Microsoft’s success in PCs wasn’t going to reproduce itself on mobile phones. Ballmer also didn’t recognize the power of the business model innovation that allowed the iPhone’s high cost to be built into monthly cell phone bills and to be subsidized by mobile operators. (Jump to the 4:00 mark.)

The biggest challenge for successful business executives—like Ballmer, Olsen and those at Western Union—when confronted with potentially disruptive innovations is to think deeply about potential strategic shifts, rather than simply mock innovations for violating current assumptions.

Another perhaps soon-to-be classic example is unfolding at State Farm Insurance.

State Farm released an TV ad that is a thinly veiled attack on Lemonade, a well-funded insurtech startup. Lemonade makes wide use of AI-based chatbots for customer service. State Farm, instead, prides itself on its host of human agents. In the ad, a State Farm agent says:

The budget insurance companies are building these cheap, knockoff robots to compete with us… These bots don’t have the compassion of a real State Farm agent.

As I’ve previously written, AI is one of six information technology trends that is reshaping every information-intensive industry, including insurance. In fact, as I recently told a group of insurance executives, I believe insurance will probably change more in the next 10 to 15 years than it has in the last 300.

See also: Lemonade Really Does Have a Big Heart  

That doesn’t mean that Lemonade’s use of chatbots for customer service will destroy State Farm. But, as State Farm should know, customer-service chatbots are only one of numerous innovations that Lemonade is bringing to the game. As several McKinsey consultants point out, AI-related technologies are driving “seismic tech-driven shifts” in a number of different aspects of insurance. Lemonade has also adopted a mobile-first strategy and is applying behavioral economics to drive other business model innovations.

State Farm executives need to get beyond the mocking and think deeply about how emerging innovations might disrupt their strategic assumptions.

One way to do so is being offered at InsuranceThoughtLeadership.com, where ITL editor-in-chief and industry thought leader Paul Carroll has offered a “State Farm Lemonade Throw Down.” Carroll offers to host an online debate between the two firms’ CEOs about how quickly AI technology should be integrated into interactions with customers.

Lemonade’s CEO, Daniel Schreiber, has accepted. I hope Michael Tipsord, State Farm’s CEO, will accept, as well.

Better for Mr. Tipsord to face the question now, while there is ample time to still out-innovate Lemonade and other startups, than to be left to reflect on what went wrong years later, as Steve Ballmer had to do with the iPhone.

Where Are Driverless Cars Taking Industry?

While more than half of individuals surveyed by Pew Research express worry over the trend toward autonomous vehicles, and only 11% are very enthusiastic about a future of self-driving cars, lack of positive consumer sentiment hasn’t stopped several industries from steering into the auto pilot lane. The general sentiment of proponents, such as Tesla and Volvo, is that consumers will flock toward driverless transportation once they understand the associated safety and time-saving benefits.

Because of the self-driving trend, KPMG currently predicts that the auto insurance market will shrink 60% by the year 2050 and an additional 10% over the following decade. What this means for P&C insurers is change in the years ahead. A decline in individual drivers would directly correlate to a reduction in demand for the industry’s largest segment of coverage.

How insurers survive will depend on several factors, including steps they take now to meet consumer expectations and needs.

The Rise of Autonomous Vehicles

Google’s Lexus RX450h SUV, as well as 34 other prototype vehicles, had driven more than 2.3 million autonomous miles as of November 2016, the last time the company published its once monthly report on the activity of its driverless car program. Based on this success and others from companies such as Tesla, public transportation now seems poised to jump into the autonomous lane.

Waymo — the Google self-driving car project — recently announced a partnership with Valley Metro to help residents in Phoenix, AZ, connect more efficiently to existing light rail, trains and buses by providing driverless rides to stations. This follows closely on the heels of another Waymo pilot program that put self-driving trucks on Atlanta area streets to transport goods to Google’s data centers.

In the world of personal driving, Tesla’s Auto Pilot system was one of the first to take over navigational functions, though it still required drivers to have a hand on the wheel. In 2017, Cadillac released the first truly hands-free automobile with its Super Cruise-enabled CT6, allowing drivers to drive without touching the wheel for as long as they traveled in their selected lane.

Cadillac’s level two system of semiautonomous driving is expected to be quickly upstaged by Audi’s A8. Equipped with Traffic Jam Pilot, the system allows drivers to take hands off the vehicle and eyes off the road as long as the car is on a limited-access divided highway with a vehicle directly in front of it. While in Traffic Jam mode, drivers will be free to engage with the vehicle’s entertainment system, view text messages or even look at a passenger in the seat next to them, as long as they remain in the driver’s seat with body facing forward.

While the Cadillacs were originally set to roll off the assembly line and onto dealer lots as early as spring of 2018, lack of consumer training as well as federal regulations have encouraged the auto manufacturer to delay release in the U.S.

Meanwhile, Volvo has met with similar constraints as it navigates toward releasing fully autonomous vehicles to 100 people by 2021. The manufacturer is now taking a more measured approach, one that includes training for drivers starting with level-two semi-autonomous assistance systems before eventually scaling up to fully autonomous vehicles.

“On the journey, some of the questions that we thought were really difficult to answer have been answered much faster than we expected. And in some areas, we are finding that there were more issues to dig into and solve than we expected,” said Marcus Rothoff, Volvo’s autonomous driving program director, in a statement to Automotive News Europe.

Despite the roadblocks, auto makers’ enthusiasm for the fully autonomous movement hasn’t waned. Tesla’s Elon Musk touts safer, more secure roadways when cars are in control, a vision that is being embraced by others in high positions, such as Elaine Chao, U.S. Secretary of Transportation.

“Automated or self-driving vehicles are about to change the way we travel and connect with one another,” Chao said to participants of the Detroit Auto Show in January 2018. “This technology has tremendous potential to enhance safety.”

See also: The Evolution in Self-Driving Vehicles  

We’ve already seen what sensors can do to promote safer driving. In a recent study conducted by the International Institute for Highway Safety, rear parking sensors bundled with automatic braking systems and rearview cameras were responsible for a 75% reduction in backing up crashes.

According to Tesla’s website, all of its Model S and Model X cars are equipped with 12 ultrasonic sensors capable of detecting both hard and soft objects, as well as with cameras and radar that send feedback to the car.

Caution, Autonomous Adoption Ahead

The road to fully autonomous vehicles is expected to be taken in a series of increasing steps. We have largely entered the first phase, where drivers are still in charge, aided by various safety systems that intervene in the case of driver error.

As we move closer to full autonomy, drivers will assume less control of the vehicle and begin acting as a failsafe for errant systems or by taking over under conditions where the system is not designed to navigate. We currently see this level of autonomous driving with Audi Traffic Jam Pilot, where drivers are prompted to take control if the vehicle departs from the pre-established roadway parameters.

In the final phase of autonomous driving, the driver is removed from controlling the vehicle and is absolved of roadway responsibility, putting all trust and control in the vehicle. KPMG predicts wide-scale adoption of this level of autonomous driving to begin taking place in 2025, as drivers realize the time-saving and safety benefits of self-driving vehicles. During this time frame, all new vehicles will be fully self-driving, and older cars will be retrofitted to conform to a road system of autonomous vehicles.

Past the advent of the autonomous trend in 2025, self-driving cars will become the norm, with information flowing between vehicles and across a network of related infrastructure sensors. KPMG expects full adoption of the autonomous trend by the year 2035, five years earlier than it first reported in 2015.

Despite straightforward predictions like these, it’s likely that drivers will adopt self-driving cars at varying rates, with some geographies moving faster toward driverless roadways than others. There will be points in the future where a major metropolis may have moved fully to a self-driving norm, mandating that drivers either purchase and use fully autonomous vehicles or adopt autonomous public transportation, while outlying areas will still be in a phase where traditional vehicles dominate or are in the process of being retrofitted.

“The point at which we see autonomy appear will not be the point at which there is a massive societal impact on people,” said Elon Musk, Tesla CEO, at the World Government Summit in Dubai in 2017. “Because it will take a lot of time to make enough autonomous vehicles to disrupt, so that disruption will take place over about 20 years.”

Will Self-Driving Cars Force a Decline in Traditional Auto Coverage?

At present, data from the National Highway Traffic Safety Administration indicates that 94% of automobile accidents are the result of human error. Taking humans largely out of the equation makes many autonomous vehicle proponents predict safer roadways in our future, but it also raises an interesting question. Who is at fault when a vehicle driving in autonomous mode is involved in a crash?

Many experts agree that accident liability will be taken away from the driver and put into the hands of the automobile manufacturers. In fact, precedents are already being set. In 2015, Volvo announced plans to accept fault when one of its autonomous cars is involved in an accident.

“It is really not that strange,” Anders Karrberg, vice president of government affairs at Volvo, told a House subcommittee recently. “Carmakers should take liability for any system in the car. So we have declared that if there is a malfunction to the [autonomous driving] system when operating autonomously, we would take the product liability.”

In the future, as automobile manufacturers take on liability for vehicle accidents, consumers may see a chance to save on their auto premiums by only carrying state-mandated minimums. Some states may even be inclined to repeal laws requiring drivers to carry traditional liability coverage on self-driving vehicles or substantially alter the coverage an individual must secure.

Despite the forward thinking of manufacturers such as Volvo, for the present, accident liability for autonomous cars is still a gray area. Following the death of a pedestrian hit by an Uber vehicle operating in self-driving mode in Arizona, questions were raised over liability.

Bryant Walker Smith, a law professor at the University of South Carolina with expertise in self-driving cars, indicated that most states require drivers to exercise care to avoid pedestrians on roadways, laying liability at the feet of the driver. But in the case of a car operating in self-driving mode, determining liability could hinge on whether there was a design defect in the autonomous system. In this case, both the auto and self-driving system manufacturers and even the software developers could be on the hook for damages, particularly in the event a lawsuit is filed.

Finding Opportunity in the Self-Driving Trend

Accenture, in conjunction with Stevens Institute of Technology, predicts that 23 million self-driving vehicles will be coursing across U.S. highways by 2035.

As a result, insurers could realize an $81 billion opportunity as autonomous vehicles open new areas of coverage in hardware and software liability, cybersecurity and public infrastructure insurance by 2025, the same year that KPMG predicts the autonomous trend will begin to rapidly accelerate. Simultaneously, Accenture predicts that personal auto premiums, which will begin falling in 2024, will hit a steeper decline before leveling out around 2050 at an all-time low.

Most of the personal premium decline is due to an assumption that the majority of self-driving cars will not be owned by individuals, but by original equipment manufacturers, OTT players and other service providers such as ride-sharing companies. It may seem like a logical conclusion if America’s love affair with the automobile wasn’t so well-defined.

Following falling gas prices in 2016, Americans logged a record-breaking 3.22 trillion miles behind the wheel. Even millennials, the age group once assumed to have given up on driving, are showing increased interest in piloting their own vehicles as the economy improves. According to the National Household Travel Survey conducted by the Federal Highway Administration, millennials increased their average number of miles driven 20% from 2009 to 2017.

Despite falling new car sales, the University of Michigan Transportation Research Institute shows that car ownership is actually on the rise. Eighteen percent of Americans purchase a new car every two to three years, while the majority (39%) make a new car bargain every four to six years.

Americans have many reasons for loving their vehicles. Forty percent say it’s because they enjoy driving and being in their cars, according to a survey conducted by Cars.com.

ReportLinker reveals that 83% of people drive daily and that half are passionate about the behind-the-wheel experience of taking on the open road. Another survey conducted by Gold Eagle determined that people even have dream cars, vehicles that they feel convey a sporty, luxurious or efficient image.

Ownership of autonomous vehicles would bring at least some liability back to the owner-occupant. For instance, owing to security concerns, all sensing and decision-making hardware related to the Audi Traffic Jam Pilot system is held onboard. With no over-air connections, software updates must be made manually through a dealer.

In situations like these, what happens if an autonomous vehicle crash is tied to the driver’s failure to ensure that software was promptly updated? Auto maintenance will also take on a new level of importance as sensitive self-driving systems will need to be maintained and adjusted to ensure proper performance. If an accident occurs due to improper vehicle maintenance, once again, the owner could be held liable.

As the U.S. moves toward autonomous car adoption, one thing becomes clear. Insurers will need to expand their product lines to include both commercial and personal lines of coverage if they are going to take part in the multibillion-dollar opportunity.

Preparing for the Autonomous Future of Insurance

Because the autonomous trend will be adopted at an uneven pace depending upon geography, socioeconomic conditions and even age groups, Deloitte predicts that the insurers that will thrive through the autonomous disruption are those with a “flexible business model and diverse product mix.”

To meet consumer expectations and maintain a critical focus on customer acquisition and retention, insurers will need a multitude of products designed to protect drivers across the autonomous adoption cycle, as well as new products designed to cover the shift of liability from driver to vehicle. Even traditional auto policies designed to protect car owners from liability will need to be redefined to cover autonomous parameters.

Currently, only 25% of companies have a business model that is easily adaptable to rapid change, such as the autonomous trend. In insurance, this lack of readiness is all the more crucial, considering the digital transformation already underway across the industry.

According to PwC, 85% of insurance CEOs are concerned about the speed of technological change. Worries over how to handle legacy systems in the face of digital adoption, as well as the need to accelerate automation and prepare for the next wave of transitions, such as autonomous vehicles, are behind these concerns.

As insurers look toward the complicated future of insuring a society of self-driving automobiles, we believe that focusing on four main areas will prepare them to respond to the autonomous trend with greater speed and agility.

Make better use of data

Consumers are looking for insurers to partner on risk mitigation. To meet these expectations, insurers will need to start making better use of data stores, as well as third-party sources, to help customers identify and reduce threats to life and property. Sixty-four percent want their insurer to provide real-time notifications about roadway safety, while, on the home front, 68% would like to receive mobile alerts on the potential of fire, smoke or carbon dioxide hazards.

“Technology is changing the insurer’s role to one of a partner who can address the customer’s real goals – well beyond traditional insurance,” said Cindy De Armond, managing director, Accenture P&C core platforms lead for North America, in a blog.

Armond believes that as insurers focus more on the customer’s prevention and recovery needs, they can become the everyday insurer, integrated into the lives of their customers rather than acting only as a crisis partner. This type of relationship makes insurer-insured relationships more certain and extends longevity.

For insurers and their insureds, the future is likely to be more about predicting and mitigating risk than about handling claims, so improving data capture and analytics capabilities is essential to agile operations that can easily adapt to new trends.

See also: Autonomous Vehicles: ‘The Trolley Problem’  

Focus on digital

Consumers want to engage with their insurer in the moment. Whether that means shopping online for coverage while watching a child’s soccer game or making a phone call to ask questions about a policy, they expect to be able to engage on their time and through their channel of choice. Insurers that develop fluid omni-channel engagement now are future-proofing their operations, preparing to survive the evolution to self-driving, when the reams of data gathered from autonomous vehicles can be used to enable on-demand auto coverage.

Vehicle occupants will one day purchase coverage on the fly, depending on the roadway conditions they encounter and whether they are traveling in autonomous mode. Forrester analyst Ellen Carney sees a fluid orchestration of data and digital technologies combining to deliver this type of experience, putting much of the power in the hands of the customer.

“On your way home, you’re going to get a quote for auto insurance,” she says. “And because your driving data could basically now be portable, you could do a reverse auction and say, ‘Okay, insurance companies, how much do you want to bid for my drive home?’”

To facilitate the speed and immediacy required for these transactions, insurers will need to digitally quote, bind and issue coverage.

Seek automation

In the U.K., accident liability clearly shifts from the driver to the vehicle for level four and five autonomous automobiles. As driverless vehicles become the norm, the U.S. is likely to adopt similar legislation, requiring a fundamental shift in how risk is assessed and insurance policies are underwritten. Instead of assessing a policy on the driver’s claims history and age, insurers will need to rate risk by variables related to the software that runs the vehicle and how likely owners are to maintain autonomous cars and sensitive self-driving systems.

The more complicated underwriting becomes, the more important automation in underwriting will be. Consumers who can get into a car that drives itself will have little patience for insurers that require extensive manual work to assess their risk and return bound policy documents. Even businesses will come to expect a much faster turnaround on policies related to self-driving vehicles despite the complexity of the various coverages that will be required. In addition, on-demand coverage will require automated underwriting to respond to customer requests.

According to Lexis Nexis, only 20% of commercial carriers have automated the quoting process, and less than half are investing in underwriting automation.

Invest in platform ecosystems

McKinsey defines a platform business model as one that allows multiple participants to “connect, interact and create and exchange value,” while an ecosystem is a set of connected services that fulfill multiple needs of the user in “one integrated experience.” By definition, an insurance platform ecosystem in the age of autonomous vehicles would be a place where consumers and businesses could research and purchase the coverage they need while also picking up related ancillary services, such as apps or entertainment to make the autonomous ride more enjoyable.

Consumers are in search of ecosystem values today. According to Bain’s customer behavior and loyalty study, consumers are willing to pay higher premiums to insurers that offer ancillary services, such as home security monitoring or an automotive services app, and they are even willing to switch insurers to get time-saving benefits like these.

More important to insurers is the ability to partner with other carriers on coverage. Using a commission-based system, insurers offer policies from other carriers to consumers when they don’t have an appetite for the risk or don’t offer the coverage in house. This arrangement allows an insurer to maintain a customer relationship, while providing for their needs and price points.

See also: Autonomous Vehicles: Truly Imminent?  

As the autonomous trend reaches fruition, insurers will need to have access to a wide range of coverage types to meet consumer and business needs, and not all carriers will be able or want to create the new products.

Extreme Customer Focus Prepares for the Future

Insurers can prepare for autonomous vehicle adoption by establishing an extreme customer focus, dedicated to establishing enduring loyalty as insurance needs change. Loyal customers spend 67% more over three years than new ones. As the insurance marketplace opens up to the sale of ancillary services, gaining wallet share from loyal consumers will certainly help to boost revenues as demand for traditional products decline, but to stay competitive, insurers will need a broader mix of coverage types.

While current coverages have remained largely unchanged over the decades, the coming years will see an industry in flux as insurers phase out outmoded types of coverage while phasing in new products and services. In this environment, the platform ecosystems may be the most critical aspect of bridging the gaps.

Today, they allow insurers to fulfill the needs of price-sensitive consumers while also meeting the evolving needs of their customers. Tomorrow, platform ecosystems will provide the “flexible business model and diverse product mix” that Deloitte says will be critical to success for insurers in the autonomous age of driving.

Driverless Cars and the ’90-90 Rule’

In programming circles, there is an aphorism known as the “90-90 rule.” It states that the first 90% of code accounts for the first 90% of the expected development time—and the remaining 10% of code takes another 90% of time. The rule is a tongue-in-cheek acknowledgement that technology projects always take longer than you expect, even when you know that they are going to take longer than you expect.

Sacha Arnoud, director of engineering at Waymo, recently used a variant of the 90-90 rule to characterize Waymo’s self-driving car program. Waymo’s experience, he said, was that the first 90% of the technology took only 10% of the time. To finish the last 10%, however, is requiring 10x the initial effort.

Arnoud’s remarks were given at a guest lecture at Lex Fridman’s MIT class on “Deep Learning for Self-Driving Cars.” He offered technical insights on the history of the Waymo program, how it is applying artificial intelligence and deep learning and how it is moving from demo to industrial-strength product.

The Waymo engineer’s lecture goes beyond most Waymo management presentations and press events. He provides vivid details on the complexity of the effort to date and insight on challenges to come—both for Waymo and for those trying to catch up to its pioneering efforts.

Here are 5 takeaways, though I recommend watching the entire presentation.

1. Industrialization requires 10x the effort.

Arnoud emphasized the large amount of work needed to go from a demo that works in a lab to an industrialized product that is safe to put on the road: “You need to 10x the capabilities of your technology. You need to 10x your team size, including finding effective ways for more engineers and more researchers to collaborate. You need to 10x the capabilities of your sensors. You need to 10x the overall quality of the system, including your testing practices.”

2. Deep learning enabled algorithmic breakthroughs.

Arnoud noted that deep learning techniques were much less advanced in 2010 when Google started its work on self-driving cars. But, in the years since, deep learning has advanced to enable algorithmic breakthroughs in several critical areas for autonomous driving, including mapping, perception and scene understanding.

Arnoud gave numerous examples, such as using deep learning to analyze street imagery to extract street names, house numbers, traffic lights and traffic signs. The ability to precompute such data and store them as maps in the car saves precious onboard computing power for real time tasks.

See also: When Will the Driverless Car Arrive?  

Deep learning is driving breakthroughs in real-time tasks as well, such as analyzing sensor data to identify traffic signals, other vehicles, obstacles, pedestrians, and so on. Deep learning capabilities also help in anticipating possible behavior of other drivers, cyclists and pedestrians, and driving accordingly.

3. Synergy with other Google units is key to Waymo’s progress.

Arnoud acknowledged the importance of Google’s “whole machine learning ecosystem” to Waymo’s progress. This includes the seminal software advances by the Google Brain team and on-going collaboration with other Google teams working on deep learning at scale, such as in vision, speech, natural language processing and maps. The Google ecosystem also provides specialized infrastructure and tools for machine learning. This includes accelerators, data centers, labelled datasets and research that support Google’s TensorFlow programming paradigm.

4. Waymo’s testing program might be its secret sauce.

Arnoud emphasized that however great Waymo’s algorithms, sensors and overall package might be, driverless cars are still complex, embedded, real-time robotic systems that must work safely with imperfect data in an unpredictable world. He highlighted Waymo’s three-prong testing program of real-world driving, simulation and structured testing as key to iterating on and productizing the technology.

Much is made of the millions public-road miles that Waymo’s cars have driven autonomously. Arnoud described this as the equivalent of about 300 years of human driving experience and 160 times around the globe. Real world driving is critical, he said, but what is more important is the ability to simulate.

Simulation is critical because it allows for Waymo to test each new iteration of software against all previously-driven miles. Even more important is the ability to test against “fuzzed” versions of those millions of miles, such as seeing how the software would handle cars going at slightly different speeds, an extra car, pedestrians crossing in front of the car and so on. Arnoud described Waymo’s simulation-based testing capability as the equivalent of 25,000 virtual cars driving 2.5 billion real and modified miles in 2017.

The third component of Waymo’s testing program is its structured testing program. Arnoud said that there is a “long tail” of driving situations that happen very rarely. Rather than trying to encounter every possibility in real-world driving, Waymo set up a 90-acre mock city at the decommissioned Castle Air Force base where it can test its cars against such edge cases. These tests are then fed into the simulation engine and fuzzed to create variations for more testing.

5. Waymo’s next steps are big (and hard) ones.

Arnoud closed with a discussion of the engineering challenges in front of Waymo. He described two big next steps.

One next step is expanding the “operational design domains” (ODD) of the cars. This includes expanding into “dense urban cores,” such as San Francisco (in which Waymo recently announced it is expanding its testing program). The other ODD was additional weather conditions, such as hard rain, snow and fog. (Waymo CEO John Krafcik recently told an audience that he was “jumping up and down” recently when it snowed 12 inches near Detroit, because it would enable Waymo’s testing in snow.)

See also: 7 Steps for Inventing the Future

The other area of focus was what Arnoud called “semantic understanding.” As an example, he pointed to the chaotic Place de l’Étoile traffic circle around the Arc de Triomphe in Paris. The circle is a meeting point of 12 roads and notoriously difficult to navigate. Arnoud says he has driven it many times without incident, however, and that such situations require a lot more than perception and vehicle operating skills. They require deep understanding of local rules and expectations. They also require constant communication and coordination with other drivers, including signals, gestures and so on. This kind of deep reasoning is key to numerous edge cases and improving the general abilities of driverless cars.

* * *

While Waymo has clearly made tremendous progress towards the driverless future, Arnoud closed his presentation by emphasizing the engineering infrastructure and the complexities of scaling that have to be addressed in order to turn driverless cars into safe production systems.

How far along is Waymo in the last 90% of that industrialization process? Arnoud never said. But, to put a point on the complexities, he showed a closing video of a Waymo car stopped at an intersection as a gaggle of kids bounced on frogger sticks across the street on all sides of the car. Some things are waiting for, he seemed to imply.

Driverless Vehicles: Brace for Impact

On June 26, Waymo (Google’s autonomous car firm), signed a deal under which Avis Budget Group will provide “fleet support and maintenance services” to Phoenix-area Waymo vehicles. Waymo uses Chrysler Pacifica minivans to autonomously shuttle Phoenix residents around town. Its first fleet of 100 minivans quickly grew into an order for 500 more.

The Waymo/Avis agreement may only be a pilot, but the implications are enormous. Not unlike standard cab companies, Waymo realized that a fleet of autonomous vehicles would need cleaning and maintenance throughout the day and storage throughout the night. When practical matters like auto cleaning and storage become news enough for a press release, something big is going on.

Here are some fun facts:

  • According to USA Today, Avis’ stock rose 14% on the news.
  • The Chrysler Pacifica was chosen, in large part, because it could close its own doors. Waymo usage experts theorized that riders might often hop out and forget to close the door.
  • Within hours of the Waymo announcement, Apple likewise unveiled a deal where Hertz Global would manage its autonomous fleet.

Autonomous vehicles have picked up the pace of disruption over the last two years. What will life be like when the Autonomy of Things takes on many of our everyday behaviors or occupations, like driving? Will we be safer? Will we need insurance? Will auto manufacturers cover accidents via product liability? Who will cover bodily injury or property damage? How will risk products be changed to fit this new model? Is there an insurance right-road to surviving autonomy?

See also: The Evolution in Self-Driving Vehicles  

Is Autonomy Impact Still Underrated?

There has been a lot of talk and certainly a wealth of words written on the impact of auto autonomy, and safety is at the top of the concerns and promises of autonomous vehicles. Insurers are, of course, focused on how autonomous vehicles might cause a decline in the need for auto insurance.

The pace of development, rollout, experimentation and expansion of autonomous vehicles has far exceeded original expectations. In his blog, Peter Diamandis (XPrize Founder) noted that a former Tesla and BMW executive said that self-driving cars would start to kill car ownership in just five years. John Zimmer, the cofounder and president of Lyft, said that car ownership would “all but end” in cities by 2025.

The Wall Street Journal reported in July 2016 that auto insurance represents nearly a third of all premiums for the P&C industry, with projections that 80% could evaporate over the next few decades as autonomous vehicles are introduced, some of them replacing legacy vehicles and some created for shared transportation. At the same time, U.S. government support strengthened in September 2016 when federal auto safety regulators released their first set of guidelines, sending a clear signal to automakers that the door was wide open for driverless cars and betting that the nation’s highways will be safer with more cars driven by machines instead of people.

Those statements, among others, might cause some scrambling. Manufacturers are working frantically to partner with AI providers, cab services and ridesharing services such as Uber, Lyft and Waymo. Naysayers will note that rural areas will be highly unlikely to use autonomous vehicles soon, and it’s true that the largest impact may be in urban areas. But if car ownership were even cut by 5% by 2030, a tremendous number of auto manufacturers and auto insurers would be affected.

Autonomy and its insurance impact isn’t limited to personal autos. Truck company Otto is testing self-driving commercial trucks — a necessary automation that could help alleviate the growing lack of truck drivers. Husqvarna has several models of autonomous lawn mowers on the market. Yara and Rolls Royce are among companies working on autonomous ships. Case, John Deere and Autonomous Tractor Corporation have all been developing driverless tractors.

In nearly every one of these cases, there are safety benefits and disruptive insurance implications, but there are also revenue growth opportunities for those that think more broadly and “outside the box.” From developing partnerships with automotive companies to leveraging the autonomous vehicle data for new services, each offers alternative revenue streams to counter the decline of traditional auto insurance. The key is experimenting with these technologies to find alternative “products and services” and develop an ecosystem of partners to support this, before the competition does.

Share and Transportation as a Service — Insurers May Like

In our report, A New Age of Insurance:  Growth Opportunity for Commercial and Specialty Insurance in a Time of Market Disruption, we cite a report from RethinkX, The Disruption of Transportation and the Collapse of the Internal-Combustion Vehicle and Oil Industries, which says that by 2030 (within 10 years of regulatory approval of autonomous vehicles), 95% of U.S. passenger miles traveled will be served by on-demand autonomous electric vehicles owned by fleets, not individuals, in a new business model called “transport-as-a-service” (TaaS). The report says the approval of autonomous vehicles will unleash a highly competitive market-share grab among existing and new pre-TaaS (ride-hailing) companies in expectation of the outsized rewards of trillions of dollars of market opportunities and network effects.

Welcome to the adolescence of the sharing economy and transportation as a service. Autonomy isn’t the only road for vehicle progress. Vehicle sharing is growing and will remain in vogue for some time. Just as Airbnb and HomeAway have given rise to new insurance products, Zipcar and Getaround and Uber have given rise to new P&C products.

At the same time, a merging of public and private transportation and a pathway to free transportation is in the early stages of being created in the TaaS model. This will shift risk from individuals to commercial entities, governments or other businesses that provide the public transportation, creating commercial lines product opportunities beyond traditional “public transportation.”

Vehicle users, whether they are riders, borrowers, sharers or public entities, are going to need innovative coverage options. Tesla and Volvo may be promising some level of auto coverage for owners of autonomous vehicles, but that kind of blanket coverage is likely to mimic an airline’s coverage of passengers and cargo — it will be limited. Those who lend their vehicle, through a software-based consolidator, such as Getaround, will need coverage that goes beyond their auto policy.

In the past few weeks, we’ve also seen how cyber attacks can undermine freight and shipping, not to mention systems. Nearly all of these service-oriented options will require new types of service-level coverage. Autonomous freight may be safer in transit, but in some ways it may also be less secure.

The lessons appear to be found in brainstorming. Technology is breeding diversity in service use and ownership. There will be new coverage types and new insurance products needed.

See also: Will You Own a Self-Driving Vehicle?  

Up Next … Flying Vehicles

Remember the movie “Back to the Future” and the Jetsons flying cars that were so cool? Well, they are quickly becoming a cool reality. A June 2017 Forbes article says flying cars are moving rapidly from fiction to reality, with the first applications of flying vehicles for recreational activities in the next five years. The article says that, in the past five years, at least eight companies have conducted their first flight tests, and several more are expected to follow suit, indicative of the frenzied activity in this space.

Companies such as PAL-VTerrafugia, AeromobilEhangE-VoloUrban AeronauticsKitty Hawk and Lilium Aviation completed test flights of their flying car prototypes, with PAL-V going further by initiating pre-sales of its Liberty Pioneer model flying car, which the company aims to deliver by the end 2018. This sounds like Tesla and its pre-sales move!

Not to be left behind … ride-sharing companies are aggressively entering the space. Uber launched the Uber Elevate program, with a focus on making flying vehicles transport a reality by bringing together government agencies, vehicle manufacturers and regulators. Google and Skype are entering the space by investing in start-ups: Google in Kitty Hawk and Skype in Lilium Aviation. Not to be left behind, Airbus has unveiled a number of flying car concepts, with plans to launch a personal flying car by 2018. Airbus also plans to build a mass transit flying vehicle…the potential next TaaS option.

So, it pays for insurers to keep their attention on autonomous vehicle trends … because it is more than the personal autonomous vehicle … it is the transformation of the entire transportation industry and will have a significant impact on premium and growth for auto insurers. As we recently found in our commercial and specialty insurance report, the transportation industry is rapidly changing and new technologies may be lending themselves to safety, but the world itself isn’t necessarily growing any safer.

Risk doesn’t end. Insurers will always be helping individuals and companies manage risk. The key will be using the trends to rapidly adapt to a shift to the new digital age. Insurers will need to understand and value new risks and offer innovative products and services that meet the changing needs in this shift during the digital age.

When Will the Driverless Car Arrive?

When Chris Urmson talks about driverless cars, everyone should listen. This has been true throughout his career, but it is especially true now.

Few have had better vantage points on the state of the art and the practical business and engineering challenges of building driverless cars. Urmson has been at the forefront for more than a decade, first as a leading researcher at CMU, then as longtime director of Google’s self-driving car (SDC) program and now as CEO of a driverless car dream team at Aurora Innovation.

Urmson’s recent “Perspectives on Self-Driving Cars” lecture at Carnegie Mellon was particularly interesting because he has had time to absorb the lessons from his long tenure at Google and translate those into his next moves at Aurora. He was also in a thoughtful space at his alma mater, surrounded by mentors, colleagues and students. And, it is early enough in his new startup’s journey that he seemed truly in “perspective” rather than “pitch” mode.

The entire presentation is worth watching. Here are six takeaways:

1. There is a lot more chaos on the road than most recognize.

Much of the carnage due to vehicle accidents is easy to measure. In 2015, in just the U.S., there were 35,092 killed and 2.4 million injured in 6.3 million police-reported vehicle accidents. Urmson estimates, however, that the real accident rate is really between two and 10 times greater.
Over more than two million test miles during his Google tenure, Google’s SDCs were involved in about 25 accidents. Most were not severe enough to warrant a regular police report (they were reported to the California DMV). The accidents mostly looked like this: “Self-driving car does something reasonable. Comes to a stop. Human crashes into it.” Fender bender results.
While we talk a lot about fatalities or police-reported accidents, Urmson said, “there is a lot of property damage and loss that can be cleaned up relatively easily” with driverless technology.
2. Human intent is the fundamental challenge for driverless cars.
The choices made by driverless cars are critically dependent on understanding and matching the expectations of human drivers. This includes both humans in operational control of the cars themselves and human drivers of other cars. For Urmson, the difficulty in doing this is “the heart of the problem” going forward.
To illustrate the “human factors” challenge, Urmson dissected three high-profile accidents. (He cautioned that, in the case of the Uber and Tesla crashes, he had no inside information and was piecing together what probably happened based on public information.)

Google Car Crashes With Bus; Santa Clara Transportation Authority

In the only accident where Google’s SDC was partially at fault, Google’s car was partially blocking the lane of a bus behind it (due to sand bags in its own lane). The car had to decide whether to wait for the bus to pass or merge fully into the lane. The car predicted that the remaining space in the bus’s lane was too narrow and that the bus driver would have to stop. The bus driver looked at the situation and thought “I can make it,” and didn’t stop. The car went. The bus did, too. Crunch.

Uber’s Arizona Rollover

Uber Driverless Car Crashes In Tempe, AZ

The Uber SDC was in the leftmost lane of three lanes. The traffic in the two lanes to its right were stopped due to congested traffic. The Uber car’s lane was clear, so it continued to move at a good pace.

A human driver wanted to turn left across the three lanes. The turning car pulled out in front of the cars in the two stopped lanes. The driver probably could not see across the blocked lanes to the Uber car’s lane and, given the stopped traffic, expected that whatever might be driving down that lane would be moving slower. It pulled into the Uber car’s lane to make the turn, and the result was a sideways parked car.

See also: Who Is Leading in Driverless Cars?  

Tesla’s Deadly Florida Crash

Tesla Car After Fatal Crash in Florida

The driver had been using Tesla’s Autopilot for a long time, and he trusted it—despite Tesla saying, “Don’t trust it.” Tesla user manuals told drivers to keep their hands on the wheel, eyes in front, etc. The vehicle was expecting that the driver was paying attention and would act as the safety check. The driver thought that Autopilot worked well enough on its own. A big truck pulled in front of the car. Autopilot did not see it. The driver did not intervene. Fatal crash.

Tesla, to its credit, has made modifications to improve the car’s understanding about whether the driver is paying attention. To Urmson, however, the crash highlights the fundamental limitation of relying on human attentiveness as the safety mechanism against car inadequacies.

3. Incremental driver assistance systems will not evolve into driverless cars.

Urmson characterized “one of the big open debates” in the driverless car world as between Tesla’s (and other automakers’) vs. Google’s approach. The former’s approach is “let’s just keep on making incremental systems and, one day, we’ll turn around and have a self-driving car.” The latter is “No, no, these are two distinct problems. We need to apply different technologies.”

Urmson is still “fundamentally in the Google camp.” He believes there is a discrete step in the design space when you have to turn your back on human intervention and trust the car will not have anyone to take control. The incremental approach, he argues, will guide developers down a selection of technologies that will limit the ability to bridge over to fully driverless capabilities.

4. Don’t let the “Trolley Car Problem” make the perfect into the enemy of the great.

The “trolley car problem” is a thought experiment that asks how driverless cars should handle no-win, life-threatening scenarios—such as when the only possible choices are between killing the car’s passenger or an innocent bystander. Some argue that driverless cars should not be allowed to make such decisions.

Urmson, on the other hand, described this as an interesting philosophical problem that should not be driving the question of whether to bring the technology to market. To let it do so would be “to let the perfect be the enemy of the great.”

Urmson offered a two-fold pragmatic approach to this ethical dilemma. First, cars should never get into such situations. “If you got there, you’ve screwed up.”  Driverless cars should be conservative, safety-first drivers that can anticipate and avoid such situations. “If you’re paying attention, they don’t just surprise and pop out at you,” he said. Second, if the eventuality arose, a car’s response should be predetermined and explicit. Tell consumers what to expect and let them make the choice. For example, tell consumers that the car will prefer the safety of pedestrians and will put passengers at risk to protect pedestrians. Such an explicit choice is better than what occurs with human drivers, Urmson argues, who react instinctually because there is not enough time to make any judgment at all.

5. The “mad rush” is justified.

Urmson reminisced about the early days when he would talk to automakers and tier 1 suppliers about the Google program and he “literally got laughed at.”  A lot has changed in the last five years, and many of those skeptics have since invested billions in competing approaches.

Urmson points to the interaction between automation, environmental standards, electric vehicles and ride sharing as the driving forces behind the rush toward driverless. (Read more about this virtuous cycle.) Is it justified? He thinks so, and points to one simple equation to support his position:

3 Trillion VMT * $0.10 per mile = $300B per year

In 2016, vehicles in the U.S. traveled about 3.2 trillion miles. If you could bring technology to bear to reduce the cost or increase the quality of those miles and charge 10 cents per mile, that would add up to $300 billion in annual revenue—just in the U.S.

This equation, he points out, is driving the market infatuation with Transportation as a Service (TaaS) business models. The leading contenders in the emerging space, Uber, Lyft and Didi, have a combined market valuation of about $110 billion—roughly equal to the market value of GM, Ford and Chrysler. Urmson predicts that one of these clusters will see its market value double in the next four years. The race is to see who reaps this increased value.

See also: 10 Questions That Reveal AI’s Limits  

6. Deployment will happen “relatively quickly.”

To the inevitable question of “when,” Urmson is very optimistic.  He predicts that self-driving car services will be available in certain communities within the next five years.

You won’t get them everywhere. You certainly are not going to get them in incredibly challenging weather or incredibly challenging cultural regions. But, you’ll see neighborhoods and communities where you’ll be able to call a car, get in it, and it will take you where you want to go.

(Based on recent Waymo announcements, Phoenix seems a likely candidate.)

Then, over the next 20 years, Urmson believes we’ll see a large portion of the transportation infrastructure move over to automation.

Urmson concluded his presentation by calling it an exciting time for roboticists. “It’s a pretty damn good time to be alive. We’re seeing fundamental transformations to the structure of labor and the structure transportation. To be a part of that and have a chance to be involved in it is exciting.”