In this issue:
- Can P3 infrastructure help pension funds?
- Will autonomous vehicles transform urban areas?
- Making sense of Tesla safety claims
- Disrupting urban transit
- Tolling interoperability being achieved
- Upcoming Transportation Events
- News Notes
- Quotable Quotes
A new report just out from the Center for American Progress (CAP) disparages the idea that troubled public-employee pension funds can improve their financial position by investing in long-term public-private partnership (P3) infrastructure concessions. The report is “Assessing Claims About Public-Private Partnerships,” by Kevin DeGood, dated Aug. 10, 2016. Since CAP is the think tank most closely associated with the Hillary Clinton presidential campaign, its recommendations will likely help shape the policies of a potential Clinton Administration.
Fortuitously, Reason Foundation has just published my “Transportation Finance” chapter in its Annual Privatization Report 2016 (available at http://reason.org/news/show/apr-2016-transportation-finance). In that chapter I report the continued growth of global infrastructure investment funds, and the recent increase in investing by U.S. pension funds in P3 infrastructure concessions. Over the past decade infrastructure investment funds have raised some $350 billion to invest as equity in P3 concessions. Since equity typically averages about 25% of a project budget (with the rest being mostly debt instruments), that could support projects worth around $1.4 trillion. I also note that these funds would dearly love to invest more in the safe, stable USA (as opposed to many riskier countries), but lament the lack of a ready “pipeline” of projects needing funding.
In the CAP report, DeGood first notes that US infrastructure projects don’t lack for ample debt financing, with tax-exempt interest rates at all-time low levels. But I don’t think anyone was making that argument, although some heavily indebted city and state governments are reluctant to add to their debt level, or may be approaching their legal debt limits, in which case a P3 project based on revenue bonds and equity investment may be a good fit.
However, when DeGood turns to pension funds, he takes a more realistic tack, recognizing the very large unfunded liabilities of many such funds and their need to flesh out their portfolios with higher-yielding but reasonably safe investments—such as infrastructure. He also recognizes that the reason P3 equity can generate high single-digit returns is the significant risk transfer that investors in such projects are willing to take on (and get paid for). But here his case turns to number crunching. He provides a chart of 24 P3 infrastructure projects that have received TIFIA loans, and for each one lists its equity investment and the fraction of the project budget that equity constituted. His dismal conclusion is that for these projects equity averaged only 14% of project budgets, an average per-project investment of just $183 million. At that rate, he calculates, just to reduce the unfunded liability of giant fund CalPERS by 5% it would have to invest in 90 such projects. And for a great many other pension funds to do likewise would require a completely unrealistic number of such projects, he maintains.
There are several basic flaws in this assessment. First, nearly half the projects in DeGood’s table are availability-payment concessions, in which the government compensates the company via annual payments, rather than allowing it to charge and keep user fees. The equity investment is a small percentage in this kind of project because the investors are not taking revenue risk. And that also means the return on equity in those projects is lower than in the typical revenue-risk concession. Second, he arbitrarily excludes the Chicago Skyway and Indiana Toll Road deals from the calculations (because they were not new construction). Yet it was the refinancing of those revenue-risk concessions last year (by pension funds) that involved the largest equity investments to date in any U.S. P3 infrastructure: $1.5 billion in the Skyway and $3.26 billion in the ITR.
For pension funds, investing in existing “brownfield” infrastructure refurbishment and operation is less-risky than new “greenfield” projects. And that’s why major pension funds such as CalPERS are investing in brownfields such as these (as well as privatized airports such as Heathrow and London City Airport). When I re-did DeGood’s table to include only the revenue-risk concessions, including the 2015 Chicago and Indiana transactions, the average equity investment was a much larger $536 million, averaging 33.7% of the project’s total cost.
Even though DeGood misjudges the good fit between revenue-risk concessions and pension fund needs (especially brownfield concessions), his closing section realistically discusses the merits of the P3 procurement method in comparison with traditional design-bid-build. And he argues, correctly, that P3 concessions “are best suited to very large, complex projects for which it is more likely to be cost-beneficial for the state to pay the premium associated with risk transfer,” concluding that for projects that pass muster via a value-for-money analysis, “P3s are a valuable alternative procurement strategy.”
While I agree that there are probably not enough greenfield revenue-risk P3 transportation projects to make a big difference to pension fund returns, the United States is chock full of aging Interstate highways that need refurbishment and modernization, as well as airports, seaports, and waterway facilities that could be long-term leased as a way to improve their management and operations while self-funding their modernization. These would all meet DeGood’s criterion of being large and complex enough (mega-projects) to be worthwhile procuring as revenue-risk concessions.
By now you have probably seen many stories with headlines like these:
- “Autonomous Taxis: Why You May Never Own a Self-Driving Car”;
- “Self-Driving Cars Will Transform the Human Environment”; and,
- “Shared Mobility Solutions Improve Social Inclusion.”
The last of these is from a news release announcing the latest iteration of a series of simulation modeling runs on how traffic in Lisbon, Portugal might be changed by a hypothetical autonomous vehicle revolution. Other simulations of this kind have been run on cities ranging from Austin to Singapore. Since the devil is always in the details, I decided to do a careful assessment of the assumptions made in this newest simulation, done under the auspices of the OECD’s International Transport Forum (ITF), several of whose conferences I’ve participated in.
The report in question, announced in ITF’s July newsletter, is called “Shared Mobility: Innovation for Liveable Cities.” The news release says the simulation demonstrated that replacing all conventional car and bus trips in Lisbon with automatically dispatched door-to-door services “would provide the same level of mobility to citizens using only 3% of the current number of vehicles.” It would also “cut emissions by one-third and on-street parking would become superfluous.”
Those are pretty amazing claims, so I downloaded the report on which they are based. The modeling uses an extensive database of origin-destination trips for Lisbon. It assumes that private cars are replaced by autonomous 6-seat shared taxis, and buses are replaced by autonomous 8- and 16-passenger taxi-buses. Commuter rail and heavy rail would continue as at present, though rail transit would lose half its current passengers.
What would it take to bring about this new state of affairs? First of all, built into the model is that privately owned cars are banned. The 45% of Lisbon residents currently driving themselves could walk or use rail—or be assigned to either a shared taxi or a taxi-bus. The assignment would be made by a central dispatch system, following an algorithm. The report asserts that this would provide former drivers with the “same level of mobility” as they now enjoy, but that seems hard to reconcile with reality. A shared taxi or taxi-bus would in many or most cases need to make multiple stops to pick up others and multiple stops to drop others off. (Think of this as giving up your car to use Super Shuttle everywhere.)
Also, at least in the United States, large numbers of people engage in trip-chaining, either on the way to work or on the way home, and that does not appear to be included in the algorithm. How would a shared-vehicle trip allow you to stop at the dry cleaners, and then the supermarket, on the way home? Or to stop at Starbucks on the way to work?
Moreover, it turns out that the simulation covers only the 37 sq. mi. of central Lisbon, not the suburbs. That would appear to mean that it covers only those who both live and work within the central area. I don’t know enough about the Lisbon metro area to guess what fraction of the trips that excludes, but this model would be a very poor fit for the typical suburbanized U.S. metro area, where suburb-to suburb commuting is the predominant pattern. And despite eliminating all Lisbon’s current bus passengers (14% mode share) and half the 14% who use rail, the report waves away potential labor opposition by stating that “labor issues could be mitigated by the fact that more Taxi-Buses than conventional buses will be needed.” How is that supposed to help preserve driver jobs, when the Taxi-Buses will be driverless?
In digging through my files to write this article, I discovered a 2015 article from Bern Grush and John Niles’ website, http://endofdriving.org, “What Do Robo-Taxi Simulations Tell Us?” Reviewing an earlier ITF Lisbon simulation, they noted some of the same points I arrived at above:
- Not taking seriously people’s desire to retain and use their presently owned vehicles;
- Not including the suburbs, which Grush and Niles say account for the large majority of the metro area’s 5 million daily trips (vs. 1.2 million in the central city modeled); and,
- Misleadingly concluding that only 10% of the current number of vehicles (in that earlier Lisbon simulation) will be needed, due to leaving out the longer trips within, and to and from, the suburbs.
Grush and Niles conclude that such simulations, while exciting, are both non-scalable and dangerous. They are non-scalable because urban core peak travel is different from the more diverse array of trips people make for many purposes and at all times of day. And they are dangerous because these simulation results “promise disappointment later if [when] reality falls significantly short of the studies’ implications.”
The first fatality in a Tesla being driven with the “Autopilot” feature engaged led to a flurry of debate about how safe the car is. Tesla CEO Elon Musk, ignoring whatever statistics he learned while studying physics at Stanford, got things off on the wrong foot by stating that the Tesla car is much safer than typical cars because people using Autopilot-equipped Teslas had driven 130 million miles before there was a fatality. He compared that with the U.S. average of one fatality for every 94 million miles, and a worldwide figure of one every 60 million miles. Peter Diamandis, chairman of the XPrize Foundation, embarrassed himself by chiming in along the same lines.
One measure I learned very early in my career, at an aerospace company, was mean time between failure—MTBF. This is a statistic derived from having a large sample size—large enough that you have a great many data points and can derive not only the mean but also the standard deviation. With Tesla’s Autopilot, all we have is a single data point, which is meaningless for purposes of comparison.
The best piece I’ve read about this problem was Mark Rogowsky’s”The Truth About Tesla’s Autopilot Is We Don’t Yet Know How Safe It Is,” on Forbes.com July 11th. Rogowsky explained in simple terms that the next Autopilot fatality could dramatically change the one per 130 million miles figure—for the worse or for the better. He also pointed out that comparing the Autopilot Tesla with all US vehicles is apples vs. oranges in several ways. The Tesla is a luxury car, so is not comparable with all categories of car. It is very new, whereas the average U.S. car is 11.5 years old. And it is larger and heavier than average, so probably safer in most crashes. And any comparison with global figures is even more illegitimate. As Rogowsky points out, cars in a great many developing countries don’t have air bags, crumple zones, anti-lock brakes, and many other safety features now standard on all U.S. passenger vehicles.
He also cited Andrew Hires of the University of Southern California, who has pointed out that the U.S. fleet of a typical zero-fatality car (based on data from the Insurance Institute for Highway Safety), such as the Audi A4 with all-wheel-drive, has 1.2 billion miles of driving so far with zero deaths—nearly 10 times more fatality-free miles than Tesla with Autopilot. An April RAND Corporation report noted that auto fatalities are so rare that an automated vehicle must accumulate hundreds of billions of miles before its safety numbers can be meaningfully compared with those of human-driven cars.
The potential of autonomous vehicles to save lives is very large, and we should all look forward to their continued development and perfection. But it’s irresponsible for advocates to throw around meaningless numbers as if they were valid measures of safety.
Both Uber and Lyft continue to expand their quasi-transit businesses, UberPool and Lyft Line. And Lyft last spring launched Lyft Carpool in the San Francisco Bay Area in cooperation with the Metropolitan Transportation Commission. These efforts are viewed as supplementing or complementing the services provided by urban transit agencies, especially first-mile and last-mile services.
A recent empirical study, organized by Prof. Joseph Schwieterman of DePaul University in Chicago used volunteers to compare making 50 different trips using either UberPool or the Chicago Transit Authority. UberPool was faster on all trips, but how much faster depended a lot on the type of trip. For trips within downtown, the difference was small—43 minutes vs. 49 minutes by CTA, with similar small differences for trips between neighborhoods and outer downtown. The big difference was on trips from one neighborhood to another, which transit is not set up to do without transfers: the average for these trips was 28 minutes via UberPool vs. 47 minutes by transit. As Schwieterman noted in his NewGeography.com article on the study, “UberPool tends to perform best where transit is at its worst, e.g., on trips between the neighborhoods, especially during off-peak periods when traffic is lighter.”
In China, leading ride-sharing company Didi Chuxing (in which Apple has recently invested) offers a taxi-hailing service, an Uber-like service, and a bus service competing directly with public transit. CEO Jean Liu described the bus service to MIT Technology Review as follows:
“The bus is like an expanded carpool shuttle service: instead of taking a public bus with many stops, and maybe no seats left, and uncomfortable, we offer shuttle-like service with typically just one or two stops. All the seats on the bus are pre-booked. We can [use our years of data] to determine popular origins and destinations, where commuters are basically making the same journey in the morning. With the scale of this network, we can pull people together.”
Where might this kind of thing lead? Nate Silver and Reuben Rischer-Baum of forecasting firm FiveThirtyEight last year wrote that, “Perhaps in the distant (or even not-too-distant) future, Uber can build its own version of ‘public’ transit, making rides so cheap that they cost less than the $4 or $5 that Americans now pay, on average, to make a trip in their personal cars.”
And how might that come about? The largest operating cost in a transit system is labor. Consequently, autonomous buses might be the means to this end. Last month Tesla CEO Elon Musk gave a preview of the company’s master plan, which includes expanding to cover all major forms of surface transportation—including high-passenger-density urban transport. He elaborated as follows: “With the advent of autonomy, it will probably make sense to shrink the size of buses and transition the role of bus driver to that of fleet manager. . . . It would also take people all the way to their destination.” A bus vehicle of this type is part of the Tesla master plan, along with semi-trucks, compact SUVs, and a new kind of pickup truck.
These developments should be sobering for transportation planners at MPOs, transit agencies, and state DOTs. If automated shuttle buses and automated versions of Uber/Lyft/Didi ride-sharing vehicles materialize in a decade or two, does it really make sense to be investing many billions of dollars in light-rail and heavy-rail systems over the next several decades? In an op-ed piece in the Los Angeles Daily News on July 6th, Susan Shelley raised this question about current transit expansion plans in that region:
“Metro CEO Phil Washington says his agency is building a transit system for 100 years from now, but every day that sounds more disconnected from reality. The future has arrived, and it’s on the road. We could be planning for improvements to our freeways, and transit service upgrades made possible by cost-effective driverless buses.”
Three days later Bryan Mistele, the CEO of traffic firm INRIX, had an op-ed in the Seattle Times, headlined “Sound Transit’s Expansion Will Be Obsolete Before It’s Built.” That plan, estimated to cost $54 billion, would be constructed over the next 25 years, and would provide transit with an additional one percent of daily trips by 2040. He argued that autonomous, connected, electric, and shared vehicles will likely cause the system to be obsolete before it opens. These are sobering thoughts, from a transportation professional who is very knowledgeable about these disruptive forces.
In the MAP-21 legislation, Congress set a deadline of Oct. 1, 2016 for all U.S. electronic toll collection (ETC) systems to be interoperable—meaning that customers could have a single tag and a single account to use electronically tolled highways, bridges, and tunnels anywhere in the country. A lot of progress has been made since then, by toll facility operators working together as well as by electronic toll system providers. In fact, the latter have achieved one version of that goal, while the facility operators are getting close, but may not meet the October 1st deadline.
Toll agencies in several regions continue to work together to achieve regional interoperability. For example, Florida’s Sunpass has been interoperable with Georgia and North Carolina systems for several years, and is very close to interoperability with South Carolina’s. And Sunpass is also on track to be interoperable with electronic tolling in Kansas and Texas within the next year.
At the national level, the Alliance for Toll Interoperability has developed a pilot interoperability hub (IOP) and business rules. ATI’s website describes the IOP hub as the only “come as you are option” for toll facility operators to achieve national ETC tag interoperability—at least for all the operators that participate.
The parallel track is to develop a fully interoperable transponder that works with all current toll facilities. The leader in that effort is Transcore, which recently launched a fusion transponder which it calls NationalPass. It works with all the major toll system protocols, including E-ZPass, Sunpass, TxTag, etc. in more than 20 states. It’s available to individuals for a $35 activation fee and an $8/month service fee.
Both of the tolling and weigh-station-bypass providers to the trucking industry are now offering fusion tags. Bestpass’s version of NationalPass is called Bestpass Complete. PrePass Plus is offering Pocket Pass, which combines two transponders in a single shell to provide comparable nationwide coverage. Hence, as I predicted last year in the Reason Foundation policy study “Truck-Friendly Tolling for 21st Century Interstates,” every truck fleet now has available nationwide electronic tolling interoperability, with a single tag and a single account.
Note: I don’t have the time or the space to list all transportation events that might be of interest to readers of this newsletter. Listed here are events at which a Reason Foundation transportation researcher is speaking or moderating.
Florida League of Cities Annual Conference, August 18-20, 2016, Diplomat Resort, Hollywood, FL (Robert Poole speaking). Details at: www.floridaleagueofcities.com
New Report on P3 Concession Projects in Texas. Despite political flapdoodle over tolling and P3 projects in Texas, multi-billion-dollar projects of this kind have been approved and three are already in operation, with nine more in various states of planning or procurement. The Texas A&M Transportation Institute has released a detailed report on the subject, including profiles of four of the projects. “Summary and Status of Concession Agreements (CDA/DB) in Texas” is report PRC-16-54F and is available on the TTI website (tti.tamu.edu).
Tolling Surveys in Auckland and Sydney. Six weeks after a New Zealand Herald columnist headlined a piece by asking “Will Drivers Be Forced to Pay 40¢ per Kilometer?” the answer came back a resounding “Yes, willingly!” A survey by the Automobile Association found that nearly two-thirds of Aucklanders would be willing to pay variable tolls to escape the city’s traffic congestion. And in Sydney, the New South Wales government has commissioned a willingness-to-pay survey as part of shifting the tolling structure on its expressways to distance-based.
Electric Cars Not Selling Well. Despite all the publicity over Tesla and other makers of trendy electric cars, the Wall Street Journal reported (July 14th) that only 115,000 such cars were sold nationwide in 2015, about 0.7% of total sales.
New Study on State Barriers to Platooning. One of the possible near-term beneficiaries of automated vehicle technology is trucking, specifically via truck platooning on major highways. But state motor vehicle regulations— especially on “following too closely”—stand as barriers to this development. A new report from the Competitive Enterprise Institute reviews the relevant laws of all 50 states and suggests possible amendments to facilitate platooning. You can download it from: https://cei.org/content/authorizing-automated-vehicle-platooning.
Midtown Tunnel a Major P3 Success. The $2.1 billion Midtown Tunnel project between Norfolk and Portsmouth, VA is expected to open this fall, up to 10 months ahead of schedule. The P3 concession shifted major construction, operations & maintenance, and revenue risk to the consortium of Macquarie, Skanska, Kiewit, and Weeks Marine. It is the first all-concrete highway tunnel in the U.S. designed for deepwater immersion, notes a detailed article in Engineering News-Record (June 27/July 4 2016). And given the 58-year term of the concession agreement, the project is designed to cope with a sea-level rise of up to two feet.
Is 30% of City Traffic Really Spent Searching for Parking?. Steven Polzin once again takes a critical look at a piece of conventional wisdom: that “many studies” have shown that 30% of city traffic is due to drivers seeking a place to park. Polzin traces this claim to a single paper by parking expert Donald Shoup of UCLA, which reported observations from 16 U.S. and European cities, dating back as far as 1927—and with just one such observation (Freiburg, Germany) accounting for 40% of the average figure for the 16 cities. “Playing ‘Telephone’ with Transportation Data” is well worth reading. (http://www.planetizen.com/node/87288/playing-telephone-transportation-data)
Tolls vs. Taxes Explained to Texans. Opponents of tolls in Texas and elsewhere are fond of equating them with taxes—even though tolls are payments for specific services that benefit the person or company that pays. There is also an extensive legal history on the difference between tolls and taxes, nicely summarized by Brian Cassidy and Brian O’Reilly, attorneys in the Austin office of Locke Lord. Their article, “The Road Ahead: Examining Transportation Infrastructure Funding,” appears in the July 2016 issue of the Texas Bar Journal.
Another Suit on Diversion of Tolls on Dulles Toll Road. The Washington Post reported (July 20th) that a class-action suit has been filed against the agencies developing the $5.8 billion Silver Line heavy-rail system. Their argument is that using Dulles Toll Road toll revenue to pay for 50% of that project’s cost converts that portion of the toll to a tax, imposed unfairly only on customers of the toll road. It also questions what it describes as an unwarranted delegation of power to the Metropolitan Washington Airports Authority to develop the transit line.
Sacyr Wins $3.1 Billion Rome Highway Concession. Spanish company Sacyr last month emerged as the winning bidder for a 43-year concession to develop a 73 km autostrade (toll road) between Rome and Latina. The project will include two tunnels totaling 2.3 km and another 86 km of non-tolled secondary roads. Sacyr is taking the traffic and revenue risk on this major project. It holds concessions for 35 roads in eight countries in Europe and South America.
Time to Rethink Taxi Regulations. With the rapid growth of companies like Uber and Lyft, the taxi industry is rapidly losing market share. Its ability to compete is hamstrung by extensive regulations that micro-manage their business. In a new paper, “Rethinking Taxi Regulations: The Case for Fundamental Reform,” Michael Farren and two colleagues use Washington, DC as a case study in calling for a complete overhaul of taxi laws and regulations. The paper was released last month by the Mercatus Center at George Mason University.
InterCounty Connector Is Relieving Maryland Congestion. Last month AAA MidAtlantic publicized new data from the Maryland DOT on traffic volumes in Montgomery and Prince Georges Counties before and after the opening of the InterCounty Connector, a variably priced toll road. Both the (non-tolled) Capital Beltway and the Eisenhower Memorial Highway, for example, show significantly less daily traffic in 2015 compared with 2011 prior to the ICC’s opening to traffic. The ICC was fought by environmental groups for several decades, before construction was finally approved.
Israeli Express Lane Company Suing Waze. Israel is the first country besides the United States to have express toll lanes: a 13 km project called Fast Lane on the highway between Ben Gurion Airport and Tel Aviv. Until recently, Waze pointed users to Fast Lane as a much faster way to travel between the two points. But after receiving a number of complaints about the high (variable) tolls, last year Waze stopped recommending it. So the Fast Lane company has filed suit, arguing that Waze is discriminating against it.
Tolled Border Crossing Under Way Near San Diego. Otay Mesa East is a planned new border crossing aimed at relieving massive congestion at the existing Otay Mesa crossing. To achieve wait times of only 20 minutes, rather than up to five hours at the existing crossing, tolls will be charged at the new crossing. SANDAG (the local MPO) and Caltrans last month announced the receipt of a $49.3 million FAST LANE grant from FHWA to help build the new SR 11 toll road that will connect the new border crossing to SR 125 and other highways in the area.
Profitable HSR Line in China?. When I saw a recent Wall Street Journal article claiming that the Beijing-Shanghai high-speed rail line was operating in the black (covering both capital and operating costs), I was skeptical. But this week I received an account from demographer Wendell Cox, who recently spent several weeks riding Chinese HSR lines, including this one. He estimated, based on published timetables, that at least 311 trains per day are operating each way on this line, which makes the claim of breaking even (or better) at least plausible. Cox points out that he was unable to obtain any real financial data to substantiate the claims, but points out that neither have we seen financials based on generally accepted accounting principles for the other two lines claimed to be self-supporting: Paris-Lyon and Tokyo-Osaka.
Correction on Texas Express Lanes. Reader Brian Lea chided my last-month report on express toll lane projects for mis-labeling SH 360 as US 360 and mistakenly stating that ETLs were being constructed on it. He did note the opening of TEXpress lanes in late July on I-30 between Grand Prairie and Dallas.
Correction re Prof. Kockelman. Reason magazine science correspondent Ron Bailey, whose article on connected vehicles I included last month, tells me that Prof. Kara Kockelman of UT Austin says he misquoted her regarding DSRC. She says she might have cited others as thinking DSRC is obsolete, but that is not her own view. I’m happy to set the record straight on this.
“Americans are stubborn, and existing zoning regulations, roads, and buildings are expensive and difficult to alter. As [Nature Conservancy’s Robert] McDonald observes, one thing hasn’t changed over the past 100-plus years: The easier it is to get from point A to point B, the farther away from the center city people are apt to live. Even the era of self-driving cars can’t change that.”
—Christopher Mims, “Advances in Driverless Cars Will fuel Suburban Sprawl,” The Wall Street Journal, June 20, 2016
“Many states still have not figured out how to resolve the highway budgetary crisis of decreasing revenue from the federal gas tax. In those states, new roadway projects are being delayed, infrastructure is deteriorating, and congestion is increasing. Florida, on the other hand, has legislated that it would use tolling to help fund expansion and ongoing maintenance for new highway projects. With South Florida’s 95 Express, Broward County’s 595 Express, and Orlando’s I-4 Ultimate Improvement project as examples, Florida has been able to proceed with multi-billion-dollar improvements to reduce congestion on our crowded highways, provide relief to commuters, and keep our economy growing.”
—Lee Becker, HNTB, Tampa Bay Times, Aug. 8, 2016
“This is the first known [autonomous vehicle] fatality, and as our society transitions to using more systems like driverless car, pilotless airplanes, driverless trucks and trains, and weapons, we will start to see more and more of these . . . deaths and the destruction of property that to us appears unfair and arbitrary. The number of fatalities associated with the use of these autonomous systems will start to rise as more and more are used. Eventually, the number of fatalities and injuries will flatten out and decrease as these systems . . . begin to mature and become capable of handling unusual situations that are difficult to simulate in test environments.”
—Timothy Carone, University of Notre Dame, in Mark Rogowsky, “The Truth About Tesla’s Autopilot Is We Don’t Yet Know How Safe It Is,” Forbes.com, July 11, 2016