I love my car… but not that much

By James Arbib | October 31, 2017

Like it or not, autonomous cars are coming right around the corner, and even the most committed motorheads will soon see the (electric) light.

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The reason is pretty simple – we may love our cars, but we love money more. And the massive financial disparity between individually owning a car and using an autonomous, electric vehicle (A-EV) means there can only be one winner.

Indeed our research shows the average American family would save more than $5,500 a year by switching to transport-as-a-service (TaaS), where you hail an A-EV wherever and whenever you need it. That equates to an almost 10% pay rise for the average earner.

And once widespread adoption makes A-EVs even more efficient and gasoline cars harder to maintain, TaaS could be up to 10 times cheaper.

Go jump

Of course owning a car has, from a purely financial point of view, always been a pretty stupid idea. As soon as you drive a new car off the lot, it’s lost on average 10% of its value. One year down the road it’s lost another 10%, while after three years you’ll be lucky to get back much more than half what you paid for it.

Not only that, but you have to pay handsomely just to keep it running, through safety inspections, registration fees and insurance, not to mention parking and the cost of gas itself.

And this for an asset that sits idle, literally parked up gathering dust, on average 96% of the time! If your financial adviser came to you suggesting such a major outlay on such a poorly-performing asset, you’d tell them where to jump.

The reason we do it, of course, is because there is no cost-effective alternative. But in TaaS, there soon will be. 

Stress free

Early adopters will recognize the benefits from day one. The cost savings are clear, but there are other advantages.

Most Americans drive alone to work, with the average commute almost half an hour one way. That’s nearly one hour freed up, each and every day. Should you choose to work in that time, TaaS becomes not just a cost saving, but a revenue generator.

You could of course instead choose to watch the latest series or movie, make some calls, read or even sleep. The point is the time is yours to do with as you please, free from the endless stresses of driving in traffic jams, stresses that have been shown to affect adversely heart rate, blood pressure and anxiety levels.

Autonomous takeover

Not everyone will be convinced. Many of us have a strong emotional connection to our cars. They represent a coming of age, a freedom to escape at any time, an expression of our individuality. But even these sentimental bonds will soon be broken.

Just imagine how the move to A-EVs plays out. As early adopters spread the word and media coverage grows, more and more people give TaaS a go – there’s no commitment, it’s cheap and a car can be hailed via an app just as it is now with Uber or Lyft.

Soon enough, some people decide there really is no need to own a car anymore, so they sell theirs. Meanwhile, TaaS just gets better and better – more cars, cheaper rides, shorter waiting times – attracting more and more new customers.

Before long, used cars begin to flood the market as people rush to ditch their expensive gas-guzzlers. At the same time, demand for these cars falls dramatically as more people realize the economics of car ownership no longer stack up against TaaS. Increasing supply and falling demand deliver a double whammy to used car prices. Buying a new car simply makes no sense at all.

Carmakers stop investing in R&D for gasoline cars and concentrate instead on A-EVs. Gas cars get more expensive and stop improving, making them even less attractive, pushing sales ever lower. Used car dealerships begin to struggle, while garages, whose sole purpose is to maintain these unfashionable cars, start to close as the whole supply chain begins to break down. Spare parts become ever harder to find. Inevitably gas stations start to disappear as demand for fuel dwindles – range anxiety suddenly flips from electric vehicles to gasoline cars.

All the while more people are switching to TaaS as city planners and regulators encourage more A-EVs as they prove to be faster and safer than cars driven by humans. Indeed public opinion moves from being skeptical of autonomous vehicles to being nervous about human drivers.

This is soon reflected in insurance premiums, which become prohibitively high for the majority of drivers, sounding the death knell for the widespread use of gasoline-powered cars driven by humans.

A bold vision of the future perhaps, but we believe an inevitable one.

That the internal combustion engine will soon be a thing of the past is unquestionable. Individually-owned cars driven by humans will quickly follow suit.

Neither will be missed as much as many now believe. The future of transport is simply too enticing.

Sarah Golden
How many cars do we actually need?

By James Arbib | June 14, 2017

RethinkX believes that within 10 years of widespread approval of autonomous vehicles, the vast majority of the population will give up individual ownership of vehicles for transportation as a service, provided by on-demand electric autonomous vehicles owned and operated by fleets.

One of the most frequent questions we have faced is around the number vehicles in the TaaS fleet that we forecast and its ability to meet demand for trips during rush hours. The common question is, if the vehicle fleet declines from 250m to 44m, how on earth do we meet demand during peak hours? When everyone wants to go to school or work at the same time, how, with such a dramatic reduction to the number of vehicles in the fleet, will there be enough cars to transport them?

This is a very valid point and requires an understanding of how many of the 250m vehicles in the fleet are currently on the road at any one time, the buffer required to meet this demand and the ability to smooth that demand through demand management. The question largely springs from misconceptions about the spread of vehicle trips throughout the day.

  1. Commutes are only 18% of total trips (including other forms of transport) or 28% of total vehicle miles traveled, which is a surprisingly low figure. Personal trips by car including errands make up a far greater proportion of total trips (29%).
  2. Journeys are far more spread out through the day than generally realized. The graph below from the U.S. Department of Transportation shows the spread of trips by hour during the day and is the best approximation we have found for vehicles in operation at the same time.
  3. It feels like there are far more cars on the road during peak hours than at other times because during peak commute times vehicles are generally going in the same direction – from residential to commercial areas and vice versa. Most of the traffic is moving in the same direction, whereas at other times a day there is a more even 2-way flow.

 

But despite the smaller-than-expected number trips occurring at peak hours, this is a genuine concern, with a few options for mitigation.

1.  Demand based pricing.

Surge pricing (as Uber calls it) can help to smooth peak hour demand. Raising prices in periods of peak demand can help to alleviate pressure on the fleet and spread out demand. It can also help drive users from the single user TaaS model to the TaaS Pool model. Research by Uber about the price elasticity of demand in surge pricing shows that demand is highly responsive to price increases. This doesn’t have to have the effect of raising average prices of TaaS – in a competitive market these increased revenues during peak hours will be largely passed onto consumers in the form of lower prices in off-peak times.

2.  Ability to work while commuting. 

Some aspects of jobs that can be done during commutes will allow people to travel at non-peak times. Many jobs by the 2020s will have elements that can be done remotely. Freed from the need to drive, people can be more flexible about when they commute to and from their place of work, hence the ability to travel when demand is lower and travel speeds faster, which can allow demand based pricing to have a greater impact on smoothing periods of peak demand.

3.  Seat capacity.

We think in terms of seat capacity not vehicle capacity. The TaaS fleet will likely eventually blend with bus fleets, with vehicles ranging in size from 4-seaters through to 40+ seats. Within the TaaS Pool model there will be the ability to increase vehicle occupancy to soak up demand during peak periods. Our model sees an increase in passengers per vehicle as TaaS Pool plays an increasingly important role in mobility, meaning fewer vehicles are required to service the same number of passenger miles.

4.  Systemic disruptions.

New communications technologies such as VR may allow an increase in remote working or socializing, which could contribute to a reduction in peak hour congestion. As autonomous vehicle share increases, parking spaces and other land in cities will be available for other uses. It is possible that as cities become more liveable that walking or cycling increases and the distribution of residential areas shifts.


Our model sees passenger miles increasing by 50% by 2030 with vehicle miles remaining nearly constant (due to increasing TaaS Pool use). Much of the increase in passenger miles comes from people currently excluded from private vehicle transport (the elderly, disabled and those on lower incomes). This demand is likely to be more price sensitive and lead to greater increases in TaaS Pool demand. Furthermore, demand-based pricing during peak hours might lead to movement from TaaS to TaaS Pool, increasing passengers per vehicle and seat occupancy.

A study from the ITF shows that a fully autonomous fleet could meet demand at all times with only 3% of the vehicle fleet in Lisbon, Portugal. Our model sees just over 11% - a more conservative figure. Part of this difference is because the ITF sees vehicle miles dropping by 37% as passengers per vehicle rise (due to an increase in ride-sharing – TaaS Pool). Lisbon is also denser than most American cities, meaning fewer redundant trips. Other differences that explain the difference are because we allow for lower utilization. There is a growing body of academic research (for example here and here) that has modeled the potential reduction in vehicle numbers due to TaaS, with figures largely falling between 5 and 11 vehicles taken out of the fleet for every TaaS vehicle. Our model equates to 8.6 to 1 (232m individual vehicles replaced by 26m TaaS vehicles). However these estimate tend not to include any smoothing of peak demand through demand-based pricing, which could increase these figures.

Related to this is a discussion of vehicle redundancy – how many unoccupied miles will be covered by TaaS vehicles. This is important because whilst they are repositioning after trips in readiness for the next trip, they are unused, and the miles covered generate no revenue (whilst depleting the vehicle lifetime). Again there is some research suggesting a figure of 3-14%, once AI is used for predictive demand management. This is an area that requires more research and we will look to deepen in future analyses.

Final note:

Our analysis is a scenario, subject to a large number of assumptions. No scenario will ever be completely accurate. There are many aspects that might make our analysis incorrect that stem from unforeseen regulatory responses, through to the ability of technology providers to create monopoly pricing situations (we assume competitive markets). Work and leisure could be disrupted through VR and other communications technologies that affect travel patterns, a low-cost transport platform could disrupt logistics or lead to a huge increase in deliveries of goods by TaaS vehicles, replacing some personal trips but increasing delivery travel, etc. What our analysis ultimately shows is that mainstream analysis needs to consider the potential of a TaaS disruption in more detail and adjust many of their assumptions to reflect those areas where our analysis highlights alternative possibilities.

 

Sarah Golden
Is Tesla’s lead bigger than we think?

By James Arbib and Tony Seba | May 11, 2017

Why would you build a million-mile car?

It wouldn’t be a selling point for most consumers who average just 10k miles per year in their cars. Who wants a car that lasts 100 years? Could you imagine an advert for a car that lasts forever? We see adverts extolling performance, safety, comfort, or fuel efficiency. If a consumer looks at the economics, they focus on the upfront cost of the purchase or the monthly payments. But lifetime? Irrelevant!

But this is exactly what Tesla is working on. In a 2015 blog post, Elon Musk mentioned that Tesla was designing its powertrain for 1 million miles, and it attracted pretty much no attention from the mainstream cognoscenti.

Here’s why vehicle lifetime is the most important factor in the economics of the car market and everyone else is missing it...

With autonomous vehicles on the cusp of reaching the mainstream, a new business model will be unleashed; transport-as-a-service (TaaS) will render individual car ownership obsolete. This new business model will change how the transportation value chain works and the success factors that drive business decisions. These vehicles will be fleet-owned with users just paying a cost per mile, which will become the key metric for building and running vehicles.

We already know that the operating cost of an EV platform is far lower than a gasoline vehicle. Fuel costs are way lower because electric motors are more efficient than combustion engines and electricity is cheaper than gasoline. Maintenance costs are way down – just 20 moving parts versus 2,000 means there’s much less to go wrong– and an operating environment that has little heat, friction or vibration – the scourges of gasoline vehicles. But the biggest cost is the depreciation cost – the way vehicle owners recover the upfront cost of the vehicle – and this is where A-EVs have a huge advantage.

In an individual ownership model, lifetime of vehicles is irrelevant.

So long as the vehicle can do, say, 150k miles, it doesn’t figure in consumer choice. In this model, buyers care about residual value – how much the car will drop in value whilst they own it. This is the basis of lease payments (and depreciation costs) and it is how the consumer calculates the cost of ownership. But in a TaaS world it’s entirely different.

TaaS vehicles will be in use most of the time and will drive more than 100,000 miles per year – and they probably won’t change hands. Residual values won’t matter – but lifetime will! Depreciation cost per mile will be based on dividing the upfront cost by the lifetime miles of the vehicle.

Upfront cost seems to attract all the attention. EVs currently suffer in comparison because they currently cost more than gasoline vehicles. But this comparison is rooted in the old world of individual ownership. The other part of the calculation – lifetime miles ­is a much more important story. Our research indicates that some EVs today can last at least 500k miles - and that’s before the new business incentives to lower cost per mile, really kick in.

A doubling of vehicle lifetime has the same effect on depreciation cost per mile as halving upfront cost.

If vehicle lifetime increases from what seems to be the current mainstream assumption of 140-200k miles to 1 million miles, then it decreases depreciation cost per mile by 5-7x. And this is possible. That’s why the focus on upfront cost in EVs is missing the point. Cars aren’t optimised for lifetime yet – why would they be? In private ownership 12 years is plenty. But change the business model to TaaS, and 1 million miles makes perfect sense. In fact, a million-mile car will soon be a minimum business imperative! One that Tesla gets but conventional car companies seem to be missing.

 

Sarah Golden
Why RethinkX – Technology Disruption, Implications and Choices

Planes, Trucks, and Automobiles – The Future is Not What it Used to Be

By Tony Seba and James Arbib | May 3, 2017

In 1911, Ferdinand Foch, the supreme commander of the Allied Forces during World War I, once famously said, “Airplanes are interesting toys, but have no military value.”

In 1927, Charles Lindbergh famously flew across the Atlantic, landing at Le Bourget field outside of Paris.

Three years later, France started building a wall, the Maginot Line - a massive series of fortifications along its borders with Germany that became the centerpiece of its defense strategy. A younger modernist generation, who had seen the evidence of the value of the airplane, favored investment in armor and aircraft, but this thinking was seen as disruptive and was defeated by the insiders and policymakers trained in 19th-century military strategy who still ran France’s military.

In the meantime, the Nazi government built the Luftwaffe, which, by 1939 had become “the most well-trained, modern, and experienced air force in the world.”

The result: it took just six weeks for the German military to make it to Paris. The Nazis went easily around and over the ‘impenetrable’ Maginot Line. The Luftwaffe deployed more than 5,000 combat aircraft to support this invasion.

Policymakers, insiders and experts who thought that the future was just a linear, incremental extension of the past, dismissed evidence of a technology disruption (aviation) and made choices for the future based on mainstream notions from the past - with massive implications for Europe and the world for generations to come.

History is littered with examples of government policies that stopped innovation and prevented industries from developing locally, causing their own citizens to become poorer and their countries to decline.

In 1865 the United Kingdom Parliament passed the Locomotive Act, which required that “self-propelled vehicles”, which included automobiles, employ a crew of three people: two onboard and a man with a red flag who had to walk at least 60 yards (55 m) ahead of the vehicle. The speed limit of these vehicles was set at 4 mph in the country and 2 mph in the cities. This regulation, known as the “Red Flag Act”, was the result of successful lobbying by the unlikely coalition of the locomotive industry and the old horse-drawn coach and carriage industry. The government effectively stopped innovation in the incipient automotive industry for 25 years. The Locomotive Act of 1896 repealed many of the provisions of the “Red Flag Act”, finally allowing the development of the automotive industry.

But it was too late. The United Kingdom, birthplace of the industrial revolution, did not benefit from one of the biggest spinoffs of that revolution: the automobile.

The United States, then an emerging economy, went on to become the 20th Century’s economic and military superpower based in part on the strength of its auto industry.

By the 1950s, the U.S. auto industry produced more vehicles than the rest of the world combined. In 1960, automotive was America’s largest industry, employing directly or indirectly one of every six working Americans. During World War II, Ford alone built 6,790 B24 Bombers, 282,354 Jeeps and 42,676 Army/Navy Cargo Trucks.

By preventing innovation and the benefits of technology disruptions, policy makers in France and the United Kingdom only ensured that the upside of building new industries would accrue to other countries, while denying and postponing the inevitable costs of the disruptions. These lessons are as important today as they were then.

The Creation of RethinkX

The founders of RethinkX met at a military think tank meeting to discuss the potential geo-political implications of the disruption of energy and transportation. There, top “mainstream” analysts discussed the linear, incremental progress that solar, batteries and electric vehicles were making and how “the transition” would take decades.

The two of us shared a different viewpoint – this is not an “energy transition” but a “technology disruption.”

Technology disruptions are not linear progressions. They are dynamic and systemic. They may take a while to build up but when they reach a tipping point, they move in exponential S curves and trigger feedback loops – both positive and negative.

Yet mainstream analysts kept making the same mistakes in providing an incomplete picture to policy makers and decision makers that led the French and British policy makers to fail to anticipate the implication of technology disruptions. And failure to foresee disruption leads to decisions based on flawed scenarios, which can become self-fulfilling prophesies, locking society into a high-cost, uncompetitive future.

Our conversation moved from transportation and energy to food, health care, finance, housing, and education. We agreed that these sectors were on the cusp of being disrupted but there was no one providing a full picture of how these disruptions were going to evolve, their implications, and the choices that society would have to make going forward.

Several hours into our conversation, we had laid out the conceptual underpinnings of what would become RethinkX.

Helping Society Make Evidence-Based Choices

There are some hugely beneficial aspects of disruption, including lower costs and broader availability of goods and services, from transport to energy to healthcare to food. This could help solve some of the world’s largest problems, including poverty, inequality and climate change.

But there are also adverse consequences that need to be acknowledged and mitigated. These include job losses and changing workforce needs, as well as value destruction for pensions and investment funds that don’t adapt in time.

That’s Where RethinkX’s Analysis Comes In

RethinkX is an independent think tank that analyzes and forecasts the speed and scale of technology-driven disruption and its implications across society. We produce compelling, impartial data-driven analyses that identify pivotal choices to be made by investors, businesses, policymakers, and civic leaders.

Rethinking Transportation is the first in a series that analyzes the impacts of technology-driven disruption, sector by sector, across the economy.

RethinkX’s follow-on analyses will consider the cascading and interdependent effects of disruption within and across sectors. Our aim is to facilitate a global conversation about the threats and opportunities of technology-driven disruption and to focus attention on choices that can help lead to a more equitable, healthy, resilient and stable society.

We invite you to be part our community of thought leaders and experts to better inform this conversation.

Join us.

Sarah Golden