A THOUGHT REPORT BY
Executive Summary
The dual trends of shared ownership and autonomous technology
are transforming the dialogue about the auto industry. Though they
haven’t yet impacted vehicle production, these themes loom ever
larger for all involved in the business of personal transportation.
ALG and its parent company TrueCar sit at
the intersection of these trends. As the forecasting division of TrueCar, ALG works closely
with automakers, lenders, fleet operators, and
insurers to plan for the future. Our independence affords us a unique perspective.
Instead of bringing more speculation to
the conversation, we took a step back and
created a model for U.S. vehicle demand
that incorporates the impact of shared
ownership and autonomous technology.
This approach provides a framework for
thinking about the future, and the flexibility to
explore divergent scenarios. The outcomes
are driven by just a handful of key assumptions about how people use vehicles.
The most extreme scenario in this Thought
Report shows a 26 percent reduction in
passenger vehicle demand by 2030, with
higher use of AV technology slashing the
number of units in operation, or what is often
called the vehicle parc, by over 50 percent.
the same. And if people increase their
commuting distances and insist on single-occupancy trips in AVs, we may see
a net increase in vehicle production.
While the future of personal mobility is
decidedly uncertain, demand modeling
and scenario planning shed light on the
range of possibilities. We invite you to join
us in exploring the future of our industry.
But our model also generates a scenario in which fully autonomous vehicles
arrive and overall vehicle output remains
The Road to 2030:
Vehicle Production and Sales in the Autonomous Era
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3
Introduction: Taking the Long View
Over the past two years the self-driving car has
emerged from the realm of science fiction. Once
seen as a distant possibility, the concept of drivers ceding control to artificial intelligence (AI) is
now firmly planted in our cultural dialogue.
Media channels burst with speculation,
providing almost daily updates on the
progress of autonomous vehicle technology.
Will fully autonomous vehicles (AVs) be in
commercial operation within five years or
will it take much longer? Are they an existential threat to the auto industry or simply
a shift in how it serves consumers’ needs?
Do they represent evolution or revolution?
With a long list of questions in front of
us, we took some time to distill this
complex problem. Our goal: create a
framework for thinking about how autonomous vehicles will impact our industry.
The good news is that the dynamics of the
auto industry, while incredibly complex at a
micro level, are much clearer when viewed
from 30,000 feet. People, pets and personal
cargo need to be moved. We move them
in vehicles that have 2-8 seats and travel
7,500-75,000 miles per year. The vehicles
themselves last 160,000-200,000 miles.
Boil it all down and we arrive at a replacement rate of 15 million to 18 million units
per year in the U.S. While economic cycles,
population growth, and technology impact
these ranges, they don’t change the basic
mechanism that drives vehicle demand.
The Road to 2030:
Vehicle Production and Sales in the Autonomous Era
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Introduction: Taking the Long View
From there we chose to focus on the
medium-term future of our industry –
what do things look like in the period
from 2030-2040? To a certain extent
the time horizon is arbitrary. We simply
don’t know how quickly AVs will proceed
down the commercialization path.
Conventional vehicle projects require at
least five years to design, tool and produce their first unit. Without knowledge of
firm plans by automakers or technology
firms to mass-produce a Level 4 AV, we
assume that the first models will enter fullscale production no sooner than 2020.
And while it will be a watershed moment
when the first AVs roll off an assembly line, that event won’t turn the world
on its head – at least not right away.
It currently takes the U.S. vehicle fleet more
than 10 years to turn over, or replace the
majority of vehicles on the road. This rate
is largely driven by household economics:
purchase cost, practical service life (a function
of repair costs) and household income.
Let’s assume that things get properly interesting about 10 years after those first AVs
emerge from the assembly line. That’s the
point at which highly divergent outcomes are
plausible: will AVs be relegated to taxi-like
services in urban markets? Will they transform the way we commute? Will suburban
households continue to own vehicles, or
will they avail themselves of autonomous
vehicle fleets (AVFs) that offer low costs
and freedom from ownership concerns in
exchange for a few minutes of waiting?
This report presents three specific scenarios for 2030 (or whenever we hit the tenth
year of AV production.) While they’re clearly
divergent, they’re clearly not exhaustive.
Our goal is to spark a broad conversation
about the fundamentals of vehicle demand
in a self-driving world. We hope that you’ll
use this framework to create some scenarios of your own. Let’s get started.
The Road to 2030:
Vehicle Production and Sales in the Autonomous Era
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Methodology: The Fundamentals of Vehicle Demand
At first glance, trying to predict the impact of AV technology on sales
volume may seem absurd. After all, even the relatively simple exercise of
forecasting 2016 sales is fraught with challenges. Stir a paradigm shift
into the mix and roll the timeline to 2030? How do we intend to do that?
Let’s start with an important distinction – the
goal of this report is to present scenarios,
not forecasts. By scenario we simply mean
an outcome based on a set of assumptions. Scenarios let us gauge a range of
impacts against a chosen baseline.
In this case our baseline is a vision of 2030 in
which nothing about the U.S. vehicle market
has changed. What does this look like?
• Passenger miles traveled (PMT)
scales linearly with population growth
(0.7% per year according to IHS.)
• 94% of PMT continues to be served
by privately owned, conventionally
operated vehicles. The balance is
served by taxi, livery, TNC, car-sharing
and daily rental vehicles (collectively,
“fleet-owned passenger vehicles.”)
• Vehicle occupancy is constant at 1.67
people per household vehicle and 2.09
for fleet-owned passenger vehicles.
• Demand for vehicle miles is expressed
as VMT = [PMT / Occupancy], as
household VMT is primarily a byproduct of the need to move people.
• Annual vehicle mileage = 12,000 miles
for household vehicles and 48,000 miles
for fleet-owned passenger vehicles.
• Temporal utilization (a function of annual
mileage and an average speed of 35 mph)
= 4% for household vehicles and 16%
for fleet-owned passenger vehicles.
• Vehicle lifespan (the final odometer reading
at the scrap yard) = 160,000 miles for
household vehicles and 200,000 miles
for fleet-owned passenger vehicles.
The Road to 2030:
Vehicle Production and Sales in the Autonomous Era
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Methodology: The Fundamentals of Vehicle Demand
Based on these assumptions, we estimate
16.5 million new units will be needed to meet
organic demand in 2030. The auto market
is highly cyclical, but this exercise strictly
measures the impact of technology on the
organic sales rate. Any of our scenarios can
be scaled up or down to account for the
health of the U.S. economy in the target year.
From here the possibilities are vast.
Will autonomous vehicles be owned
by households and used just like conventional vehicles? Will they come to
market as fleets of polite robo-taxis?
At this point it’s anyone’s guess.
To quantify the impact of these scenarios
and any combinations thereof, we took a
hard look at the drivers of organic vehicle
demand. This seemingly complex calculation
can be distilled to just three key drivers:
1. Ownership mix – fleets vs.
privately owned vehicles
2. Occupancy of each vehicle type
3. Lifespan of each vehicle type
Just three drivers? Once you’ve chosen a target year and a population
growth rate, then yes – these are the
three key drivers of vehicle demand.
Extra Trips and Empty Miles
What about growth in per-capita mileage? It’s
conceivable that people will travel further once
their seat time is freed up for other uses. A
long commute becomes more palatable, and
if autonomy eases congestion, a 60-minute
drive could take a driver 60 miles rather than 20
miles. Simply layer a growth assumption into
the population growth number to compute the
effective impact. For example, a 0.5% annual
increase in per-capita PMT on top of 0.7%
population growth: [(PMT_Current Year) * (1 +
.005 + .007)] ^ (Target Year – Current Year).
It’s also conceivable that autonomous
vehicles will make unmanned trips even if
they’re privately owned (to retrieve family
members, goods, etc.) This can be layered
into the occupancy assumption. For example, a typical household vehicle currently
conveys 1.67 passengers. This value falls
to 1.25 if 25% of a privately owned AV’s
miles are unmanned (i.e. occupancy = 0.)
The Road to 2030:
Vehicle Production and Sales in the Autonomous Era
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Methodology: The Fundamentals of Vehicle Demand
You may be wondering why annual vehicle
mileage didn’t make the list. While it may not
be intuitive, the organic steady-state sales
rate is not affected by vehicle utilization.
This is because the vehicle replacement rate
is governed by total annual VMT and the
average lifespan of vehicles in the vehicle
parc (the Units in Operation.) In the equations
on the right, you can see that an increase in
Annual Utilization (in miles) will reduce both
Units in Operation and Lifespan (in years)
by the same percentage. Thus the increase
in Utilization does not have a net impact on
Annual Vehicle Demand. A smaller vehicle
parc with higher temporal efficiency turns
over at the same rate as a larger parc with
lower efficiency. Lifespan is the key driver
– a vehicle parc comprised of units that
last longer will have a lower replacement
rate. (Note that replacement rate, sales rate
and demand are all interchangeable in the
context of organic steady-state calculations.
This implies that vehicles sales are 1:1 with
replacements – a sale only takes place when
another vehicle reaches the end of its life.)
Units in
Operation
=
PMT
Occupancy ×
Annual Utilization
[in miles]
Lifespan
(in years)
=
Lifespan [in miles]
Annual Utilization
[in miles]
Annual Vehicle
Demand
=
Units in Operation
Lifespan [in years]
Thus:
Annual Vehicle
Demand
=
PMT
Occupancy ×
Lifespan [in miles]
(Note the absence of Annual Mileage in the
final equation.)
The Road to 2030:
Vehicle Production and Sales in the Autonomous Era
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Methodology: The Fundamentals of Vehicle Demand
What about per-mile costs, the microeconomics of household transportation?
No doubt the relative cost of traveling will
be an important driver. Look closely and
you’ll see that this is already captured by
the ownership mix assumption. If high
occupancy robo-taxis, with their opaque
partitions and antibacterial seats, can get
passengers from A to B at half the cost of
a privately owned vehicle, surely people
will migrate to them en masse. Departure
latency will mitigate the migration, but market
dynamics will bake this into the price.
Transportation Network Companies are
already quantifying the cost of latency.
Having a vehicle that’s on-call 24/7, as we
do with private ownership, is an evolving
luxury feature. At present it’s essentially
binary. We choose between the immediate
departure afforded by a private vehicle and
the inherently delayed departure of a TNC
or taxi. In high-density areas we can easily envision a future with differential pricing
for two minute, five minute, and 10 minute
wait times – latency as a continuum.
Things will be much the same in terms of
leaving personal items in one’s own car or
customizing the interior environment. Fleets
may offer lockable storage bins, stored seat
positions and climate settings, and perhaps even food and beverage services to
lure consumers away from privately owned
vehicles. Errands may be handled autonomously before the evening commute – a
vehicle arrives with groceries and dry cleaning
already on board. The market will undoubtedly find a colorful range of new ways to
serve consumers. Digital content is the obvious one, but there will be many others. The
availability and pricing of these features will
have a major impact on the ownership mix.
With these themes in mind, let’s dive
into three specific scenarios.
Ride-Sharing
without Autonomy
Couldn’t ride-sharing cause a shift away
from private ownership all by itself? Why
are we framing the discussion around
autonomy instead of Transportation
Network Companies like Lyft and Uber?
The short answer is that the cost of a
human driver creates a natural cap on the
viability of TNCs for most trips. Deutsche
Bank estimates that it costs $1.54/mile to
travel by TNC in the 20 largest U.S. metro
areas, compared to $0.90/mile for a privately
owned vehicle. This cost delta means that
ride-sharing is simply too expensive to
replace private ownership outside of urban
cores. And while the cost does come down
if you share trips with strangers via Lyft Line
and UberPool, those savings are eroded by
longer wait times. Lastly, it’s worth noting
that this sizable TNC cost disadvantage
exists despite widespread discounting
and promotional fares (driven by market
share wars between the two companies.)
This is unlikely to change until the driver
is replaced by an algorithm in an AV.
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Vehicle Production and Sales in the Autonomous Era
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Scenario 1: In With a Whisper
Scenario 1 views 2030 through a skeptical lens.
It recalls the broken technological promises
of the past – EV and fuel cell vehicle proliferation, solar panels on every roof, and supersonic
air travel at reasonable prices. History is full of
broken promises, but proponents of vehicular AI claim that things are different this time.
What if they’re wrong, and autonomous vehicles are relegated to
the fringes of the market?
This scenario assumes that autonomous
fleets fully displace current taxi, livery
and TNC miles, as well as all daily rental
and car-sharing miles. At the household level, it assumes that premium AVs
capture 2% of passenger miles and that
these vehicles are still privately held. (i.e.
roughly 20% of privately owned luxury
vehicles achieve Level 4 autonomy.)
The Road to 2030:
Vehicle Production and Sales in the Autonomous Era
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Scenario 1: In With a Whisper
Current
Future
92%
Private
Conventional
94%
Private
Conventional
2%
Private Autonomous
6%
6%
Fleet
Conventional
Figure 1
Migration of
Passenger Miles
Fleet Autonomous
With the notable exception of paid drivers, industry stakeholders let
out a collective sigh of relief in this case. The status quo is preserved
for vehicle manufacturers with no change to sales against the 2030
baseline. This is because our assumptions for occupancy and lifespan
do not change just because the driver is removed from the equation.
Taxi-like services still convey 25% more passengers than privately
owned vehicles, at 2.09 vs. 1.67 today. (Ridesharing optimization
replaces the human driver with an additional passenger.) And autonomous fleets maintain the long 200,000-mile service life of conventional
fleet vehicles.
Similarly, we assume that privately owned AVs perform at par with their
conventional counterparts. Household trips convey an average of
1.67 passengers and the private AV units are scrapped at
160,000 miles.
All in all, there’s not much to report here. Let’s see what happens if we
turn up the heat.
The Road to 2030:
Vehicle Production and Sales in the Autonomous Era
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Scenario 2: Ready for Prime Time
This is where things get interesting. Scenario 2 is
a vision of 2030 in which we’ve resolved the collision liability question, Vehicle-to-Infrastructure
technology (a key accelerant) has been embraced
by NHTSA and taxpayers, and the majority of
Americans are comfortable abdicating their piloting
duties. As a result, we say goodbye to single-occu­
pancy commuting in privately owned vehicles.
Does it sound far-fetched? If so, roll the
clock out to 2040 or 2050 – the percentage impact to sales (relative to baseline) is
the same regardless of the target year.
In specific terms, we’ve pegged
this scenario as follows:
• All taxi, livery, TNC, daily rental
and car-sharing passenger miles
are served by AV fleets (6.3% of
total PMT, as in Scenario 1).
• 25% of household PMT is now served
by AV fleets rather than private vehicles (29.7% of total PMT when
combined with the bullet above).
• An additional 25% of household PMT
is served by privately owned AVs with
Level 4 capability (23.4% of total PMT).
The Road to 2030:
Vehicle Production and Sales in the Autonomous Era
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Scenario 2: Ready for Prime Time
Current
Future
47%
Private
Conventional
94%
Private
Conventional
23%
Private
Autonomous
30%
6%
Fleet
Conventional
Fleet
Autonomous
Figure 2
Migration of
Passenger Miles
The Road to 2030:
Vehicle Production and Sales in the Autonomous Era
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Scenario 2: Ready for Prime Time
100.0%
Baseline UIO
Figure 3
Units in Operation Walk
100.0%
Baseline Sales
Figure 4
Sales Walk
- 4.9%
Occupancy ∆
- 18.5%
Utilization ∆
80.3%
Scenario 2 UIO
Note that Occupancy and Utilization have a compound effect which produces a
3.7% overlap when both are changed, as in this example.
- 4.8%
Occupancy ∆
- 4.8%
Lifespan ∆
The same is true of Occupancy and Lifespan,
resulting in a 1% overlap here.
91.4%
Scenario 2 Sales
This shifts over 23% of passenger miles to
higher-occupancy, longer-lasting vehicles.
The result: an 8.6% reduction in vehicle sales. (Note that as in Scenario 1, the
migration of privately owned vehicles to
Level 4 autonomy does not affect sales.)
What happens if these trends
are carried even further?
The Road to 2030:
Vehicle Production and Sales in the Autonomous Era
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Scenario 3: The Fleet Revolution
This is the scenario in which longstanding industry stakeholders lose their footing and are forced to assess the relevance of
their business models. Vehicle production takes a sizable hit,
but the biggest impacts are sustained by businesses that serve
the ancillary needs of vehicle owners. As PMT shifts to fleets the
need for expansive networks of insurance agencies, auto parts
stores, repair shops, and consumer lending operations is radically
diminished. Incumbents in these areas of the value chain may be
able to pivot toward serving fleet customers, but the structure of
their organizations will change dramatically. And what becomes
of automotive retailers? They’re well positioned to maintain AV
fleets and their real estate may be valuable to fleet operators for
downtime storage. There’s certainly room for savvy retailers to
adapt. Rather than speculate too deeply on how this shift will
manifest across the industry, let’s take a look at the numbers.
The Road to 2030:
Vehicle Production and Sales in the Autonomous Era
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Scenario 3: The Fleet Revolution
Current
Future
14%
Private
Conventional
9%
Private Autonomous
94%
Private
Conventional
77%
Fleet
Autonomous
6%
Fleet
Conventional
Figure 5
Migration of
Passenger Miles
In specific terms, we’ve pegged this scenario as follows:
• All taxi, livery, TNC, daily rental and car-sharing passenger miles are
served by AV fleets (6.3% of total PMT, as in Scenarios 1 and 2).
• 75% of household PMT is now served by AV fleets rather than
private vehicles (76.6% of total PMT when combined with the
bullet above).
• An additional 10% of household PMT is served by privately owned
AVs with Level 4 capability (thus 85% of household PMT
is autonomous).
The Road to 2030:
Vehicle Production and Sales in the Autonomous Era
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Scenario 3: The Fleet Revolution
100.0%
Baseline UIO
- 14.8%
Occupancy ∆
- 55.5%
Utilization ∆
40.8%
Scenario 3 UIO
Figure 6
Units in Operation Walk
100.0%
Baseline Sales
Note 11.1% overlap.
- 14.4%
Occupancy ∆
- 14.4%
Lifespan ∆
74.1%
Scenario 3 Sales
Figure 7
Sales Walk
Note 2.9% overlap.
The net impact is a sobering 26% reduction in annual production and sales. Recall
that this outcome is driven by the assumption that fleet vehicles have 25% higher
occupancy (2.09 vs. 1.67 passengers)
and 25% longer lifespans (200,000 miles
versus 160,000.) Unwinding these two
assumptions brings us back to the baseline of 16.5 million units in 2030, while
boosting them to 50% above current levels
yields a dizzying sales decline of 41%.
At this point we hope you’re fired up and
eager to create your own scenarios. Get in
touch and tell us what you think the industry
will look like in 2030.
The Road to 2030:
Vehicle Production and Sales in the Autonomous Era
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Closing Remarks
In this brief survey of future vehicle production scenarios we focused on
the three key drivers of vehicle demand. We learned that the complexity of the auto market is distillable into a manageable macro model. At
this point you may be questioning whether we’ve missed the point by
focusing on vehicle production. The answer depends on your role in the
ecosystem. For automotive lenders, insurance companies and suppliers, the answer is clearly no: production volume and private ownership
are vital to these links in the value chain, and are likely to remain so. But
the story is very different for automakers, retailers, and fleet operators.
As we noted briefly at the outset, value creation in an autonomous
world will be all about charging for the experience of getting from
A to B. The hardware will play a key role in this experience but
it will drive profits in a very different way. A fleet-oriented vehicle
parc effectively decouples hardware sales from profits, affecting
a radical shift in the mobility value chain. As vehicles last longer,
automakers can produce fewer units while serving the same customer base. That customer base is paying for movement and
their price sensitivity transforms when they’re not signing up for a
three- to six-year engagement with a single piece of hardware.
In this new paradigm, household travel costs can flex from day to
day. A consumer can opt for a luxury experience on a Friday afternoon following a tough week at work. On Monday morning she might
choose the cheapest option for a trip to the office or a status-forward
option for a client meeting. Dynamic pricing
will deliver real-time price signals that drive
behavior and boost market efficiency.
This flexibility is something the auto industry
will ultimately embrace, for it opens up a rich
new landscape of ways to serve consumers.
As they spend less on vehicle hardware they’ll
spend more on other aspects of the mobility
experience. An exciting market expansion
is within our sights. We look forward to
identifying and seizing these opportunities
with our partners in the years to come.
The Road to 2030:
Vehicle Production and Sales in the Autonomous Era
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20
Sensitivity Analysis: The Impact of Autonomous Fleets
Total U.S. Light Vehicle Sales (Retail + Fleet) in 2030 with constant per-capita PMT
Sensitivity to lifespan (@ fleet AV occupancy = 5.0)
Share of total PMT served by Autonomous Fleets
Sensitivity to occupancy (@ fleet AV lifespan = 500k miles)
Share of total PMT served by Autonomous Fleets
0%
Avgerage
Occupancy
(passengers
per fleet AV)
5%
25%
50%
75%
100%
1.2
16,876,844
16,402,784
14,506,543
12,136,243
9,765,942
7,395,642
1.6
16,876,844
16,310,338
14,044,316
11,211,788
8,379,260
5,546,731
2.0
16,876,844
16,254,871
13,766,979
10,657,114
7,547,250
4,437,385
2.4
16,876,844
16,217,893
13,582,088
10,287,332
6,992,577
3,697,821
25%
50%
75%
100%
120K
16,876,844
16,408,793
14,536,588
12,196,332
9,856,077
7,515,821
160K
16,876,844
16,314,845
14,066,849
11,256,855
8,446,860
5,636,866
200K
16,876,844
16,258,476
13,785,006
10,693,168
7,601,330
4,509,493
240K
16,876,844
16,220,897
13,597,110
10,317,377
7,037,644
3,757,911
3.3
16,876,844
16,171,670
13,350,974
9,825,105
6,299,235
2,773,366
320K
16,876,844
16,173,923
13,362,241
9,847,638
6,333,036
2,818,433
16,876,844
16,123,191
13,108,582
9,340,320
5,572,059
1,803,797
500K
16,876,844
16,123,191
13,108,582
9,340,320
5,572,059
1,803,797
1M
16,876,844
16,078,097
12,883,107
8,889,371
4,895,635
901,899
75%
100%
0%
Sensitivity to lifespan (@ fleet AV occupancy = 2.09)
Share of total PMT served by Autonomous Fleets
5%
25%
50%
75%
100%
1.2
16,876,844
16,957,457
17,279,909
17,682,974
18,086,040
18,489,105
1.6
16,876,844
16,726,343
16,124,340
15,371,836
14,619,332
13,866,829
0%
Avgerage
Lifespan
(miles per
fleet AV)
5%
25%
50%
120K
16,876,844
16,933,100
17,158,125
17,439,405
17,720,686
18,001,967
160K
16,876,844
16,708,075
16,033,002
15,189,159
14,345,317
13,501,475
10,801,180
2.0
16,876,844
16,587,675
15,430,999
13,985,153
12,539,308
11,093,463
200K
16,876,844
16,573,061
15,357,928
13,839,012
12,320,096
2.4
16,876,844
16,495,229
14,968,771
13,060,698
11,152,625
9,244,552
240K
16,876,844
16,483,051
14,907,879
12,938,914
10,969,948
9,000,983
3.3
16,876,844
16,379,672
14,390,986
11,905,129
9,419,272
6,933,414
320K
16,876,844
16,370,538
14,345,317
11,813,791
9,282,264
6,750,738
5.0
16,876,844
16,258,476
13,785,006
10,693,168
7,601,330
4,509,493
500K
16,876,844
16,249,025
13,737,751
10,598,658
7,459,565
4,320,472
1M
16,876,844
16,141,013
13,197,692
9,518,540
5,839,388
2,160,236
Sensitivity to lifespan (@ fleet AV occupancy = 1.67)
Share of total PMT served by Autonomous Fleets
Sensitivity to occupancy (@ fleet AV lifespan = 160k miles)
Share of total PMT served by Autonomous Fleets
Avgerage
Occupancy
(passengers
per fleet AV)
Avgerage
Lifespan
(miles per
fleet AV)
5%
5.0
Sensitivity to occupancy (@ fleet AV lifespan = 200k miles)
Share of total PMT served by Autonomous Fleets
Avgerage
Occupancy
(passengers
per fleet AV)
0%
1.2
0%
5%
25%
50%
75%
100%
16,876,844
17,188,571
18,435,478
19,994,112
21,552,747
23,111,381
1.6
16,876,844
16,899,678
16,991,017
17,105,190
17,219,363
17,333,536
2.0
16,876,844
16,726,343
16,124,340
15,371,836
14,619,332
13,866,829
Avgerage
Lifespan
(miles per
fleet AV)
120K
0%
5%
25%
50%
75%
100%
16,876,844
17,158,125
18,283,247
19,689,651
21,096,055
22,502,458
160K
16,876,844
16,876,844
16,876,844
16,876,844
16,876,844
16,876,844
200K
16,876,844
16,708,075
16,033,002
15,189,159
14,345,317
13,501,475
11,251,229
2.4
16,876,844
16,610,786
15,546,555
14,216,267
12,885,979
11,555,690
240K
16,876,844
16,595,563
15,470,440
14,064,036
12,657,633
3.3
16,876,844
16,466,340
14,824,325
12,771,806
10,719,287
8,666,768
320K
16,876,844
16,454,923
14,767,238
12,657,633
10,548,027
8,438,422
5.0
16,876,844
16,314,845
14,066,849
11,256,855
8,446,860
5,636,866
500K
16,876,844
16,303,031
14,007,780
11,138,717
8,269,653
5,400,590
1M
16,876,844
16,168,016
13,332,707
9,788,569
6,244,432
2,700,295
The Road to 2030:
Vehicle Production and Sales in the Autonomous Era
21
Sensitivity Analysis: The Impact of Autonomous Fleets
Change in U.S. Light Vehicle Sales (Retail + Fleet) vs.
Baseline with constant per-capita PMT
Sensitivity to lifespan (@ fleet AV occupancy = 5.0)
Share of total PMT served by Autonomous Fleets
Sensitivity to occupancy (@ fleet AV lifespan = 500k miles)
Share of total PMT served by Autonomous Fleets
0%
Avgerage
Occupancy
(passengers
per fleet AV)
5%
25%
50%
75%
100%
1.2
2%
-1%
-12%
-26%
-41%
-55%
1.6
2%
-1%
-15%
-32%
-49%
-66%
2.0
2%
-1%
-17%
-35%
-54%
-73%
2.4
2%
-2%
-18%
-38%
-58%
-78%
25%
50%
75%
100%
120K
2%
-1%
-12%
-26%
-40%
-54%
160K
2%
-1%
-15%
-32%
-49%
-66%
200K
2%
-1%
-16%
-35%
-54%
-73%
240K
2%
-2%
-18%
-37%
-57%
-77%
3.3
2%
-2%
-19%
-40%
-62%
-83%
320K
2%
-2%
-19%
-40%
-62%
-83%
2%
-2%
-21%
-43%
-66%
-89%
500K
2%
-2%
-21%
-43%
-66%
-89%
1M
2%
-3%
-22%
-46%
-70%
-95%
75%
100%
0%
Sensitivity to lifespan (@ fleet AV occupancy = 2.09)
Share of total PMT served by Autonomous Fleets
5%
25%
50%
75%
100%
1.2
2%
3%
5%
7%
10%
12%
1.6
2%
1%
-2%
-7%
-11%
-16%
2.0
2%
1%
-6%
-15%
-24%
-33%
2.4
2%
0%
-9%
-21%
-32%
-44%
0%
Avgerage
Lifespan
(miles per
fleet AV)
5%
25%
50%
120K
2%
3%
4%
6%
7%
9%
160K
2%
1%
-3%
-8%
-13%
-18%
200K
2%
0%
-7%
-16%
-25%
-35%
240K
2%
0%
-10%
-22%
-34%
-45%
3.3
2%
-1%
-13%
-28%
-43%
-58%
320K
2%
-1%
-13%
-28%
-44%
-59%
5.0
2%
-1%
-16%
-35%
-54%
-73%
500K
2%
-2%
-17%
-36%
-55%
-74%
1M
2%
-2%
-20%
-42%
-65%
-87%
Sensitivity to lifespan (@ fleet AV occupancy = 1.67)
Share of total PMT served by Autonomous Fleets
Sensitivity to occupancy (@ fleet AV lifespan = 160k miles)
Share of total PMT served by Autonomous Fleets
Avgerage
Occupancy
(passengers
per fleet AV)
Avgerage
Lifespan
(miles per
fleet AV)
5%
5.0
Sensitivity to occupancy (@ fleet AV lifespan = 200k miles)
Share of total PMT served by Autonomous Fleets
Avgerage
Occupancy
(passengers
per fleet AV)
0%
0%
5%
25%
50%
75%
100%
1.2
2%
4%
12%
21%
31%
40%
1.6
2%
2%
3%
4%
4%
5%
2.0
2%
1%
-2%
-7%
-11%
-16%
Avgerage
Lifespan
(miles per
fleet AV)
0%
5%
25%
50%
75%
100%
120K
2%
4%
11%
19%
28%
36%
160K
2%
2%
2%
2%
2%
2%
200K
2%
1%
-3%
-8%
-13%
-18%
2.4
2%
1%
-6%
-14%
-22%
-30%
240K
2%
1%
-6%
-15%
-23%
-32%
3.3
2%
0%
-10%
-23%
-35%
-47%
320K
2%
0%
-10%
-23%
-36%
-49%
5.0
2%
-1%
-15%
-32%
-49%
-66%
500K
2%
-1%
-15%
-32%
-50%
-67%
1M
2%
-2%
-19%
-41%
-62%
-84%
The Road to 2030:
Vehicle Production and Sales in the Autonomous Era
22
Notes
Occupancy assumptions: Average household vehicle
occupancy is 1.67 per http://nhts.ornl.gov/2009/pub/stt.
pdf; we assume that baseline occupancy for taxi, livery,
TNC, rental, and car-sharing vehicles is 25% higher (2.09
vs. 1.67) and serves a combined 6.25% of total PMT.
“Autonomous Vehicle” refers to a vehicle capable of
Level 4 autonomy per NHTSA
•
http://www.nhtsa.gov/About+NHTSA/Press+Releases/
U.S.+Department+of+Transportation+Releases+
Policy+on+Automated+Vehicle+Development
References
VMT:
•
https://www.fhwa.dot.gov/policyinformation/tables/vmt/vmt_forecast_sum.pdf
•
http://www.fhwa.dot.gov/policyinformation/
travel_monitoring/14dectvt/14dectvt.pdf
•
https://www.fhwa.dot.gov/policyinformation/
travel_monitoring/15novtvt/
•
https://www.fhwa.dot.gov/policyinformation/
travel_monitoring/15novtvt/page3.cfm
•
http://www.advisorperspectives.com/dshort/
updates/DOT-Miles-Traveled.php
•
http://www.ssti.us/2014/02/
vmt-drops-ninth-year-dots-taking-notice/
Population (321,418,820 as of July 1, 2015):
•
http://www.census.gov/popclock/
Household VMT by trip type:
•
http://www.citylab.com/commute/2015/03/
driving-in-america-is-approaching-a-new-normal/388421/
•
https://www.fhwa.dot.gov/policy/2010cpr/execsum.cfm
•
http://traveltrends.transportation.org/Documents/
B2_CIA_Role%20Overall%20Travel_web_2.pdf
•
•
https://www.eia.gov/conference/2014/
pdf/presentations/mcguckin.pdf
http://www.post-gazette.com/news/
transportation/2016/01/16/Survey-findsmost-commuters-travel-alone-by-car/
stories/201601160020
Occupancy:
•
1.55: http://css.snre.umich.edu/css_doc/CSS01-07.pdf
•
1.67: http://nhts.ornl.gov/2009/pub/stt.pdf (page 39)
Taxi VMT as % of total:
•
https://www.fhwa.dot.gov/planning/tmip/
publications/other_reports/commercial_vehicles_transportation/sum_sect4.cfm#fn4_9
Annual mileage for NYC taxi:
•
http://www.nyc.gov/html/tlc/downloads/
pdf/2014_taxicab_fact_book.pdf
Daily rental market size:
•
Holding period:
•
http://www.fool.com/investing/general/2012/07/13/
surprising-facts-about-the-rental-car-industry.aspx
•
http://www.autorentalnews.com/channel/
remarketing/news/story/2016/01/manheim-indexup-risk-average-mileage-dips.aspx
Boston taxi utilization:
•
http://www.cityofboston.gov/mayor/
pdfs/bostaxiconsultant.pdf
Age of vehicles in US:
•
http://www.rita.dot.gov/bts/sites/rita.dot.gov.
bts/files/publications/national_transportation_statistics/html/table_01_26.html_mfd
•
http://www-nrd.nhtsa.dot.gov/Pubs/809952.pdf
Cost per mile – TNC vs. privately owned vehicle:
•
http://www.businessinsider.com/
uber-lyft-cost-versus-car-by-metro-area-2016-3
UberX vs. taxi economics:
•
http://valleywag.gawker.com/
beautiful-illusions-the-economics-of-uberx-1589509520
Others:
•
http://miter.mit.edu/articlebalancing-act-future-car-sharing-and-driving-service/
•
http://www1.nyc.gov/assets/operations/downloads/
pdf/For-Hire-Vehicle-Transportation-Study.pdf
•
https://social.ford.com/content/campaign/media-trends/
•
http://fivethirtyeight.com/features/
how-suburban-are-big-american-cities/
•
http://alankandel.scienceblog.com/2014/02/07/
annual-per-capita-california-driving-1-5-times-the-national-average/
•
http://www.mckinsey.com/industries/high-tech/our-insights/
disruptive-trends-that-will-transform-the-auto-industry
Private vehicle average annual miles:
•
•
Driver-basis: https://www.fhwa.dot.
gov/ohim/onh00/bar8.htm
Vehicle-basis: http://www.afdc.energy.gov/data/
AV impact on vehicle occupancy and GHG:
•
http://orfe.princeton.edu/~alaink/SmartDrivingCars/
PDFs/aTaxi_GHG_Emissions_Greenblatt.pdf
AV impact on total miles:
•
http://www.autorentalnews.com/fileviewer/2229.aspx
http://fortune.com/2015/11/17/
la-auto-show-vehicle-miles/
The Road to 2030:
Vehicle Production and Sales in the Autonomous Era
23
For More Information
Daniel Malik
Director, Product
[email protected]
Marilynn Youngs
VP, OEM Solutions
[email protected]
The Road to 2030:
Vehicle Production and Sales in the Autonomous Era
24
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