How can we deploy autonomous vehicles for environmental sustainability?

1. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
1
Bern
Grush
|
John
Niles
|
endofdriving.org
Environmentally
Sustainable
Deployment
of
Autonomous
Vehicles
Feature
Creep…
or
…ApplicaEon
Creep?

2. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Policy
Technology
Society
Planning
&
Deployment
Infrastructure
Environment
Urban
livability
Human
health
Climate
footprint
CriEcal
links…
2

3. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Before
the
last
Urban
Mobility
TransformaEon…
3

4. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Did
we
apply
what
we
learned?
4

5. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
5
2010
One
billion
motor
vehicles
2050
Four
billion
motor
vehicles
MANY
COSTS
• Vehicle
Kilometers
Traveled
• Vehicles
• Energy
consumpEon
• Carbon
• Parking
• Roads
• FataliEes,
injuries
KEY
BENEFIT
• Mobility
(Passenger
Kilometers
Traveled
-­‐
PKT)

6. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Car
ownership
is
a
well-­‐oiled
machine
6
The
economic
process
of
car
ownership
unEl
now,
follows
a
simple
rule:
as
the
per-­‐capita
income
of
a
populaEon
reaches
$10,000
acquisiEon
grows
rapidly.
As
it
hits
higher
incomes
(over
20,000)
growth
slows,
then
saturates
above
40,000
(1995
$)

7. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Car
ownership
is
a
well-­‐oiled
machine
7

8. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Middle-­‐class-­‐centric
opEmism
From
Wikipedia…
• [A
new
beginning…]
– Full
AV
prototype
here
– Available
2020
– Reduce
world
vehicles
count
to
Eny
fracEon
– Children
chauffeured
– No
more
DUI
– Lives
saved
• No
one
keeps
their
car
• Tap
a
smart
phone
and
a
perfect*
ride
shows
up:
– robo-­‐taxi
– robo-­‐bus
– robo-­‐limo
– robo-­‐Segway
8
…roboAc
UberizaAon
of
transit
*
Tailoring

9. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
9
Feature
Creep…
or
…ApplicaEon
Creep?
Apply
roboEcs
to
get
be#er
cars
(just
like
last
century…)
Apply
roboEcs
to
get
be#er
mobility
(just
like
“they”
promise…)

10. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
“…a
consensus
is
emerging
that
the
journey
to
autonomy
will
be
a
progressive
one
in
which
small
steps
are
made
along
the
way
and
new
features
are
added
to
vehicles
every
six
to
nine
months
or
so.”
Clearwater
InternaEonal,
Clearthought
March
2015
Feature
Creep
10

11. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Feature
creep:
beker
cars
• Focus
on
technology
• Incremental
improvements
• Replace
the
old
fleet
with
a
new
fleet
• More
cars
sold
è
new
model
lust
• More
household
vehicles
• More
infrastructure
• Increased
policy
complexity
• Insure
growth
projecEons
to
4
billion
vehicles
• High-­‐end
trickle-­‐down
è
wealthy
consumers
subsidize
creep
• Growing
transportaEon
inequity
• Creep
toward
SAE
level
5
(Body-­‐out)
è
2050?
or
later
• A
long
legacy
of
pre-­‐roboEc
vehicles
on
the
road
11
20th
Century
in
21st
Century
clothing

12. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Feature
Creep
12

13. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
ApplicaEon
creep:
beker
mobility
• Focus
on
reach,
mobility,
access
• Publicly
accessible
roboEc
vehicles
• Human
akendant
(not
driving)
• Shared
vehicles;
shared
rides
• Robo:
buses,
shukles,
TNCs,
taxis,
cars,
M2W,
M3W
• Reduced
policy
complexity
– Constrained
operaEng
areas
– Fixed-­‐loop
shukles
– RelaEvely
isolated
è
safer
– Lower-­‐risk
• P3s
• Start
now
13
Mobility
as
a
Service
(MaaS)

14. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
ApplicaEon
Creep:
EU
14

15. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
ApplicaEon
Creep:
Canada
15
Driverless
Electric
Shu>le
Buses
to
be
Studied
for
Use
at
Zibi
September
1,
2015
Okawa,
Ontario,
Canada
–
Windmill
Developments
and
the
Canadian
Automated
Vehicles
Centre
of
Excellence
(CAVCOE)
have
teamed
up
to
conduct
a
feasibility
and
planning
study
for
the
demonstraEon,
trial
and
deployment
of
fully-­‐automated,
electric
shukle-­‐buses
at
Zibi.

16. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Creep
Levels
Feature
Creep
Levels
of
AUTOMATION*
1. Driver
Assistance
2. ParEal
AutomaEon
3. CondiEonal
AutomaEon
4. High
AutomaEon
5. Full
AutomaEon
– No
human
drivers
ApplicaHon
Creep
Levels
of
REACH*
1. Route
2. Small
area
3. Large
area
4. Regional
5. NaEonal,
InternaEonal
– No
human
drivers
16
*
SAE
J3016
*
Under
development
at
GNA

17. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
ApplicaEon
Creep
DefiniEons:
Levels
of
Reach
17
Lvl
Name
DefiniHon
Tailoring
Network/Reach
PKT
1
Loop
(started)
Vehicles
on
limited,
repeHHve,
fixed-­‐
route,
fixed
schedule
routes
of
short
duraEon,
under
30
mins,
under
10
km,
under
20kph
Likle
or
none:
Vans,
minibuses
Shukle:
parking,
shopping,
urban
tourist
<1%
2
Small
Area
(2025)
Vehicles
operaEng
on
most/all
roadways/routes
in
a
constrained
area.
Vehicles
self-­‐opEmize
routes
depending
on
combinaEon
of
schedule
performance
and
user-­‐demand
responds
to
individuals
calling
for
service
by
origin
and
desEnaEon
Modest:
vehicles
from
2
to
8
passengers;
shukles,
taxis,
TNCs,
minibuses;
modest
opEmizaEon
of
vehicle
assignment.
Start
of
P3s.
Campus:
corporate,
university,
military,
reErement
community.
First-­‐mile
and
last
mile
to/from
train
staEons
or
transit
hubs.
Under
50km2
3%
3
Large
Area
(2035)
Same
as
Level
2,
plus
vehicles
operaEng
on
most/all
roadways/routes
in
an
urban
subarea/district
Full:
vehicles
from
2
to
30
passengers.
At
least
3
compeEng
fleets;
at
least
2/3
are
P3s.
Borough,
suburban
or
exurban
area,
CBD,
Island.
Under
500km2
15%
4
Regional
(2045)
As
level
3,
plus
anywhere,
any
distance,
public
roads
Full:
vehicles
from
1
to
100+
passengers;
Majority
P3s
Megaregion.
Under
5000km2
40%
5
NaEonal
(2055)
As
level
4,
plus
any
mapped
private
roadways
Full;
Majority
P3s
NaEonal,
InternaEonal
80%
©
Grush
Niles,
2015

18. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Vehicle
PopulaEon
18
Four
billion
vehicles…
or
…One
billion
vehicles?
Feature
creep
will
encourage
worldwide
car
ownership
growth
to
over
0.4
per
capita
è
Now
at
0.12
per
capita
ApplicaEon
creep
enables
this
to
stay
at
0.1
per
capita.
è
80%
of
PKT
in
shared
vehicles

19. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
AutomoEve
Manufacturing
Feature
Creep
• More
vehicles
– Household
use
– Less
tailoring
– Long
road
life
• High-­‐opEon
vehicles
– Personal/household
sales
• More
– Features
– Turnover
– Resales
ApplicaHon
Creep
• More
vehicles
– Public
use
– More
tailoring
– Short
road
life
• Simpler
vehicles
– Service/maintenance
opEmizaEon
• More
– Wearables
– Carryables
– Portables
19

20. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Parking
20
Parked
95%
of
Eme…
or
…Parked
50%
of
Eme?
Personal
Vehicles
Use
increasing
percentage
of
urban
real-­‐estate…
Shared
vehicles
Shrinking
percentage
è
opportunity
to
manage
differently

21. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
CongesEon
Feature
Creep
Bias:
owning
• More
SOVs
• Likle
or
no
tailoring*
• Plus-­‐sized
vehicles
*
right-­‐sizing
of
vehicle
for
purpose
ApplicaHon
Creep
Bias:
sharing
• More
HOVs
• Enables
high
tailoring
• Reduce
vehicle
size/
weight
per
PKT
21

22. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Tailoring
Feature
Creep
Household
vehicles
• Ownership
means:
“own
for
most
or
all
of
my
expected
needs”
• Min
tailoring
ApplicaHon
Creep
Vehicles
on
demand
• Massive
shared
fleets
enable
right
vehicle
per
call
• Max
tailoring
22

23. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Energy
• OpEmizing
managed
fleets
provide
greater
opportuniEes/incenEves
to
control:
– Energy
type
– Energy
waste
– Energy
distribuEon/storage
23

24. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Accident
risk
Feature
Creep
• Mixed
driver-­‐in/driver-­‐
out,
2020-­‐2050
• Mixing
L2,
L3,
L4,
L4.5
means
higher
risks
for
distracted
driving!
ApplicaHon
Creep
• IsolaEon
of
driver-­‐in/
driver-­‐out
reduces
risk
• Removes
distracEon
circumstances
24
“AlerAng
a
driver
to
retake
control
during
an
emergency
[is]
one
of
the
biggest
safety
challenges
for
manufacturers
of
parAally
automated
cars,
industry
officials
and
scienAsts
said.”
hXp://www.scmp.com/news/arAcle/1855591/race-­‐automaAon-­‐google-­‐and-­‐carmakers-­‐take-­‐different-­‐roads-­‐pursuing-­‐self-­‐drive

25. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Sprawl
• Influence
on
Pakern
and
Density
of
Land
Use?
• Uncertain!
– Mostly
policy
dependent
– Policy
will
be
poliEcal,
variable,
contenEous
25

26. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
RaEo
of
PKT
to
VKT
Feature
Creep
Bias:
ownership
• PKT:VKT
raEo
will
drop
• Lower
need
for
chauffer
• Why
wait?
– instant
graEficaEon
– Low
perceived
marginal
cost
ApplicaHon
Creep
Bias:
transit
• PKT:VKT
raEo
will
rise
• Price
per
trip/per
km
– High
perceived
marginal
cost
26

27. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Infrastructure
Costs
Feature
Creep
Household
vehicles
• More
congesEon
• More
parking
demand
• More
infrastructure
ApplicaHon
Creep
Large
shared
fleets
• Less
congesEon
• Less
parking
demand
• Less
infrastructure
27

28. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Transit
jobs
Feature
Creep
Bias:
ownership
• Reduce
transit
demand
• Now
5
–
8%
of
PKT
• Job
loss
ApplicaHon
Creep
Bias:
shared
fleets
• Increase
transit
demand
• Target
50
-­‐
80%
of
PKT
• Job
gains
28

29. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Transit
Subsidy
Feature
Creep
Bias:
ownership
• Lower
transit
use
• High
cost
per
shared
transit
PKT
ApplicaHon
Creep
Bias:
shared
fleets
• Massive
tailored
fleets
• High
farebox
recovery
• Enable
P3
involvement
29

30. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
TransportaEon
equity
Feature
Creep
Bias:
ownership
• Private
vehicles
are
a
high
expense
for
lower
income
families
• Dominant
ownership
ensures
lower
equity
for
non-­‐owners
ApplicaHon
Creep
Bias:
transit
• Lower
income
families
depend
more
owen
on
transit
• Shared
transit
fleets
enables
greater
equity
30

31. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Dead-­‐heading
Feature
Creep
Max
private
ownership
• Dead-­‐heading
abuse
ApplicaHon
Creep
Min
private
ownership
• Robo-­‐taxi
– some
dead-­‐heading
• Larger
tailored
fleets
– min
dead-­‐heading
• Pricing
– max
ride-­‐sharing
– min
dead-­‐heading
31

32. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Public
Private
Partnerships
(P3s)
Feature
Creep
Bias:
ownership
• Build
more
roads,
more
parking
ApplicaHon
Creep
Bias:
transit
• Build
massive
shared
fleets
(transit)
32
Across
the
board
opportunity
for
P3s

33. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Policy
Complexity
Feature
Creep
• Driver-­‐in/Driver-­‐out
mix
from
2030?-­‐2050
• Motor
vehicle
regulaEon
ApplicaHon
Creep
• P3s
bring
policy
challenges
• Transit
vehicle
regulaEon
33
Complexity
either
way

34. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
How
soon
to
the
“Final
Jump”?
Feature
Creep
Household
vehicles
• Discon@nuity
at
L5
• Technology
deployed
slowly
due
to
mix
of
driver/no-­‐driver
• L5
likely
delayed
ApplicaHon
Creep
Large
shared
fleets
• Steady
ramp
toward
L5
• Technology
deployed
sooner
due
to
Eered
use-­‐constraints
• L5
acceleraEon
enabled
34

35. Grush Niles Associates
Toronto Ÿ Seattle Transport
Futures
—
The
Future
of
the
Car
—
September
17,
2015
Thank
you!
Feature
Creep
Increases
• CongesEon
• Parking
• Energy
consumpEon
• Vehicle
populaEon
• Infrastructure
• SOVs
• Over-­‐sized
vehicles
• Accidents
• Transit
subsidies
ApplicaHon
Creep
Increases
• Tailored
vehicles
• Simpler
vehicles
• Vehicle
sharing
• Ride
sharing
• RaEo
PKT:VKT
• Transit
ridership
• Transit
jobs
• P3s
• Speed
of
L5
arrival
35
bgrush@endofdriving.org