Can automated vehicles really make our cities better? - Designing the Internet of Vehicles - End Of Driving
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Can automated
vehicles really make
our cities better?
Designing the Internet of Vehicles
Bern Grush and John Niles
Grush Niles Strategic
Presented at
Amazon’s first
Radical Urban Transportation Salon
2017.04.21
Two markets for
vehicle automation
The successive levels of vehicle
automation define two markets:
Personal, owned
Public, shared
The most critical social attribute of the era of new mobility is how we consume. Will
we really shift toward consuming rides or will we consume vehicles by continuing to
own 0.8 vehicles per capita (0.65 in Canada)? Will these ownership figures drop
significantly as some people assume?
2
Two*
diffusion( AV*
access*
anxiety* markets* MaaS*
cultural*
behavioral*
&*social*
sell$ biases* legacy* marke-ng* sell$
infra3*
cars$ structure*
rides$
compe*ng(effects(
Mo*vates(ownership( Sustains( Mo*vates(sharing( Promotes(
• transit*ridership*down* ! conges-on* • transit*transformed* ! access*
! crashes* ! health*
• infrastructure*crisis* ! parking*
• transit*ridership*up* ! livability*
• sustains*mixed*traffic* ! sprawl* • quicker*shiC*to*AVs* ! safety*
• less*urban*innova-on* ! CO2* • recover*parking*space* ! social*equity*
innova*ons(
Transit(Leap( Fleet(Governance(
• public3use,*shared*fleets* • performance*metrics* ! PKT*>>*VKT*
• start*small,*expand*by*demand* • op-mized* ! shared*>>*owned*
! transit*integra-on*
• grow,*merge,*spread* • mul-3jurisdic-onal* ! >>*social*equity*
• transform*en-re*urban*regions* • P3*funded*
There are reasons many people prefer owning a vehicle, and many reasons why not
owning can be attractive. These barriers and accelerators can be understood and
used by car sellers and ride sellers to compete. There is no reason this competition
will stop. To help the ride-selling market, we propose Transit Leap as a method to
grow shared fleets from local to regional and Fleet Governance standards to allow
rapid, managed expansion of integrated commercial and public fleets.
3Will(ride>buying(disrupt(ownership?(
Now(to(2030( by(2040( by(2050(
(likely)( (probable)( (possible)(
Bus(Taxi(
Carshare(
Buy( Buy(
TNCs(
Early(Level(4( rides( vehicles(
Private( Buy(
Buy(
vehicle(use( vehicles(
(Levels(1>4)( rides(
Ini*ally(owning( DeloiQe(says(80%( But(not(without(
will(dominate( shared(by(2040( social(innova*on(
During the early commercialization of automated vehicles, most ride-buying will be
from people who currently buy rides from transit, taxi, ride-hailing, limos, and
carshares. Most current car owners will purchase Level 2 or 3 vehicles for ownership.
What is uncertain is how fast and how far purchasing vehicles will morph into
purchasing rides. Many pundits suggest “No one will own cars in the future”. But
vehicle ownership is not only a matter of technology or finance. The desired shift
requires considerable social innovation.
4Forces(of(Diffusion(for(Automated(Vehicles(
car3dominant* cheap* service*
community* parking* personaliza-on*
>*Forces$encouraging$diffusion$
Rogers’*diffusion*factors:* high*
car* feature* safety* high3density*
• rela-ve*advantage* design* richness*
• compa-bility* convenience*
strong*
• complexity* on3demand* non*car3oriented*
network* personal* wide*
• trialability* (private* instant* community*
effect* vehicle*
• observability* *&*secure)* response*
availability** choice* personal*
assurance* “access* 243hour* security*
Encourage* status* inadequate* anxiety”* availability*
household* No*driver* Encourage*
new*travel*
habit* transit* license* robo3transit*
ownership* affordability* bargains*
Consume$vehicles**Consume$rides$
Discourage* percep-on* more*expensive*
Discourage*
$Forces$discouraging$diffusion*Robo>fleets(and(public(policy(goals(
(Fleet(Governance)(
Privately* Fleets*compe*ng* Fleets*integrated*
owned*cars* with*public*transit* with*public*transit*
Poor*mobility* BeVer*mobility* Best*mobility*
Unsustainable* Less*efficiency* Sustainable*
More*car*traffic* Increase*in*VMT* BeVer*equity*
Drop*in*transit*use* Increased*efficiency*
* More*transit*use*
Lowest*cost*
*
UITP:$Union$Interna:onale$des$Transports$Publics;$*Interna-onal*Associa-on*of*Public*Transport*
The International Association of Public Transport (UITP) has delineated three
potential futures for the coming robo-fleets: [1] mostly private, [2] lots of
commercial competition, and [3] coordinated fleets (commercial or public) that are
integrated with transit — especially rail and bus rapid transit (BRT). Collaboration
and management are more critical than automation and connectivity.
6Cloud>based(system(management(
Mobility(Network(Management(
Regional*transporta-on*systems*
Policy(performance(
Transit*integra-on*
Social*equity*
Occupancy*
Collabora*ve((MaaS)*
Availability*
Sharing*
Access*
Connected(
Automated(
There are four technology layers that comprise the full system for automobility in the
21st century. These layers move through personal, local, trip and region. The
personal layer is the automated vehicle — tangible, exciting and easily imagined. The
local layer for connection is less well-understood but critical to deliver many related
services and has considerable potential for both additional safety and concerns for
latency and cyber security. Mobility as a Service, MaaS, is the nascent layer that
manages whole trips or even monthly planning for mobility. It is this layer that
enables the change from car-buying to ride-buying. The final layer Mobility Network
Management is concerned with entire regional fleets — hundreds of thousands of
vehicles. This final layer unlocks the social value that is the assumed potential of
massive robo-fleets.
7The(Internet(of(Vehicles(
Automated("(Connected("(Collabora*ve("(Managed(
Mobility(Network(Management(
Regional*transporta-on*systems*
Policy(performance( Physical(op*miza*on(
Transit*integra-on* Massive*fleets*of*SAVs*
(and*other*connected*subscribers)*
Social*equity*
Automated*
Occupancy* Transit* Policy>based(performance(
Availability* Necessary*and*feasible*
Sharing* Fleet>based(licensing(
Access* Not*a*medallion*system*
Robo3taxis* Road3pricing*structure*
Performance3based*discount/subsidies*
Regional(—(State>wide(—(Na*onal(
Out*of*scope*for*current*transit*jurisdic-ons*
Private* Automated* Vast(efficiency(opportunity(
AVs* goods*
Bikes**
vehicles*
Mobility Network Management is a cloud-logistics system for hyper-governance and
has both operational and social performance goals. Assumption 1: Subscribing fleets
provide anonymized data that permit performance-based road pricing in place of a
taxi medallion system. Subsidies are structured as a form of negative road pricing.
This allows commercial fleet operators to profit from high-end services, then
subsidize social equity and address other performance issues listed above.
Government sets prices on roads. Fleet operators set prices on rides. Assumption 2:
Ride providers will not be jurisdictionally constrained, because differences will be
settled by the pricing scheme as a trip crosses boundaries. Assumption 3: All
motorized, automated vehicles and fleets must subscribe. Bikes are not required to
subscribe, but can do so to gain value from participating in the network.
8Social(
diffusion(
own*or*share* Automobiles*are*an*
acceptance*(fear)*
preferences* engineering*problem;*the*
nudges* system*of*automobility*is*a*
Infrastructural( social*equity* social*problem*
deployment( access*by*ability*
access*by*distance*
*spa-al*alloca-on* privacy*
AV( lanes* livability*
intersec-ons* rapid*change*
innova*on( structures*
*
vehicle*capabili-es* parking* new*externali-es* The*en-re*system*
* aVen-on* of*automobility*
telecommunica-ons* mul-modal* ethics*
*
map*maintenance* insurance* will*change*
* op-miza-on* safety*
hard' fleet* personal*security*
*
network* liability*
cyber*security* licensing*
user*subsidies*
difficult' infrastructure*funding* Automo-ve*engineers*focus*
public*transit* on*the*leC*circle;*social3
road*use*fees*
compe--on* scien-sts*and*governments*
jurisdic-on* focus*on*the*right*circles*
wicked'
Industry and media have focused on AV innovation — automation and connectivity —
for over a decade. However, consideration of difficult infrastructure issues as well as
attention to wicked social questions have been slower to materialize. If we are over-
focused on technology solutions for our urban transportation problems, we will fail to
address the underlying issues.
“Reframing social problems as a series of technological problems distracts
policymakers from tackling problems that are non-technical in nature.” Evgeny
Morosov, The Net Delusion, p 305.
9A(future(of(smaller(urban(vehicle(fleets(
5000*
Vehicle(Popula*on((000s)(
4000*
3000*
2000*
1000*
0*
2015* 2020* 2025* 2030* 2035* 2040* 2045* 2050*
Shared*cars* Personal*cars*
Simple performance variables, to be nudged by the Mobility Network Management
system, are manipulated in a simulation of a fleet sized for a population of 6.5M
growing to 10.5M (Toronto). Per capita PKT was held constant, vehicle occupancy
was nudged from 1.6 to 1.9, and the proportion of PKT in shared vehicles was
nudged from 20% to 80%.
10Sensi*vity(modeling(
Regional(Vehicle(Counts(Under(Example(Scenarios(
5000*
Shared*vehicles* Private*vehicles*
Vehicles*(000s)*
4000*
3000*
2000*
1000*
0*
Case( 1( 2( 3( 4( 5( 6( 7( 8(
PKT*in*shared*
20%* 40%* 60%* 70%* 70%* 70%* 80%* 85%*
vehicles*
Occupancy*rate*in*
1.6* 1.6* 1.6* 1.6* 2.0* 2.0* 2.0* 2.0*
shared*vehicles*
Daily*Km*per* 300* 300* 300* 300* 300* 400* 400* 400*
shared*vehicle*
Daily*PKT/vehicle*
overall*
89* 111* 150* 181* 191* 202* 269* 323*
Simple performance variables were manipulated to simulate the policy performance
of a managed network for a city of 6.5 million people. Over the eight cases shown, a
fleet of 4.25 million registered vehicles were reduced by more than three million
vehicles. Note that the shared vehicle fleet will turn over much more frequently than
the private fleet, meaning that vehicle manufacture count does not necessarily drop.
However, some vehicle manufacturers have stated intentions to build and operate
such fleets, so they could be expected to design and build vehicles for this new
purpose. Employment would change, but as these companies take over the driving
labor of the general public, new service levels will increase employment.
11Annual(Fleets(Costs((millions)( Fleet(costs((((((((|((((((((Trip(costs(
Costs*per*PKT*
depend*on*
commuter*
dispersion:*
26*to*84*cents*
Year((2020(starts(at(zero))(
Based on simple assumptions such as a 16-hour duty cycle, 24-kph average, two- to
12-seat vehicles, 50 percent occupancy, and annual vehicle costs ranging around
$100,000, we calculated fleet costs for several ranges of ride-buying market
penetration after the initial easy-to-achieve penetration of 20 percent. This first
stage is easy as it is disrupting transit and multiple household vehicles. Costs per
PKT depend on peak demand because fleet size must be scaled accordingly.
Performance incentives from the Mobility Network Management system can be
designed to push demand away from peak times which will tend to decrease fleet
size and increase profits.
12Recommenda*on(#1:((Transit(2017>2022(
Grow(ride>buying(
Skip(Level(3(AVs(
Start(Level(4(AVs(in(modest(doses(
Leap*1* Leap*2* Leap*3* Leap*4* Leap*5*
* * * * *
Fixed*Loop* Small*Area* Large*Area* City* Mega3
ShuVle:*parking,* Campus;*First/Last* CBD;*borough,* * region*
shopping,*tourist* Mile* island*
* * * * 2 *
[2km2]* [500km ]* [5,000km2]*
[5km22]*] [50km2]*
* * *
* *
Driverless;*short* Any*address;*any* Any*-me;*
2017-2022
2020-2025
2025-2035
2035-2045
2045-2060
Self3op-mizing;*
Self-optimizing; Rich3connect*with*
trips;*repe--ve* trip*in*single* any*where,*
flexible;*
flexible; transit;*strong*
* vehicle;*high* any*distance*
constrained*area*
constrained tailoring;*stop*at*
* tailoring;*high* *
*
areas most*addresses*
social*equity* *
*
No*effect*on*current*transit* * *
* *
©GrushNiles
No*drivers.*Monitors,*stewards,*security,*constrained*public/shared*applica-ons)*
Even while preparing for hyper-governance, there is an immediate starting place for
transit agencies. While addressing first/last mile and small-area starter systems with
Level 4 vehicles, municipalities will gain experience for later governance while
citizens gain experience in the systems that they will be asked one day to consider in
place of vehicle ownership. Even these Transit Leap stages are candidates for P3
involvement and baby-steps in hyper-governance. They can be started now.
13Toronto — Bern Grush bgrush@endofdriving.org @transitleap 1 647 218 8600
Seattle — John Niles jniles@endofdriving.org @endofdriving 1 206 781 4457
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