TRAVELTRENDSIn the Automated Future

Alex Rixey | Fehr & Peers DCMay 2018

AGENDA

1

2

3 Policy Responses

Predictions

Trends

Trends

1970 to 2004 INCREASE

VMT Trends

2004

VMT Trends2017 to 2040 UNCERTAINTY

Tipping Point

Travel Trends

$-

$5

$10

$15

$20

$25

2013 2014 2015 2016

Gro

ss B

oo

kin

gs (

bil

lio

ns $

)

Source: Uber

TNC ActivityRapid Growth

TNC ActivityRapid Growth

Evidence

TNC Effects

60+ % of TNC Trips

Are New Vehicle Trips

Trend Effects on TransitEvidence

www.schallerconsult.com | 2018 TRB Presentation

ChicagoNew York

Los AngelesBoston

Trend Effects on TransitWMATA

WMATA «Understanding Rail and Bus Ridership» October 2017.

Trend Effects on TransitEvidence

The Washington Post | Falling Transit Ridership Poses an ‘Emergency’ for Cities,

Experts Fear | Faiz Siddiqui | 3.24.18

Trend Effects on TransitEvidence

www.schallerconsult.com | 2018 TRB Presentation

AV DefinitionsSociety of Automotive Engineers

Autonomous

Drone

Autonomous

Trucking

Sidewalk

Delivery

Robot

On-Street

Robot

Autonomous

Vehicle

Autonomous Delivery Technologies

Autonomous Delivery Technologies

AV Predictions

AV Predictions

Potential Growth in Autonomous Vehicles as Percent of Vehicle Fleet

0%

20%

40%

60%

80%

2020 2025 2030 2035 2040

Pe

rce

nt

of

Veh

icle

Fle

et

Quarles & Kockelman (Conservative) Quarles & Kockelman (Moderate)

Quarles & Kockelman (Aggressive) Litman (Conservative)

Litman (Aggressive) Goldman Sachs

Trendline (high) Trendline (low)

AV Predictions

Tipping Point

AV Predictions

95% of Passenger Miles by 2030

Delivered by Transportation as a

Service (TaaS) in Autonomous

Electric Vehicles (AEVs)

https://tonyseba.com | 2018 TRB Presentation

Regional Travel

Demand Models

9

Freeway

Simulations

2

TNCs to AVsFehr & Peers Testing

1. Decrease access time

2. Decrease parking costs

3. Decrease impact of lost in-auto time

4. Increase auto availability

5. Increase non-work trip-making

6. Increase auto occupancy

7. Increase freeway capacity

AV TestsTravel Behavior Mechanisms

1. Decrease access time

2. Decrease parking costs

3. Decrease impact of lost in-auto time

4. Increase auto availability

5. Increase non-work trip-making

6. Increase auto occupancy

7. Increase freeway capacity

TNC EffectsTravel Behavior Mechanisms

Public and Shared Private and Mine

—OR—

How will we use AVs?

Vehicle Results

AV Tests – Regional Models

Transit Results

AV Tests – Regional Models

0

500

1,000

1,500

2,000

2,500

3,000

0% 20% 40% 60% 80% 100%

Tota

l Ne

two

rk D

elay

Automated Vehicle Fleet Percentage

AUTOMATED VEHICLE FLEET PERCENTAGE EFFECT ON TOTAL NETWORK DELAY

0.0

10.0

20.0

30.0

40.0

50.0

60.0

0% 20% 40% 60% 80% 100%

Ne

two

rk A

vera

ge S

pee

d

Automated Vehicle Fleet Percentage

AUTOMATED VEHICLE FLEET PERCENTAGE EFFECT ON NETWORK AVERAGE SPEED

AV Tests – Freeway SimulationNorthern California Case Study

Evidence

“AV” Effects

Heaven or Hell?

Source: NACTO, Blueprint for Autonomous Urbanism

Heaven or Hell?

Source: Bethesda Magazine

Depends on the desired outcome

Policy Response

Private Sector Motivation: Revenue(Miles, Minutes, and Choices)

Public Sector Motivation(s): ComplexIncrease mobility?

Improve safety?

Increase accessibility?

Promote equity?

Improve affordability?

Reduce environmental impacts?

Improve health outcomes?

Support placemaking and recreation? ….

Establish Community Priorities

Prioritize people over vehicles

“20 is plenty”

“Pavement for the people”

Support shared use of vehicles, lanes, curbs, land

Aim for public benefits via open data

Lead the transition to a zero-emission future

Engage stakeholders

Promote equity

Support fair user fees

Transit Market AssessmentPolicy Response

Transit Market AssessmentPolicy Response

Evaluate demand, then determine typology

Backbone Crowd Sourced Door to Door

Market Assessment: Tailored ServicePolicy Response

Backbone Crowd-Sourced Door-to-Door

Rail BRT/Bus Small Bus Shuttles Sharing/Pooling Personal Vehicle

High densityHigh-Moderate

densityModerate density

Low density with

centersLow density

Autonomous Rapid Transit (ART)Policy Response

Performance

20-passenger

vehicles

4-passenger

vehicles

Reduced travel delay 46% 49%

Improvement in travel time

advantage over cars 34% 36%

Improvement in travel time

advantage over BRT 33% 35%

MicrotransitPolicy Response

Micro-Transit or Micro-VehiclesImproved operational performance

Performance

Traditional

Vehicles

Micro

Vehicles

Delay (seconds) 175 31

Fuel consumption (gallons) 422 187

Invest in High-Quality TransitPrioritize trunk service in dedicated corridors

Prioritize SafetyEmphasizing safety of vulnerable users

• More frequent crossings

• Lower vehicle speeds

• Shorter stopping distances

• Designated Pick-Up/Drop-Off

• Shorter Crossing Distances

Allocate Public Space (and Time)Consider separate facilities and/or road pricing or priorities

Allocate Public Space (and Time)Curbside use, including passenger and commercial loading

Reallocate Land Used for ParkingExample: Twinbrook Metro Station

Reallocate Structured ParkingPolicy Response

Prepare for Sprawl-Inducing EffectsParticularly reduced sensitivity to travel time

TravelTrendsIn the Automated Future

Alex Rixey | Fehr & Peers DCMay 2018