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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