session 1 three revolutions - steps · • explore interactions between the three revolutions ......
TRANSCRIPT
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Session 1:
Three Revolutions
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Charting the Path to a Sustainable Mobility Future: Three
Revolutions in Global Transportation by 2030/2050
Lew Fulton, Dominique
Meroux
UC Davis, STEPS Program
Colin Hughes, Jacob Mason
ITDP
Project description and preliminary results
Nov 30, 2016
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Project Background
• This research project grows out of two previous “High Shift” studies done by ITDP and UC Davis
• This focus on 3 major impending transportation “revolutions” not included in the two previous studies: electrification, shared mobility and automation/connected vehicles
• Scenario study to 2050 focused on potential scenario impacts on CO2, energy use, costs
• Study supported by STEPS Funds and by Climate Works, Hewlett Foundation, Barr Foundation
• Project time Frame: September 2016-March 2017
• Project advisory board established
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Study scope – two main aspects
• Investigate and report on the current (2016) status of a range of types of new mobility services around the world
• Create 3 Revolutions urban passenger/vehicle travel scenarios to 2030, 2050
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Creating 3 Revolutions scenarios to 2030, 2050
• Explore scenarios related to how much the technologies and services could grow and shape future transport
• How may patterns vary in different countries?
• What types of overall mobility, energy and environmental impacts might these services have in the context of broader urban transport system developments?
• Explore interactions between the three revolutions
• Develop narratives on how each scenario could develop
• Identification of policies that could steer existing trends to maximize mobility and sustainability benefits to cities
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Scenario methodology
• Study works from MoMo-model based system used in two previous
studies to create new scenarios to 2030, 2050
• Basically an accounting “ASIF” model, that has global coverage.
IEA and UCD have built up the urban focus in recent years
• We will use a somewhat simplified urban accounting framework for this study,
without using the full MoMo model
• Build on our previous studies’ projections of urban travel
worldwide broken into at least 8 world regions
• Starting with five major economies for deep dives
• Three scenarios:
• BAU – similar to 2 previous studies – aligned with IEA projections
• 2R will keep most BAU travel aspects but adds very high LDV/bus
electrification and autonomy by 2050
• 3R involves a “revolution” in mobility - featuring shifts to much higher transit
and shared mobility levels by 2050
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Rough guide to the three scenarios
Electrification AutomationShared
Vehicles
Urban Planning/ Pricing/TDM
Policies
Aligned with 1.5 Degree Scenario
Scenario 1: Modified BAU, Limited Intervention
Low Low Low Low No
Scenario 2: Technology-dominant 2R
HIGH HIGH Low Low YES
Scenario 3: Avoid Shift Improve 3R
HIGH HIGH HIGH HIGH YES
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Variable coverage
• Variables we will attempt to quantify (left side) and treat qualitatively (right side):
• Mobility patterns/mode and technology shares– Modal stocks, VKT, PKT
– Vehicle characteristics
• Energy use
• CO2 emissions
• Market-related costs
• Accessibility
• Convenience
• Traffic congestion
• Land use/livability
• Air pollution impacts
• Health benefits
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Timetable, outputs
• Preliminary findings by November 2016
• Full draft report by January 2017
• Final report and all output materials by end February 2017
– 25-30 page main report
– Various infographic materials
– 2-page policy brief
– Ppt slide decks
• Presentation at several conferences in 2017 (suggestions welcome)
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More details and preliminary results in following slides
ALL RESULTS PRELIMINARY!
Please do not cite
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Passenger kms of travel, all years, scenarios, modes
• Huge growth in travel in China/India, 2015 to 2030
• 3R travel lower than 2R due to more compact cities, various TDM policies
• This will be elaborated in our narrative, will include an analysis of costs of modes and mode shares
0
2,000
4,000
6,000
8,000
10,000
12,000
Bas
e Ye
ar
BA
U 2R 3R
BA
U 2R 3R
Bas
e Ye
ar
BA
U 2R 3R
BA
U 2R 3R
Bas
e Ye
ar
BA
U 2R 3R
BA
U 2R 3R
Bas
e Ye
ar
BA
U 2R 3R
BA
U 2R 3R
Bas
e Ye
ar
BA
U 2R 3R
BA
U 2R 3R
2015 2030 2050 2015 2030 2050 2015 2030 2050 2015 2030 2050 2015 2030 2050
United States OECD Europe China India Brazil
LDV Passenger Kms of Travel
Other
Bus/rail
Minibus
Public AV
Public LDV
Private AV
Private LDV
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Passenger kms of travel, aggregated modes, USA
• Automated vehicle travel not significant by 2030 in any scenario, but dominates in 2050. Results in much higher travel in 2R
• US remains car dominated to 2050 - increase in travel mode mix in 3R, but mostly due to TNCs. Also significant minibus travel. Non-car travel reaches 18% in 3R
0
1,000
2,000
3,000
4,000
5,000
6,000
Base Year BAU 2R 3R BAU 2R 3R
2015 2030 2050
United States
Bill
ion
kilm
oe
ters Other
Bus/rail
Minibus
Public AV
Public LDV
Private AV
Private LDV
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United States – electrification
• We assume the following for electrification:– Very strong policies in 2R/3R to spur uptake of EVs and PHEVs, and technology keeps
improving
– By 2050 100% sales share
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Base Year BAU 2R 3R BAU 2R 3R
2015 2030 2050
United States
Private LDV Public LDV
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United States – automation
• We assume the following for automation:– Mass-market automated vehicle sales begins early 2020’s in 2R/3R
– TNC cars lead, reaching 50% in US/Eur/China by 2030
– TNC cars that are automated are electric
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Base Year BAU 2R 3R BAU 2R 3R
2015 2030 2050
United States
Private LDV Public LDV
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US LDV sales evolution in BAU, 2R Scenarios
• BAU Case – sales rise slowly with little change in vehicle types
• 2R Case – sales rise slowly with major changes in private vehicles, but few public vehicles
0
5
10
15
20
2015 2020 2025 2030 2035 2040 2045 2050
Sale
s, m
illi
on
s
Private ICE Private EV Private AV/EV
Public ICE Public EV Public AV/EV
-5
0
5
10
15
20
2015 2020 2025 2030 2035 2040 2045 2050
sale
s, m
illi
on
s
Private ICE Private EV Private AV/EV
Public ICE Public EV Public AV/EV
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US LDV sales evolution, 3R scenario
• Sales declines quickly through 2035, then recovers somewhat
• Sales remains below 2030 levels given travel demand patterns in 3R
0
2
4
6
8
10
12
14
2015 2020 2025 2030 2035 2040 2045 2050
Ve
hic
le s
ale
s, m
illi
on
s
Private ICE Private EV Private AV/EV
Public ICE Public EV Public AV/EV
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US LDV stock evolution, 3R scenario
• Stocks strongly decline after 2030, due to intensive vehicle use and higher load factors
0
50
100
150
200
2015 2020 2025 2030 2035 2040 2045 2050
veh
icle
s, m
illi
on
s
Private ICE Private EV Private AV/EV
Public ICE Public EV Public AV/EV
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US LDV travel evolution, 3R scenario
• Vehicle travel remains flat, given high travel rates of public vehicles
0
500
1000
1500
2000
2500
3000
3500
2015 2020 2025 2030 2035 2040 2045 2050
bil
lio
n k
ilo
me
ters
Private ICE Private EV Private AV/EV
Public ICE Public EV Public AV/EV
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US LDV passenger travel evolution, 3R scenario
• Overall LDV passenger travel still rises somewhat, but far less than in other scenarios
0
500
1000
1500
2000
2500
3000
3500
2015 2020 2025 2030 2035 2040 2045 2050
Bil
lio
n k
ilo
me
ters
Private ICE Private EV Private AV/EV
Public ICE Public EV Public AV/EV
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Why do sales drop so fast?
• Private vehicle sales can drop very fast given that the decline in stocks is much slower
• The intensity of use of public vehicles allows for slower sales ramp ups
0
2
4
6
8
10
12
14
2015
2017
2019
2021
2023
2025
2027
2029
2031
2033
2035
2037
2039
2041
2043
2045
2047
2049
Ve
hic
le s
ale
s, m
illi
on
s
Private vehicles Public vehicles
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US LDV energy use by scenario
• BAU - liquid fuels (green) dominates but drops due to efficiency improvements
• 2R – electricity (blue) dominant by 2050
• 3R – electricity use in 2050 about 40% lower than 2R level due to mobility changes
0
50
100
150
200
250
300
350
2015 2020 2025 2030 2035 2040 2045 2050
Bilio
n lit
ers,
gaso
line
equi
v.
TOTAL Liquid fuel TOTAL electricity
0
50
100
150
200
250
300
350
2015 2020 2025 2030 2035 2040 2045 2050
Bilio
n lit
ers,
gaso
line
equi
v.TOTAL Liquid fuel TOTAL electricity
0
50
100
150
200
250
300
350
2015 2020 2025 2030 2035 2040 2045 2050
Bilio
n lit
ers,
gaso
line
equi
v.
TOTAL Liquid fuel TOTAL electricity
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US –marginal (per-trip) costs in 2030 2R, 3R
• US – public mode costs plummet with no driver; buses more expensive than small modes
• Public costs are heavily dependent on load factors, assumed wage and markup rates
$-
$1
$2
$3
$4
$5
$6
$7
$8
$9
$10
2R 3R
2030
United States
Private - ICE
Private - EV/AV
Public - ICE
Public - EV/AV
Minibus - ICE
Minibus - EV/AV
Bus - ICE
Bus - EV/AV
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Next Steps
• Refine results, especially cost results
• Continued financial/policy analysis of modes, policy implications
• Deeper visualizations to output set
• Establish our full narratives
• Draft report by late January 2017
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Thank you!
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