Exhibit to Agenda Item #1a

Transcription

1 Exhibit to Agenda Item #1a Board Strategic Development Committee Meeting and Special SMUD Board of Directors Meeting Tuesday, February 13, 2018, scheduled to begin at 5:30 p.m. Customer Service Center, Rubicon Room Powering forward. Together.

2 Three Revolutions in Urban Transportation: Future scenarios and the relative costs of mode choices and vehicle use cases in California Presentation to SMUD Feb 13, 2018 Lew Fulton, Co-Director Junia Compostella, PhD student Sustainable Transportation Energy Pathways Program (STEPS) UC Davis

3 UC Davis ITS 3 Revolutions Program MISSION: There is an urgent need for rigorous research and impartial policy analysis to understand the social and environmental secondorder impacts of these transportation revolutions, and to guide industry investments and government decision-making to maximize public benefits. Shared (pooled) Automated (connected) Electric (ZEV) 3

4 Research undertaken by UC Davis and ITDP, part 3 of a series Global scenario study to 2050 focused on potential 3 Revs impacts on CO2, energy use, costs Study supported by UC Davis STEPS Consortium and by Climate Works, Hewlett Foundation, Barr Foundation

5 Some questions and conflicts Automation: lower per-trip costs, lower time cost for being in vehicles Just how much cheaper will it be? Private automated vehicles = longer trips? Empty running (zero passengers) of vehicles Resulting relative costs of private vehicles, shared mobility, transit? Electrification goes with automation does it really? Can get the job done with upgraded electrical system (such as hybrids) But electric running will be much cheaper and durable? Ride hailing: cost savings v. convenience and risk Complementary or at conflict with public transit use? Will lower costs reduce the incentive to ride share?

6 Our report covers three scenarios Business as usual, Limited Intervention 1R Automation only 2R With high Electrification 3R With high shared mobility, transit, walking/cycling Automation Electrification Shared Vehicles Urban Planning/ Pricing/TDM Policies Aligned with 1.5 Degree Scenario Low Low Low Low No HIGH Low Low Low No HIGH HIGH Low Low Maybe HIGH HIGH HIGH HIGH YES

7 Passenger kilometers of travel by scenario/mode World Automated vehicle travel not significant by 2030 in any country/scenario, but dominates in 2050 in most of the world. Results in much higher travel in 2R In 3R private LDVs reach very low levels; nearly 50% of travel in 2050 is in transit/non- LDV modes.

8 Trillion kilometres Urban LDV passenger kms by scenario, USA Electric vehicle travel reaches nearly 1/3 of PKMs by 2030 Passenger Kms of LDV Travel Automated 5.0 vehicle travel not significant by Shared AV/EV in any scenario, but dominates in 2R Shared EV and 3.0 3R Results in much higher travel in Shared ICE 2R Private AV/EV 0.0 Base Year BAU 2R 3R BAU 2R 3R Private EV Private ICE United States

9 billion kilometers billion kilometers Billion kilometers Urban LDV travel (VKm) by scenario, USA 2R vehicle travel rises sharply after 2030 due to lower travel costs from automated vehicles 3R vehicle travel flat despite declining vehicle stock, given higher travel per vehicle of public vehicles R Private ICE Private EV Private AV/EV Public ICE Public EV Public AV/EV BAU Private ICE Private EV Private AV/EV Public ICE Public EV Public AV/EV R Private ICE Private EV Private AV/EV Public ICE Public EV Public AV/EV

10 Stocks, millions Stocks, millions Stocks, millions Urban LDV stock evolution by scenario, USA R stocks nearly completely autonomous by R stocks strongly decline after 2030, due to lower passenger travel levels, intensive vehicle use and higher load factors 2R Private ICE Private EV Private AV/EV Public ICE Public EV Public AV/EV 250 BAU Private ICE Private EV Private AV/EV 2050 Public ICE Public EV Public AV/EV 3R Private ICE Private EV Private AV/EV Public ICE Public EV Public AV/EV

11 Exajoules Energy use by scenario, USA Far lower energy use in 2R due to EVs, and in USA Energy Use by Mode 3R due to low LDV mode shares Cycle/ebike M2W Rail Bus Shared car AV/EV 2 0 BAU BAU 1R 2R 3R BAU 1R 2R 3R Shared car ICE Private car AV/EV Private car ICE

12 CO2, gigatonnes Well-to-wheels CO2 by scenario/technology, 4DS electricity shown; USA in 2DS, CO2 from electricity drops to near zero in CO2 emissions by technology, USA BAU BAU 1R 2R 3R BAU 1R 2R 3R ICE Vehicles Electric Vehicles

13 USD billions Total cost by scenario and mode, USA Total societal (out-of-pocket) 3R cost in 2050 is only 2/3 of BAU or 2R cost, thanks to deep cuts in car ownership, energy use, and road/parking requirements 2500 USA Scenario comparison Cycle/ebike 2000 M2W Rail Bus Shared car automated 500 Shared car 0 BAU BAU 2R 3R BAU 2R 3R Private car automated Private car

14 Supportive Policies critical to success of the scenarios 3R Scenario (Automation + Electrification + Sharing): Compact Urban Development policies Efficient parking policies Heavy investment in transit/walking/cycling VKT fees (incl. congestion & emission factors): Highest Fee Largest Subsidy

15 A more detailed cost comparison: California in 2025 The following presentation assumes widespread availability of electric vehicles (EVs) and electric, connected automated vehicles (or AV/EVs) Comparison here is the cost per mile of: Private ICEs, EVs, and AV/EVs MaaS (Mobility as a Service, such as Uber) versions of EVs and AV/EVs Pooled services included, in later slides Start with looking at vehicle costs per mile, then consider passengers For some aspects need to assume specific trip lengths

16 STEP 1: Purchase cost of vehicles Midsize car, $28k in 2025, 32 MPG on road EVs cost about $10,000 more than ICEs EV battery costs at $150/kWh, 0.25 kwh/mi, 65 kwh capacity, 250 mile range Midsize vehicle ($/VMT) AV/EVs 0.45 $7500 more than EV, same efficiency 0.40 Private vehicles travel 13,700 miles per year, 0.35 MaaS 0.30 vehicles 70, $/VMT AV/EV 0.20 is expensive, unless shared Amortized purchase cost 0.00 Private ICE Private EV Private EV/AV Maas ICE Maas EV Maas EV/AV

17 2: add fuel costs Gasoline: $3.00/gal; Average electricity price for EVs: $0.13/kWh ICE: 32 MPG; EV: Midsize vehicle kwh/mi; ($/VMT) AV/EV: kwh/mi Energy 0.30 costs bring ICE vehicles closer to Fuel cost 0.25 per $/VMTmile cost of AV/EV Amortized purchase cost Private ICE Private EV Private EV/AV Maas ICE Maas EV Maas EV/AV

18 3: add insurance and maintenance Insurance cost about $1300 for ICE and EV; 1/2 for AV/EV MaaS similar as private Midsize vehicle (lower ($/VMT) rate per mi but x miles/yr) 0.50 Maintenance cost (motor, oil, tires, etc) 40% 0.40 lower for EV and AV/EV than ICE $/VMT 0.30 vehicle maintenance Vehicle insurance Fuel cost Amortized purchase cost AV/EVs 0.20 become even more competitive Private ICE Private EV Private EV/AV Maas ICE Maas EV Maas EV/AV

19 4: add parking and cleaning Assumes parking at $155/month for private vehicles 50% less for MaaS vehicles 50% less again for AV/EVs 0.70 Cleaning about $150 for private vehicles, 0.60 $1500 for MaaS vehicles 0.50 vehicle parking Parking 0.40 cost pushes ownership slightly vehicle maintenance Vehicle insurance $/VMT Fuel cost 0.30 toward AV, and toward shared Midsize vehicle ($/VMT) vehicle cleaning Amortized purchase cost Private ICE Private EV Private EV/AV Maas ICE Maas EV Maas EV/AV

20 6: add driver cost and MaaS overhead fees Drivers assumed to earn about $1.00/mile ($50k for 50,000 miles) after all expenses For an average speed of 20 MPH, this is $20/hr MaaS fees assumed to be 20% of revenues (which equal all the Midsize costs vehicle ($/VMT) in the figure) 1.60 This 1.40 rises to 30% with no driver, but off a much lower 1.20 cost base 1.00 Driver/service cost make MaaS an $/VMT 0.80 expensive option, but not for AVs 0.60 MaaS fees Driver cost vehicle cleaning vehicle parking vehicle maintenance Vehicle insurance Fuel cost Amortized purchase cost Private ICE Private EV Private EV/AV Maas ICE Maas EV Maas EV/AV

21 7: add passengers Assume 1.5 passengers per private car and 1.25 per MaaS trip Midsize vehicle ($/PMT) Assume 2 passengers at 60% price each for MaaS 1.00 pooled trip; trip is 10% farther Pooled mobility gains a cost advantage 0.80 $/PMT MaaS fees Driver cost vehicle cleaning vehicle parking vehicle maintenance Vehicle insurance fuel cost Amortized purchase cost 0.00 Private ICE Private EV Private EV/AV Maas ICE MaaS EV MaaS EV/AV MaaS EV/AV Pooled

22 8: Add a value of time for driving, travelling, parking Time cost for drivers set to $15/hr, or $0.60/mi for a 15 minute, 6 mile trip Time cost for non-drivers (whether AV or not) 50% lower Parking search / 2025 walking - Midsize vehicle ($/PMT) to destination if not door-to-door: 5 minutes Thus $1.67 per trip, or $0.28/mi for a Parking 6 mile search cost trip Travel time cost per passenger MaaS fees Time costs are equal to or in some cases Driver $/PMT greater than the out-of-pocket costs vehicle cleaning vehicle parking vehicle maintenance Pooled mobility advantage is reduced Vehicle insurance fuel cost Amortized purchase cost Private ICE Private EV Private EV/AV Maas ICE MaaS EV MaaS EV/AV MaaS EV/AV Pooled

23 9: Include only variable costs (daily decision) Ignore private car purchase, insurance cost The AV/EV private car becomes more Midsize vehicle ($/PMT) competitive with automated/shared mobility options $/PMT Parking search cost Travel time cost per passenger MaaS fees Driver cost vehicle cleaning vehicle parking vehicle maintenance Vehicle insurance fuel cost Amortized purchase cost Private ICE Private EV Private EV/AV Maas ICE MaaS EV MaaS EV/AV MaaS EV/AV Pooled

24 Much more work to do: A list of non-market cost hedonic factors to investigate This list is under development, suggestions welcome We characterize these as disutilities, including from: Travel time (and travel segments, such as modal changes when using public transit) when driving and as when a passenger When driving, parking search time and distance from actual destination Driving stress (from traffic, arguments with other drivers, getting pulled over, tickets for travel speed, weight increase) Shared trips - lack of privacy (sharing a pool on-demand car with strangers, may vary with number of strangers and if no 3 rd party driver present) EV range anxiety (time and proximity to the charger) and EV charging anxiety (time needed and availability to publically charge) Owning a car: time/hassles associated with maintenance, registration, inspections etc. Not owning a car (or using own car): no guaranteed ride; can t leave personal belongings in the car Accessibility options particularly for those who cannot drive or own a car, mobility limitations from lack of other choices

25 Next STEPS More use cases, (more modes, more trip lengths, city vs. suburban trips?) More sensitivity analysis with assumptions Do for different countries Deeper exploration of non-cost attributes Possible survey work to better understand how people value both cost and non-cost aspects, how they might travel in AVs? Add these data into a spatial model to better test real mode choices?