Moving on Mobility: Transport Solutions by Stefan Heck

Presentation by Stefan Heck, Consulting Professor, to Moving on Mobility: Last Mile Transportation Solutions at Stanford University on May 2, 2016. Organized by the Bill Lane Center for the American West, Stanford Public Policy, the Precourt Institute for Energy and Joint Venture Silicon Valley.

Transcript

1. 0 Moving on Mobility: Transport Solutions Stefan Heck Consulting Professor, Stanford University May 2, 2016
2. 1 Transportation productivity lags rest of California economy Sources: Lawrence Livermore National Labs 35% 21% 65% 80% 60% Waste Productive Use
3. 2 Our transport system today is extremely inefficient Productive use 2.6% driving 0.8% looking for parking 0.5% sitting in congestion The typical American car spends 96% of its time parked Energy flow through a combustion engine 86% of fuel never reaches the wheels Rolling resistance Energy used to move the person Aerodynamics Transmission losses Idling Engine losses Inertia Auxilliary power Deaths per year from transport More than 33,000 in US $300B annually in cost >95% Caused by human error An American road reaches peak throughput only 5% of the time... ...and even then, it is only 10% covered with cars US Transit - 5% of trips, 77% on-time vs 90%+ OECD, frequencies of 20-60 min in most cities Starved infrastructure: 2.4% of GDP on transport infrastructure (vs. 5% Europe, 9% China, 5%+ US before 1960) and <25% on transit
4. 3 Transportation Choices Downtowns • Height • Walkability • Parking Citywide • Bike network • Mobility as service Region • Caltrain • Zoning 2 miles 10 miles Best Practices Region •  BOTH housing and jobs near rail •  Boost capacity and frequency to every 7-10 minutes Cities •  Cycle track/trail bike network with safe intersections •  Encourage sharing, not autonomy alone Downtown Cores/Transit Centers •  Raise height to 6-7 stories within ½ mile of Caltrain and downtown •  Walkability/pedestrian areas •  Stack land uses and parking (under/vertically)
7. 6 g[X4egbY:XbZeTc[l
9. 8 The bad and ugly
10. 9 Bikes are cleaner, more efficient, and healthier – the California way!
11. 10 Bike Boulevard – Copenhagen vs Bay Area
12. 11 If it fits in Manhattan…
13. 12 Protected Intersections Feel Good Lots of turning collisions No actual safety improvement A few bikers feel safer Better Substantial reduction of accidents IF parking not displaced Bikers feel much safer Best Few accidents and more capacity Separate bikes and cars spatially or temporally
14. 13 200 million e-bikes in China vs. 250 million cars in US
15. 14 E-bikes double range and beat car usage with traffic and parking for under 10 mile range 0 10 20 30 40 50 60 1.5 miles 3 miles 5 miles 7 miles 10 miles Car Car + parking + traffic Bike E-bike Time implications Annual Cost 40 days weekdays 55 days of weekend 7200 3260 Car Bike + Uber Does not include parking cost
17. 16 We created our last mile problem by zoning housing and jobs apart Maps produced by Mark Shorett, Arup for SPUR!
18. 17 Last mile problems City Train Time (min) Car Time (min) Cost Frequency (min) Distance (miles) Connections Tokyo 53 90 $17 30 44 None – NEX nonstop London 15 90 $24 15 20 None – HEX nonstop Hong Kong 24 29 $12 10 24 None – HK Airport Express Zurich 11 24 $3 5 6 None – IC, Schnellbahn SFO to SF 36 20 $9 15 14 AirTrain to BART SFO to PA 56 35 $8 20-60 20 Airtrain to BART to Caltrain JFK 65 30-40 $7 5-10 18 Airtrain to LIRR/ E Subway LA 65 35-60 $9 60 16 Bus or Train to Train
19. 18 Often we moved jobs into parking lots, which breaks transit commute 0%" 5%" 10%" 15%" 20%" 25%" 30%" 35%" 40%" 45%" Residence and Workplace within ½ mile" Workplace Alone within ½ mile" Residence Alone within ½ mile" Residence and Workplace beyond ½ mile" Transit commute mode share, depending on proximity to regional rail (including ferry)! Source: SPUR
20. 19 Transit work only in places with the right frequency 3-6 min 2-5 min 4-5 min 15-20 min 12-20 min 7.5-10 min 30-60 min 5-9 min 3 min Vienna
22. 21 Fare box recovery – transportation welfare 0 20 40 60 80 100 120 140 160 180 200 Hong Kong Taipei BART Caltrain NYC Boston VTA “Fare Box Recovery” of Highway Spending
23. 22 A Train Schedule from Global High Tech Center
24. 23 Redesigned Crossing Cycle track and Ped underpass Alma lanes stay same – but all cycles 60 seconds + No peds and bikes crossing train or Alma Signal moved before track and synched to train 3 way signal turns to 2 way with left turn segment Adding center barrier eliminates train whistle Benefits •  All modes win •  Inexpensive near term before full grade separation •  Enables trains every 5 minutes •  Lost time shrinks from 31% to 10% •  50% increase in Alma throughput at rush hour •  Nearly double crossing capacity
25. 24 Sharing is “in the money” for low mileage customers 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 20,000 22,000 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 Annual cost of mobility $/vehicle equivalent Mileage driven per annum 4,876 BAY AREA 9,950 13,022 UberX Purchase New Car Leasing New Car LyftLine DriveNow Public Transit Ave. US driver (13,476 miles p.a.)1 15 13 14 14 12 9 22 Percentage of US drivers
26. 25 15% OF DRIVERS CAUSE 85% OF CRASHES 1 2 3 4 5 6 7 8 9 10 Index of Loss / Accidents 20% Safe Drivers 60% Average Drivers 20% Bad Drivers
27. 26 ACES: from 67-120 cents/mile today to 9 cents/mile and universal access Electrified Autonomous Shared Connected Autonomous maintenance & charging Peleton or 8x capacity autonomous HOV lanes Extend range Auto route •  No up front cost for batteries •  Use only size car you need Match open trips & 2 minute service Intermodal hub connections
28. 27 Outcomes of autonomy depend on how much we share Driverless Nightmare Driverless Utopia Safety VMT GHG Emissions Urban Sprawl Parking Req’ts No Change Roadway Maintenance Req’ts Low Income Mobility Autonomy as luxury car feature ACES – shared autonomy fleet From: Lauren Isaac
29. 28 Ideas to Work on Together 1.  Integrate planning: integrate road and transit planning from user convenience view as network across jurisdictions, get rid of linear forecasts (VMT, 8x capacity) and factor in learning curves 2.  Integrate & upgrade bike networks to cycle track and separate bike phase at intersections 3.  Shared uses in core/transit centers: allow growth near existing transit (height limits, multi-use with ground level retail, integrate sharing systems), stack parking and make paid (or feebate for transit) 4.  Boost transit frequency: vehicle headway/frequency to 7-10 minutes, integrate 2 wheelers, electrify, get rid of geo coverage as a metric 5.  Make data public: make all data public for intermodal mobility as a service to emerge, mandate integrated payment option via mobile phone - any app can access 6.  Encourage autonomy to be shared: give ACES access to drop off, parking, muni financing