Policy and Planning for Innovative Transportation EV Transportation & Technology Summit October 17-20, 2016 Steven E. Polzin, PhD. Center for Urban Transportation Research University of South Florida
CENTER FOR URBAN TRANSPORTATION RESEARCH Established 1988 by Florida Legislature Home of the National Center for Transit Research Applied research Policy focus Technology transfer / training Education Multi-disciplinary (Anthropology to Zoology) Real world experience Housed in USF s College of Engineering 180+ active research projects $14 million in 2015 over $5 million federal 35 full-time research faculty 20-50+ student researchers 2
Outline Where are we at? Where might we be headed? Vehicle ownership Location decisions Sharing travel How might we get there? 3
We are in Perhaps the Most Transformational Period in Transportation Since the Development of Personal Vehicles Demographics Economics Technology Governance Culture/values 4
Social and Economic Interactions Create Demand for Travel Time Growth in Income Knowledge Specialization in Employment Consumption Social relationships Time use Growth in Person Travel Commerce Communication Polzin, CUTR 2010 5
A Fundamental Need to Travel Travel is fundamental to the human desire to interact and socialize and pursue personal betterment through commerce. While people do not necessarily aspire to travel they do aspire to do things that require travel. Travel enables economic interaction and the transportation of products and is fundamental to the functioning of the economy. 6
Conceptual Framework for Thinking About Travel Demand Legal/Political Climate Culture Technology Security Economy Socio-Demographic Conditions Household/Person Characteristics Income/wealth levels and distribution Age/activity level Culture/values Racial/ethnic composition Immigration status/tenure Gender Family/household composition Housing location Business, Governance, Institutional Context Scale of activity concentration Economic structure of service delivery Travel Demand Local person travel Tourism/long trips Freight Commercial Travel Travel Impacts: 1. Change trip frequency 2. Change destination 3. Change Mode 4. Change Path Land Use Pattern Regional/national distribution Density Mix of land uses Urban form Urban design Contiguousness of development Polzin, CUTR 2009 Transportation Supply/Performance Modal Availability Modal Performance o Cost o Speed/congestion o Safety, security o Reliability o Convenience o Image, etc. o Multi-tasking opportunities 7
National Trips, VMT and VMT per Capita Trends Total VMT (000,000) 3,500,000 3,000,000 2,500,000 2,000,000 1,500,000 1,000,000 500,000 0 1990 1992 1994 1996 1998 Count Data 2007 peak 2004 peak VMT VMT per capita 2000 2002 2004 2006 2008 2010 2012 2014 14,000 12,000 10,000 8,000 6,000 4,000 2,000 0 Per Capita Annual VMT Per Capita Daily Trips Per Capita Daily Miles 5 4 3 2 1 0 40 30 20 10 NHTS Survey Data Daily Person Trips Daily Vehicle Trips 1969 1977 1983 1990 1995 2001 2009 Daily PMT Daily VMT 0 1969 1977 1983 1990 1995 2001 2009 8
Incremental Annual Change in VMT 120,000 +3.52% 80,000 Miles (000,000) 40,000 0-40,000-80,000 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 9
Changes in VMT and Capacity U.S. 4,000,000 3,500,000 1990-2002 Actual 2003-2015 Actual 2003-2015 Extrapolated 16% Annual VMT (Millions) 3,000,000 2,500,000 2,000,000 1,500,000 1990 1995 2000 2005 2010 2015 Public Road Mileage & Lane Miles (millions) 10.0 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 Lane - Miles Vehicle Miles of Travel 5.0 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 Vehicle Miles of Travel (trillions) 0.0 0.0 10
Trip Rate and Length 1800 Annual Trips per Person 5+ 1600 1400 1200 1000 800 600 400 1568 1371 1054 1067 9.47 8.68 9.29 9.00 1449 1385 10.78 9.52 20 15 10 5 Trip Length 200 0 1977 1983 1990 Adj. 1995 2001 2008 0
CIA 2013, Table 2-1 Commuting in Perspective Travel by All Modes 2009 Private Vehicle Travel 2009 Household Travel Percent of Person Trips Percent of Person Miles of Travel Percent of Person Travel Time Percent of Person Travel Time Percent of VMT Commuting 15.6 19.0 18.8 17.9 27.8 Percent of Total Roadway VMT Work-Related/Business Travel 3.0 6.3 4.6 5.2 9 76 1 Other Resident Travel 81.4 74.7 76.6 76.9 63.2 Subtotal 100% 100% 100% 100% 100% Public and Commercial Travel Public Vehicle Travel 2 2 Utility/Service Travel 12 3 Freight and Goods Movement Travel 10 4 Total 100% Sources: NHTS 2009, FHWA State Statistical Abstracts, FHWA 1 FHWA estimate based on NHTS data. 2 FHWA estimate using vehicle registration data. 3FHWA estimate based on HPMS data and NHTS. 4 FHWA estimate based on HPMS data. 12
Personal Vehicle commuting Market Shares 90 80 73.2 75.7 76.6 76.4 76.3 76.4 76.5 76.6 Commuting Market Share 70 60 50 40 30 20 10 64.4 19.7 Drive Alone Carpool 9.7 13.3 12.2 9.7 9.7 9.4 9.2 9.0 0 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 13
Non-POV Market Shares Commuting Market Share 7.0% 6.0% 5.0% 4.0% 3.0% 2.0% 1.0% Transit Bicycle 6.2% Walk Work-at-home 5.6% Taxi, Motorcycle, and Other 5.1% 5.2% 4.9% 4.6% 4.6% 4.3% 3.9% 3.3% 3.0% 2.9% 2.8% 2.8% 2.3% 1.3% 1.1% 1.0% 1.2% 1.2% 0.5% 0.4% 0.4% 0.5% 0.6% 0.0% 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 14
12.00% Census/ACS Work Trip Percent Walking Mode Share 10.00% 10.40% Percentage Walking to Work 8.00% 6.00% 4.00% 7.40% 5.60% 3.90% 2.82% 2.90% 2.77% 2.75% 2.00% 2.81% 2.80% 2.77% 0.00% 1960 1970 1980 1990 2000 2010 2020 15
Vehicle Occupancies - NHTS 2.20 2.00 1.90 1.90 Work Trip All Trips Occupancy 1.80 1.60 1.40 1.20 1.00 1.40 1.80 1.30 1.30 1.70 1.59 1.64 1.20 1.20 1.20 1.67 1.13 0.80 1969 1974 1979 1984 1989 1994 1999 2004 2009 16
Transit Ridership Trends 25 180 160 20 140 Annual Ridership, Billions 15 10 5 Riders, billion Per Capita Trips 120 100 80 60 40 20 0 0 1918 1923 1928 1933 1938 1943 1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003 2008 2013 Annual Trips per Capita 17
Current National Trends Indicator 2015 versus 2014 2016 YTD Source U.S. Population +0.8% Census Total Employment +1.7% BLS Real GDP +2.4% BEA (third estimate) Gas Price -28% EIA Public Transit Ridership VMT +3.5% +3.1% thru July FHWA -1.3% to -2.5% -1.48% thru June (NTD/BTS) APTA and NTD Amtrak Ridership (FY) -0.1% Amtrak Airline Passengers +5.0% USDOT, BTS Consistently growing transit ridership is tough 18
Congestion is the situation where someone with the freedom, resources, and desire to travel gets in the way of someone else with the freedom, resources, and desire to travel. Be careful how you solve this problem. Congestion 19
Disclaimer We haven t been able to predict Who will win the next election, Which movie or TV show will be popular, What will be the hot Christmas gift, or, Which stocks (if any) will do well this year. Therefore we shouldn t apologize for uncertainty regarding future travel. We should plan for uncertainty regarding future travel demand. 20
Everything Affects Transportation and Transportation Affects Everything Legal Political Governance Context Land Use & Infrastructure Demographics Transportation Economy Technology Environment Culture and Values 21
Hey Watson, When did you say automated vehicles will be here? And what will the impacts be? Very smart people have very different opinions on the pace of implementation, market acceptance, and impacts of technology on transportation 22
The Public is Being Bombarded with Stories on Autonomous Vehicles Cop pulls over Google self-driving car - going 24 in 35 mph zone CNN November 13, 2015 23
The Business World Is Being Rocked by Technology Deployed for Transportation GM is Investing $500 Million in Lyft to Develop Self-Driving Cars January 2016 Toyota Chief Shifts to Self- Drive: Akio Toyoda, once a skeptic, steers automaker into autonomous vehicle race. WSJ, January 2016 Transportation as a Service Envisioned as Massive Global Market Opportunity Uber Google Apple Ford Chrysler GM 24
Consequences Transportation Safety Environmental Considerations Travel Behavior Personal Mobility Economic and Employment Impact Impact on travel demand by mode Transportation System Capacity Unintended Consequences Transportation Stakeholders Transportation Infrastructure Land Use 25
Technology Implementation is Not Easy August 13, 2015 26
Factors that Influence Travel Behavior Technology Enables: - Real time information - Electronic payment - Trip planning Convenience Money Cost Time Cost - Trip scheduling - Navigation/trip tracking - Electronic hailing - Trip aggregating -----/ride matching Safety Comfort Household Travel - Dynamic pricing - Electronic satisfaction ----feedback - Automated driving Reliability Flexibility Image Environmental, Social Impact 27
Factors that Influence Safety Comfort Travel Behavior Reliability Convenience Flexibility Money Cost Household Travel Image Time Cost Environmental, Social Impact Traditional Travel Decision Making (4-Step Process) 1. Number of Trips Made (trip generation vs. communication) 2. Destination Choice (trip distribution impacted by better knowledge of choices) 3. Mode Choice Drive personal traditional car Ride in my automated car Hail automated car Ride with family/friend Taxi Ridesourcing, e-hailing, Uber, Lyft, Sidecar Ridesharing - Carma, erideshare Carsharing Personal bike Bikesharing Transit Transit Alternatives/Feeders microtransit, Bridj, Leap, MetroBee, TransLoc Walk 4. Path Assignment (Choice assisted by real time information) 28
I couldn t get my autonomous car to back down the boat ramp. I got dropped off by my TNC car service but they said I couldn t carry any fish home in their vehicle. 29 29
Impacts of Technology is Highly Dependent on Three Key Decisions Vehicle Ownership Live/Work Location Choices Shared Occupancy Mode Choice
The Vehicle Ownership Decision Average car driven about 10,000 to 12,000 miles per year About one hour per day at an average of 30 mph About 13+ million new vehicles purchased by households annually Households own about 215 million vehicles Avg. life of 17 years and 163,000 miles before scrapping Households responsible for about 2.25 trillion VMT annually U.S. vehicle fleet valued at over 2 trillion. 31
Ownership Not Just a Mobility Decision Image Functional transportation Transportation plus? Entertainment 32
Envisioned Cost Structures Imply Possible New Institutional Roles Governing/Providing Mobility Employer Community Self Private sector Government Family 33
Personal, Private Sector, or Government Ownership of Vehicles? 34
It remains to be seen what share of households would be willing to relinquish one or more vehicles. Vehicle Ownership
Key Decisions Live/Work Location Choices
Land Use Impacts Drive till you qualify becomes nap till you qualify? More house and less garage? 37
Land Use Impacts. Without having to own and park a car I can afford the urban lifestyle. After a day at the office and a nap on the ride home I can enjoy the great outdoors. 38
It remains to be seen how travelers will react to the ability to be passengers during their vehicle travel. Live/Work Location Choices
Key Decisions Shared Occupancy, Mode Choice Sharing vehicles sequentially versus sharing vehicles concurrently
Do Travelers Want to Share a Ride? The Demise of Carpooling? 90 80 73.2 75.7 76.6 76.4 76.3 76.4 76.5 70 64.4 Commuting Market Share 60 50 40 30 20 10 19.7 13.3 DRIVE ALONE CARPOOL 12.2 9.7 9.7 9.7 9.4 9.2 0 1975 1980 1985 1990 1995 2000 2005 2010 2015 41
Will a generation, many of whom haven t shared bathrooms or bedrooms or phones or televisions or dorm rooms, share small vehicles with strangers? Shared Travel/ Occupancy It remains to be seen how accommodating of vehicle sharing travelers will be and what the cost benefits and time penalties will be.
What Does it Mean for Planning? 43
So What Does This Have to do With Electric Vehicles and Planning? Electric propulsion is envisioned as being as critical to the future of transportation as shared ownership and use and autonomous operation. Issues of pace of technology innovation, deployment and customer/market acceptance are similar between electrification and other technology deployment. Electrification is perceived as critical from an environmental perspective especially with the prospect of increased demand. Electrification may drive the pace of conversion to VMT fee based revenues for transportation. 44
TRANSPORTATION ENERGY USE MEASUREMENT CONCEPTS Complexity and Uncertainty Basic Energy Use Component Possible Measures of Energy Use Propulsion energy per vehicle mile Average number of occupants Fuel production and delivery Facility and maintenance energy Construction/recycling energy Vehicle manufacturing /recycling energy Operating Energy Intensiveness Energy Intensiveness Lifecycle Energy Intensiveness Modal Energy Intensiveness Transportation Energy Impact Total Energy Impact Mode of access Network circuity Travel and location behavior changes Non-travel energy consequences of transportation 45
Comparison of Electric Vehicle Modal Energy Efficiencies City MPGe Kilowatt hours per gallon KWH/ VMT city Operating Occupancy Note KWH/Person Mile of Travel Percent of Private Vehicle Average 2016 Nissan leaf 126 0.294 0.210 91.5% 2016 Tesla S (90) 88 0.421 0.301 131.0% 2016 Chevy Volt 113 0.328 1.4 1 0.234 102.0% 2016 Volkswagen egolf 126 0.294 0.210 91.5% 2016 BMW i3 BEV 137 0.271 0.193 84.1% Auto Average 0.230 100.0% Proterra 40 foot transit bus 21.8 1.546 8.7 2 0.177 77.2% BYD ebus 1.988 8.7 3 0.228 99.2% Zero Electric motorcycle 475 0.078 1.0 4 0.078 34.0% Charlotte (ID 4008) 8.159 28.7 0.284 123.8% Houston (ID 6008) 7.223 26.8 0.269 117.2% Dallas (ID 6056) 12.464 26.1 0.478 207.9% Salt Lake City (ID 8001) 7.605 12.9 0.588 255.8% Denver (ID 8006) 5.591 19.8 5 0.282 122.7% Phoenix (ID 9209) 7.169 40.2 0.178 77.6% Sacramento (ID 9019) 7.747 19.3 0.401 174.4% Santa Clara (ID 9013) 6.859 18.1 0.379 164.8% Minneapolis (ID 5027) 8.479 23.4 0.362 157.8% LRT Average 7.922 23.9 0.358 155.8% 46
Some Observations on Electrically Powered Modes Comparative energy efficiency: The personal vehicle performs very favorably on an energy use per passenger mile basis given utilization and occupancy levels characteristically observed today. Energy efficiency is highly dependent upon utilization of the vehicle s capacity. The Proterra electric bus, to the extent that it is able to obtain the projected energy efficiency levels associated with its MPGe level look quite promising. Access and egress modes, trip circuity, and energy associated with infrastructure development are excluded from this comparison. Private vehicles would use one-third less energy than light rail vehicle travel, given the technology and utilization assumptions. Electric busses could perform better, and personal electric vehicles, such as a motorcycle, or perhaps other emerging electric personal mobility hardware, are even more efficient. 47
Denver RTD. The SD-160's dimensions are 81.37 ft by 8.71 ft by 12.50 ft and can be used in trains of up to six cars. It is powered by four AC motors which provide a maximum of 580 kw and a maximum speed of 50 mph. It has a passenger capacity of 236 passengers (including standees) with 64 seats. Passenger Miles per Light Rail Vehicle Mile for Select Cities 2013 LIGHT RAIL TRANSIT PASSENGER MILES PER VEHICLE MILE 2013 28 29 27 26 25 13 20 31 40 25 19 22 18 29 18 23 17 22 16 29 23 19 48
Changing Stakeholders Additional very smart talent involved in transportation. New powerful stakeholders and a very engaged private sector. Transformational legal, regulatory and governance issues on the table. Accelerates the planning shift away from focusing on capacity supply and project programming. 49
A Different Planning World Time frames for traditional investment implementation and amortization exceed our window of confident predictions. 5-10 years to plan, 5-10 years to construct, 25-50+ years to amortize investments Uncertainty creates an opportunity to do nothing. 50
Planning Challenges? Fewer degrees of freedom (space for infrastructure, money, political consensus) More complexities and impacts to consider in evaluation Maybe more levers of influence (land use, pricing, regulation, etc.) More partisan considerations in transportation planning and policy Uncertainty on the role of the planner: Predictor versus Prescriber 51
Unprecedented Levels of Uncertainty All fundamental determinants of travel are being impacted by technology changes: Cost, time, safety, convenience, environmental impact, etc. Simultaneously economic, demographic and other changes are occurring rapidly. Less than robust theory of travel behavior on which to evaluate impacts of changes. Limited data and research may impede our ability to confidently predict the future. 52
Uncertainty Favors Low Risk Decisions/Investments Risk Example Evaluation Method Low Risk Decision Low cost Reversible/redeployable Near-term impacts Similar examples from which to gauge impacts High Risk Decision High cost Not reversible Longer-term impacts Original/rare situation Bus Route Change Bus Network BRT HSRail in US Experimentation? Case study? Simple Model? Complex Model? 53
Planning Challenges? None of the MPOs most likely to be planning for self-driving cars have incorporated them into their most recent RTPs. 2 Of the twenty-five largest MPOs, only Philadelphia s Delaware Valley Regional Planning Commission mentions autonomous vehicles at all. There is a great deal of uncertainty about what technologies will prevail, how much and when they will penetrate the market, whether regulation will hinder or support deployment, what the direct impacts will be on capacity or safety, and how consumers will respond. Driverless cars and their potential impacts are too far removed from decisions about whether and how to invest in and maintain transportation infrastructure. Vehicle automation is just one of a number of radical changes that could influence regional transportation over the next 30 years. Staff also mentioned changes in federal transportation funding, 3D printers, improvements in telecommunications, and the impacts of and policies to address climate change as potential gamechangers. Planning for Cars That Drive Themselves: Metropolitan Planning Organizations, Regional Transportation Plans, and Autonomous Vehicles, Erick Guerra, Journal of Planning Education and Research, 2015 54
Possible Tactics Explicitly assess uncertainty and risk in the alternatives evaluation process. This might include robust scenario analysis and engagement of expert panels and reviewers to address risk and uncertainty. Specify mobility improvement strategies that are inherently more flexible by virtue of the life cycle of system components and the adaptability of the infrastructure and service concepts. Evaluate different timing options for project implementation as part of the uncertainty assessment. 55
Observations The pace of change, performance, and deployment of transportation and energy technologies will challenge planners to present well-informed estimates of project impacts as they deviate from historic norms. The net performance of various investments and services are highly dependent upon their utilization levels. The fundamental ability to scale technologies, such as electrical propulsion systems and vehicles, to market conditions (probable passenger loads) may undermine some of the historic scale of the economy efficiency that applied to larger vehicles and trains of vehicles. 56
Integrating Smart Technology with Dumb Infrastructure 57
A Path Toward Success Policy makers and industry professionals with input from the public should strive to find ways for the positive benefits of technology to be realized without ego, greed, self interest, lust for power, or incompetence denying the public the full benefits of new technologies. 58
Contact Information 59
But it might not make any difference Press to Transport Apple iphone 15G ios 27 Personal Teleportation App