DRAFT. Trends Analysis Technical Report. Commuting, Shared-Use Mobility, Smart Infrastructure, Climate Change, and Rural Transportation Trends

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1 Trends Analysis Technical Report for VTRans2040 DRAFT Commuting, Shared-Use Mobility, Smart Infrastructure, Climate Change, and Rural Transportation Trends prepared for Virginia Office of Intermodal Planning & Investment prepared by CDM Smith September 3, 2014

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3 VTrans2040 Trends Analysis Technical Report Commuting, Shared-Use Mobility, Smart Infrastructure, Climate Change, and Rural Transportation Trends VTrans2040 prepared for Virginia Office of Intermodal Planning & Investment prepared by CDM Smith September 3, 2014

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5 VTrans2040 Trends Analysis Technical Report Table of Contents 1.0 Introduction General Travel Trends Commuting Trends CURRENT COMMUTING TRENDS COMMUTING BY COUNTY Length of Commute Trips Commuting and Density Significance of trends for Virginia Shared-Use Mobility Trends Bikesharing Carsharing Carsharing Benefits Ridesharing Transportation Network Companies Significance of Trends for Virginia Smart Infrastructure Trends Surface Materials Dynamic Paint/Markings Asset Condition Monitoring Energy Roadways Solar Roadways Electric Charging Roadways Piezoelectric Roads Crash Avoidance Technology In-Vehicle Warning Systems Vehicle-to-Vehicle Communications Vehicle to Infrastructure Communications/Intelligent Networked Highways Vehicle Automation Significance of trends for Virginia Climate Change What Climate Change Means for Virginia i

6 Table of Contents, continued 6.2 Impacts on the Environment Impacts on the Transportation Network Impacts on Economy Impacts on Communities Virginia Governor s Commission on Climate Change Significance for Virginia Rural Transportation What is rural Population and employment Rural Areas and Transportation Challenges Safety Significance for Virginia Bibliography ii

7 List of Tables Table 1: Locational Preferences by Generation, Urban Land Institute Survey Table 2: Ten Virginia Counties with Lowest Commute SOV Share, by Place of Residence Table 3: Five Virginia Counties with Highest Commute Walk/Bike Share, by Place of Residence Table 4: Potentially Impacted Transportation Network in Virginia List of Figures Figure 1: Vehicle Miles Traveled in the US and Virginia, Figure 2: Vehicle Miles Traveled, Virginia Interstate and Non-Interstate Roads, Figure 3: Vehicle Miles Traveled in Virginia and Per Capita Vehicle Miles Traveled, Figure 4: Total Annual Person Miles of Travel by Age Group, National Surveys Figure 5: Rates of Trip-Making by Age Group, Figure 6: Means of Commuting by Virginia Residents, 2000 and Figure 7. Single Occupant Vehicle Mode Share, by Residence Figure 8: Change in Percentage of Commuters Working at Home, Figure 9: Time Leaving for Work in Virginia Figure 10: Commute Distance in Virginia, Figure 11: Correlations between Density and Mode Share Figure 12: Carsharing Membership in U.S. ( ) Figure 13: Definitions of Levels of Vehicle Automation Figure 14: Kegotank Bay, Virginia Pre- and Post-Hurricane Sandy Photos (Source: USGS) iii

8 List of Figures, continued Figure 15: State of Virginia, Regularly Inundated Areas, At-Risk Areas and Affected Transportation Infrastructure Figure 16: Sea-Level Rise Vulnerability in Virginia, USGS, Coastal Vulnerability Index Figure 17: Social Vulnerability Map of Coastal Virginia w/ 6 feet Sea-level Rise Figure 18: Rural and Rural Urban Commuting Area (RUCA) Census Tracts plus Corridors of Statewide Significance (CoSS) Figure 19: Virginia s Population per Square Mile by Census Tract, Figure 20: Age Group Distribution, Urban and Rural Census Tracts, Virginia, Figure 21: Rural Employment 2014 and Figure 22: Virginia Crash Severity by Roadway Type Figure 23: Virginia Broadband Access and Expansion iv

9 VTrans2040 Trends Analysis Technical Report 1.0 Introduction This technical report documents the transportation trends research conducted by the CDM Smith team as part of the VTrans2040 Trends Analysis. The following sections utilize existing data and research documents from various governmental agencies. Sections 2 and 3 discuss general travel trends and commuting trends by taking a look at historical data from the past decade or so. Sections 4 and 5 discuss potential future trends in shared-use mobility and smart infrastructure that rely on advances in technology. Section 6 discusses the potential impacts of climate change on the transportation network in Virginia and finally Section 7 discusses the challenges of rural communities and their transportation systems. Demographics and economic trends are discussed in separate technical reports under separate cover. 1-1

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11 VTrans2040 Trends Analysis Technical Report 2.0 General Travel Trends Virginians travel in an increasingly mobile world and one in which telecommunication and internet technologies can substitute for physical travel. The demand for travel in Virginia and in the United States as a whole appear to be slowly decreasing in a trend that, at least for highway travel, began during the onset of the 2007 recession. There are reasons to believe that this trend may persist, but there is actually little consensus or certainly about how the demand for travel will grow and change in the future. Figure 1: Vehicle Miles Traveled in the US and Virginia, Source: FHWA Highway Statistics, Table VM-1 and CDM Smith Virginia mirrored national trends in experiencing a sustained drop in vehicle miles traveled between 2007 and 2012 (Figure 1). The trend in Virginia reversed slightly in 2012, due to an increase in travel on non-interstate roads (Figure 2). Between 2002 and 2012, VMT declined at an annual average rate of percent, while Virginia s population, over the same period, grew at an average annual rate of 1.1 percent. Per capita VMT declined by an average of -0.4 percent per year (Figure 3). 2-1

12 Annual Vehicle Miles Traveled in Virginia (millions) Per Capita Miles (millions) Vehicle Miles Traveled on Virginia Interstates Roads (millions) Vehicle Miles Traveled on Virginia Non-Interstate Roads (millions) Figure 2: Vehicle Miles Traveled, Virginia Interstate and Non-Interstate Roads, ,000 29,000 27,000 25,000 23,000 21,000 19,000 17,000 15,000 13,000 VA Interstates, Freeways, Expressways VA Arterials, Collectors, Local Roads (Non-Interstate) 55,000 54,000 53,000 52,000 51,000 50,000 49,000 48,000 Source: FHWA Highway Statistics, Table VM-1 and CDM Smith Figure 3: Vehicle Miles Traveled in Virginia and Per Capita Vehicle Miles Traveled, ,000 82,000 81,000 80,000 79,000 78,000 77,000 76,000 75,000 74,000 Vehicles Miles Traveled Per-Capita Miles 11,500 11,000 10,500 10,000 9,500 9,000 8,500 Source: FHWA Highway Statistics, Table VM-1 and CDM Smith Planners, scholars and pundits have speculated about the causes of the VMT decline, with many tracing it to causes such as generational, economic and technological factors, as well as lifestyle preferences. FHWA reviewed travel demand by age groups from national surveys across three time periods and found a consistent and logical trend of persons traveling less as they age (Figure 4). As the nation s and Virginia s population ages (as predicted) on average, we can expect the demand for travel to decrease. However, the study also found that in 2009 the youngest age groups traveled significantly less than the same age groups in either 1995 or 2009 (FHWA, The Next Generation of Travel, 2011). Could this trend of the millennial generation traveling less persist? 2-2

13 VTrans2040 Trends Analysis Technical Report Figure 4: Total Annual Person Miles of Travel by Age Group, National Surveys Source: FHWA, 2013 According to a recent survey conducted by the Urban Land Institute, persons across the age spectrum express a preference for living in places that are walkable, have convenient transit and that are near important destinations such as work, school and entertainment (Table 1). But this preference is especially pronounced among Millenials (or Generation Y ers, those born in the 80s and 90s), who, more than the other age groups surveyed, expressed a strong preference for good access and short distances to social and other activities (Urban Land Institute, 2013). These types of attitudes have been confirmed in several surveys, but they cannot answer the question of whether these expressed preferences will produce consistently lower demand for travel. Table 1: Locational Preferences by Generation, Urban Land Institute Survey Percentage ranking at top (6-10) Gen Y Gen X Baby Boomers War Babies/ Silent Generation Short distance to work and school 82% 71% 67% 57% Walkability 76% 67% 67% 69% Distance to family/friends 69% 57% 60% 66% Distance to shopping/ entertainment 71% 58% 67% 69% Convenience of public transportation 57% 45% 50% 56% Source: Urban Land Institute, 2013 In an in-depth study focused on the factors influencing the demand for travel, a group of UCLA researchers examined the same three nation-wide household travel surveys as the FHWA study (Evelyn Blumenberg, 2012). Consistent with the FHWA study, they found that there was a significant difference in trip rates for persons between 19 and 26 years of age and everyone else anyone between the ages of 27 and 65. In 1990, younger persons made more trips than older persons. In 2001 however, the roles reversed the younger group made significantly fewer daily trips than the older cohort. In 2009, that difference not only held, it grew more pronounced 2-3

14 (Figure 5). This observation restated FHWA s review of the same household travel surveys in 2011 (FHWA, The Next Generation of Travel, 2011). Figure 5: Rates of Trip-Making by Age Group, Source: (Evelyn Blumenberg, 2012) Both the UCLA and the FHWA studies point to several causes for the differences in VMT between younger and older cohorts, beyond the normal aging that reduces the ability to travel: The aftermath of the 2008 recession is causing lasting unemployment and underemployment, affecting many younger workers as well as older workers. Many states have instituted graduated licensing programs, making it more difficult to obtain full driving privileges at age 16. The internet can substitute for travel that would otherwise be made for socializing or for shopping. In reviewing the relative strength of these effects in a statistical analysis, the UCLA study found that economic status, including income and employment status, to be the single most important factor in influencing how much an individual travels. The evidence for the assertion that people substitute internet use for transportation is scant. In fact, higher internet use actually corresponds to more travel. Lastly, the study s analysis suggested that vehicle licensing restrictions have delayed individuals vehicle use rather than eliminated it. Economic factors and lifestyle preferences appear to be influencing Millenials away from own-car driving towards public transportation and shared-use driving. A report published by the Public Interest Research Group (PIRG) describes a 40 percent increase in the number of miles traveled on public 2-4

15 VTrans2040 Trends Analysis Technical Report transportation by year olds (Davis, 2012). Younger travelers are also using cheaper, convenient curbside bus services for intercity travel. The Chaddick Institute found that 48 percent of all adult curbside bus passengers are between the ages of 18 and 25, and 73 percent of all passengers are between the ages of 18 and 35 (Schwieterman, 2011). 2-5

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17 VTrans2040 Trends Analysis Technical Report 3.0 Commuting Trends Of all trip purposes, getting to and from work, or commuting, places the greatest burden on an urban area s transportation infrastructure capacity. These two-way trips occur frequently (typically five days a week) and in large numbers (77 percent of commuters in Virginia drive alone). Commuting is a primary reason for travel it accounts for 16 percent of all person trips in the U.S. and 19 percent of all U.S. person miles of travel daily. More significantly, most of us commute to our jobs at nearly the same time of day for example, nearly 50 percent of our trips between 6 and 7 a.m. are commute trips (Federal Highway Administration, 2009). In effect, the demands of commuting trips during peak periods strongly influence the design and capacity standards to which our urban roads are built. That capacity is limited; during the core commuting travel times, congestion is increasing, especially around Northern Virginia and Hampton Roads. Over the last 30 years, and as women have entered the workforce in large numbers, commuting has changed. Many commuters now make some of their work trips as part of a trip chain dropping off children, conducting household errands, and picking up necessities on their way to and from work. These varied patterns increase the efficiency of overall travel but also have the effect of increasing the number of non-work-related trips occurring in the peak period. These trip chains can limit the use of carpooling or transit modes, as workers need the flexibility to pick up their children from school if they fall ill, for example. The Dulles Corridor Metrorail Project Impact Research (2006), for example, reported that more than 9 of 10 commuters said that dependability was important in their commute choices. 3.1 CURRENT COMMUTING TRENDS Most commuters drive to work. Across the Commonwealth, 77 percent drive alone and another 10 percent ride with one or more passengers. Between 2000 and 2010, the share of workers who drove along to work remained relatively constant (77.1% vs. 77.2%). Carpooling decreased from 12.7 percent to 10.2 percent, while working at home increased from 3.2 to 4.5 percent (Figure 6). 3-1

18 Figure 6: Means of Commuting by Virginia Residents, 2000 and 2010 Worked at home Taxicab, motorcycle, bicycle, or other means: Walked Public transportation: Carpooled Drove alone 4.5% 3.2% 1.4% 1.3% 2.3% 2.3% 4.4% 3.4% 10.2% 12.7% 77.2% 77.1% Source: American Community Survey, 2000 Census Transportation Planning Package, CDM Smith Teleworking (working from home) is an increasing trend. Telecommuting has risen 79 percent between 2005 and 2012 and 2.6 percent of the American work force telecommutes, according to the Census Bureau s ACSA survey conducted in 2013 by the Society for Human Resource Management found a greater increase in the number of companies planning to offer telecommuting in 2014 than those offering just about any other new benefit (AASHTO, 2013). 3.2 COMMUTING BY COUNTY 0.0% 10.0%20.0%30.0%40.0%50.0%60.0%70.0%80.0%90.0% The percentage of commuters who drive alone is shown for each county/city in Figure 7. For almost all Virginia Counties this percentage falls in the range of 70 to 88 percent. Commuters in the most urbanized and congested parts of the Commonwealth rely heavily on public transportation for commuting. 3-2

19 VTrans2040 Trends Analysis Technical Report Figure 7: Single Occupant Vehicle Mode Share, by Residence Source: American Community Survey and 2000 Census Transportation Planning Package The transit/walk share of trips is 26 percent in Alexandria, 24 percent in Charlottesville, 34 percent in Arlington and 11 percent in Richmond ( ACS). Table 2 presents the ten counties with the lowest percentages of singleoccupant vehicle commuting in the Commonwealth. Table 2: Ten Virginia Counties with Lowest Commute SOV Share, by Place of Residence Source: American Community Survey The five counties (cities) in Virginia with the highest walk/bike mode shares have large student populations relative to their size (Table 3). Students with part-time jobs and others with university-related jobs likely constitute a large contingent of the walk/bike population in these areas. 3-3

20 Table 3: Five Virginia Counties with Highest Commute Walk/Bike Share, by Place of Residence Source: American Community Survey Between 2000 and 2010, Alexandria, Winchester, and Arlington County experienced gains of more than four percent in the use of public transportation. These gains occurred in urban areas where higher densities of population and employment are more conducive to higher levels of transit service and usage. In contrast, the six areas with an increase of four percent or more in those working at home were widely scattered throughout the commonwealth, including rural areas (Fluvanna, Middlesex, Norfolk, Prince George, and Rappahannock Counties and Galax City), as shown in Figure 8. Figure 8: Change in Percentage of Commuters Working at Home, Source: American Community Survey and 2000 Census Transportation Planning Package The increased support among employers for telecommuting and continued advances in communications and networking technologies are likely to result in further increases in mode share for those wanting to work from home. Public transportation should also continue to see modest growth in mode share in areas where investments can be made to increase the extent, frequency and convenience of transit services. The decline in carpooling witnessed between 2000 and 2010 may be slowed or even reversed in future years as a result of 3-4

21 VTrans2040 Trends Analysis Technical Report recent innovations in car sharing, ridesharing and transportation network companies, as discussed in more detail in Section 3. These shifts in future commuting patterns will have only small, incremental impacts on the mode share of those driving alone (single occupant vehicles). Future increases in population and employment, combined with physical and budget limitations on the addition of road capacity for SOVs, may result in further spreading out of the traditional peak hours of travel. Figure 9 shows the time Virginia commuters currently leave for work according to the American Community Survey. Figure 9: Time Leaving for Work in Virginia 600,000 Time Leaving for Work in Virginia 500, , , , , :00 to 4:59 a.m. 5:00 to 5:29 a.m. 5:30 to 5:59 a.m. 6:00 to 6:29 a.m. 6:30 to 6:59 a.m. 7:00 to 7:29 a.m. 7:30 to 7:59 a.m. 8:00 to 8:29 a.m. 8:30 to 8:59 a.m. 9:00 to 9:59 a.m. 10:00 to 10:59 a.m. 11:00 to 11:59 a.m. 12:00 to 3:59 p.m. 4:00 to 11:59 p.m. Source: American Community Survey Length of Commute Trips Workers in Northern Virginia s growing suburb endure the longest commutes, time-wise. The U.S. Census measured average commute time for 30 of Virginia's larger counties and cities in 2012 (Figure 10). The longest average commute times were all in the Northern region, with Stafford County, Fauquier County, and Prince William County clocking in with commutes near 40 minutes. Lynchburg City (16.9 minutes) in the West Central region had the shortest commute time in the Census study (Commonwealth of Virginia, 2014). As population and employment continue to grow in developing and developed regions of Virginia, more and more commuters will leave earlier or later to avoid congestion. This is especially true in Northern Virginia, where the morning and evening commute hour can extend three hours or more especially in congested corridors such as I-95 and I-66. (Metropolitan Washington Council of Governments, 2011) 3-5

22 Figure 10: Commute Distance in Virginia, 2009 Source: American Community Survey Workers in Hampton Roads and Northern Virginia also tend to travel longer distances to get to work. While 26 percent of Hampton Roads commuters and 32 percent of Northern Virginia workers travel 20 miles or more to get to work, 25 percent of commuters from the rest of the Commonwealth do so. 3.3 COMMUTING AND DENSITY A region s settlement patterns and the mode of travel of travel are closely related. For all Virginia commuters, regardless of age and education: The higher in population density an area is, the more likely a commuter is to take public transportation (a moderate correlation) and the slightly more likely a commuter is to walk/bike to work (a slight correlation). The lower in population density an area is, the more likely a commuter is to drive alone, drive with others or work from home. The higher in population density an area is, the more likely an year old commuter is likely to live there. The charts on Figure 11 present these common-sense observations with census tract commute mode of travel data from the American Community Survey. 3-6

23 VTrans2040 Trends Analysis Technical Report Upward sloping lines show a positive relationship (higher density, higher likelihood of using mode) and downward sloping lines indicate a higher likelihood of traveling by a particular mode as density decreases. Figure 11: Correlations between Density and Mode Share Source: American Community Survey 3.4 SIGNIFICANCE OF TRENDS FOR VIRGINIA The cost, convenience and safety of travel will continue to influence how people get to work. Teleworking will continue to grow but will be limited by factors such as managerial prerogatives and the desire for face-to-face contact. 3-7

24 Virginia was the first state in the nation to design and implement highoccupancy vehicle lanes to accommodate passenger vehicle demands during peak hours of commute travel, and there are (30 miles) of HOV lanes in the Commonwealth. The Commonwealth is considering an expansion of its network of variable priced toll lanes that HOV passengers and drivers can use for free, and the state s system of fixed-priced toll lanes has grown as well. The time, distance and location of commuter demand depend on a combination of factors, including housing choice, the availability, convenience and cost of different modes of transportation and the flexibility that a job offers an employee to work at home or at different times of the day. Of these factors, pricing offers a means of financing transportation projects and of managing peak demands on the transportation system. 3-8

25 4.0 Shared-Use Mobility Trends Shared-use mobility describes a wide variety of new technology-enabled services and tools that give instant access to new services and travel information while complementing traditional modes like fixed route transit. These services include bikesharing, carsharing, new forms of ridesharing, technologyenabled shared ride services, new private forms of transit and travel itinerary services that ease the selection of travel options with a click of the mouse or a tap on your smartphone (Filler, 2014). WHY IS THIS IMPORTANT? Technology has made it easier than ever for travelers to access and acquire transportation services. Shared transportation has increased significantly in recent years. Advances in technology and social media are attracting users looking for efficiency and convenience in choosing transportation alternatives. At the same time, congested commutes, a lack of funding for expanding public transportation, declining car ownership rates and limited/expensive parking in denser urban areas have helped spur the growing popularity of shared transportation services. These affordable and convenient services are expanding changing the public s perceptions about travel choices. They may revolutionize how we think about getting from point A to point B, especially for short trips, and especially in urban environments. But less dense locations are seeing a rise in these types of transportation options as well. This section further discusses trends in ridesharing, bikesharing, carsharing, transportation network companies, and the significance of these trends in Virginia. The challenge is how the existing transportation network can be flexible and integrate the shared-use mobility services. 4.1 BIKESHARING Bikesharing systems use an array of networked bike stations that allow a person to rent a bicycle at one station and to return it to another station. Advanced radio frequency identification (RFID) technology (i.e. Smartcards, magnetic fobs, etc.) and specialized wireless technology give users the ability to check out a bike whenever and wherever they find a stocked bike station. Most bikeshare systems offer various types of memberships, from annual to daily plans to a per trip fee. Bikesharing systems can be categorized into three key phases, or generations. The first generation system utilized free bikes; the second generation included coin-deposit systems; and the third generation uses information technology (IT) at automated self-serve kiosks. Recent technological and operational improvements are also paving the way for a fourth generation, known as the 4-1

26 demand-responsive, multimodal system. In our region, Washington D.C. was the first jurisdiction to implement a third generation bike sharing system in the U.S. in 2008 (FHWA, 2012). Now called Capital Bikeshare, D.C. s bikeshare trips have grown steadily since the service s inception in September, In March 2014, Capital Bikeshare recorded 260,000 trips system-wide (Capital Bikeshare, 2014). Since 2007, bikeshare systems have spread to 56 cities and two universities, with over 20,000 bicycles and 2,000 stations. An additional 20 new systems are planned for 2014 (Shaheen S., 2014). Bikesharing is especially popular in major metropolitan areas across the U.S. According to a survey by Dr. Susan Shaheen with the Transportation Sustainability Research Center (TSRC) at the University of California Berkeley, bikeshare users tend to be wealthier, more educated, younger, Caucasian, and male compared to the general population. Most trips are of short duration (of up to 20 minutes for distances of about a mile). The most common use is for work and school purposes and some of the systems, show noticeable usage peaks during morning and evening commute hours (Shaheen S., University of California, Berkely - TSRC, 2012) Bikeshare Member Survey: Demographics compared to general population, bikesharing users tend to be Wealthier More educated Younger Caucasian Male Source: Shaheen et. al, 2014 Despite their popularity and consistent growth, bike sharing s growth prospects are unclear. Whether the market can expand its current user base depends in part on how cities, counties and municipalities grow their bicycle route networks and how they manage their increasingly crowded and multimodal traffic streams. Bike sharing is reliable, cheap and easy to use. Potential users have to perceive that it is safe as well. 4.2 CARSHARING Carsharing is another shared-use mobility service that allows a member to rent a commercial fleet-based vehicle, or a privately owned vehicle on a temporary basis. Commercial carshare providers are typically rental car companies with side businesses such as Zipcar, owned by Avis, or Car2Go, owned by Daimler. In Virginia, carsharing services catering to college students have popped up near universities such as Virginia Tech and Virginia Commonwealth University. According to the 4-2

27 Members Source: Shaheen, 2014 Transportation Sustainability Research Center at UCA, Berkeley, one million people in the U.S. signed up for carsharing in 2013 (Figure 12). In 2003, there were only 26,000 users (Shaheen S., Introduction to Shared-Use Mobility: Definitions, trends, and understand", 2014). Figure 12: Carsharing Membership in U.S. ( ) 1,200,000 1,000, , , , , Peer-to-peer exchanges are a new way for car owners to rent out their otherwise underutilized personal vehicles. These programs typically screen renters and provide insurance that covers the owner for the use of the car by the renter. Examples of existing peer-to-peer networks include: Getaround and Relay Rides. In the Virginia region, Relay Rides offers services in Washington, DC. Carsharing Benefits The monetary benefits of carsharing include: lower demand for parking; fewer miles driven and emissions produced; and lower transportation costs. Research conducted by Dr. Susan Shaheen at TSRC UC Berkeley has shown that for each carsharing vehicle, nine to 13 vehicles have been taken off the road. In addition, carshare users own fewer cars and some become car free (E. Martin, 2010). Carshare vehicles tend to be newer and more fuel efficient than the household cars they replace (Arlington County Commuter Services, 2014). For people who drive infrequently, the fixed costs of car ownership constitute a majority of the costs associated with driving. By switching from personal car ownership to carsharing membership, infrequent drivers could save hundreds or even thousands of dollars a year. Personal non-monetary benefits of carsharing include (Arlington County Commuter Services, 2014): New vehicles (reliability and comfort) No maintenance or repair responsibilities Vehicles always clean Different vehicles for different purposes (whereas private owners have the same car all the time) 4-3

28 Convenient locations where people live and work Guaranteed parking space Carsharing membership is a viable option for people who occasionally need a car but don't want the expense and/or trouble of car ownership. Carsharing transforms the automobile from a product with high fixed costs into a service with costs on a time or mileage basis. When used in conjunction with public transportation, walking or bicycling, carsharing can reduce or eliminate the need to own a personal vehicle. For families, carsharing can postpone or eliminate the need to buy a second car. For businesses, participation in a carsharing program can reduce or eliminate the need to store and maintain company cars, or to require employees to bring their personal cars to work (Arlington County Commuter Services, 2014). 4.3 RIDESHARING Traditional ridesharing involves carpooling and vanpooling services, often arranged for work trips. Carpool passengers may not pay for their travel, if the driver benefits by being able to use an HOV lane, or if the driver and passengers rotate driving responsibilities. Vanpooling requires a monetary commitment to justify the costs associated with operating and leasing a van. Vanpooling usually involves six or more passengers, and participants share the cost of the lease and operating expenses. In 2014, there are thirteen rideshare organizations in Northern Virginia and five in other areas of Virginia (VDOT, 2014). There are two other forms of non-traditional ridesharing that focus on real-time matching for one-way trips. Casual or instant carpooling first developed in Northern Virginia in the mid-1970 s and arose with the opening of the I-95/I-395 Expressway. Interstate 395 was the first HOV-designated corridor in the country which provided an incentive for dynamic ridesharing. Locally known as slugging, commuters drive to a number of locations, mostly park and ride lots near entrances to I-95 to be picked up by drivers who want to use the HOV lane for quicker trips into Washington, DC. Slugging now serves approximately 5,000 commuters each day in the DC area (M. Oliphant, 2013). A more dynamic development in ridesharing is the use of smartphones to request an occasional, one-way ride with someone headed towards the same destination. The Federal Highway Administration (FHWA) is funding pilot programs with a software company that offered one of the first of these ridesharing apps. Carma is an app where individuals who are interested in providing rides enroll online or through Facebook. Fees and matching arrangements are handled through the software and drivers and riders are encouraged to rate each other for future users. Carma is currently operating in major cities in Virginia. 4-4

29 4.4 TRANSPORTATION NETWORK COMPANIES Transportation network companies are the newest type of shared-use mobility services. These new start-up companies began operating in San Francisco two years ago and are now expanding into metro areas across the country. Uber, Lyft and Sidecar are examples of these ridematching services that utilize online or smart phone apps for booking rides. Uber and Lyft are WHY IS THIS IMPORTANT? As these companies become more popular, car ownership may decline with younger drivers. both available in the Hampton Roads area as well as Washington, DC. Uber just recently began operating in the Richmond area. According to research by the Eno Foundation, these types of ridematching services are becoming popular with millenials for short trips. However there have been issues and concerns with liability and insurance, safety, and pushback by the taxicab industry (Filler, 2014). Regulators are questioning whether these services are operating more like taxis and subject to regulation for safety. California s Public Utilities Commission (PUC) determined recently that these new technology-based platforms are not ridesharing services and are more akin to commercial services like taxis. However, the PUC decided that these new services deserved some room for development and created a new category called Transportation Network Companies that is subject to fewer conditions to operate. The details of how these requirements will impact these services remains unclear and details remain to be worked out (Filler, 2014). If these concerns can be addressed, ride matching can provide an affordable alternative to get somewhere that isn t readily accessible via transit. Transit experts say these new ride matching services, which appeal to younger riders, could play a crucial role in ending the reign of single-occupant cars, and many young residents have embraced them as a cheaper, more reliable and, more fun (Uber passengers get a fist bump from the driver when they first get in the car) way to get around the city (Lovett, 2013). 4.5 SIGNIFICANCE OF TRENDS FOR VIRGINIA Shared-use mobility services are providing affordable and accessible transportation options during a time of financial uncertainty. These trends have the potential to change the current paradigm of choosing driving versus transit by offering a wide variety of ways to travel more conveniently. The challenge is how to integrate these services into the existing transportation network. Virginia s local, regional and statewide transportation agencies have a role in 4-5

30 4-6 supporting these services by establishing policies and regulations to ensure public safety. The cost to government of such actions is likely to be low. Where some shared services such as bike sharing are subsidized by government, costbenefit analyses can help establish whether such support is good public policy.

31 5.0 Smart Infrastructure Trends Smart infrastructure also known as intelligent transportation systems apply information systems technologies to communicate information that helps operators and users make 'smarter' use of transport networks. Advanced technologies are in development across the globe to improve our transportation systems. Smarter roads and smarter vehicles can help improve safety, congestion and fuel economy. This section highlights some of these technologies. WHY IS THIS IMPORTANT? Innovations may lead to fuel economy, safety, and congestion reduction. 5.1 SURFACE MATERIALS In recent years, the FHWA (Larson, 2011) and the private sector have stepped up their coordinated efforts to increase highway safety through pavement design. Wet pavement crashes and poor roadway conditions are a contributing factor to traffic crashes. Emerging technologies in pavement surface condition monitoring and pavement surface materials are important components in improving the transportation system. A few US companies have invested research and redevelopment resources into developing safer pavement surfaces. In Ohio, a Midwest company licensed an environmentally-friendly, organic resin-based road surface material called Eco- Pave (Midwest, 2014). According to Midwest, Eco-Pave can improve longterm performance of unpaved and surfaced roads by increasing structural integrity and loading capacity; creating or restoring a smooth, skid-resistant running surface; extending the life of pavement and other surfaces; eliminating potholing; and reducing maintenance costs. Also in Ohio, the Cargill Deicing Technology company is promoting a patented, epoxy-aggregate pavement surface called SafeLane developed at Michigan Technological University s Institute of Snow Research. Scientists researched and tested various deicing chemical applications on various aggregates (pavements are layers of stones bound together by asphalt or cement) to determine how to help prevent ice and frost formation on roads and highways (Cargill, 2014). The aggregate in the overlay stores deicing and anti-icing chemicals, such as brine, and releases then when needed, helping prevent slippery conditions such as frost, black ice and snow pack formations. The anti-skid aggregate also provides aggressive traction for vehicular traffic in all weather conditions, and the epoxy adhesive protects infrastructure by preventing damaging water and chemicals from permeating the surface. SafeLane has been used on roadways and bridges in Ohio and Colorado (Cargill, 2014). 5-1

32 5.2 DYNAMIC PAINT/MARKINGS In 2014, the Netherlands began replacing a small portion of a roadway with light-absorbing glow-in-the-dark road markings. The road markings are painted with glow-in-the-dark paint so that they can be seen without the need for lights. They were created using a photo-luminescent powder, developed in conjunction with road construction company Heijmans (Clark, 2014), integrated into the road paint. Future concepts of this technology include weather markings snowflakes, for instance, would appear when the temperature reached a certain level. The glow in the dark paint currently lasts up to eight hours and there isn t news yet on how the paint holds up against wear and tear. 5.3 ASSET CONDITION MONITORING The World Economic Forum ranks the U.S. 19th globally in the quality of its infrastructure (World Economic Forum, 2013). The American Society for Civil Engineers (ASCE), in its annual Infrastructure Report Card, gave the U.S. a D+, citing the need to invest almost $3.6 trillion by 2020 to upgrade transportation infrastructure in the nation (American Society of Civil Engineers, 2013). The same report gave Virginia roads a D- and its bridges a C. Twenty-six percent of Virginia s bridges are structurally deficient or functionally obsolete, while 47 percent of Virginia s roads are in poor or mediocre condition. According to the ASCE, driving on roads in need of repairs, costs Virginia motorists $1.34 billion a year in extra vehicle repairs and operating costs. With aging infrastructure and declining revenue, Virginia will benefit from innovative systems that reduce inspection costs and extend the life of infrastructure assets. Examples of asset condition monitoring include road weather information systems and pavement condition monitoring. Road weather information system sites are capable of collecting significant data, that when processed, provide weather status and short term trends of conditions that may impact the safety and trip reliability within a coverage area. Pavement condition monitoring uses sophisticated equipment to collect digital data about road surface profile, rut depth, slab faulting, pavement strength, and video-logging. Ultimately, improved understanding of bridge and highway materials performance will promote the safety, mobility, longevity, and reliability of the Nation s highway transportation assets. Automated monitoring systems and improved data collection will help transportation agencies identify and address infrastructure issues early and help maintain the full operational capability of the system. Life cycle analysis software will tie all assets into single monitoring system, and helps monitor and select the most cost-effective system upkeep improvements under a budget constraint. Beyond the single pavement or bridge system, a combined maintenance system allows for tradeoff analysis and direct focus on system performance goals. 5-2

33 5.4 ENERGY ROADWAYS Solar Roadways In the spring of 2014, solar roadways became a hot topic in social media and national news outlets when a YouTube video called Solar Freaking Roadways went viral. Solar roadways consist of hexagonal solar panels made of tempered and laminated glass, covered with a textured surface to avoid sliding. The panels also include LEDs to illuminate road signage as well as heating elements to withstand snow and ice. Photo: Solar Roadways In 2009, a husband and wife team from Idaho, Julie and Scott Brusaw, received a contract from the FHWA to build the first ever Solar Road Panel prototype. After successful completion of the first contract, the couple was awarded a follow-up 2-year contract in 2011 to build and test a prototype parking lot under all weather and sunlight conditions. According to the Solar Roadways website, several businesses and government agencies have submitted letters of interest to announce their desire for sidewalks, parking lots and eventually roads. The interested entities so far include: the City of Sandpoint, Idaho; Amtrak station in Sandpoint, Idaho; Sandpoint Airport; Panhandle Animal Shelter in Ponderay, Idaho; the Idaho Transportation Department, Boise State University, Idaho; Wright State University, Ohio; and NASA's Kennedy Space Center, Florida (Solar Roadways, 2014). The FHWA has been assessing the level of interest; however the cost of mass producing the solar roadway panels has not been released. Another example of an intelligent surface that uses the sun s rays is "Solar Walk" developed in Virginia. In October 2013, George Washington University completed the first walkable solar-paneled pathway in the world on the Virginia Science and Technology Campus as a part of the sustainable Solar Walk project (George Washington University, 2013). Designed by Onyx Solar, a company based in Spain, the pedestrian walkway uses 27 slip-resistant semi-transparent walkable panels with photovoltaic technology that converts sunlight into electricity. The walkable solar panels are an extension of the public sidewalk between Exploration and Innovation Halls at the intersection of GW Boulevard and University Drive. Electric Charging Roadways Electric charging roadways are roadways that use inductive power transfer similar to the method by which electric toothbrushes are charged that would charge electric cars wirelessly as they travel along the road. Researchers at North Carolina State University are currently testing a system that uses a specialized receiver that induces a burst of power when a vehicle passes over a wireless 5-3

34 transmitter. Initial models indicate that placing charging coils in 10 percent of a roadway would extend the driving range of an electric vehicle from about 60 miles to 300 miles (LaMonica, 2013). The University of Utah has also tested a wireless charging infrastructure for city buses and has spun out a company called Wireless Advanced Vehicle Electrification to build commercial products. With the Utah system, a bus could charge its batteries from coils placed under the road surface where passengers load or at traffic lights (LaMonica, 2013). Piezoelectric Roads Another form of energy roads are piezoelectric energy roads. Piezoelectric crystals in the roadway surface generate energy from the vibrations that vehicles generate as they drive along the road. A few international and US based vendors have demonstrated piezoelectric applications in Israel, London, Oregon, and Virginia Tech. Virginia Tech is currently managing a three year project with a $1 million contract from FHWA to investigate the use of piezoelectric materials for roadway energy harvesting (Xiong, 2012). A recent study commissioned by the California Energy Commission, found that further evaluation of the piezoelectric technology power output is needed to understand whether it is economically viable (Hill, 2013). 5.5 CRASH AVOIDANCE TECHNOLOGY The Volpe Center, a research arm of the U.S. Department of Transportation, has been collaborating with the National Highway Traffic Safety Administration (NHTSA), the Intelligent Transportation Systems Joint Program Office, and the Federal Transit Administration for decades on crash avoidance research. Crash avoidance technologies allow vehicles to communicate with drivers, each other and infrastructure; information about an impending accident can warn drivers or trigger a machine-induced manoeuver to avoid a crash. FHWA estimates that 25 percent of congestion is attributable to traffic incidents, around half of which are (Texas Transportation Institute, 2004). According to Volpe, these crash avoidance technologies could reduce about 95 percent of all vehicle crashes involving unimpaired drivers (US DOT, Volpe - The National Transportation Systems Center, 2013). In-Vehicle Warning Systems In-vehicle warning systems use radar, cameras, and other sensors to scan the roadscape and warn drivers of impending crashes with visual, auditory and physical alerts. Several luxury car makers such as Volvo, BMW, Cadillac are already using in-vehicle warning system features such as autobrake and front crash protection systems in their base models. This technology helps driver avoid collisions. Another future application of in-vehicle communication is being able to connect with smart parking infrastructure to enable driverless drop-offs and pickups. This same technology could improve and expand car sharing and dynamic 5-4

35 ridesharing by allowing for nearby, real-time rentals on a per-minute or per-mile basis (ENO Foundation, 2013). Vehicle-to-Vehicle Communications Vehicle-to-Vehicle (V2V) technology allows vehicles within a certain range of each other to communicate wirelessly and exchange information such as speed and location to help drivers avoid crashes. One potential application of this technology is a warning, or an outright synchronized automated vehicle response, when a lead vehicle in a line of cars suddenly brakes or has an accident. In February 2014, the NHTSA announced its intention to pursue a mandate of this technology in new light vehicles in an effort to improve highway safety, prevent crashes, and help alleviate congestion (NHTSA, 2014). In August 2014, the agency released an advance notice of proposed rulemaking (ANPRM) and a supporting comprehensive research report on V2V communications technology. The report will include an analysis of the agency s research findings in several key areas including technical feasibility, privacy and security, and preliminary estimates on costs and safety benefits, while the ANPRM seeks public input on these findings to support the Department s regulatory work to eventually require V2V devices in new light vehicles (NHTSA, 2014). Since 2001, the Virginia Tech Transportation Institute (Institute) has been building connected-vehicle technology. Following NHTSA s announcement in February 2014, the Institute was awarded a contract to design the delivery integration framework that will allow vehicles to talk with their drivers and with other automobiles on the roadway (Virginia Tech, 2014). Vehicle to Infrastructure Communications/Intelligent Networked Highways Similar to V2V communications, vehicle-to-infrastructure (V2I) communications is a wireless information swap between vehicles and roadside fixtures such as traffic signals and signage. These roadside listening stations will link up with GPS receivers in cars to monitor traffic patterns and accidents. Information is then passed back to satellite navigation in cars to help drivers avoid congested areas and accidents. Virginia Tech s Transportation Institute in coordination with the VDOT, has built a $14 million connected-vehicle test bed along Interstates 66 and 495 near Fairfax, Virginia. It contains 43 wireless infrastructure devices installed along roadways, all communicating with dozens of cars, trucks, and motorcycles equipped with wireless communication systems. The test bed will soon expand to include 80 roadside devices. The Institute says the challenges in implementing vehicle communication systems are numerous, from creating uniform warnings and data formats across varying devices and vehicles, to sorting vital information from traffic officials that may be only for truck drivers and not passenger-car motorists, and stacking warnings and communications in order of importance. 5-5

36 Also vital is securing communication networks from hacking (Virginia Tech, 2014). Virginia Tech also has smaller set-ups that facilitate testing of various traffic scenarios, including the Virginia Smart Road, at the transportation institute s Blacksburg base, and at the Virginia International Raceway, near Danville, Virginia. The Virginia Smart Road is a state-of-the-art, full-scale, closed testbed research facility. The 2.2 mile test track is built to interstate standards and features weather-making capabilities (rain, snow, fog), a variable lighting test bed, pavement markings, an on-site data acquisition system (DAS), road weather information systems, an enhanced global positioning system (GPS), road access and surveillance, and a signalized intersection. The Smart Road will eventually become part of the public transportation system connecting Blacksburg, Virginia, to Interstate 81 (I-81). The timetable for extending the road to I-81 will depend on growing traffic demands on the Route 460 Bypass and state and federal transportation funding (Virginia Tech Transportation Institute, 2014). Transportation experts consider connected-vehicle technology a stepping stone to achieving automation. Once cars are equipped with the ability to share information and modify driver behavior for the prevention of accidents, that same technology can also direct the vehicle to perform a safety maneuver. 5.6 VEHICLE AUTOMATION Autonomous vehicles can drive themselves on existing roads and can navigate many types of roadways and environmental contexts with almost no direct human input. They have the potential to revolutionize transportation systems and the way we travel. They promise to minimize deadly crashes, provide mobility to the elderly and disabled, save fuel and lower emissions, all while increasing road capacity. NHTSA defines four levels of automation, from collision warnings, similar to currently available safety packages in new vehicles, to no hands, fully automated operation. Figure 13 shows definitions of levels of vehicle automation as defined by NHTSA. 5-6

37 Figure 13: Definitions of Levels of Vehicle Automation 0 No Automation Forward collision warning, lane departure warning, blind spot monitoring. 1 Function Specific Automation Temporarily cede control of either forward (speed) or lateral (side-to-side) movements, but not at the same time. Dynamic brake support, electronic stability control, adaptive cruise control. 2 Combined Function Automation At least two primary control functions designed to work in unison. Adaptive cruise control in combination with lane centering. 3 Limited Self-Driving Automation Enable the driver tocede full control of all safety-critical functions. Designed so that the driver is not expected to constantly monitor the roadway while driving. 4 Full Self-Driving Automation Designed to perform all safety-critical driving functions and monitor roadway conditions for an entire trip. Source: National Highway Traffic Safety Administration (NHTSA). In April 2014, Google s self-driving cars surpassed the 700,000 mile accident-free mark on California and Nevada public roads. Numerous manufacturers have also begun testing driverless systems including: Audi, BMW, Cadillac, Ford, GM, Mercedes-Benz, Nissan, Toyota, Volkswagen, and Volvo. Semi-autonomous features are now commercially available, including adaptive cruise control (ACC), lane departure warnings, collision avoidance, parking assist systems, and on-board navigation (ENO Foundation, 2013). Nissan and Volvo both have announced their intentions to have commercially viable autonomous-driving capabilities by 2020 in multiple vehicle models. Autonomous vehicles may be available on the mass market by 2022 or 2025 and by 2040, approximately 75 percent of all vehicles are expected to be autonomous (ENO Foundation, 2013). Daimler recently announced it is developing autonomous trucks that they expect to be available by Europe s CityMobile2 project is currently demonstrating low-speed fully autonomous transit applications in five cities. Additionally, autonomous vehicles are becoming increasingly common in other sectors including military, mining, and agricultural (ENO Foundation, 2013). 5-7

38 The Virginia Tech Transportation Institute has teamed with automotive companies such as General Motors to study how drivers interact with varying degrees of automated vehicle operation, including parking systems and features that can halt or slow a car to avoid crash- or near-crash events. In 2013, Google brought its autonomous car to the Smart Road for several weeks of closed-course testing (Virginia Tech, 2014). Autonomous vehicles and vehicle-to-vehicle technology could greatly improve travel safety by eliminating or reducing the danger posed by distracted or impaired driving. Researchers are also developing ways for autonomous vehicle technology to reduce congestion and fuel consumption by allowing for smoother braking and fine speed adjustments of following vehicles. This can lead to fuel savings and less brake wear. Autonomous vehicles could be expected to use existing lanes and intersections more efficiently through shorter headways (spacing between vehicles), coordinated platoons (groups of vehicles), and more efficient route choices. The effective capacity of roads, for example could increase considerably. Autonomous vehicles may also increase the demand for shared use and high occupancy vehicles travel by drastically reducing operator costs. However, currently the high costs of the new technology hamper large-scale production and mass consumer availability (ENO Foundation, 2013). While individual U.S. states have been advancing autonomous vehicle legislation through incremental measures, some states are not waiting for federal guidance on the use of fully, or partially, autonomous vehicles beyond testing purposes on public roads. Nevada, California and Florida have each passes laws approving operation of autonomous cars. Florida DOT has developed a website dedicated to implementing automated vehicles: and will hold its second Vehicle Automated Summit in December Other states with bills pending legislature include the District of Columbia, Hawaii, New Jersey, and Oklahoma. In Virginia, state agencies including the Department of Motor Vehicles, State Police, and Virginia Department of Transportation have formed a task force to discuss implications of automated vehicles in the state. The task force met for the second time in August SIGNIFICANCE OF TRENDS FOR VIRGINIA In the near term, vehicles that sense potential collisions will be able to avoid crashes by taking over control of the car, temporarily. Over the long-term, manufacturers and software companies will improve automated vehicle technology, and buses, trucks and cars will operate without drivers, if all the legal, institutional and technological kinks can be worked out. Complex questions remain relating to legal, liability, privacy, licensing, security, and insurance regulation (ENO Foundation, 2013). 5-8

39 VTrans2040 Trends Analysis Technical Report 6.0 Climate Change Nearly all climate change experts agree that the earth is warming and that the severity and frequency of storms and weather events is increasing. However, there is less consensus about what is causing the warming, whether habitats and ecosystems can adapt to the changes, and how best to mitigate impacts. Virginia s southeastern coastal zone is the second most vulnerable region in the U.S. to sea-level rise after the Gulf Coast region. Virginia s Atlantic and Chesapeake Bay coastlines are vulnerable to climate-related impacts, due to its low elevation, degraded ecosystems and rates of sea level rise. Increasingly, climate change may threaten transportation infrastructure, cause WHY IS THIS IMPORTANT? Virginia s roads, bridges and other structures are vulnerable to shoreline erosion, increasing storm intensity, increasing global temperatures and rising ocean levels. economic and social disruption and endanger lives. But the Commonwealth is mitigating the transportation-related risks through a wide range of adaptive actions. The Commonwealth is also looking at better ways of anticipating and reducing the risks to vulnerable components of the transportation system and vulnerable communities in the years ahead. 6.1 WHAT CLIMATE CHANGE MEANS FOR VIRGINIA In 2007, Governor Tim Kaine issued Executive Order 59, establishing a Climate Change Commission. The Commission was tasked with the following: Inventory the amount of and contributors to Virginia s greenhouse gas emissions, including emissions projections through 2025; Evaluate the expected impacts of climate change on Virginia s citizens, natural resources and economy; Identify climate change approaches being pursued by other states, regions and the federal government; Identify what Virginia needs to do to prepare for the likely consequences of climate change; and Identify any actions (beyond those identified in the Virginia Energy Plan) that need to be taken to achieve the 30 percent greenhouse gas reduction goal. The Commission met over the course of 2008 and issued the Final Report: A Climate Change Action Plan in December The following sections briefly summarize the climate change impacts for Virginia that were identified during 6-1

40 the extensive research conducted by the Climate Change Commission as well as newly released data and research by federal agencies. 6.2 IMPACTS ON THE ENVIRONMENT Climate change will have a significant impact on Virginia s ecosystems especially along the coast and Chesapeake Bay. Some of the potential impacts from climate change on Virginia s estuaries and coastal ecosystems include (Bauer, 2008): Higher coastal water levels and greater salinities; Increased water stratification due to rising sea level; Increases in freshwater input; Shoreline erosion and submergence due to rising sea-level, storms, decreases in sediment delivery; Increasing nutrient inputs from land and rivers; Decreases in oxygen content of estuarine waters due to increasing temperatures and changing circulation patterns, and Decreasing ph (increasing acidity) due to rising CO. Some of the Chesapeake Bay s foundation species, such as blue crabs, eelgrass, and oysters, could decline or disappear as salinity and temperatures continue to increase and weather patterns continue to fluctuate widely from year to year. Because foundation species support many other species, these impacts would be felt throughout the ecosystem (Virginia Governor's Commission on Climate Change, 2008). Shoreline erosion and submergence impacts were seen along portions of Virginia s coastline following Hurricane Sandy in Figure 14 shows an example of the land loss on Kegotank Bay, Virginia before and after the storm. 6-2

41 VTrans2040 Trends Analysis Technical Report Figure 14: Kegotank Bay, Virginia Pre- and Post-Hurricane Sandy Photos (Source: USGS) 6.3 IMPACTS ON THE TRANSPORTATION NETWORK In 2008, the Transportation Research Board released Special Report 290: Potential Impacts of Climate Change on U.S. Transportation. The study identified potential consequences of climate change on transportation. Rising sea levels with storm surge, an increase in hot days, an increase in intense storms and more frequent strong hurricanes will have significant impacts on the transportation network. Those impacts may include (Transportation Research Board, 2008): Rising sea levels with storm surge may cause: o o More frequent flooding of tunnels, marine terminals, warehouse entrances, and low-lying infrastructure; Inundation of roads, rail lines, and runways in coastal areas, and 6-3

42 o Significantly reduced clearance of dock cranes and other structures at port facilities. Increase in very hot days/heat waves impacts may cause: o o o o Thermal expansion of bridges and pavements; Rail track deformations; Lift-off limits at hot weather airports, and Limitations on hours of construction. Increase in intense precipitation events may cause: o o o Traffic disruptions; Flooding of roadways, rail lines, runways and Scouring of pipeline supports and bridge foundations. More frequent strong hurricanes may cause: o o o More frequent and costly evacuations; Greater probability of infrastructure failures, e.g. failure of bridge decks, and Damage to ports and harbors. Photo: NOAA, National Weather Service Another report by the U.S. DOT, The Potential Impacts of Global Sea Level Rise on Transportation Infrastructure, estimated the potential impacts of global sea level rise on transportation in Virginia. Table 4 shows that approximately 1.8 miles will be inundated and 9.9 miles of interstate highways are at risk of a 21 centimeter eustatic sea level rise 1. Railroads may see 4.7 miles of inundation and 35.7 miles at risk. The total impacted land area could exceed 250,000 acres. Virginia airports and ports may also experience inundation and expect impacts from sea level rise (ICF International, 2008). Figure 15 gives a visual of inundated areas in Virginia from a 21 centimeter eustatic sea level rise. 1 Eustatic sea level rise refers to the change in sea level created by any volume increase in the oceans worldwide, primarily due to thermal expansion and ice melt. 6-4

43 VTrans2040 Trends Analysis Technical Report Table 4: Potentially Impacted Transportation Network in Virginia Source: ICF International, The Potential Impacts of Global Sea Level Rise on Transportation Infrastructure,

44 Figure 15: State of Virginia, Regularly Inundated Areas, At-Risk Areas and Affected Transportation Infrastructure Source: ICF International, The Potential Impacts of Global Sea Level Rise on Transportation Infrastructure,

45 VTrans2040 Trends Analysis Technical Report 6.4 IMPACTS ON ECONOMY Impacts of climate change also have the potential to affect Virginia s economy, specifically coastal tourism and military operations. In 2014, Assateague Island was named the 23 rd best beach destination in the U.S. by TripAdvisor s Traveler Choice ranking. In Virginia Beach, coastal tourism employed approximately 11,400 jobs in 2008 at approximately $895 million in revenue. According to Photo: Steve Earley, Virginian-Pilot file photo) the Bureau of Labor Statistics, there were approximately 91,900 employees in the Leisure and Hospitality industry in June 2014 within the Virginia Beach-Norfolk-Newport News, Va.-N.C. Metropolitan Statistical Area (MSA) (Bureau of Labor Statistics, 2014). According to the Center for Naval Analyses (CNA) report on National Security and the Threat of Climate Change in 2007, there are nineteen military installations in Hampton, Norfolk and Virginia Beach. The world s largest naval station is in Norfolk. According to National Security and the Threat of Climate Change, climate change poses a serious threat to America s national security. Severe weather, sea level rise and hurricanes have the potential to impact the military s readiness by damaging base infrastructure, cause disruptions of energy supplies and add stress to weapons systems (CNA Corporation, 2007). 6.5 IMPACTS ON COMMUNITIES Human populations are sensitive the consequences of climate change, including radical shifts of weather patterns and changes in local flora and fauna. The direct and indirect effects of climate change can vary greatly from one location to the next and predicting the effects in any one location is difficult. Direct effects include changes in temperature, precipitation, and occurrence of heat waves, floods, droughts, and fires. Indirectly, climate change may cause health impacts due to ecological disruptions brought on by crop failures or displacements of populations. According to the most recent report by the Intergovernmental Panel on Climate Change (IPCC) in October 2013, potential health concerns from projected climate change include (Intergovernmental Panel on Climate Change, 2013): Greater risk of injury, disease, and death due to more intense heat waves and fires; 6-7

46 Increased risk of under-nutrition resulting from diminished food production in poor regions; Consequences for health due to lost work capacity and reduced labor productivity in vulnerable populations; Increased risks of food- and water-borne diseases and vector-borne diseases, and Modest improvements in cold-related mortality and morbidity in some areas due to fewer cold extremes, geographical shifts in food production, and reduced capacity of disease-carrying vectors due to exceedance of thermal thresholds. More frequent and severe storms, especially in coastal areas, may gradually and over the long term reduce the attractiveness of living and working in vulnerable areas. If severe enough, whole areas may become sparsely inhabited, leaving transit and highway agencies with a dilemma over what level of service to provide. In coastal areas, more frequent evacuations will need to be controlled carefully, to avoid Photo: AP Photo/Mike Groll gridlock and driver frustration during critical storm management times. The USGS has developed a Coastal Vulnerability Index that describes the vulnerability of a coastal region to sea level rise. The USGS s Coastal Change Hazards Portal visualizes this index. Figure 16 is a snapshot of Virginia s coastline from the portal. It shows a majority of Virginia s Atlantic and Chesapeake Bay coastlines are considered to have a very-high vulnerability to sea level rise (USGS, 2014). 6-8

47 VTrans2040 Trends Analysis Technical Report Figure 16: Sea-Level Rise Vulnerability in Virginia, USGS, Coastal Vulnerability Index Source: United States Geological Survey, Coastal Vulnerability Index NOAA s Social Vulnerability Index, which shows areas of high human vulnerability to hazards, is based on population attributes (e.g., age and poverty) and the built environment. By looking at the intersection of potential sea level rise and vulnerable block groups, planners can see how vulnerable populations might be affected by sea level rise. Dark red indicates block groups having a high vulnerability, and the lighter reds indicate decreasing vulnerability (NOAA). Figure 17 shows the social vulnerability of coastal Virginia affected by a six foot rise in sea-level (NOAA, 2014). 6-9

48 Figure 17: Social Vulnerability Map of Coastal Virginia w/ 6 feet Sea-level Rise Source: NOAA, Social Vulnerability Map. 6.6 VIRGINIA GOVERNOR S COMMISSION ON CLIMATE CHANGE Governor McAuliffe recently announced his plans to reactivate the Virginia Governor s Commission on Climate Change. VTrans2040 will monitor the commission s work as the transportation plan develops goals, needs and policy recommendations. 6.7 SIGNIFICANCE FOR VIRGINIA Most of Virginia s coastal cities are already planning for climate change. In 2012, the City of Norfolk conducted an action plan which called for new flood gates, higher roads and a retooled storm water system. Implementing the plan would cost more than $1 billion the size of the city s entire annual budget and protect Norfolk from about a foot of additional water. The Hampton Roads area has also been convening a climate change and sea level rise forum in the past three years and Virginia Beach will be conducting climate change adaption planning over the next year. Government agencies are allocating more funds to fortify structures in vulnerable areas, and they are planning to allocate more funds for future structures that can withstand the impacts of severe storms. These measures are straining the ability of already cash-strapped agencies to meet all of their 6-10

49 VTrans2040 Trends Analysis Technical Report program commitments. Emergency and incident response planners may need to revise and devote more resources to their evacuation plans as severe weather events increase in frequency, intensity and duration. 6-11

50 7.0 Rural Transportation The transportation system across rural communities in Virginia is vital to the social and economic wellbeing of the state. The distance between communities and scattered population require a functioning transportation system to connect people to jobs, health care, and family as well as contribute to regional economic growth by connecting business to customers, goods to markets, and tourists to destinations. Yet rural transportation systems are really a system of disparate parts and are decentralized. Most roads are funded and maintained by different levels of government cities, counties, state, and federal. While the state and federal governments provide much of the capital funding for rural public transit in the Virginia, actual operations remain primarily a local responsibility. Rail rights-of-way are usually privately owned and maintained. Airports are usually owned by public or quasi-public organizations, but they also contain facilities that are owned by individual carriers. Both public and private organizations own terminals, stations, and other loading and interchange facilities. Rural communities in Virginia also face geographic challenges including: long distances between population centers; steep grades and mountain passes; more dramatic weather events and effects on road conditions; and a dispersed system with high unit costs for service delivery, operations, and maintenance. 7.1 WHAT IS RURAL The Office of Management and Budget (OMB) designates rural areas as all counties and cities not designated Metropolitan Areas (MAs). MAs are defined as broad labor-market areas having: Central counties with one or more urbanized areas; urbanized areas (described in the next section) are densely-settled urban entities with 50,000 or more people. Outlying counties that are economically tied to the core counties as measured by labor-force commuting 2. The Office of Rural Health Policy of the U.S. Health Resources and Services Administration (HRSA), the agency responsible for enhanced access to health care, designates rural areas through Rural Urban Commuting Area Codes (RUCAs). RUCA codes are developed from OMB criteria, but include 2 Outlying counties are included if 25 percent of workers living in the county commute to the central counties, or if 25 percent of the employment in the county consists of workers coming out from the central counties the so-called "reverse" commuting pattern. 7-12

51 commutation data to urban cores and other cores economically dependent on the urban cores. This designation is to define areas eligible for HRSA Rural Health grants. Rural Virginia accounts for 68 percent of the land area in the state, approximately 27,000 square miles. Many of Virginia s Corridors of Statewide Significance (CoSS) traverse rural census tracts, including most of I-77 and Route 58 (Figure 18). Of the 69,900 miles of roadways in Virginia, 40,000 miles (57 percent) are in rural areas (VDOT, 2012). Figure 18: Rural and Rural Urban Commuting Area (RUCA) Census Tracts plus Corridors of Statewide Significance (CoSS) Source: US Census Bureau and Virginia Governor s Office of Intermodal Planning and Investment. Out of 133 Counties and Cities in Virginia, 52 are designated rural by the U.S. Department of Health and Human Services. Another 24 within Metropolitan Areas (MAs) are designated as rural based on their Rural Urban Commuting Area Scores (RUCAs). 7.2 POPULATION AND EMPLOYMENT Virginia s rural population is projected to rise approximately eight percent from 2010 to 2040 according to projections provided by The Weldon Cooper Center for Public Service (2014). This includes rural designated cities, counties, towns, and RUCAs. The populations of Stafford County, York County and the City of Suffolk, all RUCAs, are expected to see the largest growth. Stafford County s population specifically is projected to double between 2010 and Figure 19 illustrates the 2010 population per square mile by census tract. 7-13

52 Figure 19: Virginia s Population per Square Mile by Census Tract, 2010 Source: Rural areas are also home to an aging demographic. In 2012, many of America s rural counties had annual deaths surpassing births. By 2040, forecasts estimate that 30 percent of the 65 and older population (approximately 600,000 of 2 million) will live in rural areas or RUCAs in Virginia (Weldon Cooper Center for Public Service, 2012). Figure 20 illustrates the distribution of age groups between urban and rural census tracts in Figure 20: Age Group Distribution, Urban and Rural Census Tracts, Virginia,

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