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6 SECTION 1 Literature Review For the TCRP H-27A project, the panel identified a number · Among the factors that attract households to TOD, house- of fundamental questions about transit ridership and TOD. holds consistently place high value on neighborhood design, For this literature review, the research team divided these home prices and perceived value, and transit proximity. questions into four general areas: 1) TOD travel characteris- · Access to high quality transit is becoming increasingly tics; 2) transit system and land-use characteristics; 3) TOD important to firms trying to attract "creative class" workers ridership strategies; and 4) TOD resident/tenant characteristics. in the knowledge economy. Findings related to these topic areas and specific questions follow. In addition to the literature on TOD, there are larger bodies The existing research provides a largely complete story of literature that address transit operations (to maximize rid- about transit ridership and TOD. There is significant and very ership) and the travel impacts of development density, mixed detailed information about specific TOD projects in Portland, uses, and urban design. This literature review does not describe Oregon, Arlington County, Virginia (suburban Washington, all of those studies and focuses on research pertaining to TOD D.C.), and the San Francisco Bay Area, where a significant specifically. That said, some key findings from the general amount of travel behavior data has been collected through transit and land use literature are included, as they would not resident surveys (and academic research). At the macro level, be expected to differ significantly for TODs. U.S. Census data also has been thoroughly analyzed to reveal differences between TOD households and other households TOD Travel Characteristics in travel behavior and demographics. The findings are con- sistent with each other and consistent with economic and 1. What are the travel characteristics (e.g., frequency of travel behavior studies that explain why people travel as they do. by different modes) of people who live or work in a TOD? Many cities still lack detailed primary (survey) data. That 2. What was the travel pattern of the TOD resident prior to said, it is reasonable to assume that transportation and eco- moving to the TOD? nomic forces that shape TOD residency and travel behavior in California, for instance, also would apply to other settings Key Conclusions (e.g., Dallas). A lot more is known about the travel performance of TODs. · TOD commuters typically use transit two to five times more Whereas the first generations of TOD focused primarily on than other commuters in the region. TOD transit mode advocacy and assisting early adopters, now there is increased share can vary from 5% to nearly 50%. measurement and understanding of TOD travel outcomes. · Similar to findings for nonwork trips, transit share is two Some key findings in this literature review include: to five times higher, although mode shares are typically lower than commute trips (2% to 20%). · Between 1970 and 2000, transit ridership for work trips in- · The primary reason for range is that transit use is heavily creased in TOD zones, whereas ridership declined markedly influenced by relative travel times with automobile and in the metro areas surrounding TODs. extensiveness of transit service, which can vary markedly · TOD households are twice as likely to not own a car, and across regions. As the transit network links to more job own roughly half as many cars as comparable households centers, educational opportunities, and cultural facilities, not living in TODs. transit use increases. From this perspective, TOD type
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7 (e.g., suburban neighborhood versus suburban center) is they took Bay Area Rapid Transit (BART) to work every less important than specific location within the region and weekday. the quality of connecting transit service. · Noncommuter mode share: Transit served, on average, 8% · The transit mode shares are statistically reliable, and for an of nonwork trips made by surveyed station-area residents, existing rail system, one could reasonably infer the approx- again with considerable variation across TODs. At BART's imate transit mode share of a hypothetical new TOD by Pleasant Hill station for instance, transit served 15% of non- comparing it to similar TODs in the same system. work trips compared to less than 2% for sampled projects · However, there is no rule of thumb or single mode share in Long Beach and Los Angeles. The differential between number that can be easily applied to a hypothetical new transit's modal splits for work versus nonwork trips high- TOD along a new rail or bus system, due to widely varying lights the role that self-selection plays in shaping travel local travel conditions and employment distributions. choices. Notably, people tend to move to TODs partly be- · A primary reason for higher TOD transit use is self selec- cause of the desire to rail-commute and express this pref- tion. Current transit users and those predisposed to use erence most visibly in their work-trip modal choice. transit seek out TOD. · Trends: Transit's modal share remained fairly stable over · When work location is unchanged, often a significant per- the 1993-2003 period for neighborhoods surrounding rail cent (e.g., 50%) were transit users before moving to the TOD. stations. However, since transit's market share of trips gen- · Among commuters with no previous transit access, transit erally eroded over this 10-year period, it appears that TOD use can increase (up to 50%). areas have weathered the secular trend toward declining transit ridership better than most settings. · Length of residency: There is some evidence that those who Findings have lived the longest in California TODs tend to use tran- The literature shows that those who live and work near sit most often. Among those who lived in a TOD for more transit stops patronize transit appreciably more than the typ- than a decade, the share taking transit for their "main trips" ical resident of a region. The most recent comprehensive study (both work and nonwork purposes) averaged 29% versus on the travel characteristics of TOD residents and workers is 17% among those who had lived in the TOD for less than the 2003 study, Travel Characteristics of Transit-Oriented De- five years. velopment in California (Lund, Cervero, Willson, 2004). In · Intervening factors: Consistent with other research on mode this study, ridership statistics were developed for those living choice, many other factors played a critical role in influ- at 26 residential sites near rail stations in California's four encing the modal choices of station-area residents. Policies largest metropolitan areas, as well as for a smaller sample of that significantly affected modal choices included: free park- office workers, retail shoppers, hotel workers, and guests of ing at the workplace, flex-time privileges, employer contri- projects near rail stations. butions to the cost of transit passes, and, to a less degree, Key findings about station-area residents include: land-use variables like density and street connectivity. Additional information about these intervening factors is · Commute mode share: From travel-diary responses, about included in subsequent sections of this literature review. one-quarter of the surveyed California TOD residents took transit to work. This was nearly five times higher than tran- Key findings about station-area office workers include: sit's commute-trip modal share by residents who lived in the surrounding community. This five-fold ridership · Commute mode share: From the survey of those work- bonus associated with transit-oriented living is similar to ing at 10 predominantly suburban office buildings near that found in a comprehensive survey of California TOD California rail stations, on average, around 12% traveled to residents conducted in 1992 (Cervero, 1994). Patterns var- work via rail transit. This is around five percentage points ied significantly across the state, with transit capture rates more than rail's market share for TOD office workers who of nearly 50% for several Bay Area TODs, and less than 5% were surveyed in 1992 (Cervero, 1994). Modal splits varied for some Southern California locales. About half of the markedly, however. For two of the 10 office projects, 25% working residents of all California TODs said they never or more of surveyed workers rail-commuted. These two take transit to work. projects are in downtown settings with comparatively high · Frequency of travel: Across the 26 surveyed residential densities, good regional accessibility, mandatory parking sites, 29% of tenants who responded to the survey indi- charges, and within a block of the rail station. cated they commute by transit every workday, and another · Intervening factors: Besides proximity to rail transit, other 7% reported they commute several times a week. In the factors that encouraged office workers to rail-commute case of the Pleasant Hill TOD, 49% of residents indicated included: availability of free parking at the workplace;
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8 employer-provided transit passes; quality of the walking neither the county nor WMATA have to provide long-term corridor from the rail station to the office building; and commuter parking; land parcels that were devoted to park- feeder bus frequency. ing early on have all been developed. About 40,000 riders board daily at the five urban stations in the Rosslyn-Ballston Key findings about station-area hotel patrons and employ- Corridor. About 29,000 riders board at the four suburban ees and retail customers include: stations farther out along the Orange Line; only 15% of these transit riders arrive at their stations on foot, while 58% arrive · Commute mode share: Of 111 workers surveyed at two by car (Dittmar and Ohland, 2004). hotels near rail transit in California, 41% traveled to work Dittmar and Ohland compiled 2000 Census Journey to by rail transit. Work data for selected TODs in three regions with high tran- · Travel by hotel patrons: Transit was not used to access hotels sit ridership. These TODs were defined by using a half-mile near rail stations among the small sample of guests who radius buffer around selected transit stops. Table 1.1 shows were surveyed. More than half of the surveyed guests indi- high levels of both transit and walking at each of the stations, cated that they used transit during their stay. higher than the levels in the county as a whole. The Evanston · Travel by retail patrons: Of 1,259 retail patrons surveyed at and urban downtown stops had particularly high walking three shopping facilities near rail stations in California, shares, indicating that many downtown residents both live 13% had arrived by rail transit. and work downtown, and that transit supports this lifestyle. The walk shares in Arlington, however, were comparatively Research from metropolitan Washington, D.C. also found low, and the authors suggest this is due to the high number of higher transit market shares among station-area residents, regional jobs in the capital, and a historic neglect of the pedes- attributable in part to the high levels of accessibility conferred trian environment in Arlington (something that is currently by the Washington Metropolitan Area Transit Authority being improved). (WMATA) rail network (JHK and Associates, 1989). Over Renne (2005) used similar census data to more thoroughly the past three decades, Arlington County has channeled new examine trends in travel behavior and vehicle ownership from development into high-density, mixed-use projects around 1970 to 2000 for households living in 103 TODs compared five closely spaced urban rail stations in the Rosslyn-Ballston with averages for the 12 metropolitan regions where the Corridor, and employed a variety of techniques, including TODs are located. TODs were defined by using a half-mile transportation demand management programs, to encourage radius buffer around selected transit stops. While TODs may residents to use transit. As a result, 47% of residents use modes not have existed in these locations as far back as 1970 or 1980, of travel other than the automobile to get to work, and 73% today they are recognized as TODs and include a train station arrive at rail stations on foot, providing a cost savings because and dense housing at a minimum. Regions were classified into Table 1.1. 2000 journey to work mode share for selected TODs. Drove Transit Walk Alone TOD Community Share (%) Share (%) Share (%) Type Arlington County, VA 23 5 55 County Court House 37 8 43 Suburban Center Clarendon 34 6 47 Suburban Center Rosslyn 38 10 42 Suburban Center Ballston 38 7 42 Suburban Center San Francisco, CA 31 8 41 County Church/24th 34 6 38 Urban Neighborhood Embarcadero 24 44 19 Urban Neighborhood Cook County, IL 17 4 63 County LaSalle 25 37 25 Urban Downtown Chicago/Fullerton 44 8 36 Urban Neighborhood Chicago/Berwyn 38 5 42 Urban Neighborhood Evanston/Davis 19 24 42 Suburban Center Evanston/Dempster 22 14 49 Suburban Neighborhood Evanston/Main 55 22 7 Suburban Neighborhood Source: Dittmar and Ohland, 2004
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9 three groups: older and redeveloping (e.g., Chicago, Illinois; results, as transit ridership in suburban TODs, while robust, New York/New Jersey), maturing heavy rail (e.g., Atlanta, was outweighed by ridership in the rest of the MSA, which is Georgia; Miami, Florida; San Francisco, California; Washing- very dense and metropolitan.) Table 1.2 shows detailed transit ton, D.C.), and growing regions with light rail (e.g., Portland, commute data from Renne's study. Oregon; San Diego, California; Los Angeles, California; Dallas, From this data, Renne provides the following observations: Texas; Denver, Colorado; and Salt Lake City, Utah). Renne's results show that over the past 30 years, transit · Maturing-heavy rail regions experienced the highest commuting has increased amongst TOD residents from transit ridership growth and collectively have promoted 15.1% to 16.7%, while it has decreased across all regions from TOD through development partnerships (e.g., joint de- 19% to 7.1%. Despite the regions becoming increasingly velopment in Washington, D.C.) and supportive poli- auto-dependent for work trips, more than twice as many TOD cies. In comparison to Washington, D.C., Atlanta TODs residents used transit for commuting compared to the regional have experienced declining transit mode share. Renne average (16.7% versus 7.1%) in 2000. Transit commuting was surmises this is because Washington TODs include more than three times higher in maturing heavy rail regions, more mixed uses and less parking, whereas Atlanta's and more than twice as much in growing regions with light TODs include primarily office space surrounded by large rail. (The data from New York/New Jersey produced unusual parking lots. Table 1.2. Transit trends for journey to work trips for selected TODs. % Transit Transit Transit Transit Change Share Share Share Share 1970- Region 1970 (%) 1980 (%) 1990 (%) 2000 (%) 2000 (%) Older and Redeveloping Regions Chicago TOD Average (n=8) 24.0 21.7 18.7 16.7 -30.0 Chicago MSA Average 22.1 16.6 13.7 11.5 -48.0 NY/NJ TOD Average (n=26) 15.7 13.1 13.6 16.4 4.0 NY/NJ MSA Average 35.5 26.7 25.4 24.9 -30.0 TOD Average 19.8 17.4 16.1 16.5 -17.0 MSA Average 28.8 21.6 19.5 18.2 -37.0 Maturing - Heavy Rail Regions Atlanta TOD Average (n=4) 20.9 22.5 24.9 19.3 -8.0 Atlanta MSA Average 9.2 7.7 4.6 3.7 -60.0 Miami TOD Average (n=2) 0.5 2.7 5.4 6.5 1094.0 Miami MSA Average 7.1 5.0 4.4 3.9 -45.0 San Francisco TOD Average (n=18) 17.8 22.3 20.1 21.0 18.0 San Francicsco MSA Average 11.6 11.4 9.6 9.5 -18.0 Washington DC TOD Average (n=16) 19.0 27.4 32.5 30.0 58.0 Washington DC MSA Average 15.4 13.1 11.3 9.4 -39.0 TOD Average 14.6 18.8 20.7 19.2 32.0 MSA Average 10.8 9.3 7.5 6.6 -39.0 New Start - Light Rail Regions Portland TOD Average (n=5) 9.2 13.4 11.8 14.6 58.0 Portland MSA Average 5.5 7.6 5.0 5.7 3.0 San Diego TOD Average (n=6) 8.3 11.2 6.5 6.7 -19.0 San Diego MSA Average 3.7 3.4 3.5 3.4 -7.0 Los Angeles TOD Average (n=6) 6.2 11.5 10.2 8.4 37.0 Los Angeles MSA Average 4.2 5.2 4.7 4.7 11.0 Dallas TOD Average (n=6) 14.5 9.1 9.2 3.2 -78.0 Dallas MSA Average 5.2 3.5 2.3 1.8 -66.0 Denver TOD Average (n=2) 9.4 8.6 8.4 7.5 -20.0 Denver MSA Average 4.3 6.0 4.2 4.3 0.0 Salt Lake City TOD Average (n=4) 2.4 5.8 3.2 5.0 108.0 Salt Lake City MSA Average 2.2 5.0 3.1 3.0 36.0 TOD Average 8.3 9.9 8.2 7.6 -9.0 MSA Average 4.2 5.1 3.8 3.8 -9.0 Total TOD Average (n=103) 15.1 17.0 16.9 16.7 11.0 Total MSA Average (n=12) 19.0 14.1 12.0 7.1 -63.0 Source: Renne, 2005
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10 · Portland also has experienced high growth in transit use, · Although walking and biking to work has declined nation- very likely due to aggressive policies to promote transit use ally, the decline has been less pronounced in TODs. and TOD. · The same cities that had the largest increases in transit · Transit ridership growth also was realized in the TODs of ridership (Miami, San Francisco, Washington, D.C., and Miami, San Francisco, Los Angeles, and Salt Lake City. Portland) also had the lowest declines in walking and · In San Diego, Dallas, and Denver, the rate of decline in cycling to work. transit use for TODs was greater than for the region, although transit use remains about twice as high. Since High-transit commute modal shares among station-area these TODs were not built until the late 1990s or after residents are significantly a product of self-selection: those 2000, more time may be needed to fully evaluate the long with a lifestyle preference to ride transit consciously move term trend. to neighborhoods well-served by transit and act upon their preferences by riding frequently. A recent study by Cervero Renne also compiled national work trip information for and Duncan (2002) used nested logit analysis to predict tran- walk and bike trips as shown in Table 1.3. Key observations sit ridership as a function of residential location choice in the regarding these modes include: San Francisco Bay Area. Around 40% of the rail commute choice was explained by residential location. · TODs have about 3.5 times more walking and cycling than Understanding how TOD residents and employees pre- MSAs (11.2% in TODs versus 3.2% in regions). viously traveled is important in sorting out the relative Table 1.3. Walk/bike trends for journey to work trips for selected TODs. % Walk Walk/Bike Change Share Walk/Bike Share Walk/Bike 1970- Region 1970 (%) Share 1980 (%) 1990 (%) Share 2000 (%) 2000 (%) Older and Redeveloping Regions Chicago TOD Average (n=8) 13.6 14.1 9.8 8.9 -34.0 Chicago MSA Average 9.6 7.9 5.7 3.4 -64.0 NY/NJ TOD Average (n=26) 16.9 14.3 8.6 8.2 -51.0 NY/NJ MSA Average 10.0 10.2 7.3 5.8 -42.0 TOD Average 15.2 14.2 9.2 8.6 -44.0 MSA Average 9.8 9.0 6.5 4.6 -53.0 Maturing - Heavy Rail Regions Atlanta TOD Average (n=4) 13.1 16.1 7.9 7.4 -43.0 Atlanta MSA Average 4.4 3.2 3.1 1.4 -68.0 Miami TOD Average (n=2) 3.3 3.6 3.0 2.8 -15.0 Miami MSA Average 7.3 5.5 4.1 2.2 -70.0 San Francisco TOD Average (n=18) 19.8 19.1 14.9 16.1 -19.0 San Francicsco MSA Average 8.6 9.1 6.4 4.4 -49.0 Washington DC TOD Average (n=16) 17.3 18.3 14.9 14.2 -18.0 Washington DC MSA Average 8.4 7.0 5.4 3.2 -62.0 TOD Average 13.4 14.3 10.2 10.1 -24.0 MSA Average 7.2 6.2 4.8 2.8 -61.0 New Start - Light Rail Regions Portland TOD Average (n=5) 23.2 23.4 19.5 20.4 -12.0 Portland MSA Average 7.8 7.4 5.4 3.7 -52.0 San Diego TOD Average (n=6) 13.2 22.6 9.4 7.7 -42.0 San Diego MSA Average 9.5 9.1 6.1 4.0 -58.0 Los Angeles TOD Average (n=6) 15.2 13.5 10.7 9.5 -37.0 Los Angeles MSA Average 7.7 7.6 5.1 3.2 -58.0 Dallas TOD Average (n=6) 31.9 9.4 26.1 11.2 -65.0 Dallas MSA Average 5.8 3.4 3.2 1.6 -72.0 Denver TOD Average (n=2) 13.4 6.3 7.9 5.5 -59.0 Denver MSA Average 7.8 6.4 4.9 3.1 -60.0 Salt Lake City TOD Average (n=4) 12.9 8.0 6.9 7.1 -45.0 Salt Lake City MSA Average 6.5 5.7 4.5 2.3 -65.0 TOD Average 18.3 13.9 13.4 10.2 -44.0 MSA Average 7.5 6.6 4.8 3.0 -60.0 Total TOD Average (n=103) 17.4 15.8 12.3 11.2 -36.0 Total MSA Average (n=12) 7.8 6.9 5.1 3.2 -59.0 Source: Renne, 2005
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11 importance of self-selection. If most TOD residents patronized · 31% claim to walk a little more now; and transit prior to their move, then net ridership benefits are · 16% claim to walk a lot more now (total of 47% claim to somewhat reduced. Two California research projects throw walk more now). some light on this question. The 1992 study of ridership of people living near California rail stops examined how they The 2003 California survey of transit usage found a clear travel to work at their prior residence (Cervero, 1994). For pattern of changes in travel behavior before and after mov- those whose job location did not change, surveys showed that ing to a TOD. Among all residents surveyed, around 12% 56% of station-area residents rode transit to work at the pre- shifted from some form of automobile travel to transit for vious residence. Thus, TOD residency did not yield regional their main trip purposes; however, around 10% shifted from mobility benefits in the case of nearly half of the sample. taking transit to auto travel after moving to a TOD, and 56% However, impacts were not inconsequential. Among those drove as much as when they lived away from a TOD. The who drove to work when they previously lived away from change to car commuting was thought to reflect the trend transit, 52% switched to transit commuting after moving toward suburban employment in automobile-oriented within a half mile walking distance of a rail station. settings. Similar findings have been observed in Portland, Oregon. The 2003 California study also provides longitudinal in- At the Center Commons, an urban neighborhood TOD, about sights into ridership trends among TOD projects. Overall, no 56% of survey respondents currently use an alternate mode evidence was found that transit modal shares changed as TOD of transportation (i.e., transit, bike, walk, carpool) to get to housing projects matured. In the case of several surveyed hous- work; about 46% use transit. Prior to moving into the TOD, ing projects near BART's Hayward and Union City stations, about 44% used an alternate mode for work trips, and 31% the shares of commutes by transit were in the 26% to 28% used transit. In comparison, transit work-trip mode share for range in 1992 and 2003. In a few TODs where transit's com- the city of Portland was 12.3% according to the 2000 Census. mute market shares increased over time, results could reflect (Almost 75% of Center Commons respondents had an an- filtering effects: those who use rail transit may stay in place nual household income of $25,000 or less. About 78% of and maintain longer residences while those not using transit work trips on transit and 84% of nonwork trips on transit are may be more likely to leave. by residents who make $25,000 or less per year.) For nonwork In comparison to mode share, not much information trips, 55% currently use an alternate mode of transportation, about TOD trip generation rates has been captured. Because and 32% use transit. Previously, 42% used an alternate mode many TODs have grid-based street networks, there are more for nonwork trips, and 20% used transit (Switzer, 2002). project access points than in conventional suburban proj- At Orenco Station, a more affluent suburban neighborhood ects, which tends to increase the cost and complexity of TOD, 18% of TOD commuters regularly use transit, 75% travel trip generation studies (because more locations must be in single occupancy cars, and 2.7% carpool, bike, or walk monitored). Lee (2004) reviewed and compiled TOD trip (Podobnik, 2002). Sixty-nine percent of survey respondents generation data from four locations, and this data is shown indicated that they use transit more often than in their pre- in Table 1.4. From the data, it is difficult to conclude how vious neighborhood, and 25% use transit at about the same TOD trip rates compare to standard ITE trip rates, as the level. TOD rates generally fall between the two ITE apartment At The Merrick, an urban downtown TOD, 23% of resi- benchmarks. In Portland, Lapham (2001) found that the dents regularly commute to work or school by transit, 44% lower auto trip rates could only partially be explained by commute in a private vehicle, and 16% walk (Dill, 2005). higher transit use; the TODs had transit mode shares of 16% Overall in Portland, 12% commute by transit, 76% by in the morning peak period and 11% in the afternoon peak, private vehicle, and 5% walk. The mode split for all trips compared to about 5% for the city. After including transit at The Merrick is: 18% transit, 53% personal vehicle, and and pedestrian trips to analyze total trips, he still found the 29% walk. The Merrick residents also claim to drive less TOD trip rates to be lower than the ITE rates. Lapham notes and use transit and walk more compared to where they that: used to live: · Few families were observed in the TODs, so smaller house- · 45% claim to drive a lot less now; hold size may be a factor. · 23% claim to drive a little less now (total of 68% drive less · At suburban TODs, the AM peak period appeared to be now); earlier than the 7 AM to 9 AM recording period (i.e., TOD · 42% claim to use transit a lot more now; residents may travel at different times). · 28% claim to use transit a little more now (total of 70% use · Some of the larger TODs may have had more internal trips transit more now); that were not captured.