Click for next page ( 74


The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 73
and the provision of the passes using these figures, the passes were deemed responsible for at least some of the enthusiasm (Boroski et al., 2002). The Merrick Apartments TOD in Portland has the close equivalent of a free transit pass program. It is located within Portland's "Fareless Square," offering free LRT and other transit service throughout the city's extended downtown area. Surveys conducted in 2005 offer more statistics than those available for any TOD Pass Program. Of Merrick residents, 71 percent reported using transit more often than in their prior location, compared to 63 percent for all 6 TOD groupings (assembled from 8 surveyed sites) that were analyzed for this parameter, and the next-to-highest percentage among them. In terms of mode shifts upon moving to The Merrick, 26 percent shifted from non-transit to transit use for the commute trip and 74 percent continued commuting via non-transit, both higher percentages than any other neighborhood. None of the 54 respondents to this question switched from transit to non- transit. The percentage of Merrick residents "taking transit to non-commute destinations once a week or more in good weather," which ranged from about 12 to 26 percent depending on non-work trip purpose, approached twice the percentages for the best of the other 6 TOD groupings. Some 81 percent indicated that good public transit service was a major consideration in looking for their current residence location (it was the third-most-important of 34 factors suggested), compared to 76 percent average for all studied neighborhoods. This was the next-to-highest percentage for this indicator (Dill, 2006b). Although almost all of these results indicate The Merrick to be the best or next-best transit-use enhancing performer among the 6 Portland TOD groupings, this relative placement is not unex- pected given The Merrick's closest-in location. In view of this circumstance, no clear-cut evidence of free transit effects stands out, except perhaps in the exceptional degree of non-commute transit use. The Seattle-area examples of TOD-focused pass programs likewise do not offer incontrovert- ible evidence. (These were covered under "Response by TOD Dimension and Strategy"-- "Response to TOD by Primary Transit Mode"--"Traditional Bus"--"King County, Washington.") It is a reasonable but primarily anecdotally-supported speculation that offering TOD-based pass programs as part of purchase or rent programs may be a useful device for attracting low-auto- ownership, transit-using residents to TODs located on less-intensive transit services such as the conventional albeit focused express and local bus services providing the anchors for the King County TOD examples. Self-Selection of Residents Surveys of residents of rail station areas almost always reveal higher transit mode shares than are seen for residents outside rail station areas. Some investigators have questioned whether this phe- nomenon results from TOD successfully attracting new riders to transit or is a reflection of the type of people who choose to live in TOD. If the latter is the case, observed ridership or walking impacts may come about simply because "transit-oriented residents" live in TOD and collectively produce notable amounts of transit riding and pedestrian activity. This posited process has been labeled "self-selection." Resolution of this issue is seen by researchers as being important in assessing potential regional transportation impacts of introducing TOD. As a hypothetical example, if the high transit ridership associated with TOD is solely the result of moving existing transit riders close to the station, and their degree of transit use does not change, then there would be no 17-73

OCR for page 73
regional net transit ridership increase associated with TOD. Some of the more thought-provoking findings, discussed under "Self-Selection Effects on TOD Regional Travel Impacts" (the fourth sub- section below), may be interpreted to suggest that TOD resident self-selection could actually be a positive force in reducing regional auto travel and enhancing transit ridership.18 First, various related residential location choice findings are examined. Transit Access and Neighborhood Selection The 2003 California TOD travel characteristics study asked all respondents to mark the top three factors considered when moving to the current station-area residence. The top six responses for all respondents were, in rank order: "Type or Quality of Housing" (20 percent), "Cost of Housing" (18 percent), "Access to Transit" (15 percent), "Quality of Neighborhood" (15 percent), "Access to Shops, Services" (12 percent) and "Access to Highway" (10 percent). Among respondents who indicated transit access was among the top three factors, transit use was found to be much greater. About 50 percent of such respondents indicated use of transit for the surveyed trips as compared to 5 percent of other respondents (Lund, Cervero, and Willson, 2004a). A study of more than 1,000 station-area and non-station-area households in San Diego and the San Francisco Bay Area found the top reasons for selecting the present residence location to include concerns related to transportation accessibility as well as factors such as crime rate and neighbor- hood aesthetics. Among residents indicating that transit access was an important factor (32 per- cent of the sample), 74 percent selected a residence within 1/2 mile of a rail station. However, 63 percent of the total station-area residents sampled did not have transit access as a concern when choosing a residential location. Based on this and other analyses, it was concluded that transit modal preference played a relatively limited role in determining residential location choice (Chatman, 2005). An evaluation of the New Jersey Transit Village Initiative surveyed residents at three rail stations, both within and outside the "transit village" radius of 1/2 mile. Transit was cited as of major importance to residence location choice among village residents in greater proportions than it was among non-village residents. In addition, transit village residents owned fewer vehicles on aver- age than residents outside the transit village area and reported more frequent use of transit. Table 17-33 summarizes the travel characteristics found (Renne and Wells, 2003). 18 Chapter 15, "Land Use and Site Design," and Chapter 16, "Pedestrian and Bicycle Facilities," also address the subject of self-selection. Chapter 15 offers additional perspectives and anticipates findings presented here in Chapter 17, but without benefit of the post-2002 travel behavior research. In Chapter 15, see "Underlying Traveler Response Factors"--"Attitudes and Predispositions." Chapter 16, the last-published of the three "Land Use and Non-Motorized Travel" chapters, presents more from this fast-evolving area of research, primarily with a broader walkable-environments focus than TOD-only. There see "Response by Type of Strategy"--"Response to Pedestrian/Bicycle-Friendly Neighborhoods" as well as that chapter's "Underlying Traveler Response Factors" section. 17-74

OCR for page 73
Table 17-33 Travel Characteristics of New Jersey Transit Village Residents Versus Non-Transit Village Residents Attribute / Station Service Area Transit Village Area Outside Transit Village Transit of Major Importance When Choosing Home Location Metuchen 45% 35% South Amboy 20% 5% South Orange 50% 35% Average Vehicles per Household Metuchen 1.92 2.12 South Amboy 1.81 2.16 South Orange 1.67 2.10 Use Transit 10 or More Times Per Month Metuchen 30% 20% South Amboy 10% 5% South Orange 35% 25% Note: Percentages have been estimated to nearest 5% from source graphics. Source: Renne and Wells (2003). A study using data from the 2000 San Francisco Bay Area Travel Survey explored the subject of self-selection of TOD residents and concluded that residential location choice and commute mode choice are jointly related decisions and that about 40 percent of the rail-commute decision is accounted for by self-selection. A nested-logit model was estimated to look at the influences in the simultaneous decisions of whether to live near rail transit and whether to use rail transit to get to work. It appeared that: Choice of living in a rail station area is strongly influenced by having a workplace within 1 mile of a rail station, having good job accessibility via both highway and transit (measured as the number of jobs within 45 minutes by car and 30 minutes by transit), and being a lower-income household (less than $40,000 per year).19 Rail mode choice is most strongly influenced by the number of household automobiles, the ratio of transit network time to highway network time to work, the neighborhood density, and the closeness of the workplace to a rail station. With regard to workplace closeness, location within 1/4 mile showed up as being better than loca- tion within 1/2 mile which was, in turn, better than within 1 mile (Cervero and Duncan, 2002). 19 The apparent importance of lower income is potentially a reflection of a regional public policy requiring below-market-rate housing as a component of redevelopment around rail stations. 17-75

OCR for page 73
Neighborhood Choice Filtering Effects over Time In the 2003 California TOD travel characteristics study, newer residents were somewhat less likely to report transit access as a top factor for choosing the station-area residence (14 percent of 3-or- fewer-year residents) than longer-term residents (21 percent of 8-or-more-year residents). Perhaps more importantly, evidence of long-term filtering effects was found when analyzing mode choice by length of residency. Results of the relevant mode choice analysis are presented in Table 17-34. Note that the longest-term residents reported roughly twice the transit use of the newest residents. This differential response may reflect more familiarity with the transit options on the part of longer-term residents, changes in workplace location over time to take advantage of the transit options, and possibly a filtering effect whereby residents taking advantage of the transit options stay in the development while others move on. Sample sizes allowed comparison for only one specific residential site between mode shares obtained in the 2003 study and those obtained in the 1992 California transit-focused development study. At the Verandas Apartments in Union City on BART, "main" trip transit mode shares increased from 27 to 42 percent, while auto shares decreased from 69 to 54 percent and walk/bike trips held constant at 4 percent. This outcome was in the context of an increase in average household size from 1.54 to 1.71 persons and a decrease in auto ownership from 1.22 to 1.06 per household. Overall comparisons between the 2003 and 1992 studies did not, however, conclusively show that the TOD resident transit mode shares increased over the 11-year period. The small increases measured were not large enough to exhibit statistical significance (Lund, Cervero, and Willson, 2004a). The data in Table 17-34 illustrate (with respect to modes other than transit) that the 2003 California study's length of residency analysis found a lesser tendency to walk, bike, and carpool among longer-term residents. Single occupant driving shows no clear trend, while the small sample of res- idents with over a decade of residency exhibits the lowest share of single- and multi-occupant private-vehicle trips. 17-76

OCR for page 73
Table 17-34 Mode Choice by Length of Station-Area Residency Date Moved In (Approximate Length of Residency) 1993 to 1997 1998 to 2002 Percentage of trips made by 1992 or earlier (about 6-10 (about 1-5 2003 (less than the following modes: (over 10 years) years) years) 6 months) Main Trips a Single-occupancy vehicle 62.5% 66.7% 65.4% 62.2% Carpool 4.2 3.5 13.2 16.5 Rail transit 29.2 24.8 16.7 15.7 Bus transit 4.2 2.8 2.2 1.3 Walk or bike 0.0 2.1 2.3 4.3 Other 0.0 0.0 0.2 0.0 Number of trips 24 141 953 230 Commute Trips Single-occupancy vehicle 45.5% 61.4% 68.6% 63.6% Carpool 0.0 1.2 5.3 7.7 Rail transit 45.5 36.1 22.5 23.8 Bus transit 9.1 1.2 1.9 2.1 Walk or bike 0.0 2.1 1.7 2.8 Other 0.0 0.0 0.0 0.0 Number of trips 11 83 627 143 Note: a The survey instrument asked for travel information for three "main" trips on the survey day. Main trips could be for work or non-work purposes, thus most commute trips are probably already included within the "main" trips category. Source: Lund, Cervero, and Willson (2004a). At least one researcher has cautioned that the body of evidence concerning TOD transit use trends over time is not strong and does not necessarily support anticipation of long-term net increases resulting from TOD maturation. Pointed to are "new-start" LRT service examples with little evidence, over a two-decade span, of system ridership increases that are traceable to factors such as system maturity or transit-friendly synergies (Hendricks, 2005). LRT system maturity effects are examined in Chapter 7, "Light Rail Transit," within that chapter's "Related Information and Impacts" section. Prior Transit Usage and Neighborhood Selection It has been noted that people who move to transit-based housing and use the local transit station often utilized public transit before moving to the project. Some investigators have suggested this as evidence that "transit-oriented residents" choose to move into TOD. Tables 17-39 and 17-40 in the "Related Information and Impacts"--"Pre- and Post- TOD Travel Modes" subsection present the then-current commute mode choice of rail-based TOD residents, as obtained from the 1992 California transit-focused development study, cross-tabulated 17-77

OCR for page 73
with the prior choice. Only residents who did not change workplace upon moving into station-area housing were included. Data that are similar, except for covering all survey respondents answering the question, are available for Portland, Oregon. Those data are from 2005 surveys of residents at 8 LRT-based sites including TODs and some other adjoining station-area housing, and are presented in Table 17-41 of the "Pre- and Post-TOD Travel Modes" subsection. Among the findings, 56 percent of 1992 California station-area resident rail transit commuters and 65 percent of 1992 bus transit commuters were previously either rail or bus transit commuters. This finding may be reflective of respondents' workplace location situations, for example, continuing to work in the same transit-accessible place, as much as it is of any residence location effects. In Portland, only 24 percent of surveyed station-area public transit commuters were previously tran- sit commuters (Cervero, 1993; Dill, 2006b). More information on prior versus current mode shares is presented in the "Pre- and Post-TOD Travel Modes" subsection referred to above. Self-Selection Effects on TOD Regional Travel Impacts Much of the available discussion of possible self-selection effects presumes that to the extent the postulated phenomenon exists it may defeat the ability of TOD to significantly affect regional mode shares--self-selected TOD residents would, according to this view, use transit wherever they live.20 However, research on the travel behavior of "urban oriented" and "suburban oriented" per- sons suggests that the built environment constrains a person's underlying preferences, and that the effects are asymmetrical. Urban-oriented residents who find themselves in the suburbs have been observed to be less able to live out their preference for non-auto travel than are suburban- oriented residents able to realize their preferences for auto travel in highly urbanized surround- ings (Cao, Handy, and Mokhtarian, 2006). From this determination it follows that matching persons with a preference for non-auto travel to highly urbanized areas may be the more effective strategy for reducing auto trips--more effective than efforts to attract persons to such areas who are viscerally wedded to their autos (Schwanen and Mokhtarian, 2005a). If this is the case, TOD resident self-selection becomes a positive force in reducing regional auto travel, and in enhancing public transit use and walking, and not a phenomenon to be troubled by. Indeed, it could be an opportunity deserving of leveraged TOD marketing to attract those desirous of walk and transit options. 20 The short-hand "self-selection" labeling is really a misnomer when used to describe the postulated phenomenon of concern here, which covers not only residential choice, but also suppositions about pre- and post-TOD residency-choice travel behavior. All investigators seem to agree that there is an individual (or household) selection process when it comes to choosing residency in a TOD. The real question is how non- auto-oriented self-selecting residents traveled before they became TOD residents (or would travel if they could not live in a TOD) and how they travel once residing in a TOD. Self-selection is only harmful to achievement of private-vehicle travel reductions if people with attitudes and preferences inclined toward living in a transit-friendly and pedestrian-friendly environment make smaller shifts out of auto use and into use of transit and walking when becoming TOD residents than persons whose predispositions are "aver- age" or lean toward auto use. Note that research presented in this subsection uses the term "urban oriented" as more-or-less equating to "non-auto-oriented" and the term "suburban oriented" for persons who are more "auto-oriented." 17-78

OCR for page 73
An international effort involving researchers from the University of California, Davis and the Urban and Regional Research Center Utrecht has defined and examined "urban oriented" and "suburban oriented" people based on their attitudes, using surveys from California's Bay Area neighborhoods of North San Francisco (within the city of San Francisco), Concord, and Pleasant Hill (both within Contra Costa County). Although Concord and Pleasant Hill each have a BART HRT station and 3 bus routes, they are primarily typical suburban auto-oriented places. North San Francisco, although served directly by only surface trolleybus and conventional bus transit (21 bus routes, local and limited stop), is a compact mixed-use urban traditional neighborhood of the streetcar era (Schwanen and Mokhtarian, 2005b). It exhibits most if not all characteristics associ- ated with TOD including short walks to bus stops and high transit service frequencies. The research has focused on individuals attitudinally matched and mismatched with their neigh- borhood type. Urban versus suburban orientation was assessed using attitudinal survey questions, each allowing response on a five-point scale, included within a 14-page questionnaire mailed to 4,000 urban residents (North San Francisco) and 4,000 suburban residents (Concord and Pleasant Hill). A survey response rate of 25 percent was achieved. Residents of North San Francisco were classified as "matched" if they exhibited urban-oriented attitudes. Likewise residents of Concord and Pleasant Hill were classified as "matched" if they reflected suburban-oriented attitudes. Suburban-oriented residents of North San Francisco and urban-oriented residents of Concord and Pleasant Hill were classified as "mismatched." The degree of dissonance (mismatching) found was on the order of one-quarter mismatched and three-quarters matched. There was more dissonance in Pleasant Hill than in Concord, but taken together, these two suburban locales had about the same degree of dissonance as urban North San Francisco (Schwanen and Mokhtarian, 2005a). Table 17-35 consolidates the study results for weekly miles traveled by mode, whatever the trip purpose, and commute mode share. These results clearly illustrate the study findings, excepting only the case of suburban walking/jogging/biking commute mode shares, where the results are based on an extremely small sample. Although commute mode share via public transit by suburban-oriented urban respondents is 25 percent higher than for suburban-oriented subur- banites, the transit commute mode share by urban-oriented urban respondents is 140 percent higher than for their mismatched urban-oriented suburban compatriots--substantially more than double. The presumed explanation is that urban-oriented residents in the suburbs, in contrast to urban-oriented urban dwellers, may find that driving is the only practical solution given long distances to potential destinations and limited public transit services. The typical suburban fabric may simply not allow maintenance of either the desired lifestyle or reasonable auto access to workplace locations (Schwanen and Mokhtarian, 2005a and b). The weekly miles results displayed in Table 17-35 bear further explanation. At play here is not only mode choice, but also trip length/distribution. The relative closeness of destinations in the urban environment means that mileage will sometimes total less even if the applicable mode shares are higher. Thus higher public transit mode shares for urban dwellers are not accompanied by higher numbers of weekly miles via transit. This would not necessarily be the case, and certainly not to this degree, in a comparison involving suburban TOD instead of the TOD-like North San Francisco urban traditional neighborhood examined here. Aided by shorter trip lengths, operating in conjunction with higher transit and non-motorized shares, urban-oriented residents of North San Francisco produce 46 percent less highway vehicle-miles of travel (VMT) per week than the urban-oriented suburbanites. Even the 17-79

OCR for page 73
suburban-oriented urban dwellers produce 38 percent less highway VMT than their suburban dwelling counterparts. Table 17-35 Weekly Distance Traveled by Mode, and Commute Mode Share, by Nature of Neighborhood Consonance/Dissonance Neighborhood and Attitudinal Personal Vehicle Public Transit Walk/Jog/Bike Orientation Weekly Work Weekly Work Weekly Work (Consonance/Dissonance) Miles Share Miles Share Miles Share North San Francisco--urban Urban oriented (matched) 115 66.5% 21.0 28.5% 12.1 5.1% Suburban oriented (mismatched) 135 83.0% 11.9 13.8% 10.4 3.1% Pleasant Hill/Concord--suburban Urban oriented (mismatched) 215 88.1% 29.2 11.9% 7.6 nil Suburban oriented (matched) 217 88.6% 22.5 11.0% 7.2 0.4% Notes: "Public Transit" in this consolidated presentation includes bus, BART HRT, passenger ferry, light rail, etc. "Consonance/Dissonance" is based on the most straightforward of five alternative measures of neighborhood dissonance (the researchers' measure MM1), a binary indicator. "Weekly Miles" is distance traveled in the course of making short-distance trips (less than 100 miles one-way) for any purpose. "Weekly Miles" and "Work Share" (commute mode share) are both based on a sample subset, 1,358 respondents in total, identified as workers commuting at least once a month. Sources: Derived from Schwanen and Mokhtarian (2005a and 2005b). The comparisons provided above are based on descriptive analysis, not on the modeling also undertaken by the researchers, so the possibility that socioeconomic factors have influenced the results must be considered. Income is, however, reasonably consistent across the neighborhoods. Household income reported by North San Francisco respondents is 7 percent less than in Pleasant Hill, but virtually identical to that reported for Concord, while income per North San Francisco worker is about the same as in Pleasant Hill and higher than in Concord. Two household differ- ences between urban North San Francisco and suburban Pleasant Hill and Concord do stand out. North San Francisco has 0.8 vehicles per licensed driver as compared to 1.1 in each suburb, and 32 percent of North San Francisco households are singles versus 20 percent in Pleasant Hill and 12 percent in Concord (Schwanen and Mokhtarian, 2003). Given the approximate income equality, the auto ownership differential may well be a matter of choice for the urban dwellers, reflecting less need for a car in the urban neighborhood. The higher occurrence of singles in the urban neigh- borhood is fairly consistent with the tendency of many TODs to attract large proportions of younger people, as described under "Related Information and Impacts"--"Household Characteristics." A probably more significant limitation, pending further research, is that the comparisons provided pertain most directly to TOD in the Central City relative to non-TOD in the suburbs. Equivalent research comparing matched and mismatched resident behavior in suburban TOD 17-80