Traveler Response to Transportation System Changes Handbook, Third Edition: Chapter 16, Pedestrian and Bicycle Facilities (2012) / Chapter Skim
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Pages 227-296
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The SPARC researchers concluded that people can be encouraged to walk more through interventions targeted at individuals or households and tailored to individual needs. Evidence was found less convincing in the case of measures taken at the institutional level, whether workplace, school, or community.
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Behavioral Paradigms The active transportation choice responses to various types of factors discussed in this "Underlying Traveler Response Factors" section may be thought of as occurring within one or more unifying behavioral frameworks. NMT activity choices have aspects in common with other travel decisions, but also aspects which are unique to walking and bicycling.
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The Austin pedestrian studies are covered more extensively in the preceding "Response by Type of NMT Strategy" section under "Sidewalks and Along-Street Walking" -- "Sidewalk Coverage and Traffic Conditions." Also in the "Response by Type of NMT Strategy" section are several examples of active transportation behavior being fairly obviously influenced, at least in part, by conventional rather than derived demand theory. They are primarily found in the "Pedestrian/Bicycle Systems and Interconnections" subsection under "River Bridges and Other Linkages." A Combined Mode Choice Decision Paradigm A "Theory of Routine Mode Choice Decisions" has been proposed that encompasses elements of both derived-demand and direct-benefit-demand theory, and also draws from behavior-changeencouragement practice and includes considerations of special importance to walking and bicycling.
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Initial barriers might include safety or weather concerns. Trip barriers would include travel time, distance, and cost.
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new bike lane, for example, will likely attract more bike riders from other routes than it will attract persons to the bicycling mode from other modes such as auto or transit. This circumstance is why it is difficult to assess the impact of, say, new bike lanes on the basis of counts alone, without knowing what proportion of the new riders on a street have simply made route choice shifts as compared to prime mode choice shifts.
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An example is provided by a trip from home to school that requires passing by vacant and dilapidated buildings. This urban form factor may cause the parent to believe that the neighborhood crime rate is high, a mediating factor.
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ered five consecutive days of travel to and from kindergarten through 8th grade. It was found that 79 percent of students had asked permission to walk or bike to school, while 33 percent of parents reported allowing or planning to allow their child to do so at an elementary or middle school grade level they deemed appropriate.
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that much year-round climate impact, however, on overall annual non-motorized transportation (NMT) usage rates.
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only 8 hours of measurable rainfall in the study period.) Cloudy conditions, defined as less than 60 percent of the solar radiation average for the hour and place, were associated with 5.3 percent less walking activity.
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were lower on cloudy days than on sunny days and lowest by far on rainy days. In the AM peak period, volumes of all cyclists recorded on rainy days were 45 to 60 percent lower than on sunny days, and volumes recorded on cloudy days were 10 to 20 percent lower than on sunny days.
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perature nor precipitation showed any obvious correlation with a city's average overall bicycle-towork mode share. These studies worked with annual measures of daily temperatures and the number of days per year with measurable precipitation.
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Despite derivation of seasonal percentage distributions utilizing disparate methodological approaches, ranging from counts to self-reported survey responses to questions in a variety of formats, the eight paths and path groupings in Table 16-63 form a logical progression when listed from lowest to highest relative wintertime usage. North Central and Northeast U.S.
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Comparative sensitivities for slope, published in 2003 by Cervero and Duncan, were reviewed in NCHRP Project 08-78. Modeling of walk and bicycle mode choice using the year 2000 [San Francisco]
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to walk an extra mile and between 1/4 and 1/5 as disadvantageous as precipitation. Choice of walking was 1/25 as sensitive to darkness as to slope expressed as rise/run for the entire trip.
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sidered as opportunities. Such perspectives are as viewed from residences.
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highly transit-accessible areas made 42 percent of their commute trips by transit, as compared to 4 percent for those with neither home nor workplace in such areas (Gossen, 2006)
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counting any exterior connections) receives a score of 1.5.
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bicycling; they may also (along with major arterials) create barriers to NMT, and lack of sidewalks on busy streets may further inhibit walking.
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Motor vehicle volumes and speeds in adjacent traffic lanes were also determined to be significant variables (Landis et al., 2001)
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In developing the bicycle compatibility index, the research team used the perspectives of more than 200 persons in three cities (Olympia, Washington, Austin, Texas, and Chapel Hill, North Carolina) to subjectively evaluate the perceived bicycling "comfort level" in different roadway environments.
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Various other compatibility or level of service measures have been developed in recent decades for both pedestrians and bicycles. Elements frequently used include type of facility provided, such as mixed traffic lane vs.
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• Human Scale -- Size, details, and articulation of physical elements matching the size and proportions of people and their walking speed. • Transparency -- Ability to see or perceive what is going on or lies beyond the street edge, specifically including human activity.
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ity. The urban vitality characteristic, both in the case of work and in the case of other trip purposes, was an indicator of higher mode shares for walking, walk-transit, and also (for "other" trip purposes only)
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Handy, and Mokhtarian, 2006)
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Walk Trip Distance, Time, and Route Characteristics Utilitarian walking is done to accomplish activities requiring travel to another location, while recreational walking is done for exercise or enjoyment. The two objectives may be combined (Cao, Handy, and Mokhtarian, 2006)
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trip length to be 0.6 miles. However, the reported travel time averaged not 10 minutes, but 16.4 minutes.52 Walking is the mode of choice for nearly all trips of 1/10 of a mile or less.
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travel surveys were employed to plot "decay functions" of walking and cycling activity relative to increasing distance. A summary illustration of the walking prevalence data points and fitted exponential decay function curves for work, shopping, restaurant, and recreation trips is provided in Figure 16-8.
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Examination of the individual data plots from which Figure 16-8 is summarized shows a tendency for walk trip percentages to plateau at the shortest distance intervals rather than following the exponential decay function, a phenomenon familiar to modelers practiced in the conventional calibration of "gravity" trip distribution models. In other words, there is little empirical indication of walk trip travel choice differences at, say, 0.2 km.
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The distances pedestrians are willing to walk are influenced by the built environment. A number of studies have concluded that interesting walks seem shorter than boring walks.
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Thus different data, or at least different data compilations, are required to examine factors pertaining to choice and use of the walk mode for access to transit service. Most transit patrons will walk about 1/4 mile to bus service and farther to rail service (Replogle and Parcells, 1992)
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without an intermediate stop (Goldsmith, 1992, NHTSA and BTS, 2002)
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(actually peaking) seen for both work and shopping walk trips, with the highest prevalence at roughly a 1-1/2 km.
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than the work commute, and other data issues. Bike-on-bus access trips are longer than walk access to transit trips, as demonstrated in Table 16-35 within the "Response by Type of NMT Strategy" section, under "Pedestrian/Bicycle Linkages with Transit" -- "Bicycles on Transit Vehicles" -- "Bike-on-Bus Programs." Table 16-66 provides bicycle access and egress trip length distributions for three Florida bike-on-bus operations.
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Newer GPS-and-network-based research in Portland, Oregon, shows slightly more willingness to divert from minimum-distance routings, possibly because the sample was designed to give roughly equal representation to women and to include as many less-frequent cyclists as possible.56 In this study only one-half of the GPS-tracked utilitarian trips were less than 10 percent longer than the shortest possible routing. Almost 5 percent were over 50 percent longer (Broach, Gliebe, and Dill, 2009b)
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From Table 16-67 it may be concluded that aversion to bicycling on arterials with moderate to heavy vehicular traffic and no bicycle lanes applies regardless of gender or bicycling frequency (used here as a surrogate for skill level)
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erate preference for bicycle lanes among most categories, with the preference among women being weak, and with a very slight aversion to bicycle lanes indicated for infrequent cyclists. Additional details on this study, along with alternative analytical perspectives on the route choice findings, are found in the "Response by Type of NMT Strategy" section (see "Bicycle Lanes and Routes" -- "Popularity, Preferences, and Route Choice" -- "GPS- and Network-Based Research")
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In addition to travel time, most multimodal travel models assign major importance to motorized trip direct user costs, especially tolls, parking charges, and transit fares. For short suburban trips, however, there are generally no tolls or parking charges that bear on auto use.
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able distance. Commuters are particularly concerned with distance and need to minimize travel time.
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• Safety from traffic dangers and crime -- weak factor for utilitarian trips, but a strong influence on choice to walk or bike for exercise. • Sidewalks, paths, and bike lanes -- weak influence on both utilitarian and recreation/exercise active travel decisions.
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The lowest mode share in Table 16-69 is the 0.3 percent bicycle share for shopping and services trips. The impediment to bicycling of the need to carry goods pertains most directly in this case.
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• Of bicycle trips, 1-in-4 (or less) are non-discretionary utilitarian, 1-in-4 (or more)
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0.5 miles and 11.2 minutes for various types of personal business trips, and 0.8 miles and approximately 20 minutes for a social, recreational, and exercise trip category (Kuzmyak et al., 2011)
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those factors of highest priority according to the number of times they were selected. The two modes of questioning produced different prioritizations, but distance from home to school topped the list for both approaches (Zhou et al., 2009)
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section, the differences among pedestrians and bicyclists across several demographic characteristics are presented from a global perspective and discussed in terms of effects on NMT choice. Characteristics examined include gender, age, income, automobile ownership, education, and ethnicity.
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activity per resident of the "urban" neighborhoods. Walkers likely to represent "involuntary" pedestrians were markedly over-represented in the suburban neighborhoods and were forced to contend with the deficient infrastructure.
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can be inferred from these mode shares. A Centers for Disease Control and Prevention (CDC)
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Age Adult walking and especially bicycling become less prevalent with age in most but not all countries. This trend is especially pronounced in the United States.
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NMT mode share data and walking and bicycling activity data exhibit trends that are similar but not identical to each other. Table 16-74 presents 2001 NMT-related mode share data for five age groups.
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As this information and Tables 16-72, 16-73, and 16-74 suggest, there are many child pedestrians and bicyclists. The NHTS, with its enhanced methodology for drawing out information on walk trips, found children from ages 5 through 15 to be taking 28 percent of all walk trips and 58 percent of all bicycle trips in 2001.
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The Table 16-75 data cover all 2009 U.S. NMT travel.
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the less than $20,000 category to 16 percent in the $100,000 and over category. Walking results are similar, though with higher percentages, starting with 67 percent in the less than $20,000 category and then ranging from 65 percent in the $20,000 to $39,999 category up to 72 percent in the $100,000 and over category (Kuzmyak et al., 2011)
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incomes increase from under $15,000 to $30,000 dollars. From that threshold on, persons with more income are roughly 40 percent less likely to make utilitarian walk trips than persons with less than $15,000 in family income.
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zero and one car households, compared to lesser differences among vehicle ownership levels once household auto availability is established, appears to serve as a measure of necessity of walking, cycling, or walking to access transit (Pucher and Renne, 2003)
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19 percent more time walking per walk-transit trip (Agrawal and Schimek, 2007)
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In contrast, bivariate analysis suggests that as education level increases, the likelihood decreases of walking 30 minutes or more a day in connection with using public transit. The estimated likelihood was half for graduate degree holders when compared to those without a high school diploma.
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Hispanic blacks, 22 percent; non-Hispanic other, 25 percent; Hispanic, 29 percent)
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than a high school education showed little sensitivity. Physical inactivity was defined as no reported physical activity or exercise, which would include walking, within the previous month (Centers for Disease Control and Prevention, 1999)
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found women to report a significantly lower "comfort score" than men for all types of road/bicycle facilities except quiet streets, which scored highest and essentially the same for both sexes. As male and female comfort levels decreased across facility types, the percentage by which women were less comfortable than men increased until stabilizing at −17 percent.
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initiatives such as the Safe Routes to School programs. Bicycle security can be addressed through parking security provisions.
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utilizing U.S. Census 2000 Supplemental Survey travel data, did not incorporate the percentage of college students within the population into the final research models.
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Attitudes and Modal Biases Effects of attitudes and modal biases on travel choices are subject to much debate. To whatever extent they exist, they are related.
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to use to make trips of various purposes and also which mode they actually used. For commuting, 72 percent of the people preferred using an automobile, but 75 percent actually did.
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underlying mobility choices such as residential location, employment location, and vehicle ownership. The characteristics of the neighborhood chosen will in turn help define the attractiveness of alternative travel options and thereby influence short-term travel choices (Cao, Mokhtarian, and Handy, 2009, Federal Highway Administration, 1974)
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16-291 Table 16-82 Summary of Findings about NMT Effects of Residential Self-Selection (SS) Relative to Direct Impacts of the Built Environment (BE)
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16-292 Table 16-82 (Continued) Study Process Key Findings 10.
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Most of the studies listed in Tables 16-82 and 16-83 employed some form of cross-sectional analysis as the investigative technique. Three, however, had the advantage of data on travel behavior before and after residence relocation.
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Five studies have been encountered that undertook to put numbers on the proportions of built environment effects on travel behavior versus self-selection or attitudes. Table 16-84 consolidates the quantitative findings.
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Neighborhood Preference Matches and Mismatches Two research efforts included in Table 16-82 looked beyond self-selection concerns, probing what the net effects are -- with and/or without self-selection -- of different types of built environments. A San Francisco Bay Area series of studies (the 6th entry in Table 16-82 and covered further in Chapter 17, "Transit Oriented Development," as noted)
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did so. In the context of overall average driving of 33 VMT per day per individual, the low versus high walkability neighborhood VMT differential was 17 fewer miles driven for residents of highly walkable neighborhoods who were not seeking walkability and 11 miles less for residents of highly walkable neighborhoods strongly preferring high walkability (Frank et al., 2007)
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