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Estimating Bicycling and Walking for Planning and Project Development: A Guidebook (2014)

Chapter:Chapter 3 - Factors Affecting Walking and Biking

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Suggested Citation:"Chapter 3 - Factors Affecting Walking and Biking." National Academies of Sciences, Engineering, and Medicine. 2014. Estimating Bicycling and Walking for Planning and Project Development: A Guidebook. Washington, DC: The National Academies Press. doi: 10.17226/22330.
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Suggested Citation:"Chapter 3 - Factors Affecting Walking and Biking." National Academies of Sciences, Engineering, and Medicine. 2014. Estimating Bicycling and Walking for Planning and Project Development: A Guidebook. Washington, DC: The National Academies Press. doi: 10.17226/22330.
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Suggested Citation:"Chapter 3 - Factors Affecting Walking and Biking." National Academies of Sciences, Engineering, and Medicine. 2014. Estimating Bicycling and Walking for Planning and Project Development: A Guidebook. Washington, DC: The National Academies Press. doi: 10.17226/22330.
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Suggested Citation:"Chapter 3 - Factors Affecting Walking and Biking." National Academies of Sciences, Engineering, and Medicine. 2014. Estimating Bicycling and Walking for Planning and Project Development: A Guidebook. Washington, DC: The National Academies Press. doi: 10.17226/22330.
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Suggested Citation:"Chapter 3 - Factors Affecting Walking and Biking." National Academies of Sciences, Engineering, and Medicine. 2014. Estimating Bicycling and Walking for Planning and Project Development: A Guidebook. Washington, DC: The National Academies Press. doi: 10.17226/22330.
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Suggested Citation:"Chapter 3 - Factors Affecting Walking and Biking." National Academies of Sciences, Engineering, and Medicine. 2014. Estimating Bicycling and Walking for Planning and Project Development: A Guidebook. Washington, DC: The National Academies Press. doi: 10.17226/22330.
Page 27
Suggested Citation:"Chapter 3 - Factors Affecting Walking and Biking." National Academies of Sciences, Engineering, and Medicine. 2014. Estimating Bicycling and Walking for Planning and Project Development: A Guidebook. Washington, DC: The National Academies Press. doi: 10.17226/22330.
Page 28
Suggested Citation:"Chapter 3 - Factors Affecting Walking and Biking." National Academies of Sciences, Engineering, and Medicine. 2014. Estimating Bicycling and Walking for Planning and Project Development: A Guidebook. Washington, DC: The National Academies Press. doi: 10.17226/22330.
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Suggested Citation:"Chapter 3 - Factors Affecting Walking and Biking." National Academies of Sciences, Engineering, and Medicine. 2014. Estimating Bicycling and Walking for Planning and Project Development: A Guidebook. Washington, DC: The National Academies Press. doi: 10.17226/22330.

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21 3.1 Overview Chapter 2 provided an overview of the current status of walking and bicycling in the United States: who walks and bikes, how frequently, how far, and for what purposes. This chapter provides insights on the many factors found to influ- ence walking and bicycling behavior, from the choice of mode itself to the decision of whether to travel, where to travel and what route to take. These factors include • Land use and the built environment • Number, type, coverage and connectivity of facilities • Natural environment (topography, climate/weather) • Sociodemographic factors • Perceptions and attitudes Walking and biking are much more context-sensitive than motorized travel modes, particularly auto, so factors such as these can have an important impact on the travel decision. People considering making a trip by auto probably give little thought to whether they will have to travel uphill, if it is rain- ing or the temperature is uncomfortably hot or cold, whether it is day or night, or if they have to cross a major street or high- way. In contrast, because walking and bicycling involve physi- cal effort and exposure, these factors matter—particularly for travelers whose decision to walk or bike may be at the margin. Although these contextual factors matter, not all factors carry the same weight in the travel decision, and the impor- tance will vary from person to person and with the trip pur- pose being served. For example, if a person is walking or biking for fun or exercise, the presence of a sidewalk or dedi- cated bike path, or even weather or topography, may not be of central importance. On the other hand, if the trip has a utilitar- ian purpose—work, school, visiting a doctor—then factors like distance, convenience, and safety become more relevant to the decision to walk or bike. To further complicate matters, many of the factors carry different importance to different types of individuals. For example, young and athletic cyclists are found to have fewer reservations about riding in proximity to vehicle traffic or having to negotiate hills than cyclists who are less experienced or fit. However, the regular cyclists are also likely to be more concerned about the efficiency of their trip, in terms of directness and sustainable speed, where the infrequent rid- ers are more likely to add time or distance to their trip in order to feel comfortable. There is also the issue of whether the fac- tor is part of the primary decision of whether to walk or bike or whether it merely affects the choice of route or destination. NCHRP Project 08-78 reviewed extensive prior research efforts to identify and quantify the importance of these fac- tors, for the purpose of informing the development of new bicycle/pedestrian planning tools. The magnitude and diver- sity of these research studies precludes their unabridged inclusion in this guidebook; however, users are encouraged to consult Appendices 5 and 6 of the Contractor’s Final Report for more information. 3.2 Insights from International Experience If this guidebook has one overriding objective, it is to encour- age planners and analysts to consider the potential for walking and biking as broadly as possible. Although we argue that con- text matters with non-motorized travel, there is a tendency to use those factors as a way to gage—and even “cap”—walking or biking potentials. For example, one may associate walking with people of limited economic means, or biking with young people who enjoy exercise. Although such tendencies are seen in the data presented in Chapter 2, there is no reason to believe that the popularity of walking or biking could not be enjoyed by other sociodemographic segments, given the right circumstances. Western Europe provides challenges to stereotypes about walking and biking. Although high rates of biking and walk- ing in Asia and third-world countries may be explained by economic and technologic differences, the large differences C H A P T E R 3 Factors Affecting Walking and Biking

22 between walk and bike rates in the United States versus other modern western nations, including most of Europe and even Canada, are not as easily explained. A 2008 study motivated by negative health and obesity trends in the United States compared walking and biking rates in the United States with a large sample of western countries, with the findings sum- marized in Figure 3-1 (Basset, et al., 2008). The combined walking and biking rate in the United States of 10% contrasts strongly with rates of 26% in the United Kingdom, 22% in France, 32% in Germany, and 35% in Spain – even without considering countries like the Netherlands or Denmark, which are often regarded as having a unique culture. Issues of inclement weather and difficult topography also chal- lenge travelers in many of these areas, yet they walk and bike at consistently higher rates than in the U.S. Higher rates of transit use in most of these countries can also be attributed to urban design and facility networks that support non-motorized access to transit. Similarly, destina- tion areas served by transit are more likely to draw ridership if the areas are pedestrian or bicycle friendly. The Basset study found that, although walking is the most common leisure-time physical activity in the United States and Europe, Europeans walk much more for shopping, com- muting, school trips, and so forth. Short trips in Europe are often made by walking, but in the United States they are usu- ally made by automobile, which is used for 55% of trips that are about 0.5 km in length, 85% of trips that are 1 km in length, and 90% of trips longer than 1 km. Moreover, rates of walk- ing in European countries actually increase with age through age 65, and biking rates stay roughly steady with age, while both decline with age in the United States. The principal differences between the United States and its peers seem to be as follows: • More compact, mixed-use cities and urban areas with smaller footprints that provide high proximity and shorter trips Note * : Separate walk and bike rates were not reported for Spain; the shown rate is a combined rate. Source: Recreated from Figure 1 in Basset, Pucher, Buehler, Thompson and Crouter. "Walking, Cycling and Obesity Rates in Europe, North America and Australia." Journals of Physical Ac„vity and Health, 2008, 5, 795-814 by permission from publisher (Human Kine„cs). 9 5 7 13 16 19 24 22 16 22 23 21 23 35 22 45 30 1 1 1 2 8 3 2 4 15 9 9 4 9 0 25 5 5 2 8 11 11 6 8 9 10 8 8 8 17 11 12 5 12 32 0 10 20 30 40 50 60 70 80 Pe rc en t o f T rip s Transit Bike Walk Figure 3-1. Percentage of trips taken by walking, biking and public transit by country.

23 • Well-established, efficient transit systems coupled with pro- nounced efforts to maximize walk and bike access • Ubiquitous, high-quality, and well-connected bicycle and pedestrian networks and facilities • Pedestrian and bicycle-friendly policies to manage vehicu- lar traffic in high-demand areas • Higher costs of owning, operating, and parking a motor vehicle If the differences between the United States and its peers on these attributes were reduced, more U.S. travelers would have attractive non-driving opportunities, in which case walking and biking rates would be expected to increase accordingly. 3.3 Land Use and the Built Environment The European comparison suggests that the shape of the built environment may be fundamental in shaping walk- ing and biking behavior, and hence provide clues as to what these design characteristics are. The impact of land use and urban design on travel behavior has been heavily studied, and the research has established a strong set of statistical relationship between the so-called built environment and travel behavior. These attributes have come to be known as the “Ds” as follows: • Density: Of population or employment • Diversity: Variety of different land uses (mix) and their proportional balance (entropy) • Design: Orientation between development and people, enabling efficient pedestrian access (e.g., existence of pedes- trian facilities, frequency of safe crossings, intersection types and density, and building setbacks and curb cuts) • Distance to Transit: Nearest stop for particular services, stop density • Destinations: Access to regional opportunities, usually by transit Researchers have attempted to quantify the importance of these characteristics using regression models to help explain auto ownership, choice of mode, and VMT. Some of these research models have included walking as a mode but not bicycling, or have combined walking and biking into a single non-motorized mode, which is not particularly meaningful. Ewing and Cervero in their 2010 Meta Analysis tried to discern the impacts of the Ds on travel behavior. The research- ers reviewed more than 50 studies using Ds methods and attempted to synthesize average elasticities that reflect the level of impact of the particular variables on travel demand, including walk trips. These elasticities are derived from the coefficients estimated through regression and represent the percentage change that would be predicted in the dependent variable (number of walk trips in this case) in response to a 1% change in the particular independent variable. Table 3-1 presents estimates of demand elasticities for walking derived through this synthesis. To illustrate the meaning of the elasticities, a 1% increase in the level of residential density would be expected to lead to a 0.07 increase in the number of walking trips. Table 3-1 suggests that the factors having most impact on walking are intersection density (0.39), distance to the nearest store (0.25), jobs/housing balance (0.19), mix entropy and jobs within 1 mile (both 0.15), and distance to transit (0.14). These elastici- ties are not necessarily additive; it would be incorrect to assume that, if each of the variables listed in Table 3-1 were increased by 1%, the number of walk trips would increase by 1.39% (sum of all the elasticities). This is because (1) many of the measures are interrelated, so that changing one would also affect one or more of the others, and (2) the coefficients in the models from which the elasticities were derived depend on each other and the specification of the model. A better approach would be to apply the original equation to allow for these interactions, or to use the tour-based model spreadsheet developed as part of NCHRP Project 08-78 and presented in Chapter 5. Although transportation planners generally treat travel as occurring in the form of individual “trips,” travel is more Source: Ewing & Cervero, Meta Analysis (2010) “D” Variable Measure Elascity Density Residenal density 0.07 Employment Density 0.04 Commercial FAR 0.07 Diversity Mix entropy 0.15 Jobs/housing balance 0.19 Distance to nearest store 0.25 Design Intersecon density 0.39 Percent 4 way intersecons 0.06 Distance to nearest transit stop 0.14 Desnaon Accessibility Jobs within 1 mile 0.15 Table 3-1. Weighted average elasticities of walking in relation to built-environment factors.

24 realistically viewed as combinations of trips that constitute complete “tours,” beginning and ending at the same point. A tour that begins at home, goes to a location such as work, and then returns home without intermediate stops is known as a “simple” (home-based) tour. In contrast, tours that involve more than one stop and purpose are called “complex” tours. The difference is relevant because research shows that travelers in more compact, mixed-use environments (with high values of the Ds) are much more likely to make their trips as simple tours, apparently taking advantage of convenient proximity to venture out multiple times for various purposes. In contrast, travelers in areas without such proximity tend to group trips into multi-stop tours in order to increase efficiency. The same research also shows that trips by walking, biking and transit are much more likely to be made as simple tours, whereas com- plex tours are much more likely to be made by auto. These rela- tionships are evident in the models developed for the project in Seattle and presented in Chapters 4 (Section 4.3) and 5. Figure 3-2 summarizes how land use and built-environment factors affected non-motorized travel, first for walking and then for bicycling. These factors were identified in the earlier NCHRP Project 08-78 research and are provided in much greater detail in Appendices 5 and 6 of the Contractor’s Final Report. There has been much less research dealing with the effects of land use on bicycle demand than on walking, although sub- stantial evidence indicates that biking levels are also higher in areas that are more compact, have mixed uses, and feature well-connected non-motorized networks. The many studies of Pucher, et al. (1997, 2003, 2006, 2008a & b), which com- pare biking in the United States and Europe (as well as other areas of the globe), indicate that over two-thirds of all bike trips in Europe are for utilitarian purposes, versus almost half (47.3%) of all bike trips in the United States being made for social or recreational purposes. The difference between the two environments shows up in attractive destinations within reasonable distance, direct and efficient connection via the networks, and minimal conflict with motor vehicles. The links among urban densities, shorter trips, and greater use of bike for utilitarian purposes was also found in Baltes’ 1996 study of biking in 284 U.S. MSAs, and Dill and Voros’ (2007) survey of Portland cyclists. Although the aforementioned research suggests an impor- tant role for land use and accessibility in projecting walk and bike travel, the limitations in existing research pro- vided motivation to sharpen this relationship in the new methods developed under NCHRP Project 08-78. The walk- accessibility approached developed for Arlington, Virginia, demonstrated a clear relationship between high rates of walking, biking, and transit use to destinations with high walk-accessibility, implying a high number of opportuni- ties available within walking distance. This research also ascertained that bicycle travel does not favor high-density destinations as much as walking, seemingly because of the likelihood of greater conflicts with traffic and fewer safe path alternatives. Also, for short trips in dense areas, walking may Land Use & Built Environment W AL KI N G Areas with higher densies, compact pedestrian oriented design, and a mix of uses have higher rates of walking – parcularly for ulitarian purposes (Lawrence Frank & Co., 2008; Kockelman, 1996; Kuzmyak, et al., 2010). Density, per se, is less important than the mix of uses and the connecvity provided by the street network (small blocks and gridiron shape) (Ewing & Cervero, 2010). Proximity to transit and the regional accessibility afforded by transit also reduce auto reliance and encourage walking, both to access transit and overall (Parsons Brinckerhoff, 1996; Cambridge Systemacs, 2002). Compact, mixed use design at employment or commercial centers encourages access by modes other than driving, and substuon of walking to secondary desnaons (NCHRP 8 78 Arlington research, 2012). Visually interesng and aracve landscaping and building features encourage walking (Cambridge Systemacs, 1994). BI CY CL IN G Densies somewhat less important than with walking; network connecvity measures more important (NCHRP 8 78 Arlington research, 2012). Compact form contributes to shorter distances, which is associated with more ulitarian biking (Dill & Voros, 2007). Convenient and secure bike parking important (Hunt & Abraham, 2006). Figure 3-2. Land use factors affecting walking and biking.

25 be preferred to biking because of the extra burden of finding secure bicycle parking. 3.4 Facilities The largest body of research on pedestrian and bicycle travel behavior has been in relation to facilities and their various characteristics, such as: • Type of facility • Safety in relation to traffic • Steep grades • Difficult crossings The planning needs motivating these studies are as follows: • Understanding facility characteristics in relation to choice of route for bicycling • Ascertaining the comparative value of different types of bicycle facilities (on- versus off-road) • Projecting demand for a new bicycle facility or mixed- use trail • Projecting pedestrian volumes at intersections in relation to intersection design, signal timing and traffic management Figure 3-3 summarizes findings from these research studies that highlight the key relationships between facility-related factors and non-motorized travel. For either mode, the top consideration is shortest distance or travel time afforded by the given network. From that baseline standard, the next most important consideration is safety in relation to exposure to 1 Also see: Joseph Broach, Jennifer Dill, and John Gliebe, “Where Do Cyclists’ Ride? A Route Choice Model Developed with Revealed Preference GPS Data,” Transportation Research-Part A, 46: 1730–1740, 2012. Facilities W AL KI N G Less than half of all walking (45%) takes place on sidewalks (NHTSA/BTS Naonal Survey, 2002). Connecvity and directness (shortest path) are important – a 12% increase over the shortest distance path is enough to induce shortcung (Moudon, et al., 2007). Sidewalks are much more important in commercial areas than in residenal areas, owing to differences in traffic volumes and speeds (Cao, et al., 2006; Handy, et al., 1998). Shorter blocks and four way intersecons enable more frequent, efficient and safer crossings, which encourages walking. Signalizaon is the most important crossing treatment, parcularly in high traffic areas (Boarnet, et al., 2005). Grade separated pedestrian crossings (overpass or underpass) are not popular, and are not well used if they add 25 to 50% addional me to the crossing (Zegeer, 1998). BI CY CL IN G Shortest distance and minimizing exposure to traffic are top consideraons; shortest distance slightly more important (Dill & Gliebe, 2008; Dill, 2009; Menghini, et al., 2009). Safety (from traffic) a bigger concern for non regular/inexperienced cyclists; travel me more important to experienced cyclists and those making commute trips (Dill, 2009; Hunt & Abraham, 2006). Dedicated facilies—off road bike paths, on road bike lanes, and bike boulevards (traffic calmed routes through residenal communies) are all preferred to riding in mixed traffic (Dill, 2009). Riders will travel extra distance or me to use a high quality facility, with the amount of tradeoff depending on the trip purpose (ulitarian versus recreaonal) and rider experience (Snson & Bhat, 2004; Hunt & Abraham, 2006). Number of intersecons with traffic control and number of turns per mile reduces desirability of a given route; however, traffic signals are welcomed for crossing or turning at a busy intersecon (Broach, Gliebe & Dill, 20091; Aultman Hall, et al., 1997; Menghini, 2009; Snson & Bhat, 2004). Experienced cyclists prefer smooth pavement for maximum speed & comfort (Snson & Bhat, 2004). Steep grades are a bigger deterrent to cyclists than to pedestrians (Cervero and Duncan, 2003). Secure parking at desnaon was valued at 8.5 to 26.5 minutes of travel me to riders in Calgary and Edmonton (Abraham et al., 2001; Hunt & Abraham, 2006). Figure 3-3. Facility-related factors affecting walking and biking.

26 vehicle traffic. For pedestrians, this concern is manifest in hav- ing sidewalks and frequent safe crossings where vehicle travel volumes and/or speeds are high. Pedestrians are also averse to traveling in close proximity to speeding vehicle travel when walking along a busy street or highway. That said, while pedestrians find security in sidewalks, this concern appears to be scaled to the level of threat posed by vehicle traffic; side- walks are highly desired in busy commercial areas, but are not regarded as essential in all residential areas. In fact, more than half of all walking does not occur on sidewalks. Examination of the data on biking also confirms the impor- tance of networks with good coverage and connectivity that enable efficient point-to-point travel. However, because cyclists are more often sharing the street network with motor vehicles, concerns about safety are more immediate. Thus, attempting to provide cyclists with a safe and efficient network is a goal patterned after the apparent success of such efforts in Europe. Because riding on sidewalks is neither efficient for cyclists nor safe for pedestrians, bike facilities generally fall into the categories of • Marked lanes on mixed-use streets and roads • On-road (or immediately parallel) bike lanes physically separated from the vehicle right-of-way (cycle tracks) • Separate off-road paths and trails • Marked routes (bike boulevards) through suburban neigh- borhoods and low-volume streets The many studies reviewed agree that cyclists prefer these dedicated facilities to sharing the road with high traffic activ- ity, and they will decide consciously to add time or distance to their shortest distance trip in order to take advantage of such facilities. The degree to which riders prefer and use these facili- ties depends on the type of trip, the type of rider, and the type of facility. In general, on-road paths are preferred by regular/ experienced cyclists, who are typically traveling to work or for some other utilitarian purpose, while off-road paths are pre- ferred by infrequent/less experienced cyclists, who hold safety in higher regard than travel time. The referenced research studies have gone into considerable detail in quantifying these cross-relationships as to the value attached to the various options by the different rider types and trip purpose categories. The research in NCHRP Project 08-78 has attempted to take these factors into account in the new models that have been developed. Perhaps one of the most robust studies of the importance of facilities-related factors to bike use (route choice in par- ticular) was a GPS-based survey of bike travelers in Portland, Oregon. The survey found that bike travelers making utili- tarian trips for work, school, shopping, or personal business ranked minimum distance as their top criteria, followed by avoiding traffic, ability to use an on-road bike lane, minimal intersection delays, taking a signed route, using an off-road path, and lastly, avoiding hills. People using bicycles for social and recreational travel made safety their top preference over minimum distance, while those biking purely for exercise had minimizing distance as their next to last concern; these people also preferred use of off-road paths. 3.5 Factors Related to the Natural Environment The natural environment can pose numerous challenges to walking and biking. Among the factors identified by research are the following: • Climate • Extremes of temperature • Precipitation • Darkness • Topography Figure 3-4 summarizes what is known about these factor relationships with walking and biking. What the studies sug- gest is that most of these factors (excluding topography, which was essentially discussed in relation to facilities) are transient in their effects. In other words, there may be an impact on behav- ior when the particular event is occurring, but the event is not considered “normal” time. For example, a period of extended unusually high temperatures and humidity might affect nor- mal levels of walking and biking, but probably will not be a sustained effect, and normal behavior will return when condi- tions return to normal. The gray area here would seem to be in the duration of the event(s), and whether it is an anomaly or sufficiently predictable that it defines the area’s “climate.” In such cases, climate could act to set an overall expectation of conditions and behavioral norms. For example, it might be fair to assume that levels of biking and walking in Phoenix – where summer temperatures routinely exceed 100°F – would be less due to this extreme, and at least one cross-sectional study has confirmed that non-motorized travel in Sun Belt cit- ies is lower than in the more temperate climates. However, one also observes that places like Minneapolis and Chicago with extended cold and snowy winters, also have some of the highest walking and biking rates in the country. The most likely expla- nation for this conundrum may be the design of the respec- tive cities, where the older northern cities have more compact, mixed-use environments that support walking and biking. Appendices 5 and 6 of the Contractor’s Final Report supply much more information on this topic gleaned from prior stud- ies. Efforts to include temperature and precipitation variables in the new models created by the project did not yield con- sistent or significant results. Topography, however, did prove significant and is included in the models as a variable.

27 3.6 Sociodemographic Factors Chapter 2 presented information on the types of people who walk and bike. The discussion in this chapter attempts to look more deeply into how certain characteristics are more associated with particular behavioral patterns or needs. The real question to the planner in using this information, how- ever, is in whether the result is used to reduce the estimate of demand because particular demographics have not walked or biked in the past because of such factors, or if by understand- ing which factors are particularly important to these groups, whether facilities, plans, or improvements can be designed that address these particular concerns. Figure 3-5 summa- rizes these factors. For example, the NHTS survey data indicate that men are much more likely to be regular bikers than women – both for utilitarian and recreational travel. In terms of walking, men and women are equally likely to walk to work, but they are less likely than women to walk for recreation/exercise and to reach transit. Walking and biking rates decline with age and with higher income, though more in-depth studies of the behav- ioral differences indicate that women and older riders are much more concerned about the safety and security offered by the land use setting and the travel networks. If it is an objec- tive to encourage more people across a broader sociodemo- graphic spectrum to bicycle, then factors such as these should be carefully considered in the design of both communities and facilities. Similarly, when factors such as age, income, education, vehicle ownership, and ethnicity are examined, the possibility that these trends seen in domestic travel data may be inter- twined with others must be considered, raising the question of which effect is dominating. In the case of age, both walking and biking decline with age, although in Europe the trends are more constant and, in fact, may increase with age above 65. In the United States, the behavior studies show that walk- ing and biking for utilitarian purposes are highest for younger travelers, while the rates for exercise and recreation are high- est among older people. Similar trends are seen in relation to income and ethnicity, with minorities more likely to walk or Figure 3-4. Environmental factors affecting walking and biking. Natural Environment W AL KI N G Climate: Regions of the United States with extended hot and/or humid summers have walk rates less than half those in more temperate regions; however, this finding may be more associated with Sun Belt cies that are younger and have been shaped around the automobile (Pucher & Renne, 2003). Temperature: Extreme high temperatures are more of a deterrent than cold temperatures (Schneider, et al., 2009). Weather: Precipitaon is more influenal than temperature for walking (Schneider, et al., 2009). Precipitaon: The potenal for rain is more of a deterrent than the amount of rain itself (Nankervis, 1999). Darkness: A significant deterrent to walking, but less than with biking; more of an issue in crime prone areas (Cervero and Duncan, 2003). Topography: Steep slopes are a deterrent to walking, though not as much for walking as for biking. Slope is more important as a factor for work related trips than for discreonary (Cervero and Duncan, 2003). BI CY CL IN G Climate: Areas with cold winters may see a 50% reducon in bike acvity levels; areas that are both cold and snowy may see an 80% decline. Effects of hot/humid climate not as well studied (Pra, et al., 2012). Temperature: Ridership generally increases with temperatures up to 90 F; effect of humidity believed important but not well studied (Lewin, 2011). Weather: Biggest impact of weather extremes is on recreaonal riders (Lewin, 2011). Precipitaon: Precipitaon is more influenal than temperature for biking (Lewin, 2011). Darkness: Measured to be five mes more important to cyclists than pedestrians (Cervero and Duncan, 2003). Topography: Hills and steep grades discourage bike use or choice of desnaon or route. Cyclists are more sensive to steep grades than pedestrians. Experienced riders are more tolerant of grades (Cervero and Duncan, 2003).

28 bike for non-discretionary travel, and whites doing so more for social/recreational (discretionary) travel. The key question is in whether this behavior is attributable to the sociodemo- graphic characteristics. For example, are people who are older and more financially secure less likely to walk or bike because they do not have to, or is it because when they have those char- acteristics in America they most likely live in suburbs, where walking or biking opportunities for non-recreational travel are very limited or non-existent? Those households are also likely to have more vehicles and more drivers. Most of the travel models developed by NCHRP Project 08-78 have taken these factors into account, and in most cases are included in the model structure. The tour-based mod- els explicitly differentiate among male and female riders and work and non-work travel when identifying optimal bicycle paths for these populations. Planning professionals need to apply relationships like those in Figure 3-5 judiciously and question how much the sociodemographic factors are responsible for the choice. This is why accounting for these factors simultaneously with the variables associated with the transportation and land use setting using well-specified choice-based models is the preferred approach. 3.7 Attitudes and Perceptions This final category of factors is closely related to the previ- ous category, in that it involves “human factors” involved in travel decision-making. Although these factors may be tied to various sociodemographic subgroups, there are broader issues about how these potential travelers “feel” about their choices as opposed to the physical realities that may be present. Figure 3-6 presents results obtained from a 2002 National Survey of Bicycle and Pedestrian Attitudes and Behavior con- ducted by the U.S. DOT. This survey explored why people do not walk or bicycle more often. In reviewing the responses, the most common reasons given seem to have little to do with see- Sociodemographic Factors W AL KI N G Gender: Men and women are equally likely to walk to work (2001 NHTS); Men are 13% less likely to walk for recreaon/exercise or to access transit. Rates of walk to work are similar, and no difference in average trip distance (Agrawal & Schimek, 2007). Age: Rates decline with age; persons 65 and older are 25% less likely than average to walk for ulitarian purposes, but 39% more likely to walk for recreaon or exercise (Pucher & Dijkstra, 2003). Income: Walking for ulitarian purposes declines by 40% once income exceeds $30k, while walking for recreaon or exercise increases steadily as income exceeds $30k (Agrawal & Schimek, 2007). Vehicle Ownership: Walk shares are 3.5 mes higher for zero car households than single car households; persons in households where number of drivers exceed number of vehicles average a 12.3% walk share, compared to 7% where vehicles outnumber drivers (Agrawal & Schimek, 2007). Educaon: Rates of walking for both ulitarian and recreaonal purposes increase with higher levels of educaonal aainment (Agrawal & Schimek, 2007). Ethnicity: All minories engage in more ulitarian walking than whites or Asians, while the reverse is true for recreaonal walking (Agrawal & Schimek, 2007). BI CY CL IN G Gender: Men are 2 to 3 mes more likely to be regular cyclists (NCHRP 552, 2006; Moudon, et al., 2007; Dill & Voros, 2007). Non commung cyclists 50% more likely to be male (Snson & Bhat, 2004). Age: Rates decline with age; the highest rates being for young to middle aged (Moudon, et al., 2007; Dill & Voros, 2007). Income: Persons with incomes of $100k and above were much more likely to be regular riders (30%) than those from households with incomes <$35k, though relaonships in the other income strata were not systemac (Dill & Voros, 2007). Vehicle Ownership: 22% of people in households with fewer vehicles than adults are regular riders, versus 19% where vehicles equal or exceed adults (Dill & Voros, 2007). Educaon: Having a college degree showed 2.8 greater odds of being a regular cyclist, but was found to be negavely correlated with commute cycling (Sener, Eluru, & Bhat, 2010). Ethnicity: No firm relaonships were found between race/ethnicity and regular bicycle use. Figure 3-5. Sociodemographic factors affecting walking and biking.

29 ing walking or biking as inferior or irrelevant modes, or even concerns about safety. The primary reasons given seemed to have more to do with health or weather, or even simply lack of interest or time. Much less common answers had to do with age, having a safe place to walk or bike, or preferring to drive. Upon review of the other research experience presented herein, it seems hard to accept these findings as realistic when concerns about safety and security seem paramount in the empirical studies. Those empirical studies suggest that one or more of the following explanations may provide insight on the responses received in the survey: • For many people, walking is not a realistic mode for any- thing but exercise or recreation, because they are not within reasonable access of opportunities or activities important to personal or household business. • Although bicycling offers a wider range than walking in terms of opportunities, potential users still face the concerns of directness and safety. Except for recreational biking, paths to relevant opportunities are likely to be circuitous and/or require the user to vie with vehicle traffic on shared roads or at crossings. The research shows that only the more experi- enced and determined individual will travel by bicycle under these circumstances. These questions bring to the fore the concept of self-selection and the relevance it has in describing these behavioral traits. Are certain types of people inherently disposed to particular lifestyles that greatly determine how they will choose to travel? Figure 3-6. Attitudinal and perceptual factors affecting walking and biking. Attitudes and Perceptions W AL KI N G Primary reasons for not walking: Health or disability (24.5%), weather related (22%), too busy (18.8%) (Naonal Survey of Bicycle and Pedestrian Atudes and Behaviors, 2002). Minor reasons for not walking: Other transportaon is faster (4%), do not like to walk (3.5%), no safe place to walk (3%), own a vehicle and prefer to drive (2.5%) (Naonal Survey of Bicycle and Pedestrian Atudes and Behaviors, 2002). In this response, no safe place to walk is more ed to having a sidewalk than the overall fear of traffic exposure or security (see below). Safety: Presence of traffic control devices and safe vehicle speeds ranked 2nd and 3rd aer shortest distance (Weinstein and Schinek, 2005). Security: The elderly, minories, and women are most likely to curtail walk travel due to concerns about personal safety, parcularly aer dark (Commiee on Physical Acvity, Health and Transportaon, 2005). BI CY CL IN G Safety appears to be the overriding factor influencing atudes toward and willingness to travel by bicycle: All riders are apprehensive about riding in motor vehicle traffic, and will deviate from the shortest route to avoid streets with heavy traffic; regular/experienced riders may be less concerned about traffic safety than infrequent/inexperience riders, but they sll demonstrate preference for routes/facilies that buffer them from traffic (Dill & Gliebe, 2008; Hunt & Abraham, 2006; Krizek/NCHRP 552, 2006; Sener & Bhat, 2010) The argument is that people who like living in urban settings are also comfortable with traveling by transit, walking, or bicy- cle, while those who prefer more subdued, residential settings also prefer the lifestyle that goes with that setting, including accomplishing travel needs via personal vehicle. The argument further suggests that simply creating urban places and walk- able environments will not induce those who do not embrace that lifestyle to begin to walk, bike, or use transit, i.e., that their preferences are determined by a behavioral cohort that will not change, even in a very different environment. Amid growing evidence of retirees and empty-nesters opting for urban condominium living in order to have less home maintenance and be less car dependent and of millen- nials and couples without children preferring an urban set- ting for its convenience, vitality, and range of opportunities, there has been cause for debate. How widespread or sus- tained these trends is uncertain, but it leaves the dilemma of “nature or nurture” in the question of opportunity and propensity to walk or bike, or use either mode to better use transit. Although the self-selection argument has had consider- able support, particularly in academic circles, and resulted in many studies to try to quantify the magnitude of the effect, most studies appear to show that the environment factors (land use and transportation alternatives) are as or more important in predicting behavior than an embedded pro/anti mode attitude. The interested reader is urged to consult the body of experience on this topic referenced in Appendix 7 of the Contractor’s Final Report.

Next: Chapter 4 - Best-Practice Methods for Estimating Bicycle and Pedestrian Demand »
Estimating Bicycling and Walking for Planning and Project Development: A Guidebook Get This Book
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TRB’s National Cooperative Highway Research Program (NCHRP) Report 770: Estimating Bicycling and Walking for Planning and Project Development: A Guidebook contains methods and tools for practitioners to estimate bicycling and walking demand as part of regional-, corridor-, or project-level analyses.

The products of the research include a guidebook for practitioners on a range of methods for estimating bicycling and walking activity and a CD-ROM containing a GIS Walk Accessibility Model, spreadsheets, and the contractor’s final report, which documents the research and tools that operationalize the methods described in the guidebook.

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