Search

This study pools household travel and built environment data from 15 diverse US regions to produce travel models with more external validity than any to date. It uses a large number of consistently defined built environmental variables to predict five household travel outcomes – car trips, walk trips, bike trips, transit trips and vehicle miles travelled (VMT). It employs multilevel modelling to account for the dependence of households in the same region on shared regional characteristics and estimates ‘hurdle’ models to account for the excess number of zero values in the distributions of dependent variables such as household transit trips. It tests built environment variables for three different buffer widths around household locations to see which scale best explains travel behaviour. The resulting models are appropriate for post-processing outputs of conventional travel demand models, and for sketch planning applications in traffic impact analysis, climate action planning and health impact assessment.

The article first estimates models of mode choice and average trip length for 239 diverse mixed-use developments in six diverse regions. It then applies these models to twelve Leadership in Energy and Environmental Design for Neighborhood Development (LEED-ND) pilot projects to predict approximate vehicle miles of travel (VMT) per person trip. Finally, it compares LEED-ND values to regional average values from the National Household Travel Survey. The VMT per person trip, for LEED-ND projects, ranges from 24 to 60 percent of the respective regional averages. The most urban and centrally located projects tended to achieve the highest alternative mode shares and the lowest private vehicle trip lengths.

Current methods of traffic impact analysis, which rely on rates and adjustments from the Institute of Transportation Engineers, are believed to understate the traffic benefits of mixed-use developments (MXDs), leading to higher exactions and development fees than necessary and discouraging otherwise desirable developments. The purpose of this study is to create new methodology for more accurately predicting the traffic impacts of MXDs. Standard protocols were used to identify and generate data sets for MXDs in six large and diverse metropolitan regions. Data from household travel surveys and geographic information system (GIS) databases were pooled for these MXDs, and travel and built environmental variables were consistently defined across regions. Hierarchical modeling was used to estimate models for internal capture of trips within MXDs, walking and transit use on external trips, and trip length for external automobile trips. MXDs with diverse activities on-site are shown to capture a large share of trips internally, reducing their traffic impacts relative to conventional suburban developments. Smaller MXDs in walkable areas with good transit access generate significant shares of walk and transit trips, thus also mitigating traffic impacts. Centrally located MXDs, small and large, generate shorter vehicle trips, which reduces their impacts relative to outlying developments.

This paper examines the nature of land use based substitution effects on travel modes, identified by Greenwald, examining the direct impact of land uses inducing trip-making behaviors. These impacts are analyzed in the context of trip chaining, defined here as consolidating two or more non-home activities in a single departure from home. The findings suggest rather than strictly promoting one type of transportation over another, the regional impact of localized urban design practices is to consolidate trip making behavior closer to the home. As such, urban design “carrots” must be complemented with policy “sticks” in order to promote true exchanges of travel modes.

The authors examine the magnitude of health benefits from urban design characteristics that are associated with increased walking. Using geocoded travel diary data from Portland, Oregon, regression analyses give information on the magnitude and statistical significance of the link between urban design variables and two-day walking distances. From the coefficient point estimates, the authors link to the health literature to give information on how many persons would realize health benefits, in the form of reductions in mortality risk, from walking increases associated with urban design changes. Using a cost-benefit analysis framework, they give monetized estimates of the health benefits of various urban design changes. The article closes with suggestions about how the techniques developed can be applied to other cost-benefit analyses of the health benefits of planning projects that are intended to increase walking.

This paper addresses the relationship between land use, destination selection, and travel mode choice. Specifically, it focuses on intrazonal trips, a sub-category of trip making where both trip origin and trip destination are contained in the same geographic unit of analysis, using data from the 1994 Household Activity and Travel Diary Survey conducted by Portland Metro. Using multinomial logit and binary logistic models to measure travel mode choice and decision to internalize trips, the evidence supports the conclusions that (1) intrazonal trips characteristics suggest mode choice for these trips might be influenced by urban form, which in turn affects regional trip distribution; (2) there is a threshold effect in the ability of economic diversity/mixed use to alter travel behavior; and (3) greater emphasis to destinations within the area where an individual’s home is located needs to be given in trip distribution models.

In JPER volume 15, Crane (1996b) challenged the New Urbanist arguments that urban design traits such as street orientation, density, mix of land uses, and transit access automatically get travelers to substitute walking and transit for personal auto-mobile use. The work presented here starts to address that point, formally testing New Urbanist ideas about travel mode substitution. Using data from the 1994 Household Activity and Travel Behavior Survey conducted in Portland, Oregon, these findings suggest New Urbanist concepts serve to increase walking substitution; transit is not affected. These findings hold even in the face of travelers self-selecting into specific residential environments.

Travelers can be classified into two groups: choice users and captive users. Choice users select transit or automobile service when they view one option as superior, whereas captive users have only one travel option. Surprisingly, little is known about captivity effects on mode split models. This research examines the way transit service factors such as accessibility and connectivity relate to mode captivity and mode choice. Data for this investigation come from the Portland, Oregon, 1994 Household Activity and Travel Diary Survey, the Regional Land Information System for the Portland area, the U.S. Environmental Protection Agency fuel economy database, and the U.S. Department of Energy. Individual trip data were segmented into transit captive, automobile captive, and choice users based on information about private vehicle availability, transit connectivity, and distance from a transit stop. Traditional transit mode split models are compared with models that segment users into choice and captive groups. It was found that traditional models underestimate the variation in mode choice for captive users, while overestimating the attractiveness of transit for choice users. These results indicate that better transit forecasts can result if accessibility and connectivity are used to help identify captive users. Additionally, among choice transit users, differences in travel times between automobile and transit modes do little to influence mode selection, while walk access to transit has more effect than previously thought.

The authors have developed a kinetic dye test protocol that aims to predict the competitive adsorption of 2-methylisoborneol (MIB) to granular activated carbons (GACs). The kinetic dye test takes about two hours to perform, and produces a quantitative result, fitted to a model to yield an Intraparticle Diffusion Constant (IDC) during the earlier times of dye sorption. The dye xylenol orange was probed into six coconut-based GACs and five bituminous-based GACs that hosted varied pore distributions. Correlations between xylenol orange IDCs and breakthrough of MIB at 4 ppt in rapid small-scale column tests (RSSCTs) were found with R2s of 0.85 and 0.95 for coconut carbons that processed waters with total organic carbon (TOCs) of 1.9 and 2.2 ppm, respectively, and with an R2 of 0.94 for bituminous carbons that processed waters with a TOC of 2.5 ppm. The author sought to study the influence of the pore sizes, which provide the adsorption sites and the diffusion conduits that are necessary for the removal of those compounds. For coconut carbons, a linear correlation was established between the xylenol orange IDCs and the volume of pores in the range of 23.4–31.8 A widths (R2 = 0.98). For bituminous carbons, best correlation was to pores ranging from 74 to 93 A widths (R2 = 0.94). The differences in adsorption between coconut carbons and bituminous carbons have been attributed to the inherently dissimilar graphene layering resulting from the parent materials and the activation processes. When fluorescein dye was employed in the kinetic dye tests, the correlations to RSSCT-MIB performance were not as high as when xylenol orange was used. Intriguingly, it was the same pore size ranges that exhibited the strongest correlation for MIB RSSCT's, xylenol orange kinetics, and fluoroscein kinetics. When methylene blue dye was used, sorption occurred so rapidly as to be out of the scope of the IDC model.

Much has been written about the connection between land use/urban form and transportation from the perspective of affecting automobile trip generation. This addresses only half the issue. The theoretical advances in land use–transportation relationships embodied in paradigms such as the jobs-housing balance, neotraditional design standards, and transitoriented development rely very heavily on the generation of pedestrian traffic to realize their proposed benefits. The present analysis uses models and data sets similar to those used in previous work for the Portland, Oregon, area but applies them toward analysis of nonwork walking travel. The results suggest that regardless of the effects that land use has on individual nonwork walking trip generation, the impacts take place at the neighborhood level.

Research on nonwork automobile trip generation and land use previously conducted by researchers is replicated for the Portland, Oregon, region. Additionally, new variables examining new urbanist arguments are incorporated. The results suggest that any links between land use and nonwork trip behavior act primarily by influencing trip costs, in terms of distances traveled and speeds achieved, rather than directly influencing the number of trips made. This analysis is consistent with the other research, suggesting that this model is not sensitive to errors that might arise due to the unique characteristics of the urban area under review.

Objective Our objective was to describe how active transportation can help meet health and greenhouse gas emissions goals, and the ability of urban form strategies to impact both issues. In addition, we wanted to assess if there is an inverse relationship between active and motorized forms of travel. Methods A cross-sectional analysis of travel diary data was used to measure relationships among energy (kcal) burned from walking, energy (kcal) burned from motorized transportation, and the ratio of the two (the transport energy index) with regional accessibility and local walkability when adjusting for demographic factors. Multiple linear regression and descriptive statistics were employed to estimate these relationships. Results Transit accessibility, residential density, and intersection density were positive predictors of walk energy and the energy index and inverse predictors of motorized energy. The land use mix variable was negatively and significantly associated with energy burned from walking and from motorized transportation, with no significant impact on the transport energy index. Because a mixed land use pattern places destinations closer together, it reduces distances and thus energy demands for both walking and driving. Conclusions The results support the concept, previously untested empirically, that similar urban form strategies can have cobenefits for both physical activity and climate change.

This qualitative study describes environmental supports and barriers to physical activity in an older adult sample drawn from low- and high-walkable neighborhoods. Thirty-seven individuals age 55 and over were recruited and answered open-ended survey questions, with a subsample invited back to partake in a semistructured interview. Content analysis identified categories and themes linking perceptions of neighborhood-environment characteristics to activity. Emerging categories and themes did not differ across neighborhood walkability, so results are presented for both groups combined. Infrastructure was the most common category identified to encourage activity, specifically, well-maintained sidewalks, bike paths or lanes, and traffic control. Other categories of land use, landscape, and aesthetics were reported. Poorly maintained or missing sidewalks, crosswalks, bike paths or lanes, and traffic safety were categories that discouraged activity. In conclusion, the information obtained is helpful in solidifying which environmental characteristics are important to measure as they relate to activity behavior in an older adult population.

Background Few studies have investigated both the self-perceived and measured environment with objectively determined physical activity in older adults. Accordingly, the aim of this study was to examine measured and perceived environmental associations with physical activity of older adults residing across different neighborhood types. Methods One-hundred and forty-eight older individuals, mean age 64.3 ± 8.4, were randomly recruited from one of four neighborhoods that were pre-determined as either having high- or low walkable characteristics. Individual residences were geocoded and 200 m network buffers established. Both objective environment audit, and self-perceived environmental measures were collected, in conjunction with accelerometer derived physical activity behavior. Using both perceived and objective environment data, analysis consisted of a macro-level comparison of physical activity levels across neighborhood, and a micro-level analysis of individual environmental predictors of physical activity levels. Results Individuals residing in high-walkable neighborhoods on average engaged in 11 min of moderate to vigorous physical activity per day more than individuals residing in low-walkable neighborhoods. Both measured access to non-residential destinations (b = .11, p < .001) and self-perceived access to non-residential uses (b = 2.89, p = .031) were significant predictors of time spent in moderate to vigorous physical activity. Other environmental variables significantly predicting components of physical activity behavior included presence of measured neighborhood crime signage (b = .4785, p = .031), measured street safety (b = 26.8, p = .006), and perceived neighborhood satisfaction (b = .5.8, p = .003). Conclusions Older adult residents who live in high-walkable neighborhoods, who have easy and close access to nonresidential destinations, have lower social dysfunction pertinent to crime, and generally perceive the neighborhood to a higher overall satisfaction are likely to engage in higher levels of physical activity behavior. Efforts aimed at promoting more walkable neighborhoods could influence activity levels in older adults.

The effectiveness of an integrated treatment program utilizing cognitive-behavioral therapies for Panic Disorder was examined. Treatment was comprised of Cognitive Model of Panic-derived procedures, Cognitive Therapy and Applied Relaxation Training. Subjects meeting DSM-III-R criteria for Panic Disorder received thirteen 2.5-hr sessions of outpatient therapy in small groups, over a 12-week period. Subjects were given an extensive rationale of the etiology, development and maintenance of Panic Disorder, within the framework of the Cognitive Model of Panic, and controlled behavioral experiments in panic evocation to internal panicogenic cues, cognitive reappraisal of somatic and ideational cues, breathing retraining, Applied Relaxation Training and Cognitive Therapy to identify and remediate maladaptive beliefs and dysfunctional cognitive schemas. A comprehensive assessment battery was given at pre-mid-post-treatment which included measures of tripartite functioning, global severity, panic, fear, anxiety, depression and psychiatric symptomatology. Analyses indicated statistically significant improvements across all outcome domains. All subjects were free of spontaneous (uncued) panic attacks at post-treatment, and all met operationalized criteria for high endstate functioning. These findings are discussed, with recommendations for future research.