Accessibility, Income, and Person Trip Generation: Multilevel Model of Activity at Food Retail Establishments in Portland, Oregon

In the past decade, the methods for estimating multimodal transportation impacts of urban land use development have improved substantially. One assumption commonly made in these new methods is that overall person-trip rates at similarly-sized establishments of the same land use do not vary across a region. This is an assumption of convenience to permit the adjustment of ITE Trip Generation vehicle trip rates for use in different urban environments. However, this assumption is inconsistent with theories of urban economics, which recognize that businesses pay a premium to locate in areas with high levels of accessibility to attract more customers. In addition, most transportation impact analyses have ignored income effects, even though socio-economics are a proven driver of travel behavior. To test this assumption and understand the effects of accessibility and income on levels of activity at the establishment level, we examine transaction counts for 97 grocery and convenience markets in Portland, Oregon. In a multilevel negative binomial regression, we test the relationship of regional accessibility, local accessibility, and income on weekly and daily transaction rates. While there was not enough evidence to suggest a significant relationship between accessibility and transaction rates, the results indicated a significant relationship with median income of the surrounding area. The implications point to the need to consider area-wide socio-demographics in site-level transportation impact analysis. The study also provides some important discussion about the use of transaction as a proxy for person-trip rates

The Importance of Housing, Accessibility, and Transport Characteristic Ratings on Stated Neighborhood Preference

Travel demand models commonly lack the ability to understand how changing residential preferences influence future housing, land use, and transportation policies. As communities struggle to address social challenges related to increased economic uncertainty, transportation and land use planning have become increasingly centered on assumptions concerning the market for residential environments and travel choices. In response, an added importance has been placed on the development of toolkits capable of providing robust and flexible models to aid in understanding how differing assumptions contribute to a set of planning scenarios and how future residential location decisions may be made. In this study, we aim to examine the ability for current land use and transportation models to adequately account for the mechanism that drive households to prefer different neighborhoods based on typical transportation modeling methods. In particular, we conduct an original stated preference survey to identify the characteristics and preferences of individuals and households that influence unconstrained residential neighborhood preferences. Our objectives are to (a) determine the key drivers of residential neighborhood preferences, (b) test the contribution of sociodemographic and economic household characteristics commonly used in regional modeling tools to allocate households regionally across neighborhoods (e.g. household size, income, age, tenure), and (c) identify the preference profiles that can improve the sensitivity of our regional and statewide transportation-land use models to residential neighborhood preferences. The presentation for this seminar was done jointly with Steven Gehrke. It can be accessed at http://archives.pdx.edu/ds/psu/18234.https://pdxscholar.library.pdx.edu/trec_seminar/1022/thumbnail.jp

Improving Vehicle Trip Generation Estimations for Urban Contexts: A Method Using Household Travel Surveys to Adjust ITE Trip Generation Rates

The purpose of this research is to develop and test a widely available, ready-to-use method for adjusting the Institute of Transportation Engineers (ITE) Trip Generation Handbook vehicle trip generation estimates for urban context using regional household travel survey data. The ITE Handbook has become the predominant method for estimating vehicle trips generated by different land uses or establishment, providing a method for data collection and vehicle trip estimation based on the size of the development (e.g. gross square footage, number of employees, number of dwelling units). These estimates are used in traffic impact analysis to assess the amount of impact the development will have on nearby transportation facilities and, the corresponding charges for mitigating the development\u27s negative impacts, with roadway expansions, added turning bays, additional parking or traffic signalization, for example. The Handbook is often criticized, however, for its inability to account for variations in travel modes across urban contexts. For more than fifty years, ITE has collected suburban, vehicle-oriented data on trip generation for automobiles only. Despite the provision of warnings against application in urban areas, local governments continue to require the use of the ITE Handbook across all area-types. By over predicting vehicle traffic to developments in urban developments, developments may be overcharged to mitigate these developments locating in urban environments despite the lower automobile mode shares, discouraging infill development or densification. When ITE\u27s Trip Generation Handbook overestimates the vehicle impact of a development, facilities are also overbuilt for the automobile traffic and diminishing the use of alternative modes. When ITE\u27s TGH underestimates this impact, adjacent facilities may become oversaturated with traffic, pushing cars onto smaller facilities nearby. Currently, there is momentum amongst practitioners to improve these estimation techniques in urban contexts to help support smart growth and better plan for multiple modes. This research developed and tested a method to adjust ITE\u27s Handbook vehicle trip generation estimates for changes in transportation mode shares in more urban contexts using information from household travel surveys. Mode share adjustments provide direct reductions to ITE\u27s Handbook vehicle trip estimations. Household travel survey (HTS) data from three regions were collected: Portland, Oregon; Seattle, Washington; and Baltimore, Maryland. These data were used to estimate the automobile mode share rates across urban context using three different adjustment methodologies: (A) a descriptive table of mode shares across activity density ranges, (B) a binary logistic regression that includes a built environment description of urban context with the best predictive power, and (C) a binary logistic regression that includes a built environment description of urban context with high predictive power and land use policy-sensitivity. Each of these three methods for estimating the automobile mode share across urban context were estimated for each of nine land use categories, resulting in nine descriptive tables (Adjustment A) and eighteen regressions (Adjustments B and C). Additionally, a linear regression was estimated to predict vehicle occupancy rates across urban contexts for each of nine land use categories. 195 independently collected establishment-level vehicle trip generation data were collected in accordance with the ITE Handbook to validate and compare the performance of the three adjustment methods and estimations from the Handbook. Six land use categories (out of the nine estimated) were able to be tested. Out of all of the land uses tested and verified, ITE\u27s Trip Generation Handbook appeared to have more accurate estimations for land uses that included residential condominiums/townhouses (LUC 230), supermarkets (LUC 850) and quality (sit-down) restaurants (LUC 931). Moderate or small improvements were observed when applying urban context adjustments to mid-rise apartments (LUC 223), high-turnover (sit-down) restaurants (LUC 932). The most substantial improvements occurred at high-rise apartments (LUC 222) and condominiums/townhouses (LUC 232), shopping centers (LUC 820), or coffee/donut (LUC 936) or bread/donut/bagel shops (LUC 939) without drive-through windows. The three methods proposed to estimate automobile mode share provides improvements to the Handbook rates for most infill developments in urban environments. For the land uses analyzed, it appeared a descriptive table of mode shares across activity density provided results with comparable improvements to the results from the more sophisticated binary logistic model estimations. Additional independently collected establishment-level data collections representing more land uses, time periods and time of days are necessary to determine how ITE\u27s Handbook performs in other circumstances, including assessing the transferability of the vehicle trip end rates or mode share reductions across regions

Adjusting ITE’s Trip Generation Handbook for Urban Context

This study examines the ways in which urban context affects vehicle trip generation rates across three land uses. An intercept travel survey was administered at 78 establishments (high-turnover restaurants, convenience markets, and drinking places) in the Portland, Oregon, region during 2011. This approach was developed to adjust the Institute of Transportation Engineers (ITE) Trip Generation Handbook vehicle trip rates based on built environment characteristics where the establishments were located. A number of policy-relevant built environment measures were used to estimate a set of nine models predicting an adjustment to ITE trip rates. Each model was estimated as a single measure: activity density, number of transit corridors, number of high-frequency bus lines, employment density, lot coverage, length of bicycle facilities, presence of rail transit, retail and service employment index, and intersection density. All of these models perform similarly (Adj. R2 0.76-0.77) in estimating trip rate adjustments. Data from 34 additional sites were collected to verify the adjustments. For convenience markets and drinking places, the adjustment models were an improvement to the ITE’s handbook method, while adjustments for restaurants tended to perform similarly to those from ITE’s estimation. The approach here is useful in guiding plans and policies for a short-term improvement to the ITE’s Trip Generation Handbook. The measures are useful for communities seeking to develop local adjustments to vehicle trip rate estimates, and all could be calculated from spatial data available in most locations. The paper concludes with a discussion on what long-term improvements to the ITE’s Trip Generation Handbook might entail, with further implications in planning and practice

How Do Stressed Workers Make Travel Mode Choices That Are Good For Their Health, Safety, and Productivity?

It is well recognized in transportation and psychology research that commuting stress has consequences for commuters\u27 travel safety, home environment, and work performance. Little research has addressed questions involving the possible interdependence between work stress, family stress, and commuting stress: Do workers having many demands from work and family life get more stressed out from a stressful commute? Or do stressed workers try to cope with work and non-work stress by choosing more relaxing travel modes? This proposal integrates the perspectives from transportation, psychology, and health science by focusing on the relations between commuting stress, commuting mode choice, and consequences of such choice for commuters\u27 health. To fill the gaps in the transportation and psychology literature, our proposal addresses two key research questions:1) Under what life and work circumstances are commuting workers more likely to commute via car vs. public transit vs. bicycle vs. on foot? 2) What are the different implications of choosing different commuting modes for commuters’ mental and physical health and work outcomes? In Study 1, we used nationally representative census data and we devised a series of multinomial, logistic regression models to predict the probability of choosing each commute mode to address research question 1. In Study 2, we used cortisol and survey data collected daily over a workweek to address research question 2. Findings from this research shed light on possible intervention opportunities that help commuting workers cope with various sources of life stress while making more informed decisions on travel mode choice. We contend that commuting workers, their employers, and transportation agencies and planners can all take part in these interventions that can benefit commuting workers’ productivity and well-being, organizational bottom line as well as performance and safety of the transportation system

Adjusting ITE’s Trip Generation Handbook for urban context

This study examines the ways in which urban context affects vehicle trip generation rates across three land uses. An intercept travel survey was administered at 78 establishments (high-turnover restaurants, convenience markets, and drinking places) in the Portland, Oregon, region during 2011. This approach was developed to adjust the Institute of Transportation Engineers (ITE) Trip Generation Handbook vehicle trip rates based on built environment characteristics where the establishments were located. A number of policy-relevant built environment measures were used to estimate a set of nine models predicting an adjustment to ITE trip rates. Each model was estimated as a single measure: activity density, number of transit corridors, number of high-frequency bus lines, employment density, lot coverage, length of bicycle facilities, presence of rail transit, retail and service employment index, and intersection density. All of these models perform similarly (Adj. R2 0.76-0.77) in estimating trip rate adjustments. Data from 34 additional sites were collected to verify the adjustments. For convenience markets and drinking places, the adjustment models were an improvement to the ITE’s handbook method, while adjustments for restaurants tended to perform similarly to those from ITE’s estimation. The approach here is useful in guiding plans and policies for a short-term improvement to the ITE’s Trip Generation Handbook. The measures are useful for communities seeking to develop local adjustments to vehicle trip rate estimates, and all could be calculated from spatial data available in most locations. The paper concludes with a discussion on what long-term improvements to the ITE’s Trip Generation Handbook might entail, with further implications in planning and practice

A Practitioner\u27s Guide to Urban Trip Generation

In 1976, the Institute of Transportation Engineers (ITE) compiled their first Handbook of guidelines for evaluating development-level transportation impacts. Decades later, these methods are still ubiquitously used across the US and Canada. Only recently, with the third edition of the ITE Trip Generation Handbook, have new data and approaches been adopted. In this study NITC researcher Kristina Currans takes aim at understanding issues inherent in the collection and application of ITE’s data and methods in various urban contexts. This technology transfer guide touches on the main findings from this work

Issues in Trip Generation Methods for Transportation Impact Estimation of Land Use Development: A Review and Discussion of the State-of-the-Art Approaches

As agencies develop more robust planning objectives for creating sustainable and livable communities, the research community has continued developing supportive tools and methods to provide more accurate and robust means for estimating transportation impacts for site-level development review. This paper is a review of the state-of-the-art trip generation methods for land use transportation impact estimation. First, it provides an overview of the more recent available and peer-reviewed estimation methods. Second, the authors offer a discussion of the successes of state-of-the-art approaches using common themes of research to identify corresponding consistency with theories of travel behavior and urban economics. These themes include: (a) the ability to estimate overall amounts of activity; (b) built environment and multimodal estimation; (c) socio-and economic demographics; (d) mixed and/or multiuse methods; and (e) land use (dis)aggregation. The main objective of this paper is to, throughout the discussion and conclusions, identify the largest and potentially problematic gaps in the state-of-the-art methods available for practice in order to allow researchers, agencies, and practitioners to both be aware of these limitations and forge forward new innovations to solve these on-going problem

Getting to Know the Data: Understanding Assumptions, Sensitivities, Uncertainty, and Being Conservative While Using ITE\u27s Trip Generation Data in the Land Development Process

Many agencies rely on trip generation estimates to evaluate the transportation impacts of land development in urban and suburban areas alike. Over the past decade, substantial attention has been paid to one national set of guidelines—the Institute of Transportation Engineers (ITE) Trip Generation Handbook (2014) and corresponding Manual (2012)—focusing in particular to improve the use of these data and supplementary methods for urban contexts. The purpose of this study is to explore the typical data provided in the Handbook, within the context of these new improved state-of-the-art methods. As ITE’s describes, “an example of poor professional judgment is to rely on rules of thumb without understanding or considering their derivation or initial context” (Institute of Transportation Engineers, 2014, p. 3). This research aims to improve the understanding of these data—still ubiquitously used across the US—to encourage increased engagement with their meaning, and following, to provide the users (e.g., engineering, planners, agencies, and developers) with the landscape from which these data were collected and for which they represent. From here, more informed decisions can be made about whether these data provide an adequate or accurate estimation transportation impacts within varying contexts and applications.https://pdxscholar.library.pdx.edu/trec_seminar/1117/thumbnail.jp