William Bachman

Many Pathways from Land Use to Health: Associations between Neighborhood Walkability and Active Transportation, Body Mass Index, and Air Quality

Abstract The literature shows single-use, low-density land development and disconnected street networks to be positively associated with auto dependence and negatively associated with walking and transit use. These factors in turn appear to affect health by influencing physical activity, obesity, and emissions of air pollutants. We evaluated the association between a single index of walkability that incorporated land use mix, street connectivity, net residential density, and retail floor area ratios, with health-related outcomes in King County, Washington. We found a 5% increase in walkability to be associated with a per capita 32.1% increase in time spent in physically active travel, a 0.23-point reduction in body mass index, 6.5% fewer vehicle miles traveled, 5.6% fewer grams of oxides of nitrogen (NOx) emitted, and 5.5% fewer grams of volatile organic compounds (VOC) emitted. These results connect development patterns with factors that affect several prevalent chronic diseases.

Elimination of the Travel Diary: Experiment to Derive Trip Purpose from Global Positioning System Travel Data

Several recent pilot studies combined Global Positioning System (GPS) technology with travel survey data collection to evaluate opportunities for improving the quantity and accuracy of travel data. These studies used GPS to supplement traditional data elements collected in paper or electronic travel diaries. Although many traditional trip elements can be obtained from the GPS data, trip purpose has remained an important element, requiring the use of a diary to continue. Presented are the results of a proof-of-concept study conducted at the Georgia Institute of Technology that examined the feasibility of using GPS data loggers to completely replace, rather than supplement, traditional travel diaries. In this approach, all GPS data collected must be processed so that all essential trip data elements, including trip purpose, are derived. If this processing is done correctly and quickly, then the computer-assisted telephone interview retrieval call could be shortened significantly, reducing both respondent burden and telephone interview times. The study used GPS data loggers to collect travel data in personal vehicles. The GPS data were then processed within a geographic information system (GIS) to derive most of the traditional travel diary elements. These derived data were compared with data recorded on paper diaries by the survey participants and were found to match or exceed the reporting quality of the participants. Most important, this study demonstrated that it is feasible to derive trip purpose from the GPS data by using a spatially accurate and comprehensive GIS.

Linking land use with household vehicle emissions in the central puget sound: methodological framework and findings

A leading cause of air pollution in many urban regions is mobile source emissions that are largely attributable to household vehicle travel. While household travel patterns have been previously related with land use in the literature (Crane, R., 1996. Journal of the American Planning Association 62 (1, Winter); Cervero, R. and Kockelman, C., 1997. Transportation Research Part D 2 (3), 199–219), little work has been conducted that effectively extends this relationship to vehicle emissions. This paper describes a methodology for quantifying relationships between land use, travel choices, and vehicle emissions within the Seattle, Washington region. Our analysis incorporates land use measures of density and mix which affect the proximity of trip origins to destinations; a measure of connectivity which impacts the directness and completeness of pedestrian and motorized linkages; vehicle trip generation by operating mode; vehicle miles/h of travel and speed; and estimated household vehicle emissions of nitrogen oxides, volatile organic compounds, and carbon monoxide. The data used for this project consists of the Puget Sound Transportation Panel Travel Survey, the 1990 US Census, employment density data from the Washington State Employment Security Office, and information on Seattle’s vehicle fleet mix and climatological attributes provided by the Washington State Department of Ecology. Analyses are based on a cross-sectional research design in which comparisons are made of variations in household travel demand and emissions across alternative urban form typologies. Base emission rates from MOBILE5a and separate engine start rates are used to calculate total vehicle emissions in grams accounting for fleet characteristics and other inputs reflecting adopted transportation control measures. Emissions per trip are based on the network distance of each trip, average travel speed, and a multi-stage engine operating mode (cold start, hot start, and stabilized) function.

ACCURACY OF GLOBAL POSITIONING SYSTEM FOR DETERMINING DRIVER PERFORMANCE PARAMETERS

Global Positioning System (GPS) technology can continuously monitor the time and location of vehicle usage. By recording and analyzing detailed vehicle activity data, researchers can analyze the safety and environmental implications of driver behavior and trip-making patterns. In 2000, NHTSA awarded the Georgia Institute of Technology a contract to equip 1,100 vehicles with a GPS-enhanced device to collect speed and location data. The objective was to acquire more accurate information on the role of excessive speed on crash frequency and severity. GPS technology allows the researcher to continuously measure driver speed, acceleration, and location. When merged with roadway characteristics within a geographic information system (GIS) environment, determinations of driver risk-taking behavior can be made. Second, continuous logging of GPS data allows researchers to capture high-resolution vehicle activity immediately before a crash event, reducing the potential error and bias introduced during determination of precrash speed estimates. Until May 1, 2000, the military degraded the position accuracy of GPS signals for commercial use, known as selective availability. For researchers, life without selective availability is a great improvement. Travel routes can clearly be discerned without the addition of differential correction units. The accuracy of speed, acceleration, and position data obtained from GPS signals for use in determining driver performance parameters without selective availability were tested. The test included four GPS packages, both corrected and uncorrected, simultaneously validated against a distance-measuring instrument. Equipment configuration, data collection methods, and sources of error are reported. The results suggested that non-corrected data can be used to obtain data within a reasonable range of the application requirements. Even without selective availability, GPS accuracy is still problematic in urban canyons and under heavy tree canopies. Although filtering for urban canyon outliers is labor intensive in a continuous monitoring situation, improvements in GIS hold promise for automation of this task.

Modeling regional mobile source emissions in a geographic information system framework

Suburban sprawl, population growth, and automobile dependency contribute directly to air pollution problems in US metropolitan areas. As metropolitan regions attempt to mitigate these problems, they are faced with the difficult task of balancing the mobility needs of a growing population and economy, while simultaneously lowering or maintaining levels of ambient pollutants. Although ambient air quality can be directly monitored, predicting the amount and fraction of the mobile source components presents special challenges. A modeling framework that can correlate spatial and temporal emission-specific vehicle activities is required for the complex photochemical models used to predict pollutant concentrations. This paper discusses the GIS-based modeling approach called the Mobile Emission Assessment System for Urban and Regional Evaluation (MEASURE). MEASURE provides researchers and planners with a means of assessing motor vehicle emission reduction strategies. Estimates of spatially resolved fleet composition and activity are combined with activity-specific emission rates to predict engine start and running exhaust emissions. Engine start emissions are estimated using aggregate zonal information. Running exhaust emissions are predicted using road segment specific information and aggregate zonal information. The paper discusses the benefits and challenges related to mobile source emissions modeling in a GIS framework and identifies future GIS mobile emissions modeling research needs.

Assessing Impacts of Improved Signal Timing as a Transportation Control Measure Using an Activity-Specific Modeling Approach

Metropolitan areas in nonattainment for transportation-related air pollutants rely on transportation control measures (TCMs) to reduce emissions and meet clean-air goals. However, since traditional transportationrelated air quality models use emission rates based on average speeds, only TCMs that either increase or decrease vehicle activity to speeds in which emissions are lower show reductions in output of air pollutants. In recent years, transportation air quality analysis has shifted to an activityspecific modeling approach that correlates emissions to vehicle operating mode. With an activity-specific approach, the emission reduction potential of a TCM can be evaluated by its ability to decrease time spent in modes in which emissions are disproportionately elevated. Signal timing improvements are attractive TCMs for traffic flow improvement. However, with traditional modeling, they may greatly decrease extremes in modal activity yet not show significant emission reduction if only moderate changes in average speed are realized. The benefits of using activityspecific modeling for evaluation of improved signal coordination as a TCM are described. A brief overview of the development of an activityspecific carbon monoxide emission rate model is provided, data collection for on-road vehicle activity estimates is briefly outlined, and a comparison of traditional emission modeling versus activity-specific modeling is provided to estimate the air quality benefits from improved coordination at a study intersection. Results for the study intersection indicate that more significant reductions in carbon monoxide emissions are realized using an activity-specific approach than with traditional methods.

HIGH-EMITTING VEHICLE CHARACTERIZATION USING REGRESSION TREE ANALYSIS

A small fraction of motor vehicles on the roadway emit a disproportionate fraction of pollutant emissions, especially for carbon monoxide and hydrocarbons. Generally, these “high emitters” or “super emitters” exhibit higher emissions rates under all operating conditions than do “normal emitters.” Since the instantaneous emissions response between normal- and high-emitting vehicles can differ by one or more orders of magnitude, so do their average emissions over a “typical” trip. Identifying the proportion of normal- and high-emitting vehicles in an urban area and quantifying their emissions is vital for accurate emission inventory accounting. A methodology by which high and normal emitters can be classified is presented. Unlike previous emitter classification approaches, the approach is data driven and relies entirely on hot-stabilized emissions results. A statistical classification scheme, better known as hierarchical tree based regression, is used to separate vehicles into homogenous emitter categories. The approach is shown to have a number of advantages. First, it is flexible with respect to both the number of classes and types of variables used to identify classes. Second, it considers the influence of a large number of vehicle and technology attributes on emitter status. Third, it ensures that the highest emitters can be isolated from the normal emitters, so that separate emission rate models can be developed for these vehicles. Finally, the approach does not combine the effects of starts and hot-stabilized operations within the definition of high emitter, leading to a classification scheme whereby vehicles with poor start emissions characteristics will not be incorrectly classified as vehicles with poor hot-stabilized emission characteristics.

Geographic information system framework for modeling mobile-source emissions

Because vehicle activities and the emissions associated with them can be correlated with specific points in time and space, the modeling capabilities of a geographic information system (GIS) are well suited to the modeling of mobile-source emissions. A GIS-based modeling approach can provide emissions estimates for both on-network and off-network vehicle activities on a modal basis (as a function of various vehicle operating modes that significantly affect vehicle emission rates). An entire metropolitan region can be modeled on a zone, link, and point basis. Vehicle subfleet composition can be tracked or estimated and combined with estimates of vehicle activity and characteristic operating modes to provide emissions estimates in a spatial and temporal context. Emissions from various modal activities are aggregated into grid cells to be used as input to an airshed model. Identifying spatial and temporal distributions of these activities adds to a greater understanding of emissions impacts. A research proto...

GLOBAL POSITIONING SYSTEM WITH AN ATTITUDE: METHOD FOR COLLECTING ROADWAY GRADE AND SUPERELEVATION DATA

The use of a specialized Global Positioning System (GPS) to conduct high-speed surveys of roadway alignment, grade, and cross-slope characteristics is discussed. The system uses a single GPS receiver that has 24 channels monitoring four separate antennas (six channels each). The collection of attitude (heading, pitch, and roll) is made possible through the relative orientation of the antennas. By mounting the system on a road surveillance vehicle, accurate grades, superelevation, and crown measurements can be made without differentially correcting the GPS data. However, to gather precise positional data that correspond to the roadway measurements, differential correction with a GPS base station at a fixed known point is required. The design and use of this attitude GPS unit are addressed. Accuracy specifications for static testing are provided along with techniques to maximize this accuracy. Kinematic data collection is depicted for a local road and a freeway off-ramp. The use of digital terrain modeling technology provides a promising graphic database representation of the roadway characteristics.

Applying GPS Data to Understand Travel Behavior, Volume I: Background, Methods, and Tests

With the high costs associated with primary data collection, methods to improve the use and accessibility of newer sources of data such as Global Positioning System (GPS) data can benefit many transportation practitioners. GPS data can have multiple uses beyond traditional applications such as estimates of speed and travel times. GPS-related data that have been collected from automatic vehicle location systems, from highway sensors, as supplemental information to traditional travel surveys, and via passive technologies [e.g., Bluetooth, radio frequency identification (RFID), and smartphones] have shown promise for additional planning purposes. Some challenges to increased use of GPS data include addressing data bias; balancing precision, coverage, and confidentiality; resolving institutional issues such as data ownership; and addressing the complexity of combining these data with other sources to discern behavioral relationships. This report provides guidelines on the use of multiple sources of GPS data to understand travel behavior and activity. The guidelines are intended to provide a jump-start for processing GPS data for travel behavior purposes and provide key information elements that practitioners should consider when using GPS data. The report is structured in two volumes. Volume 1 presents the methods used and results of tests conducted. Volume II translates the results of the tests conducted into guidelines for planners and researchers to implement these procedures.