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Uses of Census Data in Transportation

Modeling and Forecasting

Advances in Agent Population Synthesis and Application in an Integrated Land Use and Transportation Model

Authors: Pritchard, David R; Miller, Eric J Transportation Research Board-500 Fifth Street, NW Washington, DC 20001

Transportation Research Board 88th Annual Meeting

Publication Date: 2009

Abstract:

Agent-based microsimulation models of socioeconomic processes require an initial synthetic population derived from census data. This paper builds upon the Iterative Proportional Fitting (IPF) procedure's well-understood statistical properties. While typical applications of IPF are limited in the number of attributes that can be synthesized per agent, a new method introduced here implements IPF with a sparse list-based data structure that allows many more attributes per agent. Additionally, a new approach is used to synthesize the relationships between agents, allowing the formation of household and family agents in addition to individual person agents.

Subject Areas and Index Terms

Highways; Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning

Data collection; Land use planning; Microsimulation; Population growth; Public transit; Socioeconomic factors; Statistical analysis; Transit operating agencies; Travel surveys; Agent based models; Iterative proportional fitting

Availability: Transportation Research Board Business Office

Modeling and Forecasting

An area-level model of vehicle-pedestrian injury collisions with implications for land use and transportation planning

Authors: Wier, Megan; Weintraub, June; Humphreys, Elizabeth H; Seto, Edmund; Bhatia, Rajiv

Accident Analysis & Prevention

Publication Date: Jan 2009

Abstract:

There is growing awareness among urban planning, public health, and transportation professionals that design decisions and investments that promote walking can be beneficial for human and ecological health. Planners need practical tools to consider the impact of development on pedestrian safety, a key requirement for the promotion of walking. Simple bivariate models have been used to predict changes in vehicle-pedestrian injury collisions based on changes in traffic volume. We describe the development of a multivariate, area-level regression model of vehicle-pedestrian injury collisions based on environmental and population data in 176 San Francisco, California census tracts. Predictor variables examined included street, land use, and population characteristics, including commute behaviors. The final model explained approximately 72% of the systematic variation in census-tract vehicle-pedestrian injury collisions and included measures of traffic volume, arterial streets without transit, land area, proportion of land area zoned for neighborhood commercial and residential-neighborhood commercial uses, employee and resident populations, proportion of people living in poverty and proportion aged 65 and older. We have begun to apply this model to predict area-level change in vehicle-pedestrian injury collisions associated with land use development and transportation planning decisions.

Subject Areas and Index Terms

Highways; Pedestrians and Bicyclists; Planning and Forecasting; Safety and Human Factors

Collisions; Land use planning; Multivariate analysis; Pedestrian accidents; Pedestrian safety; Regression analysis; Spatial analysis; Traffic volume; Transportation planning; San Francisco (California)

Availability: Find a library where document is available

Order URL: http://worldcat.org/issn/00014575

Modeling and Forecasting

An Investigation in Household Mode Choice Variability across Metropolitan Statistical Areas for Urban Young Professionals

Authors: Long, Liang; Lin, Jie World Conference on Transport Research Society-Secretariat, 14 Avenue Berthelot 69363 Lyon cedex 07,

11th World Conference on Transport Research

Publication Date: 2007

Abstract:

Contextual effects, especially associated with geographical variability, on travel behavior must be considered in spatial transferability of household travel survey data and demand model coefficients. In this paper a hierarchical modeling approach is applied to quantify geographical variability of household shopping trip mode choice by neighborhood type (defined by census tract) across eight metropolitan statistical areas. Residents of the neighborhoods studied are primarily urban young professionals. The individual level variables come from the 2001 National Household Travel Survey (NHTS) and the neighborhood level variables are derived from the Census Transportation Planning Package (CTPP) 2000. The model results confirm mode choice is dependent on where the household lives after controlling for household characteristics. With the similar household and census tract features the variability of household mode choice across geographic areas can be ignored. Lastly, the model limitations and future research are discussed.

Subject Areas and Index Terms

Highways; Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning

Households; Mode choice; Public transit; Travel behavior; Travel surveys; Trip purpose; Urban transportation; Young adults

Availability: World Conference on Transport Research Society

Modeling and Forecasting

Applying the TRANSIM Model Paradigm to the Simulation and Analysis of Transportation and Traffic Control Systems

Authors: Dixon, Michael P; Chang, Karl; Keecheril, Sajeev; Orton, Brent National Institute for Advanced Transportation Technology-University of Idaho, P.O. Box 440901 Moscow, ID 83844-0901 ; Research and Special Programs Administration-1200 New Jersey Avenue, SE Washington, DC 20590

Monograph

Publication Date: Mar 2007

Abstract:

This report focuses on improving the TRANSIMS transportation planning model. TRANSIMS has been validated to a limited degree for traffic operations due to the lack of readily available standard performance measures and operations data output. This studied developed a Traffic Data Extractor Tool (TDET) that provides more useful performance measures that those of TRANSIMS. Validation results for unsignalized intersections concluded that TRANSIMS tends to over estimate control delays and major street left turns are not modeled accurately. For signalized intersections, TRANSIMS performed very well. Compared with the field data, in some cases TRANSIMS surpassed Highway Capacity Software. Transportation planning models are also reliant upon demographic knowledge associated with traffic analysis zones (TAZs). Census data is an obvious choice for "loading" TAZs with demographic data. These demographic input data are limited since TAZs must be either be a size equal to the smallest census data level or composed of combined elements of the census data, forming larger TAZs. Part 2 provides a methodology for incorporating remotely sensed data and local land use zoning data to disaggregate the census block demographics to smaller, user defined TAZs thus providing a higher spatial resolution to the planning model process and increasing model accuracy.

Subject Areas and Index Terms

Highways; Operations and Traffic Management; I73: Traffic Control

Highway capacity; Highway operations; Traffic control; Traffic data; Traffic delay; Traffic simulation; Transportation planning; Travel demand; Unsignalized intersections; Validation; TRANSIMS (Computer model); Traffic analysis zones

Availability: National Technical Information Service

Modeling and Forecasting

California Statewide Exploratory Analysis Correlating Land Use Density, Infrastructure Supply, and Travel Behavior

Authors: Yoon, Seo Youn; Golob, Thomas F; Goulias, Konstadinos G Transportation Research Board-500 Fifth Street, NW Washington, DC 20001

Transportation Research Board 88th Annual Meeting

Publication Date: 2009

Abstract:

The critical link between land use and transportation is human environment relations. Measurement of the environment includes representation of the spatial opportunities available to engage in activities and the infrastructure accessed by trip makers. In this paper an experiment is reported using travel behavior data from the statewide travel survey in California and a variety of activity opportunity measures at two different levels of geographic aggregation that are the tract and the block group levels covering the entire state. Using regression models the authors find these spatial measures to be significant explanatory variables and that measures form both aggregation levels explain behavior capturing a variety of complex influences. This study is also a demonstration that land use indicators and infrastructure availability can be included in travel behavior equations used in the four step and/or activity based forecasting models with largely available data in the Census Transportation Planning Package, network data available in transportation agencies, and typical regression methods included in statistical packages. Next steps are also outlined in the paper.

Subject Areas and Index Terms

Highways; Planning and Forecasting; I72: Traffic and Transport Planning

Cluster analysis; Land use planning; Population density; Regression analysis; Traffic forecasting; Transportation planning; Travel behavior; Travel surveys; California

Availability: Transportation Research Board Business Office

Modeling and Forecasting

Development of a Florida Modeling Portal: Summary

Authors: Gan, Albert Florida International University, Miami-Lehman Center for Transportation Research, 10555 W Flagler Street Miami, FL 33174 ; Florida Department of Transportation-605 Suwannee Street Tallahassee, FL 32399-0450

Monograph

Publication Date: Mar 2007

Abstract:

Researchers developed an information portal named FSUTMSOnline (www.fsutmsonline.net). The portal serves as a central location for the exchange and sharing of information, data, and ideas for transportation modelers in Florida. The portal was developed as a weblog application that allows easy and frequent updates by designated administrators who do not need to be familiar with web programming. The developed portal includes individual pages for the Model Task Force (MTF), modeling newsletters, training workshops, model documentation, travel data, research projects, technical support, discussion forum, and useful links. Researchers also created pages for individual FSUTMS standard models to allow model coordinators to post model and data files for easy access by transportation modelers. The system includes a model download permitting process to allow users to make download requests for review and approval by model coordinators. This permitting process is designed to safeguard the use of model files. The portal includes other typical features, such as a mailing list sign-up and quick links to external web pages. A centerpiece of the web portal is a GIS application designed to facilitate the maintenance and extraction of data for FSUTMS model inputs. Developed as an ArcGIS Server 9.2 application, it includes data for the following: highway, transit, and Transportation Analysis Zone (TAZ) networks; roadway inventory information from the Roadway Characteristics Inventory (RCI); census data at the tract, block group, and block levels; employment data from InfoUSA; and multiple years of traffic count data from both permanent and portable traffic monitoring stations.

Subject Areas and Index Terms

Data and Information Technology; Freight Transportation; Highways; Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning

ArcGIS; Census; Data sharing; Employment; Florida; Geographic information systems; Highways; Information exchange; Inventory; Permits; Public transit; Traffic analysis zones; Traffic counts; Transportation data; Transportation models; Web portals

Availability: Research and Innovative Technology Administration

Modeling and Forecasting

Discrete-Continuous Microsimulation of Development Decisions in a Spatial Market Model

Authors: Abraham, John E; Hunt, John Douglas World Conference on Transport Research Society-Secretariat, 14 Avenue Berthelot 69363 Lyon cedex 07,

11th World Conference on Transport Research

Publication Date: 2007

Abstract:

A microsimulation of development decisions in Ohio is described in this paper where land developers respond to construction costs and floor space rents. The simulation incrementally changes the spatial built form of Ohio over several decades by changing the state variables of 4 acre units of land covering the entire state and a surrounding halo. A mixed discrete-continuous logit model is used, with the utility of the discrete choice of future development type being the expected maximum of the choice of development intensity within the range development type. The utility of one particular development-type/intensity option is a function of construction cost variables and the rent revenue. The continuous formulation is shown to provide appropriate expected values as long as reasonable ranges of intensity are allowed and dispersion parameters are appropriate. Initial residential data consisted of Census data and acres of land by development type. Initial continuous intensities for residential space were developed through a simultaneous two-level optimization procedure. The first level is a Langrangian optimization of the relative use of development types by zones, the second level a genetic algorithm to determine the average consumption rates of land by different household income and size categories. The residuals of this procedure were interpreted as the variation in intensity within development types. User input data for land attributes consists of discrete distributions by traffic analysis zone (TAZ). Joint distributions of pairs of attributes are sometimes also specified, in which case matrix expansion is used to ensure consistency with the single-variable distributions. From the distributions land is discretized, to support the microsimulation approach and future integration with geographic information system (GIS) grid-cell layers.

Subject Areas and Index Terms

Highways; Planning and Forecasting; I72: Traffic and Transport Planning

Data collection; Development; Discrete systems; Geographic information systems; Land use planning; Microsimulation; Transportation planning; Zoning; Ohio; Discrete choice; Traffic analysis zones

Availability: World Conference on Transport Research Society

Modeling and Forecasting

Exploring Causal Connections Among Job Accessibility, Employment, Income, and Automobile Ownership Using Structural Equations Modeling

Authors: Gao, Shengyi; Mokhtarian, Patricia L; Johnston, Robert A Transportation Research Board-500 Fifth Street, NW Washington, DC 20001

Transportation Research Board 86th Annual Meeting

Publication Date: 2007

Abstract:

Using structural equation modeling, this study empirically examines the causal connections between job accessibility, workers per capita, income per capita, and autos per capita at the aggregate level with year 2000 census tract data in Sacramento County, California. Under the specification of the conceptual model, the model implied covariance matrix exhibits a reasonably good fit to the observed covariance matrix. The direct and total effects show that job accessibility has a negative effect on autos per capita, autos per capita has a positive effect on workers per capita and income per capita, workers per capita has a positive effect on income per capita and autos per capita, and education attainment has a positive effect on workers per capita, income per capita and autos per capita. Job accessibility has a negative total effect on workers per capita, income per capita and autos per capita. These results are largely consistent with theory and/or with empirical observations across a variety of geographic contexts. They suggest that structural equation modeling is a powerful tool for capturing the endogeneity among job accessibility, employment, income and auto ownership, and has other advantages over linear regression in this context.

Subject Areas and Index Terms

Data and Information Technology; Highways; Planning and Forecasting; Policy; I21: Planning of Transport Infrastructure

Accessibility; Automobile ownership; Employment; Income; Industrial location; Land use planning; Regression analysis; Residential location; Spatial analysis; Structural equation modeling; Transportation policy; Travel demand; Sacramento County (California

Availability: Transportation Research Board Business Office

Order URL: http://gulliver.trb.org/news/blurb_detail.asp?id=7286

Modeling and Forecasting

Forecasting Pedestrian and Bicycle Demands Using Regional Travel Demand Models and Local Mode Share/Trip Distance Data

Authors: Horowitz, Zachary; Parisi, David; Replinger, John Transportation Research Board-500 Fifth Street, NW Washington, DC 20001

Transportation Research Board 89th Annual Meeting

Publication Date: 2010

Abstract:

Columbia River Crossing (CRC) staff, with input from the CRC's Pedestrian and Bicycle Advisory Committee (PBAC), developed a methodology for forecasting year 2030 pedestrian and bicycle travel demands for an improved non-motorized facility proposed for the replacement Interstate 5 (I-5) Bridge across the Columbia River. Forecasts took into account three primary factors related to pedestrian and bicycle demand: existing and future land uses, percentage of trips by mode, and walking and bicycling trip lengths. During peak summer conditions in 2007, about 80 pedestrians and 370 bicyclists crossed the I-5 Bridge daily. Many other pedestrians and bicyclists are discouraged from doing so because of the existing non-standard facilities on the bridge and connecting multi-modal infrastructure. Future pedestrian and bicycle trips over the I-5 Bridge were forecast using a variety of data, including mode share data from the US Census, information from local travel surveys, results from a bicycle trip study conducted by Portland State University, and travel characteristics associated with the Hawthorne Bridge, the heaviest traveled bridge by pedestrians and bicyclists in the region. Average travel times by mode were converted into trip distances by mode, creating a matrix of pedestrian and bicycle mode shares by trip length. Future scenarios, developed for sensitivity testing, considered the forecasted number of trips from the regional travel demand model and factored them by the respective pedestrian and bicycle mode share percentages. The results were a range of daily pedestrian and bicycle forecasts, all of which showed a substantial increase in travel demand.

Subject Areas and Index Terms

Pedestrians and Bicyclists; Planning and Forecasting; I21: Planning of Transport Infrastructure

Bicycle commuting; Bicycling; Cyclists; Modal split; Pedestrian safety; Traffic forecasting; Travel demand; Walkways; Portland Metropolitan Area (Oregon); Columbia River Bridge; Interstate 5

Availability: Transportation Research Board Business Office

Modeling and Forecasting

Improving Socioeconomic Forecasting for Medium-Sized Metropolitan Planning Organizations in Virginia

Authors: McCray, Danielle R; Miller, John S; Hoel, Lester A Virginia Transportation Research Council-530 Edgemont Road Charlottesville, VA 22903 ; Virginia Department of Transportation-1401 East Broad Street Richmond, VA 23219 ; Federal Highway Administration-1200 New Jersey Avenue, SE Washington, DC 2059

Monograph

Publication Date: Sep 2008

Abstract:

Socioeconomic forecasts are the foundation for long range travel demand modeling, projecting variables such as population, households, employment, and vehicle ownership. In Virginia, metropolitan planning organizations (MPOs) develop socioeconomic forecasts for a given horizon year at a traffic analysis zone level, and the Virginia Department of Transportation (VDOT) uses these forecasts as input to the four-step travel demand model system. This report identifies the socioeconomic forecasting practices currently used by four medium-sized Virginia MPOs, computes the accuracy of socioeconomic forecasts generated by one such MPO, and recommends practices for improving such forecasts. This research found that medium-sized Virginia MPOs are using similar techniques to forecast socioeconomic variables. These techniques are to (1) identify jurisdictional population control totals based on U.S. Census and Virginia Employment Commission data; (2) disaggregate population projections to the zonal level based on comprehensive plans, local knowledge, and historic trends; (3) apply historic ratios of households to population and autos to population to forecast households and autos; (4) use historic trends and local expertise to determine future employment; and (5) revise zone projections through coordination with local jurisdictions. Using a forecast that was developed for the Lynchburg region in 1981 with a horizon year of 2000, the study area percent error was computed as the difference between the forecasted and observed values for the entire study area. While the study area percent error for number of vehicles and employment was less than 10%, the study area percent errors for population and households were 48% and 14%, respectively. Two adjacent zones accounted for approximately 80% of the population error and 90% of the household error, and the error resulted because anticipated development therein did not materialize. The zone percent error is the average difference between forecasted and observed values for each zone. Population, households, and vehicles had similar zone percent errors of 61%, 65%, and 54%, respectively, while the employment zone percent error was 154%. Four recommendations for improving forecasts are given. First, localities should provide updates to MPO or Planning District Commission (PDC) staff as changes in land development occur, and such staff should perform socioeconomic forecasts more frequently than the current practice of every five years. Second, MPOs should consider providing two sets of socioeconomic variables for the travel demand model: (1) the baseline forecast (which is the MPO's best estimate) and (2) the baseline forecast modified by some percentage that accounts for the possibility of forecast error. Third, best forecasting practices should be shared among MPOs through a user's group, a workshop, or some other forum where MPO and PDC staff will be in attendance. Fourth, VDOT should communicate these recommendations to MPO staff who are responsible for completing socioeconomic forecasts.

Subject Areas and Index Terms

Economics; Highways; Planning and Forecasting; Research; Society; I72: Traffic and Transport Planning

Accuracy; Automobile ownership; Case studies; Employment; Error analysis; Forecasting; Households; Medium sized cities; Metropolitan planning organizations; Population forecasting; Recommendations; Socioeconomic factors; Travel demand; Lynchburg (Virginia

Availability: National Technical Information Service

Modeling and Forecasting

Investigating Contextual Variability in Mode Choice in Chicago Using a Hierarchical Mixed Logit Model

Authors: Long, Liang; Lin, Jie; Proussaloglou, Kimon

Urban Studies

Publication Date: Oct 2010

Abstract:

In this paper, a hierarchical random-coefficient mixed logit model is applied to quantify variability in commuters' mode choice in the Chicago metropolitan area, especially concerning the contextual variability by the traits of census tract of residence. It is found that individual mode choice behavior varies considerably across residential locations. Moreover, the contextual effects are found to modify the marginal utility of mode choice. Especially, in-vehicle travel time and gasoline cost are significant covariates of census tract traits (such as percentage of blue-collar residents, ethnicity). Furthermore, random variation is present even after both contextual and individual traits are controlled for, suggesting intrinsic randomness in individual mode choice. The hierarchical structure of quantifying contextual variability proves to be a useful tool in capturing intrinsic heterogeneity in mode choice. The study findings have important implications for integrated land use and transport planning especially at the geographical levels below that of the region.

Subject Areas and Index Terms

Highways; Planning and Forecasting; I72: Traffic and Transport Planning

Commuters; Commuting; Logits; Mode choice; Strategic planning; Travel behavior; Trip length; Chicago (Illinois)

Availability: Find a library where document is available

Order URL: http://worldcat.org/issn/00420980

Modeling and Forecasting

Investigating Network Access and Agglomeration Economy Using Spatial Autoregressive Models

Authors: He, Sylvia Y Transportation Research Board-500 Fifth Street, NW Washington, DC 20001

Transportation Research Board 88th Annual Meeting

Publication Date: 2009

Abstract:

Transport network accessibility is a known determinant of employment center growth. Firms value access to the regional transport network and major transportation hubs. However, as the urban form shifts from monocentric to polycentric, the value associated with regional transportation network access may have been significantly reduced. Local accessibility, which would facilitate interactions between firms located in close proximity, may have become more important in the new urban form. In this paper, I calibrate the weights matrices of spatial autoregressive models to examine whether local network access is more important than regional network access in the size of employment centers. The data consist of 541 census tracts inside the 41 employment centers in the Los Angeles region of 2000. Results show that spatial autoregressive models improve the goodness-of-fit compared with OLS. More importantly, autoregressive models with certain calibrated weights matrix outperform others. The outcome suggests that there are stronger economic interactions among intra-center tracts than inter-center tracts. The results shed a new light on transportation planning that policy makers may focus on improving local accessibility through transportation investments to facilitate growth of employment centers.

Subject Areas and Index Terms

Highways; Passenger Transportation; Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning

Accessibility; Central business districts; Hubs; Public transit; Regional planning; Regional transportation; Transit operating agencies; Travel surveys; Autoregressive models; Employment centers

Availability: Transportation Research Board Business Office

Modeling and Forecasting

Making Best Estimates of Spatial Distribution of Average Household Vehicle Miles Traveled: Assays in San Francisco Bay Area and Boston Metropolitan Region

Authors: Rooney, Michael Steven; Srinivasan, Sumeeta Transportation Research Board-500 Fifth Street, NW Washington, DC 20001

Transportation Research Board 87th Annual Meeting

Publication Date: 2008

Abstract:

This report proposes a technique for estimating the spatial variation of average household vehicle-miles traveled (VMT). The dependent variable, VMT, is estimated for block groups in the metropolitan regions of two cities-San Francisco, CA, and Boston, MA. The independent variables were obtained from the U.S. Census and include variables such as commute time to work and percentage of workers using public transit. Model-predicted values for zip-code-level VMT demonstrate a correlation coefficient of 0.90 with values imputed from Massachusetts state vehicle inspections data. These findings are proposed as evidence that "snap-shot" estimates of urban and regional variations in household VMT may be possible through the manipulation of freely available Census data. However, the results do indicate spatial autocorrelation and future estimates must take into account such spatial anomalies in estimating VMT.

Subject Areas and Index Terms

Highways; Passenger Transportation; Planning and Forecasting; Society; I72: Traffic and Transport Planning

Commuters; Households; Traffic data; Travel surveys; Travel time; Trip purpose; Vehicle miles of travel; Work trips; Boston Metropolitan Area; San Francisco Bay Area

Availability: Transportation Research Board Business Office

Modeling and Forecasting

Methodology to Match Distributions of Both Household and Person Attributes in Generation of Synthetic Populations

Authors: Ye, Xin; Konduri, Karthik Charan; Pendyala, Ram M; Sana, Bhargava; Waddell, Paul Transportation Research Board-500 Fifth Street, NW Washington, DC 20001

Transportation Research Board 88th Annual Meeting

Publication Date: 2009

Abstract:

The advent of microsimulation approaches in travel demand modeling, wherein activity-travel patterns of individual travelers are simulated in time and space, has motivated the development of synthetic population generators. These generators typically use census-based marginal distributions on household attributes to generate joint distributions on variables of interest using standard iterative proportional fitting (IPF) procedures. Households are then randomly drawn from an available sample in accordance with the joint distribution such that household-level attributes are matched perfectly. However, these traditional procedures do not control for person-level attributes and joint distributions of personal characteristics. In this paper, a heuristic approach, called the Iterative Proportional Updating (IPU) algorithm, is presented to generate synthetic populations whereby both household-level and person-level characteristics of interest can be matched in a computationally efficient manner. The algorithm involves iteratively adjusting and reallocating weights among households of a certain type (cell in the joint distribution) until both household and person-level attributes are matched. The algorithm is illustrated with a small example, and then demonstrated in the context of a real-world application using small geographies (blockgroups) in the Maricopa County of Arizona in the United States. The algorithm is found to perform very well, both from the standpoint of matching household and person-level distributions and computation time. It appears that the proposed algorithm holds promise to serve as a practical population synthesis procedure in the context of activity-based microsimulation modeling.

Subject Areas and Index Terms

Highways; Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning

Activity choices; Algorithms; Distributions (Statistics); Households; Microsimulation; Systems analysis; Maricopa County (Arizona); Activity based modeling; Iterative proportional fitting; Person trips

Availability: Transportation Research Board Business Office

Modeling and Forecasting

Mid-Ohio Regional Planning Commission Model Validation: Summary

Authors: Schmitt, David; Donnelly, Robert M; Anderson, Rebekah S

Transportation Research Board Conference Proceedings

Publication Date: 2008

Abstract:

The new Mid-Ohio Regional Planning Commission (MORPC) model is a disaggregate tour-based model applied with the microsimulation of each individual household, person, or tour. The model area is divided into 1,805 internal and 72 external zones and includes Franklin, Delaware, and Licking counties, and parts of Fairfield, Pickaway, Madison, and Union counties. The primary inputs to the model are transportation networks and zonal data, in which each zone has the standard socioeconomic characteristics that would normally be found in a four-step model. The main differences from the prior four-step model are that the new model accounts for travel at the tour level, as opposed to the trip level, and for each individual household and person, as opposed to zonal and market segment aggregates. This summary shows the highway validation statistics, including some of the standard reports as suggested in the "Ohio Department of Transportation Traffic Assignment Procedures." It also shows the validation of the work purpose travel distribution compared with the Census Transportation Planning Package.

Subject Areas and Index Terms

Highways; Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning

Forecasting; Microsimulation; Travel demand; Validation; Mid-Ohio Regional Planning Commission; Tour-based models

Availability: Transportation Research Board Business Office

Find a library where document is available

Order URL: http://worldcat.org/isbn/9780309113434

Modeling and Forecasting

Model-Based Approach to Synthesize Household Travel Characteristics across Neighborhood Types and Geographic Areas

Authors: Lin, Jie; Long, Liang

Journal of Transportation Engineering

Publication Date: Dec 2008

Abstract:

Household travel survey data are crucial in regional travel demand analysis. However, good quality data are not always available owing to financial constraints, privacy concerns, poorly designed sampling schemes, and/or low response rates. Thus, various data synthesis techniques have been proposed in the past. In this paper, we identify the limitations of the existing data updating/synthesis methods and propose a two-level random coefficient model to synthesis household travel characteristics across geographic areas. Then the two-level structure was applied to the sampled households in the 2001 National Household Travel Survey across (consolidated) metropolitan statistical areas of various population sizes. One particular travel characteristic, journey to work vehicle trip rate, is investigated. The study findings confirm the effect of neighborhood (defined at the census tract level) attributes (e.g., intersection density, average auto mobile work trip travel time) on household number of journey to work vehicle trips. This effect is significant on the urban households of study, whereas the suburban counterparts across the country do not seem to be affected by their living environments after controlling for neighborhood type. In general, the two-level structure is shown statistically superior to the one level.

Subject Areas and Index Terms

Highways; Planning and Forecasting; I72: Traffic and Transport Planning

Coefficients; Data processing; Data quality; Geography; Mathematical models; Neighborhoods; Travel patterns; Travel surveys; Work trips

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Order URL: http://worldcat.org/oclc/8674831

Modeling and Forecasting

Nonnormality of Data in Structural Equation Models

Authors: Gao, Shengyi; Mokhtarian, Patricia L; Johnston, Robert A

Transportation Research Record: Journal of the Transportation Research Board

Publication Date: 2008

Abstract:

With the use of census block group data on sociodemographics, land use, and travel behavior, the cutoffs suggested in the literature for trustworthy estimates and hypothesis-testing statistics were tested, and the efficacy of deleting observations as an approach to improving multivariate normality in structural equation modeling was evaluated. It was found that the deletion of enough cases to achieve multivariate normality yielded results that were substantively different from those for the full sample and required that 17% of the sample be discarded. Alternatively, after only a few true outliers were deleted (0.8% of the sample), the measures of univariate and multivariate nonnormalities fell into the acceptable range for maximum likelihood estimation to be appropriate. The pursuit of a multivariate normal distribution by the deletion of observations should be consciously weighed against the loss of model power and generalizability in the interpretation of the results. That is, the analyst should proactively find the balance between the two extremes of (a) a model on the full sample that is unreliable because of extreme nonnormality and (b) a model on a sample that has discarded so many cases to achieve multivariate normality that it is no longer fully representative of the desired population. It is further argued that the process of finding that balance should be exposed to the audience rather than ignored or suppressed.

Subject Areas and Index Terms

Data and Information Technology; Highways; Planning and Forecasting; I72: Traffic and Transport Planning

Data collection; Estimation theory; Maximum likelihood method; Multivariate analysis; Normal distributions; Statistical analysis; Structural equation modeling; Travel behavior; Travel surveys

Availability: Transportation Research Board Business Office Order URL: http://trb.org/news/blurb_detail.asp?id=9918

Find a library where document is available

Order URL: http://worldcat.org/isbn/9780309125994

Modeling and Forecasting

Population Updating System Structures and Models Embedded Within the Comprehensive Econometric Microsimulator for Urban Systems (CEMUS)

Authors: Eluru, Naveen; Pinjari, Abdul Rawoof; Guo, Jessica Y; Sener, Ipek N; Srinivasan, Sivaramakrishnan; Copperman, Rachel B; Bhat, Chandra R University of Texas, Austin-Center for Transportation Research, 3208 Red River Street Austin, TX 78705 ; Southwest Region University Transportation Center-Texas Transportation Institute, Texas A&M University College Station, TX 77843-3135

Monograph

Publication Date: Oct 2007

Abstract:

This report describes the development of a population update modeling system as part of the development of the Comprehensive Econometric Microsimulator for SocioEconomics, Land-use, and Transportation Systems (CEMSELTS). CEMSELTS itself is part of the Comprehensive Econometric Microsimulator for Urban Systems (CEMUS) under development at The University of Texas at Austin. The research in the report recognizes that modeling the linkages among demographics, land use, and transportation is important for realistic travel demand forecasting. The population update modeling system focuses on the modeling of events and actions of individuals and households in the urban region. An analysis framework is proposed to predict the future-year population characteristics by modeling the changes to all relevant attributes of the households and individuals. The models identified in the analysis framework are estimated for the Dallas-Fort Worth region. The econometric structures used include deterministic models, rate-based probability models, binary logit models, multinomial logit models, and ordered-response probit models. To verify the outputs from these models, the predicted results for the year 2000 are compared against observed 2000 Census data.

Subject Areas and Index Terms

Highways; Planning and Forecasting; Society; I72: Traffic and Transport Planning

Demographics; Econometric models; Forecasting; Land use; Microsimulation; Transportation planning; Travel demand; Urban areas; Dallas-Fort Worth Metropolitan Area

Availability: National Technical Information Service

Modeling and Forecasting

UPlan: Geographic Information System as Framework for Integrated Land Use Planning Model

Authors: Walker, W Thomas; Gao, Shengyi; Johnston, Robert A

Transportation Research Record: Journal of the Transportation Research Board

Publication Date: 2007

Abstract:

A geographic information system (GIS) framework is appealing to model supply-side decisions because spatial relationships commonly used by developers to evaluate building sites, such as the proximity to transportation facilities, existing land uses, political boundaries, and environmentally sensitive areas, are defined precisely in the GIS layers. The GIS captures spatial synergisms that are lost in tabulations by traffic zone or larger forecasting districts. Further, the results are defined for individual parcels (grids). This method interfaces directly with the concerns of residents and other interest groups. Uncertainty and error in postmodel allocations from zones to parcels in existing land use models can significantly blur and degrade the relevance of forecasts made with existing models. The development patterns predicted by UPlan, a planning model, tend to be realistic and provide a basis for land use planning and evaluation. A GIS land use survey, supplemented with simulation model networks and census data, was used to calibrate the model. The calibrated UPlan model did a reasonably accurate job of allocating the various categories of land uses to predefined composite growth areas. The generalized UPlan model is applicable in a wide variety of rural, suburban, and urban settings. The model, as presented, was configured as a travel simulation integrated land use planning tool, but the method also can be used as the supply-side component within a comprehensive land use modeling framework.

Subject Areas and Index Terms

Highways; Planning and Forecasting; Public Transportation; I21: Planning of Transport Infrastructure

City planning; Computer models; Geographic information systems; Land use; Land use planning; Urban areas; Urban design; Urban growth; Urban transportation; Integrated models (Planning)

Availability: Transportation Research Board Business Office

Order URL: http://www.trb.org/news/blurb_detail.asp?id=8392

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Order URL: http://worldcat.org/isbn/9780309104203

Modeling and Forecasting

Validation of Atlanta, Georgia, Regional Commission Population Synthesizer

Authors: Bowman, John L; Rousseau, Guy

Transportation Research Board Conference Proceedings

Publication Date: 2008

Abstract:

This paper presents the results of initial base-year and back-cast validation of the new Atlanta (Georgia) Regional Commission (ARC) population synthesizer (PopSyn), which acts as the conduit of land use information to the travel demand model. It takes information from the census and the land use model and creates a detailed synthetic population consistent with land use forecasts. A travel demand model can then predict travel for this population. The synthetic population includes a record for each household in the region and a record for each person in the household, so it is well suited for use by travel demand models employing disaggregate microsimulation. Although a PopSyn constitutes a powerful tool, it should be used with caution. By design, it provides misleadingly precise details about every person in the population. Because of limitations of its inputs and its synthesizing procedures, at best only some of the person and household characteristics accurately represent the population at the regional level of geographic aggregation, and many of those characteristics can be imprecise and inaccurate for very small geographic areas such as census tracts. A fundamental goal in the development of a PopSyn therefore is to synthesize as accurately and precisely as possible, for as disaggregate geography as possible, as many variables as possible that determine travel behavior. And a fundamental requirement in the use of a PopSyn should be to rely on it only for the characteristics it accurately represents and to aggregate results to a level at which the synthetic population is precise and accurate.

Subject Areas and Index Terms

Highways; Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning

Disaggregate analysis; Forecasting; Land use; Land use models; Travel behavior; Travel demand; Validation; Atlanta (Georgia); Atlanta Regional Commission; Population synthesis

Availability: Transportation Research Board Business Office; Find a library where document is available Order URL: http://worldcat.org/isbn/9780309113434

Modeling and Forecasting

Wisconsin Passenger and Freight Statewide Model: Case Study in Statewide Model Validation

Authors: Proussaloglou, Kimon; Popuri, Yasasvi; Tempesta, Daniel; Kasturirangan, Krishnan; Cipra, David

Transportation Research Record: Journal of the Transportation Research Board

Publication Date: 2007

Abstract:

This paper reports the model validation process for a passenger and a freight statewide model developed for the Wisconsin Department of Transportation. These policy-sensitive planning models are used to understand and quantify passenger and freight flows in Wisconsin and to support system-planning analyses at a statewide level. Examples of policies being tested include the impact of different land use scenarios and transportation projects on highway traffic, the diversion of traffic along key corridors, and the ridership potential of enhanced intercity bus service. The passenger model was estimated by using the Wisconsin add-on for the 2001 National Household Travel Survey (NHTS), and the freight model was estimated by using Transearch commodity flow data. Model validation relied on the NHTS data, statewide automobile and truck traffic counts, intercity transit ridership estimates, and 2000 U.S. Census data including the Census Transportation Planning Package, FHWA's validation manual, and NCHRP Report 365. The Wisconsin statewide models are presented as case studies to highlight the data sources, model estimation and validation methodologies, and results obtained at a statewide level. The passenger and freight validation results support the robustness of the models at a statewide and a corridor level. The methodology and standards discussed for the Wisconsin statewide models provide another data point to help establish guidelines for statewide model validation.

Subject Areas and Index Terms

Highways; Planning and Forecasting; I72: Traffic and Transport Planning

Case studies; Commodity flow; Freight and passenger traffic; Intercity travel; Travel demand; Validation; Wisconsin; Census Transportation Planning Package; National Household Travel Survey; Statewide Modeling and Forecasting

Availability: Transportation Research Board Business Office

Order URL: http://www.trb.org/news/blurb_detail.asp?id=8489

Find a library where document is available

Order URL: http://worldcat.org/isbn/9780309104296

Updated: 06/06/2011
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