Arentze, T., Timmermans, H.J.P., Hofman, F., 2007. Creating synthetic household populations: problems and approach. Transportation Research Record, 2014, 85-91.
Beckman, R.J., Baggerly, K.A., Mckay, M.D., 1996. Creating synthetic baseline populations. Transportation Research Part A, 30(6), 415-429.
Bowman, J.L., 2004. A comparison of population synthesizers used in microsimulation models of activity and travel demand. Draft paper available from http://jbowman.net/papers/2004.Bowman.Comparison_of_PopSyns.pdf Bowman, J.L.,Bradley, M., 2006. Activity-based travel forecasting model for SACOG: population synthesis. Technical Memo Number 2, prepared for Sacramento Area Council of Governments. Available from http://jbowman.net/ProjectDocuments/SacSim/SACOG%20tech%20memo%202--Pop%20Synth.20060731.pdf Bowman, J.L.,Rousseau, G., 2008. Validation of Atlanta, Georgia, regional commission population synthesizer. Transportation Research Board Conference Proceedings, 2(42), 54-62.
Eluru, N., Pinjari, A.R., Guo, J.Y., Sener, I.N., Srinivasan,S., Copperman, R., Bhat, C.R., 2008. Population updating system structures and models embedded within the comprehensive econometric microsimulator for urban systems. Transportation Research Record, 2076, 171-182.
Frick, M., Axhausen, K.W., 2004. Generating synthetic populations using IPF and Monte Carlo techniques: some new results. Presented at the 4th Swiss Transport Research Conference.
Guo, J.Y.,Bhat, C.R., 2007. Population synthesis for microsimulating travel behavior. Transportation Research Record, 2014, 92-101.
Simpson, L., Tranmer, M., 2005. Combining sample and census data in small area estimates: iterative proportional fitting with standard software. The Professional Geographer, 57(2), 222-234.
Smith, K.S., Shahidullah, M., 1995. An evaluation of population projection errors for census tracts. Journal of the American Statistical Association, 90(429), 64-71.
Smith, K.S., Tayman, J., 2003. An evaluation of population projections by age. Demography, 40(4), 741–757.
Srinivasan, S., Ma, L., Yathindra,K., 2008. Procedure for forecasting household characteristics for input to travel-demand models. Project Report of University of Florida, Florida Department of Transportation, TRC-FDOT-64011-2008, available from http://www.fsutmsonline.net/images/uploads/reports/FDOT_BD545_79_rpt.pdf Sundararajan, A.,Goulias, K.G., 2003. Demographic microsimulation with DEMOS 2000: Design, validation, and forecasting. In Transportation Systems Planning: Methods and Applications, Eds. K.G. Goulias, CRC Press, Boca Raton, Ch. 14.
Tayman, J., 1996. The Accuracy of Small-Area Population Forecasts Based On A Spatial Interaction Land-Use Modeling System. Journal of the American Planning Association, 62(1), 85-98.
Voas, D., Williamson, P., 2000. An evaluation of the combinatorial optimisation approach to the creation of synthetic microdata. International journal of population geography, 6(5), 349-366.
Williamson, P., Birkin, M., Rees, P.H., 1998. The estimation of population microdata by using data from small area statistics and samples of anonymised records. Environment and Planning A, 30(5), 785–816.
2009 Auld, Joshua A., Abolfazl Mohammadian and Kermit Wies. Population Synthesis with Subregion-Level Control Variable Aggregation.Journal of Transportation Engineering 135, no. 9 (2009): pp 632-639.
Abstract - This paper details the development of a fully customizable population synthesis program designed to be used for almost any geographic area or input variable. The design addresses several important issues that have been raised regarding other population synthesis methods, including the false-zero cell problem. To address this problem, a routine was developed that allows for the aggregation of control variable categories during execution at the subregional level based on a user-controlled aggregation threshold parameter input, which reduces the areas where false-zero cells are most likely to occur. This procedure also greatly eases the task of data preparation. As part of the study, new validation methods were developed and used to compare the new procedure against other procedures and known test variable distributions. Finally, detailed analysis regarding the trade-off between complexity and computational effort was also undertaken. The use of these new routines and validation methods along with an understanding of the trade-off between complexity and computational effort will allow for the development of more realistic synthetic populations. http://dx.doi.org/10.1061/(ASCE)TE.1943-5436.0000040 Lang, Robert E., Mariela Alfonzo and Casey Dawkins. American Demographics Circa 2109.Planning 75, no. 5 (2009): pp 10-15.
Abstract - This article provides a forecast of what the United States population may look like 100 years from now. Although estimates vary widely, depending on what scenarios of birth rates and immigration are considered, a mid-range estimate is that there will be nearly 600 million Americans in 2109, which represent just under double the current population. The United States is the only developed country that is on track to add substantial population. However, if the U.S. fails to upgrade its crumbling infrastructure, its economic growth may slow and that may diminish its attraction to immigrants. Although traditional racial and ethnic categories will lose meaning as the country's ethnic identity becomes more complex, the U.S. population will probably continue to have a majority of white residents. Cities will expand to accommodate this additional growth, and neighborhoods will become more diverse. Resources will be strained (but probably not depleted) supporting this growth, which makes energy and environmental policies vital in determining the size of the future population's impact on the environment.
Miller, John S. Socioeconomic and Travel Demand Forecasts for Virginia and Potential Policy Responses: A Report for Vtrans2035: Virginia’s Statewide Multimodal Transportation Plan, (2009), 100p.
Abstract - VTrans2035, Virginia’s statewide multimodal transportation plan, requires 25-year forecasts of socioeconomic and travel activity. Between 2010 and 2035, daily vehicle miles traveled (DVMT) will increase between 35% and 45%, accompanied by increases in population (28% to 36%), real household income (50%), employment (49%), transit trips (75%), and enplanements (104%). Of the 2.27 to 2.87 million additional Virginians forecast by 2035, most (1.72 to 2.34 million) will settle in one of four planning district commissions (PDCs). These PDCs, and their expected population increases, are George Washington Regional (0.25 to 0.28 million), Richmond Regional (0.33 to 0.41 million), Hampton Roads (0.31 to 0.41 million), and Northern Virginia (0.83 to 1.23 million). Virginia will likely see the number of people age 65 and over double from 1 million at present to 2 million in 2035. Four potential policy responses to these forecasts are given in this report: (1) encourage increased density at select urban locations to reduce CO2 emissions; (2) use cost-effectiveness as a criterion to select project-level alternatives for achieving a particular goal; (3) identify policy initiatives to serve increased demographic market segments, and (4) quantify the economic harm of general aviation airport closures. These policy responses are not the only ones feasible but were selected because they necessitate the interagency coordination that is the premise of VTrans2035. The first two policy responses demonstrate limited but real promise. The first may reduce DVMT by 1.1% to 6.4% of the baseline 2035 DVMT forecast, for a reduction of 1.507 million metric tons of CO2 annually. Yet DVMT is affected to a greater degree by factors over which decision makers exert less influence than with density. For example, the 2035 baseline DVMT decreases by 7% if an alternative population forecast is assumed; 10% to 65% if real household income remains relatively flat; and 49% to 82% if fuel costs increase to $10/gal by year 2035. Thus, the best estimates of travel activity are highly sensitive to underlying assumptions regarding economic conditions, and the report accordingly documents, for each desired forecast, a range of possible values. The analysis of the second policy response found that the cost-effectiveness of plausible alternatives in a hypothetical case study varied by a factor of 3. By extension, this finding suggests that an ability to choose project alternatives based solely on each alternative’s ability to meet a single goal or a limited number of goals—and without constraint by funding source (e.g., highway or transit, capital or operations)—can increase the cost-effectiveness of a project. The remaining two policy responses suggest that consideration of diverse alternatives, such as programs to help older persons continue driving, may be productive as suggested in some literature. Because the report does not contain the data necessary to evaluate the impacts of these programs, the report merely identifies such programs and demonstrates how they could be considered given the demographic changes forecast to occur between now and 2035. http://www.virginiadot.org/vtrc/main/online_reports/pdf/09-r16.pdf
http://ntl.bts.gov/lib/37000/37700/37769/09-r16.pdf Tirumalachetty, Sumala and Kara M. Kockelman. Microsimulation of Household and Firm Behaviors: Anticipation of Greenhouse Gas Emissions for Austin, Texas, (2009), 129p.
Abstract - Anthropogenic greenhouse gas (GHG) emissions can be attributed to household and firm travel and building decisions. This study demonstrates the development and application of a microsimulation model for household and firm evolution and location choices over time, along with evolution of the light duty vehicle fleet, residential building stock and travel decisions of persons and businesses in Austin, Texas over a 25-year period (from 2005 to 2030). Year 2005 zonal-level population and address-level employment data for the Austin, Texas region, coupled with various other aggregate data sets, are used to simulate the evolution of individual households and firms over time and space. Simulation results suggest a nearly 130% increase in vehicle-miles traveled (VMT), as population increases. and nearly the same increase in GHG emissions under the business-as-usual scenario. Total GHG emissions from household energy consumption are predicted to increase nearly 86% over the 25-year forecast period in the base scenario, and around 70% in other scenarios. In contrast, average energy demand per firm is predicted to increase by 57% over the 25-year forecast period, mainly due to a transition to larger firm sizes. http://swutc.tamu.edu/publications/technicalreports/167272-1.pdf
http://ntl.bts.gov/lib/31000/31100/31179/167272-1.pdf Ye, X., Konduri, K., Pendyala, R.M., Sana,B., Waddell, P., 2009. Methodology to match distributions of both household and person attributes in generation of synthetic populations. Presented at the 88th Annual Meeting of Transportation Research Board, Washington D.C.
2010 Auld, Joshua and Abolfazl Mohammadian. Efficient Methodology for Generating Synthetic Populations with Multiple Control Levels.Transportation Research Record: Journal of the Transportation Research Board, no. 2175 (2010): pp 138-147.
Abstract - This paper details a new methodology for controlling attributes on multiple analysis levels in a population synthesis program. The methodology determines how household- and person-level characteristics can jointly be used as controls when populations are synthesized as well as how other multiple-level synthetic populations, such as firm and employee or household and vehicle, can be estimated. The use of multilevel controls is implemented through a new technique involving the estimation of household selection probabilities on the basis of the probability of observing each household, given the required person-level characteristics in each analysis zone. The new procedure is a quick and efficient method for generating synthetic populations that can accurately replicate desired person-level characteristics. http://dx.doi.org/10.3141/2175-16 Auld, Joshua, Taha H. Rashidi, Abolfazl Mohammadian and Kermit Weis. Evaluating Transportation Impacts of Forecast Demographic Scenarios Using Population Synthesis and Data Transferability, (2010) 15p.
Abstract - A population synthesis tool has been developed which allows an analyst to input future demographic scenarios for a modeled region to generate forecast year synthetic populations. The utility allows both direct manipulation of base-year marginal distributions for the forecast scenario and incorporates new models to estimate changes in the marginal distribution for some significant control variables. The models allow for an improved estimation of forecast year marginal totals. To demonstrate the application of the new utility, a travel data simulation model has been estimated and validated which enables the transference of a collection of travel demand indicators from a source, the National Household Travel Survey, to the forecast year synthetic population. The combination of the synthetic population with the simulated travel demand indicators will allows for an analysis of potential transportation impacts of estimated demographic changes without running a complete travel demand model when investigating multiple scenarios.
Transportation Research Board 89th Annual MeetingTransportation Research BoardWashington,DC,USA StartDate:20100110 EndDate:20100114 Sponsors:Transportation Research Board - Transportation Research Board 89th Annual MeetingTransportation Research BoardWashington,DC,USA StartDate:20100110 EndDate:20100114 Sponsors:Transportation Research Board, Cation,
Gargiulo F., Ternes, S., Huet, S., Deffuant, G., 2010. An iterative approach for generating statistically realistic populations of households. PLoS ONE, 5(1), e8828, doi:10.1371/journal.pone.0008828.
Javanmardi, Mahmoud, Taha H. Rashidi and Abolfazl Mohammadian. Household Travel Data Simulation Tool: Software and Its Applications for Impact Analysis.Transportation Research Record: Journal of the Transportation Research Board, no. 2183 (2010): pp 9-18.
Abstract - Data transferability is seen as an alternative solution to costly travel surveys for urban areas where regular travel data are difficult to collect, especially in small and mid-sized communities. A comprehensive travel data transferability model and a software tool that can facilitate travel data transferability and simulate synthetic household-level disaggregate travel data have been developed. The model is built on earlier transferability studies by a significant enhancement of the approach and resolution of many limitations of previous studies. The software tool has been tested on two case studies in Des Moines, Iowa, and New York State. Nine household-level travel attributes are simulated for the synthetic population of these regions. A comparison of the simulated travel data with the actual observed data, obtained from the National Household Travel Survey add-on samples, proves the accuracy of the model. It is also shown that updating the parameters of the distributions of travel attributes can further improve the results. The model is then used for some basic policy evaluations and a sensitivity analysis that includes scenarios such as changes to the demographics, aging population, and investments in the education system. The result of the sensitivity analysis also confirmed the wide capabilities of the model. Notes - (Kouros) http://dx.doi.org/10.3141/2183-02 Mohammadian, Abolfazl, Mahmoud Javanmardi and Yongping Zhang. Synthetic Household Travel Survey Data Simulation.Transportation Research Part C: Emerging Technologies 18, no. 6 (2010): pp 869-878.
Abstract - Due to the high cost, low response rate and time-consuming data processing, few metropolitan planning organizations can afford collecting household travel survey data as frequently as needed. This paper presents a methodology to simulate disaggregate and synthetic household travel survey data by examining the feasibility of the spatial transferability of travel data. Households are clustered into several homogeneous groups to identify the distributions of their travel attributes. These distributions are then transferred to similar groups in other regions. Furthermore, updating methods are suggested and developed to calibrate the parameters of the transferred distributions for the application area. A user friendly software is developed that facilitates the entire process. To validate the model, a synthetic population for the state of New York, excluding the New York City, is generated by a two-stage population synthesis procedure. Then, travel attributes of each household are simulated and by linking the generated travel data to the synthetic population, a synthetic household travel dataset is generated for the application context. Finally, using a new validation dataset from the application area, comparisons against the simulated data are made to examine the effectiveness of the simulation process. http://www.sciencedirect.com/science/article/B6VGJ-4YP16SD-1/2/166b4662840d37af03564b048f6f12a5 Ryan, J., Maoh, H., Kanaroglou, P., 2010. Population synthesis for micorsimulating urban residential mobility. Presented at the 89th Annual Meeting of Transportation Research Board, Washington D. C.
Smith, Larry T. An Economical Methodology for Development of Land Use and Socio-Economic Forecasts for Long-Range Transportation Plans (Lrtps), (2010) 9p.
Abstract - The Central Mississippi Planning and Development (CMPDD), the Metropolitan Planning Organization (MPO) for the Jackson, MS area, developed an innovative methodology for forecasting population, number of dwelling units, employment and school enrollment based upon adopted Land Use Plans from counties and municipalities (most of which the CMPDD prepared) in the study area for the 2030 Jackson Urbanized Area Transportation Plan (the Long-Range Transportation Plan). That LRTP was part of the Statewide Mississippi Unified Long-Range Transportation Infrastructure Plan (MULTIPLA), which won an American Association of State Highway and Transportation Officials (AASHTO) award for State-MPO cooperation. The forecast methodology utilized measurements of acreage from adopted Land Use Plans for various land uses, including residential, commercial, industrial, and public/quasi-public uses, and applied residential population density factors from the ITE Trip Generation Manual to develop the forecasts. These forecasts were applied by a consultant, using TRANSCAD traffic simulation software, to develop traffic projections for all arterial and collector roadways in the study area to determine where traffic capacity deficiencies would occur in 10-year increments for 2010, 2020 and 2030. The presenter will use a power point presentation to discuss how the methodology was utilized to prepare the population and other forecasts and the development of the 2030 Jackson Urbanized Area Transportation Plan. This economical methodology is particularly useful for small or medium-sized MPO’s which do not have a large staff to develop the necessary forecasts for an LRTP.
12th National Conference on Transportation Planning for Small and Medium-Sized CommunitiesTransportation Research BoardFederal Highway AdministrationFederal Transit AdministrationWilliamsburg,VA,USA StartDate:20100922 EndDate:20100924 Sponsors:Transportation Research Board, Federal Highway Administration, Federal Transit Administration - 12th National Conference on Transportation Planning for Small and Medium-Sized CommunitiesTransportation Research BoardFederal Highway AdministrationFederal Transit AdministrationWilliamsburg,VA,USA StartDate:20100922 EndDate:20100924 Sponsors:Transportation Research Board, Federal Highway Administration, Federal Transit Administration, Cation,
Lee, Der-Horng and Yingfei Fu. Cross-Entropy Optimization Model for Population Synthesis in Activity-Based Microsimulation Models.Transportation Research Record: Journal of the Transportation Research Board, no. 2255 (2011): pp 20-27.
Abstract - Microsimulation techniques for disaggregate activity-based travel demand models are expected to synthesize a desired number of fully specified individual activity patterns. A data prerequisite for this technique is the so-called synthetic population, a key input for activity-generating procedures. The iterative proportional fitting method has been widely used to estimate the multiway demographic tables for different geographic areas. This study proposed a cross-entropy optimization model in which generalized constraints for different demographic characteristics of the synthetic population could be included. A quasi-Newton algorithm was devised to solve the proposed problem. Encouraging results obtained from the model application suggested that the proposed method held much promise for generating a more realistic synthetic population with different types of demographic characteristics and could be generally applied in different geographic areas. http://dx.doi.org/10.3141/2255-03 Ma, L. (2011) Generating disaggregate population characteristics for input to travel demand models. Ph.D. Dissertation, the University of Florida, USA.
Mueller, K. and K. W. Axhausen. Occam's Razor and Some Randomness: Generating a Synthetic Population for Switzerland, (2011) Abstract - Agent-based microsimulation models simulate the behavior of agents over time. For land use models (e.g., UrbanSim), time is measured in years, and the simulations aims at predicting a future system state. In contrast, transportation models (e.g., MATSim-T) estimate the utilization of the network during one day. For both kinds of models, the initial step is the definition of agents and their relationships. Synthesizing the population of agents often is the only solution, due to privacy and cost constraints. In this paper, the authors assume that the model simulates persons grouped into households, and a person/household population needs to be synthesized. However, the methodology presented here can be applied to other kinds of agent relationships as well, e.g. persons and jobs/workplaces or persons and activity chains. Generating a synthetic population requires (a) reweighting of an initial population, taken from census or other survey data, with respect to current constraints, and (b) choosing the households that belong to the generated population. The reweighting task can be performed using an Iterative Proportional Fitting (IPF) procedure, which obeys the Principle of Minimum Discrimination Information. However, IPF cannot control for attributes at both person and household levels. A frequently applied pattern is to estimate household-level weights using IPF, so that they match the control totals for the households, and then, using the household-level weights, generate a population of households that best fits the person-level control totals. Recently, an alternative fitting routine named Iterative Proportional Updating (IPU) has been proposed. IPU is capable of estimating household-level weights that fit the control totals at both person and household levels. After such a multi-level fitting procedure, the generation of synthetic households relies only on the estimated weights and does not need to control at person level anymore. Another approach to multi-level fitting presented in recent literature is to estimate the weights directly with the objective to minimize relative entropy, in accordance to the Principle of Minimum Discrimination Information. The authors use both procedures, and a novel algorithm for multi-level fitting, to generate synthetic populations of Switzerland. The three approaches are compared with respect to convergence speed, ease of implementation, and goodness-of-fit -- for the latter, the authors check the generated population against the complete Swiss census. This will help choosing a good strategy for multi-level fitting. A common feature of many recent synthesis procedures is the replication of persons and households: The generated population does not contain any persons or households not present in the reference sample. This is a problem if the number of attributes is large and the reference sample is considerably smaller than the target population: In this case, many identical individuals will be generated. The authors evaluate a novel approach to introduce heterogeneity in the synthetic population while preserving its statistical properties. For their Switzerland case study, the authors compare two synthetic populations, with and without heterogeneity, to each other. This evaluation will serve as a proof of concept for their procedure.
European Transport Conference 2011Association for European TransportTransportation Research BoardGlasgow,Scotland StartDate:20111010 EndDate:20111012 Sponsors:Association for European Transport, Transportation Research Board - European Transport Conference 2011Association for European TransportTransportation Research BoardGlasgow,Scotland StartDate:20111010 EndDate:20111012 Sponsors:Association for European Transport, Transportation Research Board, Cation,