Creating a Synthetic Household Travel and Activity Survey: Rationale and Feasibility Analysis

2000 ◽  
Vol 1706 (1) ◽  
pp. 82-91 ◽  
Author(s):  
S. P. Greaves ◽  
P. R. Stopher
Keyword(s):  
Survey Data ◽  
Travel Demand ◽  
Model Development ◽  
Synthetic Data ◽  
Data Set ◽  
Travel Survey ◽  
Simulation Procedure ◽  
Demand Models ◽  
Study Results ◽  
Household Travel

Proposed is a new approach for developing the travel survey data required for use in local travel-demand models. Using readily available local sociodemographic information in conjunction with a freely available national travel survey, a simulation procedure is described to create, in effect, a synthetic household travel survey. The reasons for interest in such a procedure are outlined, including the costs and difficulties associated with gathering high-quality travel data. Consideration is then given to alternatives for local model development, such as the use of national data averages and borrowed models. The simulation procedure is then described and tested in a region that has recently completed a travel survey; this provides a direct source of comparison of the merit of the approach. Trip production models are then built using the synthetic data set. The case study results show that the synthetic data ( a) offer significant improvements over the use of borrowed models and ( b) estimate new models that are similar to those same models estimated using the local travel survey data. It is concluded that these results show that the approach has considerable promise. Finally, some future directions are described, including the planned extension of the approach to other regions.

Household Travel, Household Characteristics, and Land Use: An Empirical Study from the 1994 Portland Activity-Based Travel Survey

1998 ◽  
Vol 1617 (1) ◽  
pp. 10-17 ◽  
Author(s):  
Xiaoduan Sun ◽  
Chester G. Wilmot ◽  
Tejonath Kasturi
Keyword(s):  
Land Use ◽  
Travel Demand ◽  
Land Development ◽  
Data Set ◽  
Travel Survey ◽  
Forecasting Models ◽  
Demand Models ◽  
Residence Location ◽  
Household Travel ◽  
Use Factors

How a household’s travel behavior is influenced by its socioeconomic and land use factors has been a subject of interest for the development of travel demand forecasting models. This study investigates the relative importance of these factors based on the number of household daily trips and vehicle miles traveled (VMT). The travel data used in the study come from the 1994 Portland Activity-Based Travel Survey. In addition to income, vehicle ownership, and household size, other significant factors in household travel have been identified, such as the presence of car phones, dwelling type, home ownership, and even the length of resident’s time in the current home. Most important, this study has qualitatively revealed that land use makes a big difference in household VMT, whereas its impact on the number of daily trips is rather limited. After controlling for the land use variables, such as density and land development balance, it appears that there is little difference in household income distribution among three different land use areas. The household life stage/lifestyle appears to be more relevant to the residence location. And the land use development of the residence location imposes the greatest impact on the household daily VMT. The results from this study provide some empirical evidence to the development of travel forecasting models. Especially by examining the relationship between land use and household travel, the results shed light on how to incorporate land use factors into comprehensive travel demand models that can be used by policy makers in evaluation of alternative land use policies. This study serves as a step toward more comprehensive studies on transportation and land use. The results presented represent a preliminary analysis of an extensive data set; considerable additional analysis is already in process.

Exploration of Long-Distance Interregional Commuting Issues: Analysis of Northern California Interregional Commuters Using Census Data and Focus Group Interviews

1996 ◽  
Vol 1521 (1) ◽  
pp. 29-36 ◽  
Author(s):  
Richard W. Lee
Keyword(s):  
Focus Group ◽  
Survey Data ◽  
Travel Demand ◽  
Census Data ◽  
Basic Research ◽  
Northern California ◽  
Single Family ◽  
Long Distance ◽  
Travel Survey ◽  
Demand Models

Recent national and local travel surveys indicate substantial increases in types of travel that are not well explained by most applications of traditional travel demand models. Understanding phenomena such as nonwork travel, the travel patterns of nontraditional households, or long-distance interregional commuting requires new basic research. A promising approach to primary travel demand research was developed and is described. A case study of interregional commuting in Northern California that combined quantitative analysis of census and travel survey data with focus group techniques is presented. Census data provided the basis for defining various types of commuters; the characteristics of these types were then elaborated via the focused interviews including “rolling focus groups” aboard commuter vans. Approximately 40 commuters were interviewed in depth. The interviews illuminated important issues that clarify the census and travel survey data. The findings indicate that an affordable single-family home is the primary motivation of interregional commuters; a variety of personal, household, and schedule adaptations make commuting palatable; and key prerequisites for interregional commuting include a job and lifestyle that permit adherence to a routine. Interregional commuters appear to be good candidates for shared-ride modes.

Case Study in the Application of Adjusted Census Data for Planning Projects

1998 ◽  
Vol 1617 (1) ◽  
pp. 56-63
Author(s):  
Victor J. Siaurusaitis ◽  
Larry J. Saben
Keyword(s):  
Travel Demand ◽  
Census Data ◽  
Model Development ◽  
Traffic Model ◽  
Data Collection Process ◽  
Demand Models ◽  
Home Interview ◽  
Adjustment Factors ◽  
Data Definition ◽  
Census Adjustment

The reasons for differences between locally collected data and the 1990 census data, as determined from a detailed analysis of model development efforts in a planning study, are detailed. Agencies around the country are beginning to use census data that have been adjusted based on newly released Federal Highway Administration publications. The recently completed Transportation Planner’s Handbook on Conversion Factors for the Use of Census Data has been published to assist planners in using the 1990 census to develop and calibrate local travel demand models. Collecting new data to complete the development of a local model is not always an option. The 1990 census provides another source of information to assist in traffic model estimation. Potential users of the census need to be aware that there would appear to be a variance between results obtained from the census journey-to-work files and locally developed home interview surveys, even after the use of the census adjustment factors. The project in Atlanta, Georgia, involved detailed traffic model development and calibration, in conjunction with factor-adjusted census data. Because of the intimate understanding of the data for the study area, and the development of the model set from the beginning, differences between the locally collected data and census were explainable. Possible problems that can arise when comparing the data as they relate to geography, data definition, and accuracy of the data collection process are detailed.

scholarly journals Evaluating the Effects of Household Characteristics on Household Daily Traffic Emissions Based on Household Travel Survey Data

2019 ◽  
Vol 11 (6) ◽  
pp. 1684 ◽  
Author(s):  
Chengcheng Xu ◽  
Shuyue Wu
Keyword(s):  
Survey Data ◽  
Household Income ◽  
Traffic Emissions ◽  
Contributing Factors ◽  
Travel Survey ◽  
Household Characteristics ◽  
Positive Effects ◽  
Household Travel Survey ◽  
Household Travel ◽  
Pm2.5 Emissions

This study aimed to investigate the effects of household characteristics on household traffic emissions. The household travel survey data conducted in the Jiangning District of Nanjing City, China were used. The vehicle emissions of household members’ trips were calculated using average emission factors by average speed and vehicle category. Descriptive statistics analysis showed that the average daily traffic emissions of CO, NOx and PM2.5 per household are 8.66 g, 0.55 g and 0.04 g respectively. The household traffic emissions of these three pollutants were found to have imbalanced distributions across households. The top 20% highest-emission households accounted for nearly two thirds of the total emissions. Based on the one-way ANOVA tests, the means of CO, NOx and PM2.5 emissions were found to be significantly different over households with different member numbers, automobile numbers, annual income and access to the subway. Finally, the household daily traffic emissions were linked with household characteristics based on multiple linear regressions. The contributing factors are slightly different among the three different emissions. The number of private vehicles, number of motorcycles, and household income significantly affect all three emissions. More specifically, the number of private vehicles has positive effects on CO and PM2.5 emissions, but negative effect on NOx emissions. The number of motorcycles and the household income have positive effects on all three emissions.

Developing Custom Tools for Deriving Complex Data from Travel Survey Databases

2005 ◽  
Vol 1917 (1) ◽  
pp. 80-89 ◽  
Author(s):  
Mohan Venigalla ◽  
Soujanya Chalumuri ◽  
Rajit Mandapati
Keyword(s):  
Survey Data ◽  
Large Scale ◽  
System Development ◽  
Specific Information ◽  
Complex Data ◽  
Functional Requirements ◽  
Travel Survey ◽  
Personal Transportation ◽  
Household Travel

Data from large-scale travel survey databases, such as the Nationwide Personal Transportation Survey (NPTS) and the National Household Travel Survey (NHTS), are often used to derive complex parameters for transportation modeling applications not originally targeted by the surveys. When situations demand complex data manipulation tasks, publicly available tools for the purpose do not obviate the need for data users to sift through entire databases and develop custom solutions. This paper presents a flexible methodology for developing custom database tools for cost-effectively deriving application-specific information from travel survey data. The seven-step methodology accounts for assessment of needs, verification of validity of travel survey data to the application, establishment of scientific justification, development of functional requirements of the system, development of data model, definition of processes, and development and testing of tools. To demonstrate the methodology, a case study involving derivation of locality-specific parameters for emission factor models from the NPTS and NHTS databases is presented. With the use of this methodology, a custom database application called Travel-Related Inputs Model for MOBILE6.x (TRIMM) was developed for this case study. The working mechanisms of TRIMM are illustrated. The methodology outlined, though specific to travel survey databases, is sufficiently generic to be used for developing custom tools to derive various modeling parameters from large transportation databases.

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