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.

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.

Impact of Major Road Supply on Individual Travel Time Expenditure: An Exploration with a 30-Year Variation of Infrastructure and Travel

2018 ◽  
Vol 2672 (3) ◽  
pp. 56-68
Author(s):  
Ryosuke Abe ◽  
Kay W. Axhausen
Keyword(s):  
Travel Time ◽  
Large Scale ◽  
Travel Demand ◽  
Road Traffic ◽  
Land Development ◽  
Transportation Infrastructure ◽  
Major Road ◽  
Birth Cohorts ◽  
Data Set ◽  
The Impact

This study estimates the impact of major road supply on individual travel time expenditures (TTEs) using data that cover 30-year variations in transportation infrastructure and travel behavior. The impacts of the supply of road and rail infrastructure are estimated with a data set that combines records of large-scale household travel surveys in the Tokyo metropolitan area conducted in 1978, 1988, 1998, and 2008. Linear and Tobit models of individual TTEs are estimated by following the behavior of birth cohorts over the 30-year period. The models incorporate the changes in transportation infrastructure, measured as lane kilometers of two levels of major road stock and vehicle kilometers of urban rail service. The results show significant negative effects of lane kilometers for higher-level and lower-level major roads on the TTEs for all travel purposes and for commuting, after controlling for socioeconomic backgrounds and generations of individuals. This study discusses that, in Tokyo, the estimated effect is more likely to reflect the effect of a major road network per se on individual TTEs than the (indirect) effect of major road supply on individual TTEs working through land development activities (i.e., induced car travel demand). For example, the caveat is that actual road investment decisions still need to consider the induced component of road traffic in addition to the (direct) effect that is estimated in this study.

Metaanalysis of Travel Survey Methods

1998 ◽  
Vol 1625 (1) ◽  
pp. 72-78 ◽  
Author(s):  
Madhuri S. Korimilli ◽  
Ram M. Pendyala ◽  
Elaine Murakami
Keyword(s):  
Travel Demand ◽  
Survey Methods ◽  
Response Rates ◽  
Design Parameters ◽  
Modeling Tools ◽  
Travel Survey ◽  
Household Travel ◽  
Household Travel Surveys ◽  
The Impact ◽  
Comparative Examination

Travel surveys often serve as the primary sources of information on travel demand characteristics. They provide critical data for transportation planning and decision making. In recent times, several factors motivate a comparative examination of travel survey methods. First, new travel demand modeling tools, such as those based on activity-based methods, are placing greater demands on travel behavior data gathered from household travel surveys. Second, response rates from household travel surveys have been showing a steady decline, possibly because of an increasingly survey-fatigued population. Third, declining resource availability at metropolitan planning agencies places emphasis on the need to maximize response rates to lower data collection costs per completed respondent. Ideally, a comparative examination of travel survey methods is best done through a carefully constructed experimental design that permits the isolation of the impact of various survey design parameters on response rates. However, the conduct of such a controlled experiment virtually is impractical. A metaanalysis of a sample of travel surveys conducted in the past 10 years is presented. A predictive model of response rates is developed by using linear regression techniques and the practical application of the model is demonstrated through several numerical examples.

Impact of Underreporting on Mileage and Travel Time Estimates: Results from Global Positioning System-Enhanced Household Travel Survey

2003 ◽  
Vol 1854 (1) ◽  
pp. 189-198 ◽  
Author(s):  
Jean Wolf ◽  
Marcelo Oliveira ◽  
Miriam Thompson
Keyword(s):  
Travel Time ◽  
Global Positioning System ◽  
Travel Demand ◽  
Positioning System ◽  
Gps Technology ◽  
Travel Survey ◽  
Household Travel Survey ◽  
Time Estimates ◽  
Global Positioning ◽  
Household Travel

Trip underreporting has long been a problem in household travel surveys because of the self-reporting nature of traditional survey methods. Memory decay, failure to understand or to follow survey instructions, unwillingness to report full details of travel, and simple carelessness have all contributed to the incomplete collection of travel data in self-reporting surveys. Because household trip survey data are the primary input into trip generation models, it has a potentially serious impact on transportation model outputs, such as vehicle miles of travel (VMT) and travel time. Global Positioning System (GPS) technology has been used as a supplement in the collection of personal travel data. Previous studies confirmed the feasibility of applying GPS technology to improve both the accuracy and the completeness of travel data. An analysis of the impact of trip underreporting on modeled VMT and travel times is presented. This analysis compared VMT and travel time estimates with GPS-measured data. These VMT and travel time estimates were derived by the trip assignment module of each region's travel demand model by using the trips reported in computer-assisted telephone inter views. This analysis used a subset of data from the California Statewide Household Travel Survey GPS Study and was made possible through the cooperation of the metropolitan planning organizations of the three study areas (Alameda, Sacramento, and San Diego, California).

Incorporating Land Use into Methods of Synthetic Population Generation and of Transfer of Behavioral Data

2017 ◽  
Vol 2668 (1) ◽  
pp. 11-20 ◽  
Author(s):  
Elizabeth C. McBride ◽  
Adam W. Davis ◽  
Jae Hyun Lee ◽  
Konstadinos G. Goulias
Keyword(s):  
Land Use ◽  
Travel Behavior ◽  
Travel Demand ◽  
Behavioral Data ◽  
Synthesis Methods ◽  
Population Synthesis ◽  
Household Travel Survey ◽  
Synthetic Populations ◽  
Synthetic Population ◽  
Household Travel

This paper describes a new method of population synthesis that includes land use information. The method is based on an initial identification of suitable land use summaries to build a spatial taxonomy at any spatial scale. This same taxonomy is then used to classify household travel survey records (persons and households) and in parallel geographic subdivisions for the state of California. This land use information is the added dimension in the population synthesis methods for travel demand analysis. Synthetic population generation proceeds by expanding (re-creating) the records of the households responding to the survey and the entire array of travel behavior data reproduced for the synthetic population. The basis for selecting the variables to use in the synthetic population is first testing their significance in simplified specification in models of travel behavior that include land use as an explanatory variable and account for the shape of behavioral data (e.g., observations with no travel). The paper shows differences between synthetic populations with and without land use data to demonstrate the behavioral realism added by this approach.

Unit of analysis in conventional trip generation modelling: an investigation

2004 ◽  
Vol 31 (2) ◽  
pp. 272-280 ◽  
Author(s):  
Daniel A Badoe ◽  
Chin-Cheng Chen
Keyword(s):  
Travel Demand ◽  
Empirical Test ◽  
Model Estimation ◽  
Trip Generation ◽  
Unit Of Analysis ◽  
Travel Survey ◽  
Household Travel Survey ◽  
Trip Production ◽  
Household Travel ◽  
Production Modelling

This paper examines the importance of the unit of analysis selected for trip generation modelling when the model estimation data are collected in a household travel survey. The paper reviews the literature on the arguments made for the use of the "individual" or the "household" as the unit of analysis in trip production modelling, and then through a statistical exposition it determines what should be the appropriate unit of analysis. An empirical test of the forecast performance of household- and person-trip generation models is conducted using data collected in a household-travel-behaviour survey in the Greater Toronto Area of Canada. The paper concludes that the household is theoretically the preferable analysis unit to use in trip production modelling when the model estimation data are collected in a household travel survey in which the household is the sampling unit. The empirical test indicates that household-trip generation models yield predictions of trips at the household and traffic zone level, respectively, that are marginally more accurate than those yielded by person-trip generation models.Key words: trip generation, travel demand forecasting, household trip generation, person trip generation, sampling unit, travel demand modeling, activity-based travel forecasting.

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.

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