Development of Trip Production Rates for Synthesized Households

1998 ◽  
Vol 1625 (1) ◽  
pp. 79-85 ◽  
Author(s):  
Shari P. Scobee ◽  
Michael DuRoss ◽  
Edward C. Ratledge
Keyword(s):  
Household Member ◽  
University Of Delaware ◽  
Production Rates ◽  
Survey Nonresponse ◽  
Household Level ◽  
Travel Survey ◽  
Production Models ◽  
Trip Production ◽  
Household Travel ◽  
The University

Survey nonresponse bias is an important consideration in the development of survey designs for transportation studies. Researchers at the University of Delaware have developed a technique for reducing the survey nonresponse, as well as the cost of the travel survey. The method involves obtaining complete household and person characteristics for each household member; however, detailed travel data are gathered for only one randomly selected household member. Although the University of Delaware survey technique provides multiple benefits with respect to survey response rates and costs, it presents complications for travel model developers, particularly with respect to the development of trip production models. Because the trip production models are typically developed at the household level, the person-level trip rates from such a survey need to be expanded to represent a household’s trip rates. A method is presented for generating synthesized household trip production rates by using the 1995/96 Delaware Household Travel Survey, which gathered travel information for only one household member.

scholarly journals Modeling Public Transport Users’ Trip Production in Hawassa City, Ethiopia

2021 ◽  
Author(s):  
Girma Gebre ◽  
Emer Tucay Quezon
Keyword(s):  
Linear Regression ◽  
Public Transport ◽  
Traffic Management ◽  
Regression Models ◽  
Explanatory Power ◽  
Linear Regression Models ◽  
Household Level ◽  
Trip Purpose ◽  
Production Models ◽  
Trip Production

Today, overcrowded public transport demand, resulting in huge costs in an urban area. Similarly, there are a lot of people who use public transport in Hawassa city. This study aimed to develop public transport users' trip production models at the household level. Some socio-economic characteristics and trip detail of the public transport users were collected randomly from the different households through a questionnaire survey. The data gathered was fed into IBM SPSS package version 20 to develop linear regression models. The developed models are associated with trips for purpose and time intervals of trips made. The developed linear regression models, general trips, work trips, educational trips, and trips made before 8:00 AM and after 4:00 PM had good explanatory power. The value of explanatory power comprised of 0.656, 0.722, 0.549, 0.610 and 0.510. These values indicated the explanation power of the socio-economic characteristics on the trips made. It means the daily trips production was significantly affected by the number of working individuals, the different age brackets, cars and motorcycles, and the monthly income per household. The most frequent public transport users’ trips production regarding the trip purpose and time are work trips and occurred after 4:00 PM. This scenario represented a good model developed in this study. Hence, it is suggested that Hawassa city’s traffic management office use the developed models to predict the future trips demand to provide a proper scheme to avoid congestion during the peak hour of the day.

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.

scholarly journals MODELING PUBLIC TRANSPORT USERS’ TRIP PRODUCTION IN HAWASSA CITY, ETHIOPIA

2021 ◽  
Vol 12 (2) ◽  
pp. 75-90
Author(s):  
Girma Gebre ◽  
Emer T. Quezon
Keyword(s):  
Linear Regression ◽  
Public Transport ◽  
Traffic Management ◽  
Regression Models ◽  
Explanatory Power ◽  
Linear Regression Models ◽  
Household Level ◽  
Trip Purpose ◽  
Production Models ◽  
Trip Production

Today, overcrowded public transport demand, resulting in huge costs in an urban area. Similarly, there are a lot of people who use public transport in Hawassa city. This study aimed to develop public transport users' trip production models at the household level. Some socio-economic characteristics and trip detail of the public transport users were collected randomly from the different households through a questionnaire survey. The data gathered was fed into IBM SPSS package version 20 to develop linear regression models. The developed models are associated with trips for purpose and time intervals of trips made. The developed linear regression models, general trips, work trips, educational trips, and trips made before 8:00 AM and after 4:00 PM had good explanatory power. The value of explanatory power comprised of 0.656, 0.722, 0.549, 0.610 and 0.510. These values indicated the explanation power of the socio-economic characteristics on the trips made. It means the daily trips production was significantly affected by the number of working individuals, the different age brackets, cars and motorcycles, and the monthly income per household. The most frequent public transport users’ trips production regarding the trip purpose and time are work trips and occurred after 4:00 PM. This scenario represented a good model developed in this study. Hence, it is suggested that Hawassa city’s traffic management office use the developed models to predict the future trips demand to provide a proper scheme to avoid congestion during the peak hour of the day.

Does Investing in Rail Transit Benefit the Poor? A Comparative Study of Rail and Bus Travel by Low-Income Households in the California Household Travel Survey

2018 ◽  
Vol 2672 (6) ◽  
pp. 11-20
Author(s):  
Ryland Lu
Keyword(s):  
Low Income ◽  
Household Income ◽  
Bus Rapid Transit ◽  
Rail Transit ◽  
Rapid Transit ◽  
Travel Survey ◽  
Household Travel Survey ◽  
The Poor ◽  
Household Travel ◽  
Low Income Households

This paper addresses academic discourse that critiques urban rail transit projects for their regressive impacts on the poor and proposes bus funding as a more equitable investment for urban transit agencies. The author analyzed data from the 2012 California Household Travel Survey on transit trips in Los Angeles County. The author cross-tabulated data on the modal breakdown of transit trips by household income category and on the breakdown of household income associated with trips by bus and rail transit modes. The author also comparatively evaluated the speed of trips (as a ratio of miles per hour) taken by rail and by bus by low-income households in the county. The author found convincing evidence that, on average, trips low-income households made by rail transit covered a greater distance per hour than trips taken by bus transit, but that trips made on the county’s bus rapid transit services with dedicated rights-of-way had a higher mean speed than those taken by rail. Moreover, the mode and income cross-tabulations indicate that rail transit projects only partially serve low-income households’ travel needs. To the extent that equitable transit planning entails minimizing the disparities in access, both rail and bus rapid transit projects can advance social justice if they are targeted at corridors where they can serve travel demand by low-income, transit dependent households.

FLES Workshops at the University of Delaware

Hispania ◽  
1958 ◽  
Vol 41 (2) ◽  
pp. 213
Author(s):  
Daymond Turner
Keyword(s):  
University Of Delaware ◽  
The University

Time Stability of Zonal Trip Production Models

1972 ◽  
Vol 98 (4) ◽  
pp. 799-806
Author(s):  
Norman Ashford ◽  
Frank M. Holloway
Keyword(s):  
Time Stability ◽  
Production Models ◽  
Trip Production
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