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

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.

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.

Pluriversal Brazil

2020 ◽  
Vol 74 (2) ◽  
pp. 67-76
Author(s):  
Natalia Brizuela ◽  
Tatiana Monassa
Keyword(s):  
Production Models ◽  
Brazilian Cinema ◽  
Early Late

This conversation with directors Patricia Ferreira Pará Yxapy, André Novais Oliveira, Filipe Matzembacher, Marcio Rolon, and Julia Katharine took place over email exchanges and recorded phone conversations in the weeks between late June and early late August of 2020. In lieu of a real conversation, in person or online, all of the interviewees were sent the same set of questions, upon which they were invited to reflect. The directors were chosen because of the independent production models they work with, and because their voices, here placed side by side, portrays the sense of heterogeneity and pluriversality that today makes up Brazilian cinema.

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