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TRIP GENERATION OF POST OFFICES

P G Azar, Prahlad D. Pant

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Abstract

The trip generation phase of urban transportation planning is one of the most important stages of the travel demand forecasting process. Trip generation helps to estimate vehicular trips generated by a parcel of land or zone from a knowledge of the land use properties of the land or zone. This article has examined trip generation of 15 post offices in Cincinnati, Ohio. The data on trips that have destinations at the post offices were collected manually during the business hours of a typical weekday. The average, minimum, and maximum daily and peak-hour vehicle trip rates were calculated for 9 independent variables selected by this study. Regression analysis was performed to examine the strength of association between the vehicle trip generation and the independent variables.

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What this paper is about

The trip generation phase of urban transportation planning is one of the most important stages of the travel demand forecasting process. Trip generation helps to estimate vehicular trips generated by a parcel of land or zone from a knowledge of the land use properties of the land or zone. This article has examined trip generation of 15 post offices in Cincinnati, Ohio. The data on trips that have destinations at the post offices were collected manually during the business hours of a typical weekday. The average, minimum, and maximum daily and peak-hour vehicle trip rates were calculated for 9 independent variables selected by this study. Regression analysis was performed to examine the strength of association between the vehicle trip generation and the independent variables.

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Available abstract

The trip generation phase of urban transportation planning is one of the most important stages of the travel demand forecasting process. Trip generation helps to estimate vehicular trips generated by a parcel of land or zone from a knowledge of the land use properties of the land or zone. This article has examined trip generation of 15 post offices in Cincinnati, Ohio. The data on trips that have destinations at the post offices were collected manually during the business hours of a typical weekday. The average, minimum, and maximum daily and peak-hour vehicle trip rates were calculated for 9 independent variables selected by this study. Regression analysis was performed to examine the strength of association between the vehicle trip generation and the independent variables.

Key concepts: Trip generation, TRIPS architecture, Transport engineering, Destinations, Variables, Land use, Demand forecasting, Regression analysis

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