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Title: Forecasting urban highway travel for year 2005

Abstract

As part of a study aimed at estimating suburban highway needs for year 2005, models were developed for forecasting daily vehicle miles of travel (DVMT) for urban areas and its distribution by highway functional class, urban location, and urban area size. A regression model combining both time series and cross-sectional data is used to establish the relationship between the per capita DVMT of 339 urban areas in the United States and a set of explanatory variables including real income, employment, number of persons per household, number of driver licenses per 1000 persons, a variable representing highway supply deficiency, and a time variable. The dynamic shift over time in share of travel between urban locations and highway functional classes as urban areas grow in size is represented by conditional logit models. This paper presents the major findings from the forecasting and distribution models for urban highway travel in year 2005. 30 refs., 3 figs., 9 tabs.

Authors:
 [1]; ; ;  [2]
  1. Tennessee Univ., Knoxville, TN (USA). Transportation Center
  2. Oak Ridge National Lab., TN (USA)
Publication Date:
Research Org.:
Oak Ridge National Lab., TN (USA)
Sponsoring Org.:
DOE/CE
OSTI Identifier:
6488679
Report Number(s):
CONF-910126-3
ON: DE91000560
DOE Contract Number:  
AC05-84OR21400
Resource Type:
Conference
Resource Relation:
Conference: Annual transportation research board meeting, Washington, DC (USA), 13-17 Jan 1991
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; 29 ENERGY PLANNING, POLICY AND ECONOMY; ROAD TRANSPORT; FORECASTING; URBAN AREAS; TRAVEL; ALGORITHMS; COMPUTER CALCULATIONS; COST; ECONOMETRICS; FUEL CONSUMPTION; HUMAN POPULATIONS; LICENSES; MATHEMATICAL MODELS; REGRESSION ANALYSIS; ROUTING; SOCIO-ECONOMIC FACTORS; STATISTICAL DATA; STATISTICAL MODELS; TRANSPORTATION SECTOR; VEHICLES; DATA; ECONOMICS; ENERGY CONSUMPTION; INFORMATION; INSTITUTIONAL FACTORS; LAND TRANSPORT; MATHEMATICAL LOGIC; MATHEMATICS; NUMERICAL DATA; POPULATIONS; STATISTICS; TRANSPORT; 320203* - Energy Conservation, Consumption, & Utilization- Transportation- Land & Roadway; 298000 - Energy Planning & Policy- Consumption & Utilization

Citation Formats

Miaou, Shaw-Pin, Rathi, A K, Southworth, F, and Greene, D L. Forecasting urban highway travel for year 2005. United States: N. p., 1990. Web.
Miaou, Shaw-Pin, Rathi, A K, Southworth, F, & Greene, D L. Forecasting urban highway travel for year 2005. United States.
Miaou, Shaw-Pin, Rathi, A K, Southworth, F, and Greene, D L. 1990. "Forecasting urban highway travel for year 2005". United States. https://www.osti.gov/servlets/purl/6488679.
@article{osti_6488679,
title = {Forecasting urban highway travel for year 2005},
author = {Miaou, Shaw-Pin and Rathi, A K and Southworth, F and Greene, D L},
abstractNote = {As part of a study aimed at estimating suburban highway needs for year 2005, models were developed for forecasting daily vehicle miles of travel (DVMT) for urban areas and its distribution by highway functional class, urban location, and urban area size. A regression model combining both time series and cross-sectional data is used to establish the relationship between the per capita DVMT of 339 urban areas in the United States and a set of explanatory variables including real income, employment, number of persons per household, number of driver licenses per 1000 persons, a variable representing highway supply deficiency, and a time variable. The dynamic shift over time in share of travel between urban locations and highway functional classes as urban areas grow in size is represented by conditional logit models. This paper presents the major findings from the forecasting and distribution models for urban highway travel in year 2005. 30 refs., 3 figs., 9 tabs.},
doi = {},
url = {https://www.osti.gov/biblio/6488679}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Aug 01 00:00:00 EDT 1990},
month = {Wed Aug 01 00:00:00 EDT 1990}
}

Conference:
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