Uses of National Household Travel Survey Data in - NHTS Home ...
Uses of National Household Travel Survey Data in - NHTS Home ...
Uses of National Household Travel Survey Data in - NHTS Home ...
Create successful ePaper yourself
Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.
Bike and Pedestrian Studies<br />
Estimat<strong>in</strong>g Nonmotorized <strong>Travel</strong> Demand<br />
Authors:<br />
An, Meiwu; Chen, Mei<br />
Pedestrians 2007<br />
Transportation Research Record: Journal <strong>of</strong> the Transportation Research Board Issue: 2002<br />
2007<br />
Abstract:<br />
The model<strong>in</strong>g <strong>of</strong> nonmotorized travel demand has mostly been conducted at the large spatial level (e.g.,<br />
city, county, or census tract level) by us<strong>in</strong>g data from the Bureau <strong>of</strong> the Census and the <strong>National</strong><br />
<strong>Household</strong> <strong>Travel</strong> <strong>Survey</strong>. This paper <strong>in</strong>troduces a model<strong>in</strong>g approach for estimat<strong>in</strong>g the mode share <strong>of</strong><br />
nonmotorized trips by us<strong>in</strong>g data from multiple sources at a f<strong>in</strong>er spatial scale. The correlations between a<br />
number <strong>of</strong> socioeconomic, environmental, and <strong>in</strong>frastructural factors and the nonmotorized share <strong>of</strong> the<br />
daily commute are analyzed at the level <strong>of</strong> the census block group. A neighborhood analysis concept is<br />
developed to take the length <strong>of</strong> nonmotorized trips <strong>in</strong>to consideration. Multiple regression analysis shows<br />
that employment density, the percentage <strong>of</strong> the student population, median household <strong>in</strong>come, and<br />
average sidewalk length together provide the strongest power for prediction <strong>of</strong> the nonmotorized mode<br />
share. The potential applications <strong>of</strong> the methodology and the implications for data collection are also<br />
discussed.<br />
Subject areas and Index Terms<br />
Economics; Education and Tra<strong>in</strong><strong>in</strong>g; Highways; Pedestrians and Bicyclists; Plann<strong>in</strong>g and Forecast<strong>in</strong>g;<br />
Society; I72: Traffic and Transport Plann<strong>in</strong>g<br />
<strong>Data</strong> collection; Employment; Income; Modal split; Mode choice; Multiple regression analysis;<br />
Neighborhoods; Nonmotorized transportation; Socioeconomic factors; Students; <strong>Travel</strong> demand; <strong>Travel</strong><br />
surveys; Trip length<br />
Availability: Transportation Research Board Bus<strong>in</strong>ess Office Order URL:<br />
http://www.trb.org/news/blurb_detail.asp?id=8488; F<strong>in</strong>d a library where document is available Order<br />
URL: http://worldcat.org/isbn/9780309104289<br />
2