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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Travel Behavior Analysis 2008</title>
      <link>https://trid.trb.org/View/879051</link>
      <description><![CDATA[This collection of 20 papers is concerned with advances in travel behavior analysis.  Specific topics discussed include the following:  part-day home working; forecasting telecommuting; choice model of residential neighborhood and bicycle ownership; reliability of travel time; commuter travel behavior changes between 1970 and 2000; value of savings in travel time in Switzerland; travel time in multiple-purpose trips; choice model of new technologies for car choice in Canada; route choice under uncertainty; accessibility, travel behavior, and new urbanism; how commuters know when to leave home; examination of space-use behavior; traveler responses to real-time information about bus arrivals; nonnormality of data in structural equation models; travel behavior of elderly women in rural and small urban areas of North Dakota; the influence of urban form on work travel behavior; parameters for a prospect theory model for travel choice analysis; value of travel time savings under random taste heterogeneity; the evolution of trip rates in Toronto and Montreal, Canada; and social activities and travel demand.]]></description>
      <pubDate>Mon, 26 Jan 2009 11:49:07 GMT</pubDate>
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      <title>Analysis of Travel Time in Multiple-Purpose Trips</title>
      <link>https://trid.trb.org/View/847387</link>
      <description><![CDATA[This paper investigates the travel time attributed to each activity in a trip chain by developing a travel-time price for multiple-purpose trips. Travel-time price is a ratio of the associated travel time of an activity to the activity duration. The travel-time price developed here has three characteristics. First, it accounts for the influence of sociodemographics and urban form characteristics on travel time. Second, it represents the intra-activity trade-off of travel time between activity duration and its associated travel time for different activity types. Third, it represents the interactivity trade-off of travel time between different types of activities. By using the data from the AMADEUS activity–travel diary collected in the Netherlands in 2000, a regression analysis was carried out for multiple-purpose trips stemming from one base, and the results were compared with those of an analysis of single-purpose trips from one base. The focus was on weekday, nonwork, out-of-home activities performed by heads of households. This daily activity behavior is interpreted as an outcome of the long-term decisions made about work and housing locations. The results indicated that, although multiple-purpose trips are not as common, they are more efficient than single-purpose trips. Socio-demographics and spatial characteristics were not statistically significant for the travel-time price of maintenance activities but were mostly significant for discretionary activities. In addition, nonwork out-of-home travel time is largely influenced by the duration of discretionary activities, gender, working hours, and the spatial setting.]]></description>
      <pubDate>Thu, 22 May 2008 07:42:12 GMT</pubDate>
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      <title>GETTING AROUND A TRADITIONAL CITY, A SUBURBAN PLANNED UNIT DEVELOPMENT PUD), AND EVERYTHING IN BETWEEN</title>
      <link>https://trid.trb.org/View/425322</link>
      <description><![CDATA[Beyond some studies relating density to mode choice, vehicle miles of travel, or gasoline consumption, little is known about the relationship of location and land use to household travel patterns.  Against this backdrop a 16,000-record travel survey for Palm Beach County, Florida, was analyzed.  Six communities were culled from the larger data base, and household travel data were then tested for statistically significant differences in trip frequency, mode choice, trip chaining, trip length, and overall vehicle hours of travel.  Households in a sprawling suburb generate almost two-thirds more vehicle hours of travel per person than comparable households in a traditional city. Although travel differences are significant, they are smaller than one might expect given the more than 10-fold difference in accessibility among the communities.  Sprawl dwellers compensate for poor accessibility by linking trips of household members in multipurpose tours.  Implications for land planning are more complex than simply pedestrianizing or transitizing the suburbs. Communities should internalize as many facilities and services as possible.  This is true even where the automobile reigns supreme.  Communities should concentrate facilities and services in centers and corridors.  This will facilitate efficient automobile trips and tours.  The more sprawling the area, the more important this becomes, for through activity centers, linked accessibility to activities can be maintained even as direct accessibility falls off.]]></description>
      <pubDate>Thu, 09 May 2002 00:00:00 GMT</pubDate>
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