Engineering topics

Southworth, Frank

Publications and source records attributed to Southworth, Frank.

4 records

DOE OSTI2012

New York State 2009 NHTS Comparison Report

The U.S. Department of Transportation (USDOT) initiated an effort in 1969 to collect detailed data on personal travel, with the most recent surveys being the 1995 Nationwide Personal Transportation Survey (NPTS) and the 2001 and 2009 National Household Travel Surveys (NHTS). The primary objective of these surveys is to collect trip-based data on the nature and characteristics of personal travel so that the relationships between the characteristics of personal travel and the socio-economic and demographic characteristics of the traveler and his/her household can be established. In addition to the number of sample households that the national NPTS/NHTS survey allotted to New York State, NYDOT procured an additional sample of households in the 1995, 2001, and 2009 surveys. The comparisons drawn in this report compare the results from these NYS sampled households to the results from households drawn for the rest of the nation. Many of the differences between NYC counties and others in the state result from the striking differences in private vehicle ownership levels, with less than one in two NYC drivers and only 64% of NYC households owning a vehicle in 2009: versus 9 out of 10 drivers owning a vehicle, and between 1.5 and 2 vehicles owned per household, on the average, in the state's other metro areas. And this situation has changed very little over the past fourteen years covered by the three latest NPTS/NHTS surveys. While households in metro areas outside NYC do not own a vehicle largely due to income constraints, many households in NYC/Manhattan do not own a vehicle by choice. However, the statistics suggest that the mobility of zero-vehicle households in NYC/Manhattan is by no means deterred by the lack of a vehicle. While the private vehicle tripmaking rate of NYC residents was between one half and one third that in the state's other metro areas, and their daily VMT about half that of other metro areas, most of their daily travel needs were met by walking or by public transit. As a result, their daily trip-making rates remain consistent with those of vehicle-owning households when all modes of travel are considered. This again indicates that owning a vehicle or being a driver in NYC was less important for meeting a household's mobility needs than anywhere else in NYS. The high levels of public transit usage within NYC replace a great deal of automobile use, and this plus greater use of walk trips results in significantly lower travel generated carbon dioxide emissions per household in NYC than elsewhere in the state. In contrast, the comparatively limited level of public transit ridership in the state's smaller and medium sized metro areas places a much greater reliance on the privately owned vehicle, be it an automobile or the increasingly popular SUV.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2011

Set of Comparable Carbon Footprints for Highway Travel in Metropolitan America

The authors describe the development of a set of carbon dioxide emissions estimates for highway travel by automobile, truck, bus and other public transit vehicle movements within the nation s 100 largest metropolitan areas, in calendar year 2005. Considerable variability is found to exist across metropolitan areas when these greenhouse gas emissions are measured on a per capita and a per gross metropolitan product (GMP) basis. Least square regression modeling shows a relationship between emissions per capita and per GMP with truck traffic share, transit share, employment density, population dispersion within the metro area, and GMP per capita. As a result many of the nation s largest metropolitan areas tend to have lower CO2 emissions per capita and per GMP than smaller and more recently developed metro areas.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2011

Travel Demand Modeling

This chapter describes the principal types of both passenger and freight demand models in use today, providing a brief history of model development supported by references to a number of popular texts on the subject, and directing the reader to papers covering some of the more recent technical developments in the area. Over the past half century a variety of methods have been used to estimate and forecast travel demands, drawing concepts from economic/utility maximization theory, transportation system optimization and spatial interaction theory, using and often combining solution techniques as varied as Box-Jenkins methods, non-linear multivariate regression, non-linear mathematical programming, and agent-based microsimulation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2011

Overview of the FAF3 Freight Flow Matrix Construction Process

PROJECT DESCRIPTION The FAF3 is a FHWA freight data product which provides a national O-D matrix of commodity flows to, from, and within the United States. FAF3 freight flows are reported in terms of both annual tons and annual dollars of freight moved by mode of transportation. Based largely on the 2007 CFS, FAF3 utilizes domestic freight flow characteristics, geographic regions, and the SCTG commodity coding system from CFS. However, many freight flows were not captured by the 2007 CFS due to scope and sample size limitations. Approximately 100,000 establishments were sampled out of some 754,000 freight moving establishments in 2007 and imports are out of scope entirely. To estimate missing data values, the approach taken in FAF3 was to use a combination of a novel Log-linear modeling approach (LLM) with an iterative proportional fitting (IPF) routine that also uses additional data inputs to fill in the missing pieces. The complete FAF3 O-D Commodity Mode database is made up of 131 Origins x 131 Destinations x 43 Commodity Classes x 8 Modal categories, for annual tons and dollars. This poster illustrates how the 2007 CFS data were integrated with several additional data sources using LLM and IPF to create a comprehensive FAF3 national freight flow matrix. More detailed documentation on the sources and methods utilized in the development of FAF3 are available from the FHWA website at the following website: http://www.ops.fhwa.dot. gov/freight/freight_analysis/faf/index.htm.

99 GENERAL AND MISCELLANEOUS↗