Cover Image

Not for Sale



View/Hide Left Panel
Click for next page ( 159


The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 158
Time, day of the week, day of the year, and conditions (such as weather, road, and traffic conditions); and Factors that influence travel choice (such as whether a person would have chosen another route or a particular mode if road conditions or facilities were different). Results and their presentation. User survey results should be summarized to highlight key findings. The results can then be used to identify how transportation choice should be evaluated and how a particular policy or project is likely to affect transportation options. Standard statistical analysis techniques can be used to evaluate the accuracy of survey results. Geographic information can be presented on maps, and time series data can be graphed to illustrate trends. Results from user surveys can be presented by mode, group, or location to meet analysis requirements. For example, to analyze the effects a highway project will have on the travel choices of transportation-disadvantaged people, it may be appropriate to present survey data indicating the number of people in various groups near the project site (e.g., nondrivers, low- income persons, and persons with disabilities), their current travel patterns (e.g., how many currently walk and bicycle along the proposed route), and how these travel modes are likely to be affected. In an environmental justice context, user demand and evaluation surveys can be carried out to estimate the specific effects a particular project would have on protected populations. These surveys also can be used to assess problem areas and the efficacy of possible improvements. Assessment. User demand and evaluation surveys are a commonly applied tool for determining the current circumstances facing pedestrians and cyclists. Problem areas identified in these surveys can then be addressed as a transportation project is designed. More specifically, this gives planners a better understanding of features to avoid or include for facilitating travel by alternative modes when designing upgraded or reconfigured facilities. As is true of any user survey, however, the results will reflect only the views and experiences of current or past users. Those who have not been able or willing to use the various forms of alternative transportation will not be represented. Thus, it must be recognized that these surveys are only one useful source of information; they cannot be regarded as completely definitive for establishing the needs and preferences surrounding alternative transportation issues RESOURCES 1) Dixon, Linda. 1996. "Bicycle and Pedestrian Level-of-Service Performance Measures and Standards for Congestion Management Systems." Transportation Research Record 1538. Washington, DC: Transportation Research Board, National Research Council, pp. 19. This article describes LOS ratings for walking and cycling conditions to help identify ways to improve and encourage nonmotorized transportation. The ratings take into account the existence of separated facilities, conflicts, speed differential, congestion, maintenance, amenities, and traffic demand modeling (TDM). These are relatively easy-to-use methods for evaluating non-motorized roadway conditions that may be simpler to apply than other, more data-intensive methods. 162