Click for next page ( 35

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 34
group. TrafLoad uses the traffic ratios obtained at a Level 1A site to convert short-duration clas- sification counts obtained at any associated Level 1B site to estimates of AADTi by lane. (See Part 4, Step CF, available online at As in the case of monthly traffic ratios, the monthly/DOW traffic ratios applied to short-duration counts obtained at any Level 1B site should be "current year" traffic ratios; i.e., they should be developed from data that are collected over a 12-month period that includes the month dur- ing which the short-duration count is collected. The research team makes two observations about this factoring procedure. The first is that the conversion process involves dividing by the MADW for each Type 1 VC group. Hence, the accuracy of the resulting estimates of AADTi is affected by the similarity of the seasonal and DOW volume patterns for the VCs within each VC group but not by the similarity (or dis- similarity) of these patterns between VC groups. The second observation is that the adjust- ment procedure uses traffic ratios obtained from a single Level 1A site, a site that should have seasonal and DOW volume patterns that are very similar to those at the corresponding Level 1B site(s). For this reason, the resulting estimates of AADTi should be substantially bet- ter than those that can be produced at Level 2 sites. 3.4 Level 2 Classification Sites Level 2 classification sites are classification sites that do not qualify as Level 1 classification sites. That is, less than 12 months of current data are available for these sites, and they are not associated with another site on the same road for which 12 months of current data are avail- able. A few of these sites are continuous classification sites at which data are missing for one or more months. However, most of these sites are ones at which classification counts are col- lected as part of a state's short-duration classification-count program. Counts collected as part of this program fall into three categories: 1. Coverage counts that are collected periodically (e.g., once every third year) at a relatively fixed set of sites to provide general information about truck volumes and how these vol- umes are changing over time; 2. Expected project counts, collected at sites at which highway projects are anticipated, to pro- vide data for use in the planning and design process; and 3. Project-specific counts, collected either to provide additional information about sites at which expected project counts have already been collected or to provide data to be used for projects that had not been anticipated. Most short-duration counts collected for pavement design projects are likely to fall into the second of these categories. That is, they are likely to be collected to support pavement design projects that are anticipated to occur in the near future. These potential projects should be 2-34

OCR for page 34
identified by highway planners as soon as practical. Planning and programming tools avail- able for this purpose include pavement management systems. The early identification of pavement projects and scheduling of classification counts requires coordination among the data-collection staff, the pavement design staff, and other agency staff involved in the programming and prioritization process. While this level of communication is not easy, it has several advantages. It allows the traffic engineering office to schedule needed counts so that they can be collected efficiently. It ensures that data are available to designers when needed, thus speeding up the design process. And finally, it provides an opportunity to collect extra counts to be used in the design of major projects. As discussed below, estimates of AADTi developed from three or four 7-day counts collected over the course of a year are likely to produce appreciably better estimates of AADTi than similar estimates developed from a single 48-hour classification count. A key to this approach is to be generous when estimating possible pavement design locations. Traffic volume and classification counts at most locations are considered to be reliable for at least 2 years. Thus, even if an expected pavement design project does not make this year's design list, it will likely make next year's list, and traffic data will already be collected and available for that location. Even with good communication between pavement and traffic engineering staff, it may not be possible to collect all the traffic data required as part of the routine data-collection effort. Accordingly, allowance should always be made for a possible need for project-specific counts to supplement the expected project counts. Short-duration classification counts are usually collected using automatic vehicle classifiers (AVCs). However, at some urban sites, manual classification may be preferred. Because man- ual counts usually cover only part of a day, estimates of AADTi derived from manual counts are not likely to be as good as estimates derived from accurate classification counts obtained with AVCs for periods of 48 hours or more. Accordingly, these two types of short-duration counts are distinguished from each other by calling AVC sites Level 2A sites and calling man- ual classification sites Level 2B sites. The two following subsections contain brief discussions of the collection and analysis of counts at these two types of classification sites. AVC Sites (Level 2A) Level 2A classification sites are sites at which automatic vehicle classifiers (AVCs) are used to obtain one or more classification counts over the course of a year. Accurate AVC counts usu- ally require that vehicles are traveling at constant speed with adequate spacing between vehi- cles, conditions that may be difficult to meet in urban areas. Each AVC count should cover a period of at least 48 weekday hours (though TrafLoad's Level 2A procedure is capable of esti- mating AADTi from 24-hour classification counts). Improved estimates of AADTi will be pro- duced if count duration is extended or if multiple classification counts are collected over the course of a year. 2-35

OCR for page 34
Section 3.3 included a discussion of TrafLoad's use of data from continuous classification- count sites (Level 1A sites) to develop sets of monthly and DOW traffic ratios. These traffic ratios are used by TrafLoad to convert the short-duration counts collected at Level 2A sites to estimates of AADTi. For any Level 2A site, the traffic ratios used are those developed for the seasonal and DOW factor groups to which the site belongs. As observed in Section 3.3, monthly traffic ratios that are derived from current year data work better for this purpose than monthly traffic ratios derived from historic data. For this reason, when providing TrafLoad with a set of Level 2 classification counts to be factored, the user should (if possible) also provide TrafLoad with Level 1A counts for a 12-month period that includes the month(s) during which the Level 2 counts were collected. The quality of the estimates of AADTi that are produced will tend to vary with the degree to which the seasonal and DOW patterns in truck volumes at the Level 2A site match the vol- ume patterns in the seasonal and DOW factor groups to which the site has been assigned. Use of 7-day counts reduces or eliminates the need for DOW factoring, and use of multiple counts over the course of a year reduces the need for seasonal factoring. Thus, 7-day counts and mul- tiple counts are strategies for increasing the amount of data collected in order to improve the quality of AADTi estimates. Hourly distribution factors for each Level 2A site are developed by TrafLoad from the counts collected at the site. TrafLoad sets the monthly traffic distribution factors for each Level 2A site equal to the monthly traffic ratios for the seasonal factor group to which the site has been assigned. Manual Classification-Count Sites (Level 2B) In order to classify vehicles reliably on the basis of axle-spacing criteria, AVCs must be located where vehicles are neither accelerating nor decelerating and where the spacing between vehi- cles is sufficient to allow consecutive vehicles to be readily distinguished. Because these con- ditions are difficult to meet in urban areas, urban classification counts frequently are collected manually. (Alternatively, classification on urban streets and roads may be limited to length classification.) Manual classification counts are usually collected only during daylight hours, usually for a period of 6 to 12 consecutive hours. Conversion of these partial-day counts to estimates of AADTi is a two-step process: 1. Each set of partial-day classification counts is converted to a set of estimates of volume by VC for the day on which the counts were collected. 2. The procedures discussed in the preceding section are used to convert these estimates of 24-hour volume by VC to estimates of AADTi. Procedures for performing the first of these two steps are discussed below. This step adds some additional error to the resulting estimates of AADTi (over and above the error intro- duced by the factoring procedures discussed above). Accordingly, sites at which classification counts are obtained manually are described as Level 2B sites. 2-36