سال انتشار: ۱۳۸۵

محل انتشار: هفتمین کنفرانس مهندسی حمل و نقل و ترافیک ایران

تعداد صفحات: ۱۲

نویسنده(ها):

Bahram Jamei – Virginia Department of Transportation
William W. Mann –

چکیده:

The AASHTO “Green Book” states that highway functional classification is an important tool in comprehensive transportation planning. It suggests grouping all roadways in a metropolitan area based on the degree to which each roadway provides land access or mobility. Freeways and local roadways are easy to classify. It is the collectors and minor arterials that are more difficult and subject to biases by the engineer creating the classifications. To eliminate ambiguities, engineers usually turn to defining a variable(s), quantifying it and then using guidelines tolabel them. VDOT engineers have used trip lengths to review the functional classifications of all roadways in Northern Virginia. Trip length is a variable that can be determined for every link in the highway network and can be done for any other area, provided that area has a trip table and a highway network. Most areas with population of 250,000 have these data.
Functional classification in Northern Virginia, as well as in most regions, is dynamic as new roadways are built and old roadways are upgraded. Also, transportation planning consultants change some of the gray area classifications (for example, collector versus minor arterial) to make the transportation models behave better. This relook at the functional classifications for Northern Virginia was done by quantifying the average vehicle trip length for all links (over 15,000) in the network. Using the current functional classifications, the average (and standard deviation) trip length by classification and by jurisdiction was determined. This trip length analysis showed:
· Distinct differences between roadway classifications,
· Distinct differences between urban and suburban roadways,
· Anomalies in the functional classifications.
For next steps, it is suggested that the anomalies be addressed and “fixed” to see if that improves the travel forecasting process.