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Analysis of link capacity estimation methods for urban planning models

Authors :
Dheenadayalu, Yogesh
Wolshon, Brian
Wilmot, Chester
Source :
Journal of Transportation Engineering. Sept-Oct, 2004, Vol. 130 Issue 5, p568, 8 p.
Publication Year :
2004

Abstract

A common travel analysis technique is to ascribe capacities to links in a planning network based on functional classification or facility type, under which a four-lane divided arterial, for example, would be assigned the same capacity everywhere, irrespective of the surrounding land use, the presence of traffic signals, and whether turning lanes are provided or not. While this practice has been used for many years and is typically adequate for the analysis of large road networks, there are penalties (in terms of lost accuracy) that accompany its use. The objective of this research was to evaluate different techniques to determine what information was necessary to reasonably estimate link capacity while decreasing the time, effort, and cost of data collection. It was found that assigning capacities on a link-specific basis produced significant differences when compared to the practice of assigning average capacities, suggesting that travel demand modeling could be improved by using link-by-link estimates of capacity. The results of this study also supported the concept that improvements gained by using all Highway Capacity Manual adjustment factors were marginal compared to the improvement achieved by including only the g/C ratio and number of lanes; suggesting further that ignoring other factors like lane widths, heavy vehicles, turning movements, etc. will still result in reasonably accurate estimates of volume, travel time, and travel speed. CE Database subject headings: Urban planning; Network analysis; Traffic capacity; Traffic volume; Travel demand; Transportation planning.

Details

Language :
English
ISSN :
0733947X
Volume :
130
Issue :
5
Database :
Gale General OneFile
Journal :
Journal of Transportation Engineering
Publication Type :
Academic Journal
Accession number :
edsgcl.121417366