Using stop bar detector information to determine turning movement proportions in shared lanes
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Authors
Gholami, Ali
Tian, Zong
Issue Date
2016
Type
Article
Language
Keywords
intersection detector , shared lane , turning vehicle volume , regression , genetic programming
Alternative Title
Abstract
Turning vehicle volumes at signalized intersections are critical inputs for various transportation studies such as level of service, signal timing, and traffic safety analysis. There are various types of detectors installed at signalized intersections for control and operation. These detectors have the potential of producing volume estimates. However, it is quite a challenge to use such detectors for conducting turning movement counts in shared lanes. The purpose of this paper was to provide three methods to estimate turning movement proportions in shared lanes. These methods are characterized as flow characteristics (FC), volume and queue (VQ) length, and network equilibrium (NE). FC and VQ methods are based on the geometry of an intersection and behavior of drivers. The NE method does not depend on these factors and is purely based on detector counts from the study intersection and the downstream intersection. These methods were tested using regression and genetic programming (GP). It was found that the hourly average error ranged between 4 and 27% using linear regression and 1 to 15% using GP. A general conclusion was that the proposed methods have the potential of being applied to locations where appropriate detectors are installed for obtaining the required data. Copyright (C) 2016 John Wiley & Sons, Ltd.
Description
Citation
Gholami, A., & Tian, Z. (2016). Using stop bar detector information to determine turning movement proportions in shared lanes. Journal of Advanced Transportation, 50(5), 802�"817. doi:10.1002/atr.1376
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License
In Copyright (All Rights Reserved)
Journal
Volume
Issue
PubMed ID
DOI
ISSN
0197-6729