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Real-time inductive-signature-based level of service for signalized intersections

Authors
OH, CHEOLRitchie,Stephen G.
Issue Date
Jan-2002
Publisher
TRANSPORTATION RESEARCH BOARD NATL RESEARCH COUNCIL
Citation
TRAFFIC FLOW THEORY AND HIGHWAY CAPACITY 2002: HIGHWAY OPERATIONS, CAPACITY, AND TRAFFIC CONTROL, no.1802, pp.97 - 104
Indexed
SCIE
SCOPUS
Journal Title
TRAFFIC FLOW THEORY AND HIGHWAY CAPACITY 2002: HIGHWAY OPERATIONS, CAPACITY, AND TRAFFIC CONTROL
Number
1802
Start Page
97
End Page
104
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/46853
DOI
10.3141/1802-12
ISSN
0361-1981
Abstract
The Highway Capacity Manual (HCM) presents a procedure for estimating signalized intersection control delay, which is used to determine level of service (LOS) and to evaluate intersection performance. The HCM is used extensively by traffic engineers. However, it is intended as an offline decision support tool for planning and design. To meet user requirements of advanced traffic management and information systems, new LOS criteria are required for real-time intersection analysis. The objective of this research was to demonstrate a technique for development of such LOS criteria. The study used a new measure of effectiveness, called reidentification delay (RD), derived from analysis of vehicle inductive signatures and reidentification of vehicles traveling through a major signalized intersection in the city of Irvine, California. Two main issues regarding real-time LOS criteria were tackled. The first was how to determine the threshold values partitioning the LOS categories. To provide reliable real-time traffic information, the threshold values should be decided on so that RDs within the same LOS category would represent similar traffic conditions as much as possible. RDs in different LOS categories should also represent dissimilar traffic conditions. The second issue concerned the aggregation interval to use for RD in deriving LOS categories. An investigation of both fixed and cycle-based aggregation intervals was conducted. Several clustering techniques were then employed to derive LOS categories, including k-means, fuzzy, and self-organizing map approaches. The resulting real-time LOS criteria were then determined. The procedures used in this study are readily transferable to other signalized intersections for the derivation of real-time LOS.
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ERICA 공학대학 (DEPARTMENT OF TRANSPORTATION AND LOGISTICS ENGINEERING)
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