2019
DOI: 10.1155/2019/1628417
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Pattern Recognition Using Clustering Analysis to Support Transportation System Management, Operations, and Modeling

Abstract: There has been an increasing interest in recent years in using clustering analysis for the identification of traffic patterns that are representative of traffic conditions in support of transportation system operations and management (TSMO); integrated corridor management; and analysis, modeling, and simulation (AMS). However, there has been limited information to support agencies in their selection of the most appropriate clustering technique(s), associated parameters, the optimal number of clusters, clusteri… Show more

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Cited by 29 publications
(14 citation statements)
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References 28 publications
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“…Results from the SD optimization model gives the optimal value for a mode share of public transportation which is 52.87%. This exceeds the government's target to achieve a mode share of 50% by the year 2030 [22]. However, result from SD optimization analysis shows that the congestion index in Kuala Lumpur is 0.8963 in 2030.…”
Section: Resultsmentioning
confidence: 83%
See 1 more Smart Citation
“…Results from the SD optimization model gives the optimal value for a mode share of public transportation which is 52.87%. This exceeds the government's target to achieve a mode share of 50% by the year 2030 [22]. However, result from SD optimization analysis shows that the congestion index in Kuala Lumpur is 0.8963 in 2030.…”
Section: Resultsmentioning
confidence: 83%
“…This will cause the number of traffic volume to increase, and government will need to decide on constructing more new roads. The phenomenon in traffic studies is known as the Downs Thomson paradox [22]. The phenomenon occurs when more new roads are build, more travelers will occupy the new roads as the attractiveness increases.…”
Section: Loop 1: Road Construction Loopmentioning
confidence: 99%
“…In terms of regional identification, we use a combination of the rotated empirical orthogonal function (REOF) and cluster analysis and consider the spatial continuity of the clustering results. Clustering with the reduced dimensions from the REOF is very effective in data classification (Saha et al ., 2019) and has been applied to geographical zoning in many studies (Han and Zhai, 2015; Yao, 2020). In this article, the K‐medoids clustering method is selected.…”
Section: Methodsmentioning
confidence: 99%
“…Clustering analysis is the most practical method for the identification of traffic patterns that are representative of traffic conditions in support of analysis, modeling, and simulation (AMS) (30) studies (31)(32)(33)(34). Clustering analysis has been recommended for the development and calibration of simulation, particularly those used to assess transportation system operations and management (TSMO) strategies.…”
Section: Cluster Analysis For Partitioning Operational Conditionsmentioning
confidence: 99%
“…Clustering analysis has been recommended for the development and calibration of simulation, particularly those used to assess transportation system operations and management (TSMO) strategies. Partitioning the field traffic conditions allows agencies to better plan, design, and evaluate new technologies and strategies for traffic operation (33,35).…”
Section: Cluster Analysis For Partitioning Operational Conditionsmentioning
confidence: 99%