Pattern Recognition Using Clustering Analysis to Support Transportation System Management, Operations, and Modeling

Saha, Rajib; Tariq, Mosammat Tahnin; Hadi, Mohammed; Xiao, Yan

doi:10.1155/2019/1628417

Cited by 28 publications

(14 citation statements)

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%

“…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%

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Minimizing the Congestion Index and Mode Share of Traffic Congestion in Urban Area

Idris

2022

JEBI

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Urbanization is heavily influenced by the transportation that becomes fundamental to the mobility of human activities. However, unchecked growth in transportation raises serious concerns about many issues such as congestions, limited parking, and public transit problem. This phenomenon also overwhelms Kuala Lumpur, the capital city of Malaysia that has a high number of car ownership. Consequently, traffic congestion in urban area has affected people living there in terms of lost time on the road and waste of fuel consumption. In this regard, this research aims to minimize the congestion index and mode share in Kuala Lumpur based on the tested of six travel demand strategy variables. The problem was model and optimized using system dynamics (SD) optimization approach. Results of the developed SD optimization model shows that the optimized congestion index is 0.89863 while the mode share is 52.87% in 2030 compared to SD baserun which are only 1.1021 and 21.7% for congestion index and mode share respectively. This finding shows that SD optimization performed a better result in terms of achieving the targeted of congestion index and mode share of < 0.6 and 50% by 2030 compared to SD baserun. From the managerial perspective, this research helps towards achieving the government’s congestion index and mode share targets through strategizing the ways on attracting public transportation and discouraging the usage of private cars in Kuala Lumpur.

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Section: Resultsmentioning

confidence: 83%

Section: Loop 1: Road Construction Loopmentioning

confidence: 99%

Minimizing the Congestion Index and Mode Share of Traffic Congestion in Urban Area

Idris

2022

JEBI

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“…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%

Characteristics of spring consecutive dry days with different durations across China based on the objective zoning approach

Zeng

Sun

2021

Atmospheric Science Letters

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The duration of dry periods is closely related to drought conditions and is used to evaluate the degree of drought. In this article, using the rotated empirical orthogonal function (REOF) and K‐medoids clustering methods and considering the spatial continuity, 500 stations in China are divided into 10 clusters to analyze the variation characteristics of consecutive dry days (CDDs) with different durations in spring. In Clusters 1–5 over the middle and lower reaches of the Yangtze River, South China, North China, and eastern and western Southwest China, the contribution percentage of short‐duration CDDs to total dry days decreases, while that of medium‐ and/or long‐duration CDDs increases, which leads to an increase in the total dry days and the duration of CDDs. In Clusters 6–8, the total dry days decrease, which are mainly contributed by the decreases in medium‐duration CDDs (for Cluster 6 over southern Northeast China) or long‐duration CDDs (for Clusters 7–8 over northern Northeast China and southern Xinjiang). The total dry days change little in Clusters 9–10 over eastern Northwest China and northern Xinjiang, which is attributed to the offset among the changes in the three‐type duration CDDs. In Clusters 6–10, the duration of CDDs shortens overall. The decadal changes of spring dry days in China exhibit remarkable regional differences. The total day days and three‐type duration CDDs in some clusters (1, 4, and 8) all have significant decadal changes, but they have not in Cluster 7. And the decadal change times also exhibit regional differences. The investigation of different‐duration CDDs in this study provides more information on droughts at different time scales in China.

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“…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%

Using High-Resolution Signal Controller Data in the Calibration of Signalized Arterial Simulation Models

Tariq

Hadi

Saha

2021

Transportation Research Record

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Calibration of traffic simulation models is a critical component of simulation modeling. The increased complexity of the transportation network and the adoption of emerging vehicle- and infrastructure-based technologies and strategies have motivated the development of new methods and data collection to calibrate the simulation models. This study proposes the use of high-resolution signal controller data, combined with a two-level clustering technique for scenario identifications and a multi-objective optimization technique for simulation model parameter calibration. The evaluation of the calibration parameters resulting from the multi-objective optimization based on travel time and high-resolution signal controller data measures indicate that the simulation model that uses these optimized parameters produces significantly lower errors in the split utilization ratio, green utilization ratio, arrival on green, and travel time compared with a simulation model that uses the software’s default parameters. When compared with a simulation model that uses calibration parameters obtained based on the optimization of the single objective of minimizing the travel time, the multi-objective optimization solution produces comparably low travel time errors but with significantly lower errors for the high-resolution signal controller data measures.

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Pattern Recognition Using Clustering Analysis to Support Transportation System Management, Operations, and Modeling

Cited by 28 publications

References 28 publications

Minimizing the Congestion Index and Mode Share of Traffic Congestion in Urban Area

Minimizing the Congestion Index and Mode Share of Traffic Congestion in Urban Area

Characteristics of spring consecutive dry days with different durations across China based on the objective zoning approach

Using High-Resolution Signal Controller Data in the Calibration of Signalized Arterial Simulation Models

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