1. Estimating network fundamental diagram using principal component analysis-based strategy: A case study of urban transport networks.
- Author
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Yusoff, Wan Muhammad Fazdlie Aqmal Bin Wan, Jusoh, Ruzanna Mat, Shukri, Fatin Amirah Ahmad, Ali, Fazilatulaili, Rafiuddin, Nurhana Mohamad, and Ali, Sharifah Aishah Syed
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TRAFFIC monitoring , *SENSOR networks , *SENSOR placement , *VEHICLE detectors , *PRINCIPAL components analysis - Abstract
The purpose of this study is to find the resourceful links to use as monitoring resources (detectors/sensors) to collect traffic data in order to estimate an accurate Network Fundamental Diagram (NFD). The NFD which depicts the relationship between average flow and average occupancy is an established tool utilized for observing and reducing traffic congestion in major cities. The ultimate goal is to critically select resourceful link(sensors) using a systematic technique assisted by principal component analysis (PCA). This allows the construction of reduced NFDs with less number of sensors while retaining the most informative link(sensors). The performance of the proposed method is tested and compared with four other link selection methods, evaluated with real loop-detector data from an urban network. The suggested method enables the selection of the appropriate sensor for traffic monitoring by correlating the primary component to the relevant resourceful variable (link). The evaluation results indicate good estimation accuracy and effective. These findings highlight the effectiveness of the suggested PCA-based method in identifying an ideal sensor placement on networks. It is expected that the proposed strategy will play a significant role in achieving smart yet economical sensor installation whilst improving the estimation of NFD. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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