A case study of urban rail transit network in Klang Valley

• Main Author: Lee, Nicholas Bryan Zhi Yi
• Format: Final Year Project / Dissertation / Thesis
• Published: 2024
• Subjects: TA Engineering (General). Civil engineering (General); TF Railroad engineering and operation
• Online Access: http://eprints.utar.edu.my/6414/1/1903174_FYP_Report_%2D_Nicholas_Bryan_Zhi_Yi_Lee.pdf; http://eprints.utar.edu.my/6414/

The urban rail transit networks worldwide are experiencing a growing disparity between supply and demand. In the context of Klang Valley, travelling with the urban rail transit network results in significant journey time between origin and destination (OD) compared to private vehicles due to the mature road network. The current Klang Valley urban rail transit network consists of radial lines, necessitating transfers at central business district (CBD) interchange stations and leading to bottleneck congestion. This study aims to assess the quantitative improvement of the forecasted network, which includes the introduction of LRT 3 and MRT Circle Line, in comparison to the existing operational network. Additionally, the compatibility of the available urban rail transit network infrastructure with passenger flow demand is evaluated. A comprehensive analysis was conducted with quantitative indicators including average shortest path length, betweenness centrality, closeness centrality, degree centrality, and clustering coefficient. Results indicate the important stations are predominantly located around CBD areas. The results indicate significant improvements in the forecasted network across various weighted analysis. The global average shortest path length decreased by 5.38% in unweighted network, while increased by 6.23% in time-weighted and 4.71% in distance-weighted network analysis. Similarly, global closeness centrality decreased by 5.16% in the unweighted network but increased by 6.06% and 3.50% in the time-weighted and distance-weighted analyses, respectively. Betweenness centrality showed overall increases of 16.05% (unweighted), 17.89% (time-weighted), and 18.75% (distance-weighted). Global degree centrality shows 0.83% increment while significant decrease of 18.53% was observed in global clustering coefficient. Strong regression values of compatibility analysis between network infrastructure and passenger flow based on average shortest path length and closeness centrality, with regression values ranging from 63.49% to 78.97%, while betweenness centrality shows lower regression ranging from 17.58% to 29.61%. The forecasted network demonstrates enhanced connectivity and reduced significance of individual stations with the additional shorter routes between OD pairs, effectively addressing congestion and long journey times.