Planned Congestion Dataset: PCU-Based Infrastructure Capacity Analysis for Phnom Penh, Cambodia
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https://data.mendeley.com/datasets/pdyystfnz8/1
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资源简介:
This dataset accompanies the manuscript “Planned Congestion: How Development Approvals Embed Latent Infrastructure Failure in Rapidly Urbanising Cities — Evidence from Phnom Penh, Cambodia.” It provides all parameters, calculations, and scenario outputs required to reproduce the Passenger Car Unit (PCU)-based infrastructure capacity analysis presented in the paper.
The dataset operationalises the concept of planned congestion, defined as infrastructure failure embedded in the development process through the decoupling of development approval from capacity-based planning. The case study focuses on Phnom Penh, Cambodia, where rapid speculative urban development has outpaced infrastructure provision.
The Excel workbook is structured to ensure full transparency and reproducibility. The Parameters sheet contains all baseline inputs, including total floor area, worker density, modal split assumptions, PCU conversion factors, peak-hour factors, and network capacity. The Base_Calculation sheet reconstructs the core V/C calculation under current and full occupancy conditions. The Occupancy_Scenarios sheet presents V/C ratios across occupancy levels from 20% to 100%, corresponding to Figure 2 in the manuscript. The Modal_Split_Sensitivity sheet provides sensitivity analysis across different motorcycle–car modal shares, corresponding to Appendix A4.2. Additional sheets include extended sensitivity analyses and figure-ready datasets.
All calculations are formula-based and visible within the workbook to facilitate verification. No external or proprietary data are used; the dataset is fully synthetic and derived from transparent assumptions documented in the manuscript.
This dataset enables replication of all reported results, including the finding that the system operates at Level of Service F (V/C ≈ 1.17) at current occupancy (~60%) and reaches systemic overload (V/C ≈ 1.95) under full occupancy.
提供机构:
Mendeley Data
创建时间:
2026-04-27



