Planned Congestion Dataset: PCU-Based Infrastructure Capacity Analysis for Phnom Penh, Cambodia

Description

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.

Steps to reproduce

Step 1. Open the dataset Download and open the Excel file: Planned_Congestion_Dataset.xlsx Step 2. Review model parameters Go to the “Parameters” sheet. Key inputs include: Total floor area (A) Floor area per worker (F) Peak-hour factor (P) Road capacity (C) PCU conversion factors (motorcycle and car) Car occupancy rate These parameters define all subsequent calculations. Step 3. Reproduce the base case calculation Go to the “Base_Calculation” sheet. Follow the calculation steps: Compute total workers: A / F Apply modal split (motorcycle and car shares) Convert workers to peak-hour trips: multiply by peak-hour factor (P) Convert trips to PCU demand: Motorcycle trips × PCU_m Car trips ÷ occupancy × PCU_c Sum total PCU demand Compute V/C ratio: total PCU demand / road capacity (C) This reproduces: V/C ≈ 1.17 at ~60% occupancy V/C ≈ 1.95 at full occupancy Step 4. Verify occupancy scenarios (Figure 2) Go to the “Occupancy_Scenarios” sheet. Vary occupancy from 20% to 100% Observe corresponding V/C ratios These values correspond to Figure 2 in the manuscript. Step 5. Verify modal split sensitivity (Appendix A4.2) Go to the “Modal_Split_Sensitivity” sheet. Compare V/C across different motorcycle shares Observe how lower motorcycle share increases V/C This reproduces Appendix A4.2. Step 6. Inspect figure-ready data Go to the “Figure_Data” sheet. Data for Figure 2 (occupancy vs V/C) Data for Figure 3 (car vs PCU comparison) These tables are directly used to generate figures in the manuscript. Step 7. Modify parameters (optional) Users may change values in the “Parameters” sheet to test alternative scenarios. All dependent calculations update automatically. All results in the manuscript can be reproduced by following the steps above without the use of any external data or software.

Institutions

• Handong Global University

  Gyeongsangbuk-do, Pohang

Categories

Licence