A free, web-based vertical transportation analysis tool for early-stage building design.
Architects, developers, and engineers can use this app to determine how many elevators a building needs, what size and speed they should be, and whether the design meets industry wait-time standards — all before engaging an elevator consultant.
Enter your building's floor areas (or upload an architect's area chart spreadsheet), select a building type, and the engine will:
- Calculate population demand from gross floor areas using BOMA net-to-gross ratios and industry density standards
- Zone the building into elevator banks automatically (Al-Sharif population-split method) or from spreadsheet-defined zones
- Back-solve for the minimum number of elevators that satisfy interval, handling capacity, and average wait time criteria simultaneously
- Select elevator speed and capacity from ASME A17.1 standard platforms using travel-height rules
- Estimate structural loads (pit reactions, machine beam loads, shaft dimensions) for early coordination with structural engineers
- Estimate electrical requirements (motor HP, kVA, feeder sizing, disconnects) per NEC Article 430
- Run Monte Carlo simulations (1,000 trials) to produce P10/P90 confidence intervals on wait times, validating the deterministic results
| Type | Density | Arrival Rate | Max Interval | Max AWT |
|---|---|---|---|---|
| Office (Standard) | 135 SF/person | 12% | 35 s | 30 s |
| Office (Prestige) | 175 SF/person | 13% | 33 s | 22 s |
| Hotel | 250 SF/person | 11% | 35 s | 25 s |
| Residential | 350 SF/person | 6.5% | 60 s | 42 s |
| Hospital | 120 SF/person | 10% | 35 s | 35 s |
| Ballroom / Event | 10 SF/person | 25% | 40 s | 40 s |
Toggle on Monte Carlo mode to run a probabilistic analysis alongside the deterministic calculation. Each trial samples random passenger counts (Poisson-distributed) and destination floors (population-weighted CDF), computing a full RTT for each sample. The result is a distribution of wait times with P10 and P90 bounds — useful for understanding real-world variability that a single deterministic number can't capture.
- Excel import — Drop in an architect's area chart (.xlsx) and the parser auto-detects floor levels, areas, floor-to-floor heights, zones, and density overrides
- Excel export — Download the area chart data back to .xlsx
- PDF export — Generate a professional single-page landscape report suitable for including in design packages
The calculation engine follows the classical Round Trip Time (RTT) methodology from CIBSE Guide D: Transportation Systems in Buildings. Key references:
- CIBSE Guide D (2020) — Transportation Systems in Buildings
- Dr. Albert So — "Fundamentals of Traffic Analysis" (Elevator World)
- Al-Sharif et al. — "Zoning a Building in Lift Traffic Design"
- Peters Research — "Lift Planning for High-Rise Buildings"
- Wang Sheng et al. — "Elevator Traffic-Flow Prediction Based on Monte Carlo Method" (Elevator World)
- ASME A17.1 / CSA B44 — Safety Code for Elevators and Escalators
- NEC Article 430 — Motors, Motor Circuits, and Controllers
A detailed methodology document is included in the repo: Methodology Synopsis (PDF)
- Frontend: React, TypeScript, Tailwind CSS, Recharts, shadcn/ui
- Backend: Express (Node.js)
- Computation: All analysis runs client-side in the browser — no server calls needed for calculations
- Hosting: Vercel
git clone https://github.com/Eric-Meller/elevator-traffic-analyzer.git
cd elevator-traffic-analyzer
npm install
npm run devThe app will be available at http://localhost:5000.
All values are planning-level estimates intended for early-stage architectural design coordination. Results should be verified by a qualified elevator consultant during detailed design. This tool is not a substitute for a professional traffic analysis.
MIT