BRT Corridor Demand — CMP 2008 vs 2021 Reality
The 2008 PCMC Comprehensive Mobility Plan proposed a network of BRT corridors to handle growing cross-city demand. For each corridor, the CMP modelled peak-hour passenger flows. Thirteen years later, the 2021 Pune Metro DPR traffic surveys measured actual demand on many of the same corridors — providing a rare opportunity to evaluate how accurate the CMP forecasts were.
The results are uneven: some corridors (NH-50 Nashik Phata–Moshi, Nashik Phata–Wakad) saw demand roughly double the 2008 projections by 2021. Others held closer to forecast. The CMP's 2008 corridor map also proposed specific sections with start/end coordinates and per-section trip estimates.
Corridor Overview
Corridors Tracked
Total Peak Demand 2008
Total Peak Demand 2021
2008 Projections vs 2021 Observations
The NH-4 (Old Highway) corridor recorded the highest projected demand in 2008 at 189,427 — not included in the 2021 comparison data. For corridors where both years are available, NH-50 (Nashik Phata–Moshi) and Nashik Phata–Wakad show the largest absolute growth: both roughly doubled between 2008 and 2021, reflecting the northward expansion of PCMC's residential and commercial footprint.
Proposed Route Map
The CMP proposed 30 specific route sections across 8 BRT corridors. Each section has defined start and end coordinates and a projected passenger demand. The map below shows the midpoint of each section, with bubble size proportional to projected daily trips.
Proposed BRT Sections — CMP 2008 (Bubble = Projected Trips/Day)
See Also
- PMPML BRT Service Statistics — Actual PMPML BRT operations 2023–2025: fleet, ridership, revenue
- Traffic Surveys — 2008 baseline and 2021 metropolitan surveys
- PCMC Growth Context — Population, urban expansion, and CMP transport demand projections
- Public Transport Overview — Three eras of bus transit
Data sources: PCMC Comprehensive Mobility Plan (2008) for projected BRT corridor demand and route sections; Pune Metro DPR traffic surveys (2021) for observed corridor traffic.
Data Queries
SQL queries powering the visualizations above.
