InfraLens
HomeIS CodesIRCCPHEEOHandbookDesign RulesPMCQA/QCBIMArticlesToolsAbout Join Channel
Join
HomeIS CodesIRCCPHEEOHandbookDesign RulesPMCQA/QCBIMArticlesToolsAbout Join WhatsApp Channel
InfraLens
HomeIS CodesIRCCPHEEOHandbookDesign RulesPMCQA/QCBIMArticlesToolsAbout Join Channel
Join
HomeIS CodesIRCCPHEEOHandbookDesign RulesPMCQA/QCBIMArticlesToolsAbout Join WhatsApp Channel
IRC 9 : 1972
PDFGoogleCompareIRC Portal
Link points to Internet Archive / others. Not hosted by InfraLens. Details

Traffic Census on Non-Urban Roads

International Comparison — Coming Soon
CurrentEssentialRecommended PracticeTransportation · Traffic Engineering / Data
OverviewValues7InternationalTablesFAQ15Related

Overview

IRC 9:1972 is the Indian Standard (IRC) for traffic census on non-urban roads. IRC 9:1972 is the foundational code for traffic census methodology on non-urban Indian roads — national highways, state highways, major district roads, and other district roads. Traffic data is the ground truth for road design, capacity analysis, pavement thickness selection, and economic evaluation. IRC 9 specifies minimum 7 consecutive days of counting for annual estimation, decennial comprehensive census, vehicle classification (2W, 3W, Car, LCV, Truck, Bus, MAV, etc.), PCU conversion factors, seasonal variation factors, directional splits, and growth projections. Amendment No. 1 (2015) added automatic electronic counter specifications (video, pneumatic tube, inductive loop); Amendment No. 2 (2022) added GPS-based O-D data collection methods and ITS integration. Traffic census is now partially automated — National Transport Planning and Research Centre (NATPAC) operates continuous count stations on major NH for real-time data. State PWDs are upgrading to electronic counting. However, data quality issues remain: manual counts have ±10-15% error, and long-term archives are inconsistent.

Specifies methodology, sample size, duration, classification, and reporting requirements for traffic census on non-urban roads (NH, SH, MDR, ODR) — the fundamental data input for road design, capacity analysis, pavement design, and economic evaluation.

Status
Current
Usage level
Essential
Domain
Transportation — Traffic Engineering / Data
Type
Recommended Practice
Amendments
Amendment No. 1 (2015) — automatic electronic counter specifications; Amendment No. 2 (2022) — GPS O-D data collection, ITS integration
Typically used with
IRC 64IRC 106IRC SP 79IRC 37
Also on InfraLens for IRC 9
7Key values5Tables15FAQs
Practical Notes
! 7-day count should include at least one weekend — weekday vs weekend traffic often differs 30-50% on arterials. Weekend-only counts are typically under-representative.
! Seasonal variation factors are corridor-specific. Kolkata-Siliguri NH34 has huge Durga Puja and Poila Baisakh peaks; Goa coastal highway has December tourism peak — apply corridor-specific factors.
! Manual classified counts are accurate but labour-intensive (~4 observers × 24 hours × 7 days = 672 person-hours per station). Automatic counters 80-90% cheaper per station but need calibration.
! Pneumatic tube counters fail on potholed pavements (tube gets damaged). Use inductive loop or video counters on worn pavements.
! Video-based counters with AI classification now mainstream — NHAI has deployed on DMIC expressway, Samruddhi Mahamarg. 95%+ classification accuracy.
! Axle-load surveys (separate from traffic census) equally important for pavement design. Portable weighing station collects axle weights; combined with volume gives ESAL (Equivalent Single Axle Load).
! Growth rate projection: 5-8% annual is standard for NH. Recent data suggests 3-5% for mature NH corridors and 10-15% for new expressways. Verify with 3-year historical growth.
! PCU conversion: IRC 64 gives standard factors; corridor-specific variations possible for truck-heavy vs passenger-heavy routes. Re-calibrate PCU using local observations when practical.
! Directional split (e.g., 70:30) matters for capacity analysis — peak-direction flow is critical constraint. Non-urban highways typically 55:45 to 60:40 directional, higher during commute.
! Peak Hour Factor (PHF) at 0.08-0.12 means peak hour traffic is 8-12% of daily. For urban/interstate PHF is higher (0.10-0.13) due to commute pattern.
! Data archiving: corridor-level electronic database essential. Many state PWDs lost historic census data — rendering trend analysis impossible.
! DPR stage: traffic forecast 30-year horizon is basis for investment decision. 30% error in growth projection (not uncommon) translates to wrong road capacity decisions.
! Bus vs truck ratios matter: bus-heavy corridors need different design (wider passing lanes, bus bays) vs truck-heavy (stronger pavement, wider shoulders).
! Cross-border traffic (e.g., Nepal, Bangladesh borders): separate counting for international traffic; often under-reported due to informal border crossings.
! Origin-Destination (O-D) surveys: separate from volume census; uses roadside interview or GPS-based tracking; provides travel pattern matrix — essential for network planning.
! Speed-and-delay surveys: using floating car technique, drive-along a corridor timing speed drops. Identifies bottlenecks — essential for upgrade prioritization.
! Modern trend: smartphone-based O-D data (via Google, Uber, etc.) increasingly replaces traditional interview surveys. Cost-effective but needs data access agreements.
! Truck driver compliance: many trucks exceed axle-load limits. Census must capture this — combine with weighbridge data where available.
! For PPP BOT projects, traffic projections are basis for toll revenue forecast. Overestimation (common in concessionaire bids) leads to project failure — conservative traffic projections recommended.
! Covid impact on traffic census (2020-2021): significant disruption. 2022+ data more reliable for post-Covid projection. Historic 2017-2019 data useful baseline.
traffic censustraffic countADTAADTPCUclassified countsIRC

International Equivalents

🌐
International Comparison — Coming Soon
We're adding equivalent international standards for this code.

Key Values7

Quick Reference Values
min census duration days7
census frequency years10
NH station spacing km50
SH station spacing km100
typical NH growth pct5-8
typical SH growth pct3-5
typical PHF non urban0.08-0.12
Key Formulas
AADT = ADT × Monthly Seasonal Factor / 12
Projected traffic (Year n) = Base traffic × (1 + growth_rate)^n
Total PCU = Σ (Vehicle count × PCU factor) across all categories
Peak Hour Factor (PHF) = Peak Hour Volume / (AADT / 24)

Tables & Referenced Sections

Key Tables
Table 6.1 — Vehicle classification scheme
Table 7.1 — PCU conversion factors
Table 8.1 — Seasonal factor matrix (monthly)
Table 10.1 — Typical traffic growth rates by corridor type
Table 11.1 — Peak Hour Factor typical values
Key Clauses
Cl. 2 — Census types: origin-destination (O-D) study, classified volume count, speed-and-delay study, turning-movement count at intersections
Cl. 3 — Sample locations: minimum 1 station per 50 km of NH, 1 per 100 km of SH; locate at mid-block positions representative of corridor
Cl. 4 — Duration: 7 consecutive days minimum for annual estimation; 24-hour continuous count preferred; short-count (3-day) acceptable for preliminary studies
Cl. 5 — Frequency: decennial (every 10 years) for highways; annual spot counts at key stations; special counts for project DPR
Cl. 6 — Vehicle classification: 2W (two-wheeler), 3W (auto-rickshaw), Car/Jeep, LCV (light commercial vehicle), 2A truck (2-axle), 3A truck (3-axle), MAV (multi-axle vehicle), Bus, Tractor/Trailer
Cl. 7.1 — PCU conversion: per IRC 64 and IRC 106. Typical factors: 2W=0.5, 3W=0.7, Car=1.0, LCV=1.5, Truck=3.0, Bus=3.0, MAV=4.5
Cl. 7.2 — ADT (Average Daily Traffic): weekly average; AADT (Annual Average Daily Traffic): year-long average — obtained by applying seasonal factors to short-duration counts
Cl. 8 — Seasonal variation: monthly seasonal factors derived from continuous count stations on corridor; apply to short-count data
Cl. 9 — Directional split: 60:40 or 70:30 common for inter-city highways; 50:50 for symmetric corridors; documented in report
Cl. 10 — Growth rate: project traffic forward using Compound Growth per IRC 37. Typical 5-8% annually for NH, 3-5% for state highways
Cl. 11 — Peak hour factor (PHF): ratio of peak-hour volume to 1/24 of ADT. Typical 0.08-0.12 for non-urban roads
Cl. 12 — Data collection methods: manual classified counts, automatic pneumatic/inductive/video-based counters, GPS-enabled vehicle tracking for O-D
Cl. 13 — Data quality: counter calibration, observer accuracy (manual), quality-control of electronic data, cross-verification
Cl. 14 — Reporting: tabulation of counts, ADT by classification, PCU conversion, growth projections, capacity analysis input for road design
Cl. 15 — Archive: census data maintained at corridor/state level; digitized records for historical trend analysis

Related Resources on InfraLens

Cross-Referenced Codes
IRC 64:2017Guidelines for Capacity of Roads in Rural Are...
→
IRC 106:1990Guidelines for Capacity of Urban Roads in Pla...
→
IRC SP 79:2008Tentative Specifications for Stone Matrix Asp...
→
IRC 37:2018Guidelines for the Design of Flexible Pavemen...
→

Frequently Asked Questions15

How long should traffic census last?+
Per Clause 4: minimum 7 consecutive days for annual ADT estimation. Longer is better. Include weekday + weekend to capture variation. 24-hour continuous count preferred over daytime-only.
What vehicle classification to use?+
Per Clause 6: 2W (two-wheeler), 3W (auto-rickshaw), Car/Jeep, LCV (light commercial vehicle), 2A truck, 3A truck, MAV (multi-axle), Bus, Tractor/Trailer. Use IRC-standard 9-category classification for comparability.
How to convert vehicle counts to PCU?+
Per Clause 7.1 and IRC 64: typical PCU factors — 2W=0.5, 3W=0.7, Car=1.0, LCV=1.5, Truck=3.0, Bus=3.0, MAV=4.5. Total PCU = Σ (vehicle count × PCU factor). Used for capacity analysis.
What is AADT vs ADT?+
ADT (Average Daily Traffic) is weekly average from census. AADT (Annual Average Daily Traffic) is full-year average derived from ADT using seasonal factors. AADT is the parameter used for design and capacity analysis.
What seasonal factors should I apply?+
Clause 8: monthly seasonal factors derived from continuous count stations on the corridor. Typical range 0.85 (lean season) to 1.20 (peak season). For example: Kolkata-Siliguri has Durga Puja peak (1.30+), lean summer (0.85). Apply to short-count to estimate AADT.
How often should traffic census be repeated?+
Per Clause 5: decennial (every 10 years) comprehensive census recommended. Annual spot counts at key stations. Special counts for DPR preparation. Infrequent census creates planning blind spots.
What is the typical traffic growth rate for India?+
Per Clause 10: 5-8% annually for National Highways, 3-5% for state highways. New expressways see 10-15% initially, settling to 6-8% by Year 5. Verify with 3-year historical data for corridor-specific rate.
Can I use electronic counters per IRC 9?+
Yes — Amendment No. 1 (2015) explicitly allows pneumatic tube, inductive loop, and video-based automatic counters. Video counters with AI classification now standard for new deployments. Calibration against manual counts recommended.
What is the Peak Hour Factor (PHF)?+
PHF = peak hour traffic / (AADT / 24). Typical 0.08-0.12 for non-urban roads. Higher (0.10-0.13) for urban/interstate commute corridors. Lower (0.06-0.09) for tourism/recreational routes.
How do I conduct O-D (origin-destination) surveys?+
Clause 2: roadside interview (trucks pulled aside, asked origin and destination — classic method), license-plate matching between stations, or GPS-based tracking. Modern: smartphone mobility data (Google Mobility, Uber) — cheaper, privacy-compliant.
Does traffic census need weighbridge axle weights?+
Separate survey recommended — axle-load surveys (using portable weighing pads) capture axle weights by truck class. Combined with volume data gives ESAL for pavement design. IRC 37 uses this.
What are common errors in traffic census?+
(1) Manual count observer fatigue (>6 hours), (2) pneumatic tube damage on potholed pavement, (3) seasonal factor not applied, (4) peak direction underestimate, (5) 2W/3W undercount (difficult to distinguish at speed), (6) cross-border traffic omission.
How is O-D data used?+
O-D matrix shows travel pattern between origin-destination pairs. Used for: network planning, trip assignment modeling, decision on new corridors, toll forecast for PPP projects. Essential for regional planning.
What about axle-load violations?+
Not directly IRC 9 scope, but census should flag overloaded trucks — evidence for enforcement. Mumbai-Nagpur expressway census shows 15-25% of trucks over legal axle weight. Causes premature pavement failure.
For PPP projects, how robust should traffic projections be?+
Critical — toll revenue forecast depends on projection accuracy. Conservative (low-side) projections preferred to avoid project failure. Independent traffic consultant recommended; financial modelling should include sensitivity analysis on ±25% traffic variation.

QA/QC Inspection Templates

📋
QA/QC templates coming soon for this code.
Browse all 300 templates →