1. Project Introduction — Background & Problem Statement

1.1 Background

Reliable traffic data is the bedrock of every sound road safety, transport planning, and infrastructure investment decision. Without knowing how many vehicles use a road, what types they are, how fast they travel, how pedestrians interact with traffic, and how volumes shift across times of day, week, and year — road authorities cannot design safely, engineers cannot size infrastructure appropriately, and planners cannot prioritize interventions where they are most needed.

In Liberia and across the Mano River Union sub-region, systematic traffic counting is rarely conducted, poorly standardized, and almost never integrated into a shared national data management system. Traffic data that does exist is fragmented across projects, inaccessible to road authorities and planners, and quickly becomes outdated without periodic updating. The result is that major road safety, engineering, and policy decisions are made on the basis of estimates, assumptions, or outdated surveys — leading to misallocated investment and missed opportunities to prevent crashes and save lives.

The Traffic Count Project (PT-TC) is RSAI's initiative to build a systematic, multi-method, technology-enabled traffic counting and data management capability — generating the reliable, classified, and GIS-integrated traffic data that underpins road safety risk assessments, star ratings, blackspot identification, transport planning, and investment decisions across Liberia's road network.

1.2 Problem Statement

The current state of traffic data in Liberia and the sub-region presents the following critical gaps:

  • No standardized national traffic counting methodology — existing counts use inconsistent approaches, intervals, vehicle classification schemes, and site selection criteria, making data incomparable across projects and time periods
  • No national traffic count database or data management system — traffic data exists in scattered project reports and spreadsheets, with no central repository accessible to road authorities, planners, or researchers
  • Limited coverage of vehicle classification, pedestrian counts, and speed data — most existing counts capture only total vehicle volumes, missing the disaggregated data needed for road safety analysis and design
  • No systematic integration of traffic data with road safety audits, crash analysis, or risk mapping — preventing the evidence-based identification of crash blackspots and high-risk corridors
  • Absence of IoT-enabled, automated, or cloud-based traffic monitoring infrastructure — leaving Liberia dependent on expensive manual counts that cannot be sustained continuously
  • No traffic growth rate data or trend analysis — making it impossible to forecast future demand, assess infrastructure capacity, or model the safety implications of traffic growth
  • Peak hour, seasonal variation, and festivity factor data not collected — resulting in infrastructure and signal timing decisions that do not reflect actual peak demand conditions
You cannot build safer roads for traffic you have never counted, cannot map risk on corridors you have never measured, and cannot make smarter investments without knowing who is using the road and how.
Strategic Role in 2026

In 2026, RSAI's strategic goal for PT-TC is to establish a national road traffic data management bank — a centralized, cloud-based, GIS-integrated repository of traffic count data available for analysis and sharing with road authorities, development banks, researchers, and planning agencies. This traffic data bank becomes the quantitative foundation for RSAI's star rating inputs, risk mapping, blackspot identification, transport planning advisory, and policy recommendations — positioning RSAI as Liberia's primary source of reliable, current, and systematically collected road traffic intelligence.

The Traffic Count Data Pipeline

PT-TC generates traffic intelligence through a structured data pipeline — from field counting through to policy application:

Site Selection Location type, road function, hazard assessment
→
Data Collection Manual, video, automated counts
→
Validation Error checking, outlier detection
→
Database Entry Cloud-based traffic data bank
→
Analysis & GIS Dashboards, risk maps, charts
→
Policy Application Star rating, blackspot, planning

2. Project Objectives

  1. Establish a standardized national traffic counting methodology for Liberia — defining site selection criteria, counting methods, vehicle classification schemes, 15-minute interval protocols, and data validation standards applicable across all road types and contexts.
  2. Conduct systematic manual, video-based, and automated traffic counts at selected sites across the national road network — collecting Average Daily Traffic (ADT), directional flow, turning movement, peak hour, and seasonal variation data.
  3. Collect disaggregated vehicle classification data — covering cars, buses, trucks, two-wheelers, three-wheelers, pedestrians, and other road users — providing the granular traffic intelligence needed for road safety design and risk assessment.
  4. Conduct speed and flow analysis at priority corridors — measuring travel time, speed distribution, congestion indicators, delay patterns, and overtaking behavior to support speed management and intersection safety interventions.
  5. Build and operationalize a national road traffic data management bank — a cloud-based, GIS-integrated database housing all PT-TC traffic count data, accessible for analysis and sharing with road authorities, development banks, planners, and researchers.
  6. Develop GIS-based traffic maps, dashboards, and technical reports that translate raw count data into accessible, decision-ready traffic intelligence for road authorities, infrastructure investors, and policy makers.
  7. Integrate traffic count data with road safety audits, crash data, blackspot identification, and ManoRAP star rating inputs — creating a comprehensive evidence base for risk mapping and targeted intervention.
  8. Build institutional capacity and manpower development among field supervisors, data analysts, and road authority staff in traffic counting methodology, data management, and analytical reporting.
  9. Establish a periodic traffic count programme — including seasonal counts, festivity factor assessments, and traffic growth rate tracking — to maintain a current and growing national traffic data baseline over time.

3. Project Approach & Methodology

The PT-TC project adopts a multi-method, technology-enabled, and quality-assured traffic counting approach — combining three counting methods based on site type, data requirement, and available resources, with all outputs feeding into a centralized, cloud-based national traffic data management bank.

Manual Traffic Counts Trained field teams conduct structured manual traffic counts at selected sites — recording vehicle classification, directional flow, turning movements, pedestrian crossing volumes, and traffic behavior at 15-minute intervals. Field logs are maintained and supervised by qualified field supervisors. Manual counts are used where automated infrastructure is not yet installed, providing flexibility and comprehensive behavioral observation including overtaking, signal compliance, and road user interaction.
Video-Based Traffic Counting Camera-based video recording is deployed at priority sites — capturing continuous traffic flow that can be reviewed and classified post-collection. Video counting enables higher accuracy, independent verification, and detailed analysis of vehicle classification, speed estimation, gap acceptance, and traffic behavior patterns. Video footage is stored and analyzed using traffic analysis software with data uploaded to the national traffic database.
Automatic Traffic Counters (ATCs) & IoT Technology Automatic Traffic Counters are installed at permanent or semi-permanent high-priority count sites — providing continuous, real-time traffic volume, speed, and vehicle classification data. IoT-enabled counters transmit data directly to the cloud-based traffic data bank, enabling continuous monitoring of traffic density, flow rate, peak patterns, congestion indicators, and traffic growth rates without ongoing manual field presence.
Data Validation & Quality Control All traffic count data undergoes structured validation — including error checking, outlier detection, cross-validation between counting methods, and seasonal adjustment using festivity factors and growth rate corrections. A data quality control protocol ensures all data entering the national database meets defined accuracy and completeness standards before being released for analysis or policy use.
National Traffic Data Management Bank All validated traffic count data is uploaded to RSAI's cloud-based national traffic data management bank — a structured, GIS-integrated database cataloguing count sites, vehicle classifications, directional flows, speed data, pedestrian volumes, seasonal patterns, and traffic growth rates. The database is designed for analysis, sharing, and long-term data ownership — providing road authorities, development banks, and planning agencies with a reliable, current national traffic baseline.
GIS Mapping, Dashboards & Technical Reporting Traffic count data is processed into GIS-based traffic maps, interactive dashboards, and structured technical reports — visualizing average daily traffic distributions, peak hour concentrations, vehicle mix profiles, speed and congestion patterns, and pedestrian exposure hotspots across the network. Outputs are integrated with ManoRAP star rating inputs and crash blackspot analysis to create a comprehensive road safety intelligence product.

Vehicle Categories Counted & Classified

PT-TC systematically counts and classifies all road user categories — providing the disaggregated traffic intelligence needed for road safety design, risk assessment, and policy:

Cars & Light Vehicles
Buses & Minibuses
Trucks & Heavy Vehicles
Two-Wheelers (Motorcycles)
Three-Wheelers (Tricycles)
Pedestrians
Non-Motorized Vehicles
Special & Oversized Vehicles

Temporal Data Collection Framework

Traffic counts are structured across multiple time dimensions to capture daily, weekly, seasonal, and annual traffic patterns:

15-Min Intervals

Sub-hourly counts capturing peak and off-peak flow variations throughout the counting day.

Peak Hours

Morning, afternoon, and evening peak hour analysis for signal timing, intersection design, and congestion management.

Days & Weeks

Weekday vs. weekend variation analysis capturing market day, school day, and commuter traffic patterns.

Seasonal & Annual

Seasonal counts capturing wet/dry season variation, festivity factors, and annual traffic growth rate trends.

Key Data Outputs from PT-TC

The PT-TC project produces the following core traffic data outputs — each feeding directly into road safety assessment, planning, and policy applications:

Average Daily Traffic (ADT) Reports Classified ADT data by vehicle category, direction, and road type — providing the foundational traffic volume input for road design standards, pavement design, capacity analysis, and star rating assessments.
Speed & Flow Analysis Reports Speed distribution data, travel time measurements, congestion indicators, delay patterns, and flow rate analysis — supporting speed management interventions, signal timing optimization, and identification of speed-related crash risk.
Turning Movement & Intersection Analysis Directional flow and turning movement counts at intersections and conflict points — providing the data needed for intersection design, signal timing, and road safety audit of high-risk junction configurations.
Pedestrian Crossing Volume Reports Pedestrian flow data at crossing points, market areas, school zones, and hospital zones — identifying high-exposure pedestrian locations requiring safety treatment, signage, or controlled crossing infrastructure.
GIS Traffic Maps & Risk Mapping Layers Spatially referenced traffic volume, speed, and vehicle mix data integrated into GIS — producing traffic density maps, risk mapping layers for ManoRAP, and blackspot-linked traffic exposure data for road safety investment prioritization.
Traffic Growth Rate & Trend Analysis Annual traffic growth rate data and trend analysis from periodic and continuous counting sites — providing the traffic forecasting inputs needed for infrastructure capacity planning, road design life assessment, and toll policy pricing models.

4. Project Organization & Staffing

Implementing Organization: Road Safety Action International (RSAI)

Role Function in PT-TC
RSAI Programme Director Strategic oversight, client engagement, institutional partnership, and data bank governance
Lead Traffic Engineer / Data Manager Design and manage the counting methodology, database architecture, GIS integration, and technical reporting standards
Field Supervisors Manage field counting teams, ensure counting protocol compliance, maintain field logs, and conduct on-site quality checks
Traffic Count Field Teams Conduct manual and video-based traffic counts at assigned sites — recording vehicle classifications, pedestrian volumes, directional flows, and turning movements at 15-minute intervals
ATC & IoT Equipment Technicians Install, configure, maintain, and troubleshoot automatic traffic counters and IoT monitoring devices; manage data transmission to the cloud database
GIS & Data Analysts Process, validate, and analyse traffic count data; produce GIS maps, dashboards, ADT reports, speed analysis, and technical outputs for policy and planning use
Database Administrator Manage the national traffic data bank — ensuring data integrity, access control, regular updates, backup, and structured data sharing with authorized stakeholders
Ministry of Public Works (MPW) Primary government data user and partner; provides site access, road network information, and institutional endorsement of the national traffic data bank
Development Banks & Project Owners Commission traffic count surveys for road investment projects; use PT-TC data for traffic demand analysis, design justification, and toll policy pricing
M&E Officer Track counting programme milestones, monitor data quality, assess capacity development outcomes, and report to stakeholders and clients

5. Project Schedule

The PT-TC counting programme is implemented in five phases — from methodology development and equipment procurement through to database operationalization and ongoing periodic counting:

1
Methodology Development & Site Selection Develop the standardized national traffic counting methodology — defining site selection criteria, counting protocols, vehicle classification schemes, 15-minute interval standards, data validation procedures, and quality control processes. Conduct site assessments to select priority counting locations across all road types, including high-risk corridors, urban intersections, border crossing points, and rural trunk roads. Produce the site inventory and counting schedule.
2
Equipment Procurement & Database Setup Procure manual counting tools, video recording equipment, and automatic traffic counters. Configure IoT-enabled data transmission systems and set up the cloud-based national traffic data management bank — including database architecture, GIS integration, dashboard interface, and user access controls. Train field supervisors, counting teams, and database operators on equipment use and data protocols.
3
Baseline Traffic Count Programme Conduct the inaugural systematic traffic count programme across all selected sites — deploying manual, video-based, and automated counting methods as appropriate per site type. Collect classified ADT, directional flow, turning movements, pedestrian counts, speed data, and peak hour data at all sites. Conduct seasonal and festivity factor counts to capture full traffic variation patterns. Upload all validated data to the national traffic data bank.
4
GIS Analysis, Dashboard Development & Reporting Process all baseline traffic count data through GIS analysis — producing traffic density maps, risk mapping layers, ADT reports, speed analysis outputs, peak hour profiles, and vehicle mix reports. Develop the interactive traffic dashboard for RSAI and road authority use. Produce the first national traffic count technical report. Integrate traffic data with ManoRAP star rating inputs and crash blackspot data for comprehensive road safety risk mapping.
5
Periodic Counting Programme & Data Bank Growth Establish the ongoing periodic traffic counting programme — including quarterly, seasonal, and annual counts at priority sites to track traffic growth rates, update ADT baselines, and capture changing traffic patterns. Expand the national traffic data bank continuously, adding new sites and updating existing data. Promote data sharing with road authorities, development banks, and planning agencies as the data bank grows into Liberia's primary road traffic intelligence resource.

6. Indicative Budget

Budget Category Description Indicative Share
Personnel & Field Teams Traffic engineers, field supervisors, counting teams, GIS analysts, database administrator, M&E officer 30%
Equipment & Technology Automatic traffic counters, IoT devices, video cameras, manual counting tools, field tablets, equipment installation 25%
Database & GIS Systems Cloud database setup, GIS software, dashboard development, data transmission systems, cybersecurity 15%
Field Operations & Logistics Site access, transportation, field accommodation, counting day logistics, safety equipment for field teams 15%
Reporting & Dissemination Technical report production, GIS map outputs, dashboard publication, data sharing with stakeholders 10%
Administration & Overheads Programme management, quality control, training, institutional coordination 5%
Total 100%

7. Monitoring, Evaluation & Learning (MEL)

Count Site Coverage Number of count sites established across the national road network; coverage by road type, region, and functional classification; % of high-risk corridors with current ADT data.
Traffic Data Bank Growth Number of records in the national traffic data bank; data completeness rate per site; % of sites with classified, validated data across all vehicle categories and temporal dimensions.
Data Quality & Validation % of count records passing validation and quality control checks; outlier detection rate; cross-method consistency scores between manual, video, and automated counting results.
Data Use & Institutional Uptake Number of road authority, development bank, and planning agency users accessing the traffic data bank; number of road safety audits, star rating assessments, and planning studies using PT-TC data.
Capacity Development Number of field supervisors, counting teams, and road authority staff trained in traffic counting methodology and data management; quality improvement in field counting outputs over successive counting cycles.

8. Project Log Frame — Outputs, Outcomes & Impact

Number of sites counted; ADT, classified, speed, and pedestrian data collected per site
Level Statement Indicators Means of Verification
Impact Road safety, infrastructure investment, and transport planning decisions in Liberia grounded in reliable, current, and classified traffic data — contributing to reduced crashes, smarter investment allocation, and better-designed roads % of major road investment decisions referencing PT-TC traffic data; improvement in road design standards compliance on projects using PT-TC data; contribution to ManoRAP star rating accuracy Road project documentation; MPW investment records; ManoRAP assessment reports; development bank project appraisals
Outcome 1 A national road traffic data management bank operational — providing reliable, classified, GIS-integrated traffic intelligence accessible to road authorities, planners, and development partners Database operational and regularly updated; number of sites with current ADT data; number of authorized data users accessing the bank Database records; user access logs; data download statistics; stakeholder uptake reports
Outcome 2 Road safety audits, ManoRAP assessments, blackspot identification, and transport planning using reliable PT-TC traffic data inputs Number of audits and assessments citing PT-TC data; % of star rating assessments incorporating classified ADT inputs from the data bank Audit reports; ManoRAP assessment documentation; planning study citations
Outcome 3 Strengthened institutional capacity for traffic data collection, management, and use among RSAI staff and road authority partners Number of staff trained; data quality scores improving over time; road authority staff independently conducting counts using PT-TC standards Training records; quality assessment reports; institutional capacity reviews
Output 1 Standardized national traffic counting methodology developed and adopted Methodology documented; adopted by RSAI and road authorities; field protocols operational Methodology documentation; adoption records
Output 2 Systematic traffic counts conducted at priority sites across the national road network Field count records; data files; field logs
Output 3 National traffic data management bank established and operational Database live; data uploaded, validated, and accessible; GIS integration active Database operational records; user access logs
Output 4 GIS traffic maps, dashboards, and technical reports produced and disseminated Maps, dashboards, and reports produced per count cycle; stakeholders receiving outputs Published reports; GIS map files; dashboard usage statistics
Output 5 Periodic traffic counting programme established for ongoing data bank growth Quarterly, seasonal, and annual counts scheduled and conducted; growth rate data compiled Count schedule records; periodic count reports; database update logs
Activity 1 Develop counting methodology and select count sites Methodology finalized; sites selected and documented Methodology document; site inventory
Activity 2 Procure equipment and set up cloud database Equipment procured; database operational Procurement records; database setup documentation
Activity 3 Conduct baseline traffic count programme at all sites Counts completed; data validated and uploaded Field count records; database upload logs
Activity 4 Process data, produce GIS outputs and technical reports GIS maps, dashboards, and reports produced Published outputs; GIS files; report records
Activity 5 Establish and implement periodic counting programme Periodic counts conducted on schedule Count schedule; periodic count reports
Activity 6 Build capacity and promote data bank use Training delivered; data bank actively used by road authorities and partners Training records; user access logs; uptake reports

9. Conclusion

Every vehicle counted is a data point that makes the road it travels safer to design and manage.

Every peak hour measured is evidence that informs where signals are needed and where crashes will happen next.

Every record in the national traffic data bank is a building block of the evidence infrastructure Liberia's roads deserve.

The Traffic Count Project is RSAI's commitment to ensuring that every road safety decision, every infrastructure investment,
and every policy recommendation in Liberia is grounded in reliable, current, and systematically collected traffic data —
held in a national data bank that grows, improves, and serves every road user in the country.

Partner With Us

We welcome partnerships with institutions committed to evidence-based road planning and traffic data management in Liberia:

Ministry of Public Works Road Authorities World Bank African Development Bank Development Partners Transport Planners Research Institutions Technology Partners

Together, we can build Liberia's first national road traffic data management bank — and make every road investment decision smarter, every safety assessment stronger, and every infrastructure design safer.