Traffic Monitoring Guide

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The Federal Highway Administration (FHWA) provides high-quality information to serve Government, industry, and the public in a manner that promotes public understanding. Standards and policies are used to ensure and maximize the quality, objectivity, utility, and integrity of its information. FHWA periodically reviews quality issues and adjusts its programs and processes to ensure continuous quality improvement.

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Except for the statutes and regulations cited, the contents of this document do not have the force and effect of law and are not meant to bind the States or the public in any way. This document is intended only to provide information regarding existing requirements under the law or agency policies.

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Table of Contents

• Acronyms
• Traffic Monitoring Guide Executive Summary
  • ES.1 Background
  • ES.2 Scope
  • ES.3 Users
  • ES.4 Manual Organization
  • ES.5 Supporting Information - Appendices Overview
• Chapter 1 Traffic Monitoring Program Introduction
  • 1.1 Introduction
    • 1.1.1 Legal Background
    • 1.1.2 TMG Organization
  • 1.2 Traffic Monitoring Program Purpose
  • 1.3 Traffic Data Types Introduction
    • 1.3.1 Volume Data
    • 1.3.2 Speed Data Collection
    • 1.3.3 Vehicle Classification Data
    • 1.3.4 Weight Data
    • 1.3.5 Travel Time
    • 1.3.6 Origin and Destination
  • 1.4 Traffic Data Program Users
    • 1.4.1 Federal Data Submittal Needs
      • 1.4.1.1 Introduction of HPMS Traffic and Travel Data Elements
      • 1.4.1.2 Introduction to the Traffic Monitoring and Analysis System
    • 1.4.2 Traffic Data Needs
    • 1.4.3 Data Usage Summary
  • 1.5 Program Design Considerations
    • 1.5.1 Statewide Traffic Monitoring Program Types (Regional, Roadway, Project Specific) Overview
      • 1.5.1.1 Regional and Sub-Area Traffic Monitoring Design
      • 1.5.1.2 Roadway Facility Specific Traffic Monitoring Design
    • 1.5.2 Components of a Traffic Data Program
      • 1.5.2.1 Continuous Count Program (Volume, Speed, Classification, and Weight)
      • 1.5.2.2 Short-Term Count Program (Volume, Speed, Classification, and Weight)
      • 1.5.2.3 Coverage Counts Program (Full Roadway Network Traffic Data Coverage Program)
      • 1.5.2.4 Special Counts Program (Roadway- or Supporting Program-Specific Traffic Data)
      • 1.5.2.5 Micromobility Permanent Data Program
      • 1.5.2.6 Micromobility Short Term Count Program
  • 1.6 Program Evaluation
  • 1.7 Coordinating Count Programs and Sharing Data
  • 1.8 Documentation and Metadata
• Chapter 2. Traffic Data Collection Technology and Equipment
  • 2.1 Monitoring Technology and Equipment
    • 2.1.1 Types of Traffic Data Collected
    • 2.1.2 Detection Methods
    • 2.1.3 Equipment Types
    • 2.1.4 Equipment Components
    • 2.1.5 Sensor Types Overview
    • 2.1.6 Sensor Technology Combinations
    • 2.1.7 Strengths And Weaknesses Of Commercially Available Sensor Technologies
  • 2.2 Selecting Motorized Traffic Monitoring Technologies
    • 2.2.1 Vehicle Detection Equipment Capabilities by Traffic Data Types
    • 2.2.2 Equipment Selection Considerations
    • 2.2.3 Equipment Selection for Short-Term Temporary Counts
    • 2.2.4 Equipment Selection for Continuous Counts
    • 2.2.5 Sensor and Equipment Location Considerations
    • 2.2.6 Sensor Layout and Configuration for Motorized Vehicle Detection
  • 2.3 Selecting Micromobility Counting Equipment
    • 2.3.1 Challenges Unique to Micromobility Counting
    • 2.3.2 How to Select Micromobility Counting Equipment Type
    • 2.3.3 Sensor Layout and Equipment Set-up
    • 2.3.4 Pressure and Seismic Sensors
    • 2.3.5 Video Image Processing
  • 2.4 Traffic Monitoring Equipment Evaluation, Maintenance, Calibration, and Quality Assurance Considerations
    • 2.4.1 Equipment Testing and Technology Evaluation
    • 2.4.2 Equipment Installation, Maintenance, and Operation
    • 2.4.3 Equipment Calibration and Data Monitoring
    • 2.4.4 Quality Assurance Considerations
• Chapter 3. Methodologies for Traffic Data Collection and Processing
  • 3.1 How To Design A Continuous Count Traffic Volume Data Collection Program
    • 3.1.1 Purpose
    • 3.1.2 Continuous Count Station Program Objectives (Volume)
    • 3.1.3 Continuous Count Program Design Process (Volume)
    • 3.1.4 Establishing And Evaluating a Continuous Count Program (VOLUME)
      • 3.1.4.1 Step 1: Review of the Existing Continuous Count Program
      • 3.1.4.2 Step 2: Develop an Inventory of the Available and Needed Continuous Count Locations and Equipment
      • 3.1.4.3 Step 3: Determine the Traffic Patterns to Be Monitored
      • 3.1.4.4 Step 4: Establish Temporal Pattern Groups
      • 3.1.4.5 Step 5: Determine Appropriate Number of Continuous Count Locations
      • 3.1.4.6 Step 6: Select Specific Count Locations
      • 3.1.4.7 Step 7: Compute Temporal Factors
  • 3.2 How To Design a Vehicle Classification Count (Axle and Length) Data Program
    • 3.2.1 Program Design Process Overview
    • 3.2.2 Step 1: Review the Existing Continuous Vehicle Classification Count Program
    • 3.2.3 Step 2: Develop an Inventory of Available Vehicle Classification Count Locations and Equipment
    • 3.2.4 Step 3: Determine the Traffic Patterns to Be Monitored
    • 3.2.5 Step 4: Establish Monthly Pattern Groups
      • 3.2.5.1 Understand Differences in Travel Patterns for Different Vehicle Classes
      • 3.2.5.2 Vehicle Classes Used for Factoring
      • 3.2.5.3 Select Factoring Methodology
      • 3.2.5.4 Create Initial Factor Groups (Traditional Approach)
    • 3.2.6 Step 5. Develop Monthly Factors
      • 3.2.6.1 Test the Quality of the Selected Groups
      • 3.2.6.2 Determine the Precision of the Factors
      • 3.2.6.3 Refine the Factor Groups
    • 3.2.7 Step 6 Determine the Appropriate Number of Continuous Vehicle Classification Locations
      • 3.2.7.1 Collect Additional Data and Refine the Established Process
    • 3.2.8 Step 7 Compute Final Group Temporal Adjustment Factors
  • 3.3 How To Design a Continuous Vehicle Weight Data Monitoring Program (Weight)
    • 3.3.1 Statewide WIM Program
    • 3.3.2 Step 1. Review the Existing Weight Data Collection Program
      • 3.3.2.1 Heavy Vehicle Weight User Needs
      • 3.3.2.2 Truck Weight Data Summaries
    • 3.3.3 Step 2. Inventory Existing WIM Sites and Assess WIM Site
    • 3.3.4 Step 3. Determine the Roadway Groups to Be Monitored
    • 3.3.5 Step 4. Establish Load Factor Groups
    • 3.3.6 Step 5. Determine the Appropriate Number of Weight Data Collection Locations
    • 3.3.7 Step 6. Select New Sites to Meet WIM Program Needs
    • 3.3.8 Step 7. Integrate the WIM Sites with the Remaining Count Program
      • 3.3.8.1 Total Size of the Weight Data Collection Program
  • 3.4 How To Design A Short-Term Data Collection Program
    • 3.4.1 Steps to Develop Short-Term Count Data Collection
    • 3.4.2 Duration of Counts
    • 3.4.3 Spacing and Geographical Coverage Methods for Grouping Count Locations (for Factoring)
    • 3.4.4 Count Frequency
    • 3.4.5 Special Needs Counts
    • 3.4.6 Statistical Samples in the Special Needs Program
    • 3.4.7 Point-Specific Estimates in the Special Needs Program
    • 3.4.8 Coordinating the Short-term and Special Needs Counts
    • 3.4.9 Adjusting Short-term Volume Counts to AADT
  • 3.5 How To Collect Speed Data Using Portable Counts
  • 3.6 How to Design a Short-Term Classification Data Collection Program (Axle and Length)
  • 3.7 How To Account for Traffic Variability
    • 3.7.1 Traffic Variability
    • 3.7.2 Programs and Technology Designs that Account for Traffic Variability
    • 3.7.3 Micromobility Permanent Data Program
  • 3.8 Traffic Data Processing
    • 3.8.1 Calculations and Computations for End-of-Year Processing
    • 3.8.2 Methods for AADT Calculations for CCS
    • 3.8.3 Procedure for AADT Calculation Based on CCS Data Using the FHWA Formula
    • 3.8.4 Computation of AVDT and DVDT
    • 3.8.5 Estimating Annual Average Daily Traffic Volumes from Short-Term Counts of More Than 24-Hours
    • 3.8.6 Estimating Annual Average Daily Truck Traffic Volumes from Short-Term Counts
  • 3.9 Factors
    • 3.9.1 Temporal Factors
    • 3.9.2 Axle Correction Factoring
    • 3.9.3 Factoring Short Term Counts
      • 3.9.3.1 Micromobility Example: Factoring Short-Term Counts
      • 3.9.3.2 Micromobility Weather Factor
    • 3.9.4 Considerations for Collecting Motorcycle Data and Correction Factoring
  • 3.10 Quality Assurance – Starts with The Data Quality Act Requirements
• Chapter 4. Traffic Monitoring Data Formats
  • 4.1 Monitoring Technology and Equipment
    • 4.1.1 Data Submission Frequency
    • 4.1.2 File Naming Recommendations
  • 4.2 Station Description Data Format (Pipe Delimited only)
    • 4.2.1 File Naming Recommendation
    • 4.2.2 Station Description – Pipe-Delimited Format
  • 4.3 Traffic Volume Data Format (Fixed Width or Pipe Delimited)
    • 4.3.1 File Naming Recommendation
    • 4.3.2 Traffic Volume Data – Fixed-Width Format
    • 4.3.3 Traffic Volume Data – Pipe-Delimited Format
  • 4.4 Vehicle Speed Data Format (Fixed Width or Pipe Delimited)
    • 4.4.1 File Naming Recommendation
    • 4.4.2 Vehicle Speed Data – Fixed-Width Format
    • 4.4.3 Vehicle Speed Data – Pipe-Delimited Format
  • 4.5 Vehicle Classification Data Format (Fixed Width or Pipe Delimited)
    • 4.5.1 File Naming Recommendation
    • 4.5.2 Vehicle Classification – Fixed-Width Format
    • 4.5.3 Vehicle Classification – Pipe-Delimited Format
  • 4.6 Weight Data Format (Fixed Width or Pipe Delimited)
    • 4.6.1 File Naming Recommendation
    • 4.6.2 Weight – Fixed-width Format
    • 4.6.3 Weight Data – Pipe-Delimited Format
  • 4.7 Detailed Individual Vehicle Record (IVR) Data Format (Fixed Width or Pipe Delimited)
    • 4.7.1 Traffic Volume Only Format (V)
    • 4.7.2 Speed and Length Classification Data Format (T)
    • 4.7.3 Axle Classification Data Format (C)
    • 4.7.4 Weight Data Format for Reporting Axle Weights (W)
    • 4.7.5 Vehicle Classification and Wheel Weights (Z)
  • 4.8 Micromobility Count Station Description Data Format (Fixed Width or Pipe Delimited)
  • 4.9 Micromobility Count Data Format (Fixed Width or Pipe Delimited)
• Chapter 5. Federal Data Reporting Requirements and Tools: HPMS and TMAS
  • 5.1 Highway Performance Monitoring System (HPMS) Requirements For Traffic Data
  • 5.2 HPMS Requirements
    • 5.2.1 HPMS Data Model
    • 5.2.2 AADT Reporting on Mainlines and Ramps
    • 5.2.3 Rounding AADTs
    • 5.2.4 Motorcycle Counts
    • 5.2.5 Vehicle Classification Counts
    • 5.2.6 Truck AADT
    • 5.2.7 Estimates of Travel by Vehicle Type
    • 5.2.8 Volume Group Assignments
    • 5.2.9 Traffic Metadata
  • 5.3 Guidelines for Collecting Traffic Data to Support HPMS
    • 5.3.1 Permanent (Continuous) Counts
    • 5.3.2 Short-Term Counts
    • 5.3.3 Ramp Counts
    • 5.3.4 Vehicle Classification Counts
    • 5.3.5 Equipment Calibration
  • 5.4 Calculation of Data Items
    • 5.4.1 AADT
    • 5.4.2 AADT_SINGLE_UNIT
    • 5.4.3 PCT_DH_SINGLE_UNIT
    • 5.4.4 AADT_COMBINATION
    • 5.4.5 PCT_DH_COMBINATION
    • 5.4.6 K_FACTOR
    • 5.4.7 DIR_FACTOR
    • 5.4.8 FUTURE_AADT
  • 5.5 Traffic Monitoring and Analysis System (TMAS)
    • 5.5.1 TMAS Requirements and Features
• Chapter 6. Third-Party Traffic Data
  • 6.1 Data Needs
  • 6.2 Data Quality
  • 6.3 Data Ownership
    • 6.3.1 Data Storage and Possession
    • 6.3.2 Data Rights
    • 6.3.3 Version Control
  • 6.4 Costs
  • 6.5 Summary
• References
• Glossary

List of Appendices

• Appendix A –Vehicle Types
• Appendix B – TMAS Quality Control Checks
• Appendix C – Compendium of Data Quality Control Criteria
• Appendix D – Equipment Calibration
• Appendix E – NCDOT Clustering Method for MEPDG
• Appendix F – Traffic Data for Pavement Design
• Appendix G – Length Based Class Memo
• Appendix H – Bike/Ped Site Selection Process/Publication – Florida Department of Transportation (FDOT's) Nonmotorized Site Selection Methodology (excerpts from the Statewide Non-Motorized Traffic Monitoring Program Recommendations Report December 2018)
• Appendix I – Motorcycle Data Collection Methods
• Appendix J – Traffic Pattern Examples
• Appendix K – Typical Interchange AADT Estimation
• Appendix L – AASHTO AADT Calculation
• Appendix M – Double Threshold WIM Array

List of Figures

• Figure 1-1. Steps for Establishing a Data Program
• Figure 2-1. Example of Traffic Monitoring Equipment and Site Layout
• Figure 2-2. Example of Sensor Output Conversion to Vehicle Classification Data
• Figure 2-3. Example of Speed and Axle Spacing Monthly Trend Analysis
• Figure 2-4. Example of Loop Sensor Layout
• Figure 2-5. Example of Piezo Sensor Layout
• Figure 2-6. Example of Loop and Piezo Sensor Layout
• Figure 2-7. Example of Portable Pneumatic Tube Layout
• Figure 2-8. Example of Portable Pneumatic Tube Layout with a Knot and Two Counters
• Figure 2-9. Example of Staggered WIM Sensor Layout for Plate Sensors
• Figure 2-10. Equipment Selection Process
• Figure 2-11. Examples of Inductance Loop Detector Shapes for Bicyclist Counting
• Figure 2-12. Example A of Passive Infrared Sensor Combined with Inductance Loop Detectors
• Figure 2-13. Example B of Passive Infrared Sensor Combined with Inductance Loop Detectors
• Figure 2-14. Typical Configuration for Active Infrared Sensor
• Figure 2-15. Example of Pneumatic Tube Configuration for Counting Directional Bicyclist Traffic
• Figure 2-16. Examples of Pressure Sensors on Natural (A) and Paved (B) Surfaces
• Figure 2-17. Example of Video Capture of Bicycles and Pedestrians
• Figure 3-1. Example of Differences in Monthly Travel Patterns by Day of Week in Montana
• Figure 3-2. Relationship between 𝒕𝒕𝟎𝟎. 𝟎𝟎𝟎𝟎𝟎𝟎, 𝒏𝒏 − 𝟏𝟏𝟏𝟏𝒏𝒏 Statistic and Number of Sites
• Figure 3-3. Tandem Axle Load Distributions with Different Loading Conditions
• Figure 3-4. Weekly Bicycle and Pedestrian Traffic
• Figure 3-5. FHWA'S 13-vehicle Category Classification
• Figure 3-6. Example of Differences in Time-of-Day Traffic Volume by HPMS Vehicle Class
• Figure 3-7. Example of Differences in Traffic Volume by Day of Week for Florida Site
• Figure 3-8. Example of Monthly Volume Pattern for a Rural Road in Wyoming
• Figure 3-9. Example of Differences in ACF by DOW and MOY in Montana
• Figure 4-1. Direction and Lane Code Example
• Figure 4-2. Illustration of Class 09 - Semi-Truck, 04 - Bus, and 06 - Dump-Truck
• Figure 4-3. A Regular Intersection Crosswalk Numbering Illustration
• Figure 4-4. A "T" Intersection Crosswalk Numbering Illustration 1
• Figure 4-5. A "T" Intersection Crosswalk Numbering Illustration 2
• Figure 5-1. HPMS TOPS Development Process

List of Tables

• Table 1-1. Examples of Highway Traffic and Travel Data Uses
• Table 2-1. Basic Data Types Reported by Traffic Monitoring Devices
• Table 2-2. Strengths and Weaknesses of Commercially Available Sensor Technologies for Motorized Vehicle Detection and Counting
• Table 2-3. Strengths and Weaknesses of WIM Technologies for Moving Motorized Vehicle Detection, Counting, Weighing, and Classifying
• Table 2-4. Strengths, Weaknesses, and Applications of Micromobility Detection Technologies
• Table 2-5. Motorized Vehicle Detection Sensor Comparison
• Table 2-6. Common Technologies Used for Counting Vehicles Versus Axles
• Table 2-7. Common Technologies for Classifying Motorized Vehicles
• Table 2-8. Intrusive and Non-Intrusive Technologies
• Table 2-9. Sensors for Motorized Vehicle Data Collection for Short-Term Counts
• Table 2-10. Sensors for Motorized Vehicle Data Collection for Permanent Count Locations
• Table 3-1. Minimum Recommended Volume Factor Groups
• Table 3-2. Advantages and Disadvantages of Monthly Pattern Group Types
• Table 3-3. Reference Accuracy and Precision for AADT Estimates
• Table 3-4. HPMS Vehicle Class Groups/FHWA Vehicle Classes
• Table 3-5. Example Classification Factor Groups
• Table 3-6. Example of Monthly Factors by Vehicle Class at a Single Site
• Table 3-7. Motorcycle Traffic Volume Estimation
• Table 3-8. ADTm by Day of Week
• Table 3-9. ADT Calculation Example
• Table 3-10. ADT Vehicle Type Computation Example
• Table 3-11. Example of A Normalized Load Spectrum for Vehicle Class 9 Single and Tandem Axles from FDOT
• Table 3-12. Example Truck Loading Groups
• Table 3-13. Example of Statistic Computation for Load Factor Group Precision Estimates
• Table 3-14. Statistics Used for Sample Size Computation
• Table 3-15. Estimating Spacing of Short-Duration Counts
• Table 3-16. Traffic Segments and Classification Short-Term Program Based on Functional Classification and Truck Activity
• Table 3-17. Example Abbreviated Dataset (Selected Hours) Showing Partial-day Counts
• Table 3-18. Example of Hourly Totals for Time-of-Day and Day-of-Week
• Table 3-19. Example of Day-of-Week Averages
• Table 3-20. Example Calculation of the ACF
• Table 3-21. Number of Axles Per Vehicle
• Table 3-22. 2011 Mixed-Mode Traffic Count Statistics for Midtown Greenway Near Hennepin Avenue, Minneapolis, Minnesota
• Table 4-1. Data Submission Frequency
• Table 4-2. Station Description Record
• Table 4-3. FIPS State Codes
• Table 4-4. Direction of Travel Codes
• Table 4-5. Lane of Travel Codes
• Table 4-6. Functional Classification Codes
• Table 4-7. Values Corresponding to Vehicle Classification Groupings
• Table 4-8. Posted Route Signing Codes
• Table 4-9. Traffic Volume Record – Fixed-Width Format
• Table 4-10. Time Covered Fields – 60-Minute Data
• Table 4-11. Traffic Volume Record Example (60-minute Time Interval – 4 Lanes with All Lanes and Directions Combined)
• Table 4-12. Vehicle Speed Record – Fixed-Width Format
• Table 4-13. Total Number of Speed Bins
• Table 4-14. Speed Record Example (15 Bins, 2 lanes with Lanes or Directions Not Combined at 5-Minute Interval with No Restrictions) – Fixed-Width Format
• Table 4-15. Speed Record Example (21 Bins, 4 Lanes with Lanes or Directions Not Combined at 60-Minute Interval with No Restrictions, Total Volume Not Recorded) – Fixed Width Format
• Table 4-16. Speed Record Example (25 Bins, 2 Lanes with Lanes or Directions Not Combined at 60-Minute Interval) – Fixed Width Format
• Table 4-17. Vehicle Classification Record – Fixed-Width Format
• Table 4-18. Vehicle Classification Record Example (3 Length-Class Bins, 4 Lanes with Lanes and Directions not Combined at 60-Minute Interval for 2 Hours) – Fixed Width Format
• Table 4-19. Vehicle Classification Record Example (13 Axle-Class Bins, 2 Lanes with Lanes or Directions not Combined at 15-Minute Interval) – Fixed Width Format
• Table 4-20. Weight Record – Fixed-Width Format
• Table 4-21. Weight Record Example – Fixed-Width Format
• Table 4-22. Units of Measurement
• Table 4-23. Individual Vehicle Record Collected by Volume Device (V Variant) – Fixed-Width Format
• Table 4-24. Individual Codes for Class and Body Type 1<5
• Table 4-25. Individual Codes for Class and Body Type when Code 1>=5
• Table 4-26. Individual Vehicle Record (Volume Site) Example (Southbound Lane 1, Note – Record Length Ends With 5 Blanks) – Fixed-Width Format
• Table 4-27. Speed and Length Classification Individual Vehicle Record (T Variant) – Fixed-width Format
• Table 4-28. Individual Vehicle Record (Speed Site) Example (Northbound Lane 2) – Fixed-Width Format
• Table 4-29. Individual Vehicle Record by Classification (Axle) Device (C Variant) – Fixed width
• Table 4-30. Individual Vehicle Record (Classification Site) Example (Eastbound Lane 4) – Fixed-Width Format
• Table 4-31. Individual Vehicle Record by Weight (Axle) Device (W Variant) – Fixed Width Format
• Table 4-32. Individual Vehicle Record (Weight Site) Example (Westbound Lane 3) – Fixed-Width Format
• Table 4-33. Individual Vehicle Record Collected by Weight (Left and Right) Device (Z Variant) – Fixed- >Width Format
• Table 4-34. Individual Vehicle Record (Left and Right Site) Example (Westbound Lane 1) – Fixed-Width Format
• Table 4-35. Summary of the Micromobility Station Record Data Fields
• Table 4-36. Function Class and Area Type Codes
• Table 4-37. Type of Sensor Codes
• Table 4-38. Primary Count Purpose Codes
• Table 4-39. Posted Route Sign Codes
• Table 4-40. Summary of the Micromobility Count Record Data Fields
• Table 4-41. Type of Count Codes
• Table 4-42. Helmet Usage Codes
• Table 4-43. Age Codes
• Table 4-44. Count Data Reporting Scheme for Non-Intersection Traveled Way Scenarios
• Table 4-45. Count Data Reporting Scheme for Intersection Crosswalk Counting Scenarios
• Table 5-1. HPMS Traffic Data Items
• Table 5-2. Combined Area Type and Functional System Groups