U.S. Department of Transportation
Federal Highway Administration
1200 New Jersey Avenue, SE
Washington, DC 20590
202-366-4000


Skip to content U.S. Department of Transportation/Federal Highway AdministrationU.S. Department of Transportation/Federal Highway Administration

Policy and Governmental Affairs
Office of Highway Policy Information

FHWA Home / Policy & Governmental Affairs / Highway Policy Information / Office of Highway Policy Information

Office of Highway Policy Information (OHPI) – Highway Performance Monitoring System (HPMS) – HPMS Reassessment 2010+

Highway Performance Monitoring System (HPMS)

Executive Summary

Introduction

The primary purpose of the Highway Performance Monitoring System (HPMS) is to serve data and information needs to reflect the condition and operating characteristics of the nation's highways. HPMS data support the analyses needed for the biennial condition and performance reports to Congress. One of the required data elements for the HPMS program is vehicle-miles traveled (VMT). VMT is derived from average annual daily traffic (AADT), so an accurate measure of AADT is essential. Traffic data collected on the highest volume routes have the most significant impact since these data represent a large share of total statewide and national travel. These routes are also often the most difficult locations to monitor. State and public agencies use various strategies to develop effective counting programs at these locations.

The objective of this project is to investigate and document information that can be shared with states on various procedures being used to estimate and report traffic data on high-volume routes. This study focuses on the accurate collection of traffic data on high-volume routes, as well as the processes that accompany the collection of these data. The study develops best practices and guidelines for improving the quality of AADT estimates on these high-volume routes.

Information Sources

The information for developing this report was gathered through review of published literature and telephone interviews with representatives of state Departments of Transportation (DOTs). Representatives of the top 13 states with the highest mileage of highways with high traffic-volumes were interviewed. The states are: California, Texas, Florida, Georgia, Illinois, Massachusetts, Maryland, Michigan, Ohio, New York, New Jersey, Virginia, and Washington.

Summary of Interview and Literature Review Results

The following are summaries of the major findings from the interviews and literature review.

Data Collection and Processing Approaches

 Data Collection Equipment
Quality Assurance and Control

The states interviewed employ the following approaches for data quality control and assurance:

Issues and Challenges

The major issues and challenges facing state DOTs and other agencies are:

Best or Common Practices

Based on the findings from the interviews and literature review, the best or common practices were identified to address the issues and challenges. Table ES-1 summarizes the practices adopted by states to overcome or mitigate the issue and challenges.For each category, the best or common practices are described and illustrated with examples from the states. The examples are intended to illustrate the successes of the various approaches in addressing the issues, and also to serve as resources to states seeking guidance. Additional sources of information relevant to the practices are also identified in the report. Further detailed resource information is provided on the accompanying CD to supplement information presented in this report.

ES-1: Best or Most Common Practices used by States
Category Practice Areas Issues Addressed
A.
General
A1. Training and Guidelines
  • Safety to field crew
  • Equipment installation, calibration, and maintenance
  • Data quality control and assurance
  • Institutional issues
B.
Data Collection Equipment
B1. Equipment Selection, Calibration and Maintenance
  • Technological limitations of detection equipment
  • Safety of field crew on high-volume routes
  • Equipment failures and damage
  • High quality data on high-volume routes
B2. Use of Non-Intrusive Equipment
  • Safety of field crew on high-volume routes
  • Installation and maintenance costs
  • Equipment damage — loops and sensors
  • Congested and stop-and-go traffic conditions
  • Construction and incidents

C.
Data Collection

C1. Use of Safety Strategies

  • Safety of field crew on high-volume routes
  • Data collection on high-volume routes
  • Congested and stop-and-go traffic conditions

C2. Ramp Balancing

  • Safety of field crew on high-volume routes
  • Data collection on high-volume routes
  • Congested and stop-and-go traffic conditions

C3. Innovative contractual Practices

  • Improved data quality
  • Institutional issues, e.g., funding
  • Lack of interagency cooperation

C4. Use of ITS Data

  • Safety of field crew on high-volume routes
  • Limited coverage of traffic monitoring program
  • Congested and stop-and-go traffic conditions
  • Construction and incidents
D.
Data Processing and Quality Control
D1. Data Processing and Quality Control Procedures
  • Raw data analysis and AADT estimation
  • Assumptions and business rules
  • Data quality control and assurance issues
D2. Adjustment Factors and Growth Factors
  • Raw data analysis and AADT estimation
  • Assumptions and business rules

 

Guidelines for Data Collection for High-Volume Routes

For traffic data gathering and processing, each state DOT follows a set of procedures, chooses, and uses equipment that best meets their specific needs. The guidelines are intended as a guide or reference source based on states' experiences and lessons learned to help states seeking direction or guidance on addressing common or specific issues relating to traffic data collection and processing for high-volume routes.

Data Collection

The following steps are considered useful for traffic monitoring on high-volume routes.

  1. Define high-traffic volume — It is important to define a high-traffic volume route in terms of traffic volume. It is recommended that 50,000 AADT be used as the threshold.

  2. Identify high-volume locations — The next step is to identify routes carrying high traffic volume. This is important in selecting and planning installation of data collection equipment.

  3. Select data collection strategies — Several strategies for collecting traffic data on high-volume routes have been identified. These strategies are being practiced in some states and are designed to address the issues and challenges associated data collection on high-volume routes. These include:

    • Provide training including safety guidelines for all field personnel.
    • Coordinate equipment installation (e.g., inductive loops) with pavement construction and maintenance activities.
    • Use ramp-balancing techniques.
    • Use technologies for better classification and lane-by-lane detection of vehicles.
    • Develop data and resource sharing agreements among local agencies that coordinate traffic collection activities.
    • Use contractors for data collection.

Data Processing and Data Quality Assurance

The following are recommended elements in data processing and quality assurance of AADT data. These are intended to guide states in validating and evaluating the quality of data from different sources and for different applications. Methods of calculating adjustment and growth factors are also included.

  1. Data validation — Data processing to verify validity and completeness is carried out using either in-house software packages or legacy mainframe programs.

  2. Adjustment factors and growth factors – Adjustment factors based on TMG recommendations are needed to convert short-term volume counts to AADTs. Several approaches have been identified to guide the states in selecting those that best meet their needs.

  3. Assessment of data quality — The recently developed framework1 for assessing traffic data quality is recommended for use in assessing the quality of data from different sources and for different applications. The framework presents a comprehensive methodology for evaluating the quality of traffic data using a set of quality measures.

Use of ITS and Other Data Sources

ITS data offer a valuable source of traffic data especially to the HPMS program. Some state DOTs rely on ITS-generated data to report AADT for HPMS for parts of their program, other states have concerns about the quality and reliability of such data. Potential approaches to encourage the use of ITS data for traffic monitoring applications include:

  1. Resource sharing — Merge ITS field infrastructure (like inductive loops and sensors) with traditional traffic counting devices to allow the use of the traffic counters/ classifiers alongside ITS devices. It is recommended that a program be developed that combines ITS and traditional traffic monitoring.

  2. Compatible equipment — Investigate the use of compatible equipment or sensor-sharing arrangements where the signals from in-road sensors are split into two devices. The intent would be to use ITS sensors for traditional data gathering without impacting ITS operations.

  3. Strategic locations — The need to select strategic locations for ITS sensors is critical to traffic monitoring. Identifying and locating ITS sensors strategically would also allow the sensors to be maintained jointly by the traffic monitoring group and ITS groups.

  4. Supplemental data source — Increase use of data from ITS data archives could supplement HPMS and traffic monitoring programs States are encouraged to develop ITS data archives based on experiences in other states.

Equipment

Selection of data collection equipment is determined by individual state experiences, needs, and conditions. The following are expected to guide the selection of equipment and technologies.

Concluding Remarks

The practices and guidelines presented in this report are intended as a reference for states to improve the quality of traffic data collection and processing on high-volume routes especially. The guidelines are not intended as uniform standards that all states must follow, and they are not intended to replace existing successful practices. The following are general conclusions from this examination of current data collection and processing practices.

________________
1Traffic Data Quality Measurement, Battelle for FHWA, Office of Highway Policy Information, 2004

<< Previous   Next >>

 

Page last modified on November 7, 2014.
Federal Highway Administration | 1200 New Jersey Avenue, SE | Washington, DC 20590 | 202-366-4000