American Association of State Highway and Transportation Officials

Special Committee on Research and Innovation

 

FY2023 NCHRP PROBLEM STATEMENT

 

Problem Number:  2023-D-21

 

Problem Title

Practical Ground Truth Method and Tools for Evaluating Accuracy, Precision, and Bias of Traffic Volume Counting Equipment

 

Background Information and Need For Research

Traffic data accuracy is fundamental to many critical functions of highway and transportation agencies. As traffic monitoring and detection technologies continue to mature and third-party traffic data sources become more widely available, traffic count programs are asked to evaluate these alternatives. Inconsistency in data quality varies across vendors and technologies. In addition, traffic data quality change over time due to equipment aging and environmental effects on equipment performance. Thus, the ground truth about traffic count accuracy obtained immediately after equipment installation may not remain representative over time due to equipment issues or intermittent environmental effects on sensor performance.  The FHWA Traffic Monitoring Guide recommends calibration of all permanent and portable traffic counter each year.  Several ASTM standards and methods (E 177–20, E 2300–09, E 2532–09, E 2759–10) address the topics related to evaluating accuracy, precision, and bias of traffic volume counts. However, some of the methodologies may require updates to incorporate new technologies and statistical methods and their effect on the procedures described in the standards. In addition, highway agencies have developed their own methods and procedures. The lack of uniformity or consistency in methods used by different agencies to evaluate the accuracy of traffic counts leads to challenges with analyses of national traffic data sets, comparison of traffic trends between different agencies, or even using traffic data within a given agency, if different technologies have been used to collect traffic data. The lack of consistency in methods to obtain ground truth data about traffic volume counts also creates challenges in evaluating accuracy of traffic volume estimates obtained using analytical tools.

To address the need to know how accurate traffic counts are upon equipment installation or at any time during equipment operation, equipment performance validation methodologies and standard specifications, which are widely accepted and implemented into practical supporting tools, are critically needed to objectively evaluate and quantify accuracy of traffic counts obtained by different technologies. This is a fundamental step to assure soundness of the decisions made based on the data and statistics derived from the traffic counts. This research focuses specifically on practical methods to determine the accuracy of traffic monitoring devices commonly used for collecting data to compute highway traffic statistics.

 

Research questions or tasks to be addressed include:

1.         What are technological, operational, and environmental challenges with obtaining accurate traffic count data from automated traffic counters used for highway traffic statistics? Understanding of these challenges will help in identifying sound and practical methods, testing conditions, and limitations of the existing methods for determining accuracy of traffic counts. 

2.         What practical ground-truth methods are currently available and used to determine accuracy, precision, and bias of traffic counts collected by automated traffic counters? What criteria are currently used to validate traffic count data accuracy, precision, and bias? Are the existing methods still relevant? What are the obstacles or limitations in implementing these methods in practice? This should include methods for evaluating traffic counter technology itself, as well as implementation of this technology at a particular traffic monitoring site. Both accuracy and reliability (i.e., consistent accuracy over time) of traffic counts should be considered. 

3.         Develop guidance how the existing ground-truth methods (how long of a count to make, how many lanes should be counted, how many vehicles to count, what accuracy criteria and parameters to include with each method to be detailed) could be improved and/or made more practical. Select or enhance an existing method or propose a new method that best meets the needs of highway agencies for testing and accepting installation of automated traffic counters commonly used to collect data for highway traffic statistics or for accepting traffic data collected by portable traffic counters.

4.         Are the selected existing or the proposed new method(s) universally applicable and practical? Test automated traffic counters commonly used to collect data for highway traffic statistics and document findings. Consider a permanently installed traffic counting site and 2–3 commonly used portable traffic monitoring technologies installed and tested side-by-side. A minimum of four test sites is recommended. Practicality and potential implementation of selected methodology(s) on roads with different traffic and site characteristics should evaluated (including roadways with throughputs over 2,000 vehicles per hour per lane and medium/low traffic volume of 500 to 5,000 AADT) under prevailing conditions during typical equipment installation or data collection season). Consider practicality and limitations of implementing the selected ground truth testing methodology(s) at remote or very low volume locations, as well as urban locations, including test duration, safety, and vandalism considerations. Document findings and technologies tested.

5.         Adjust, as necessary, finalize, and document the recommended practical ground truth method(s) for evaluating accuracy, precision, and bias of traffic volume counts.

6.         Develop practical tools, such as guidance document, specification, and/or supporting software to apply the ground truth method to evaluate accuracy, precision, and bias of traffic volume counts.

7.         Prepare a final report documenting the results of this study which will include references methods and the limitations when utilizing these methods that may exist (such as weather, through put limits, congestion limitations or minimum numbers of vehicles needed) and traffic monitoring technologies tested.

The potential research results are of national interest and necessary to address strategic objectives of state DOTs because traffic volume data is a key input into management and decision support systems implemented at the national and state-level (such as those systems mandated by Title 23 Sec. 303 - Management systems), including HPMS, pavement and bridge management and maintenance, congestion, and safety management systems. Ability to quantify the accuracy of traffic counts is critical for the effective and informed use of these data in management systems, as well as for road and bridge design and transportation planning projects.

The seven research tasks listed above identify the scope needed to help assure that the research objectives can be successfully achieved within the constraints of the proposed time and funds. The goal of the proposed research is to produce implementation-ready ground truth method(s) and practices in the form of standard specifications, detailed practical procedures that states’ personnel could follow, and/or practical software tools to assure ease of implementation of the research results in practice.

 

Literature Search Summary

Several ASTM standards address topics relevant to evaluating accuracy, precision, and bias of traffic volume counts, including the following: E 177-20 Standard Practice for Use of the Terms Precision and Bias in ASTM Test Methods, E 2300-09 Standard Specification for Highway Traffic Monitoring Devices, E 2532-09 Standard Test Methods for Evaluating Performance of Highway Traffic Monitoring Devices, E 2759-10 Standard Practice for Highway Traffic Monitoring Truth-in-Data. In addition, highway agencies have developed their own methods and procedures. Different approaches need to be reviewed and analyzed and potential best practices and limitations need to be identified for different road and traffic conditions. The reasons why the current standards have limited implementation and why the implemented methodologies vary from agency to agency need to be explored and documented.

 

Research Objective

The objectives of this research are (1) develop a new or enhance an existing practical ground truth method for evaluating accuracy, precision, and bias of traffic volume counts obtained from portable and permanent automated traffic counters commonly used to collect data for highway traffic statistics and (2) develop practical procedures, specification, and/or software tools, to help with practical implementation of the selected methodology. The results of this research may lead to the update of ASTM E 2532 – 09 Standard Test Methods for Evaluating Performance of Highway Traffic Monitoring Devices. See 7 potential tasks in Section 2 above.

 

Urgency and Potential Benefits

This need was first identified by the TRB Traffic Monitoring Committee ACP70 survey of professionals in 2016. All highway agencies use traffic count data, but it is rarely known how accurate said data are. The need is even more relevant with the development and deployment of new traffic data collection technologies, such as using video recognition with artificial intelligence and machine learning technologies. Common standards and procedures are necessary to quantify accuracy of traffic counts and assure informed uses of traffic data and improved data sharing practices between transportation agencies. Application of such methods will allow uniform and unbiased quantification of traffic data accuracy coming from different data sources.

Those benefiting from this research include federal, state, county, MPO, and city traffic program managers; and the public at large (due to improved data quality for transportation decision-making).

 

Implementation Considerations

The state DOT offices involved in traffic data collection and data use will be involved in implementing the results of this research, including: Planning, Programming, Traffic Operations, Transportation System Management and Operations (TSM&O), and Design. 

States will be able to implement the research findings by adopting the recommended ground truth methods, procedures, specifications, and tools. Implementation will be supported with communication methods such as webinars, training, and peer exchanges. The AASHTO Committee on Data Management and Analytics will be a key benefactor of these results. The results of this project may lead to revision and update of ASTM E 2532 – 09 or a development of a new AASHTO specification. In addition, the practical methods and support tools developed in this project (implementing the proposed methodology) will further assure the ease of implementation of the research results in practice.

Several issues arise with some of the procedures described in ASTM E 2532 – 09. The most critical one appears in Sections 7.2.9 and 7.3.7, which state “If any specified TMD data item is not output or its difference as calculated in 7.2.8 (for all values of the data item measured) exceeds the specified tolerance, declare the TMD nonfunctional or inaccurate and record that it failed the Type-approval Test.” By including the words “for all values of the data item measured” the standard does NOT make provision for random errors through the specification of a confidence interval along with the accuracy value. Including a confidence interval would also allow for precision and bias to be determined, contrary to what is now stated in Sections 7.2.10 and 7.3.8 of the standard. Other issues are the omission of the mention of alternative ground-truth methods.

 

Recommended Research Funding and Research Period 

Funding Requested: $400,000. Research Period: 30 months.

 

Problem Statement Author(S): For each author, provide their name, affiliation, email address and phone.

           Olga Selezneva, Applied Research Associates, oselezneva@ara.com, (410) 203-2285

           Lawrence A. Klein, Klein & Associates, larry@laklein.com, (714) 356-2275

           Steven Jessberger, Federal Highway Administration, steven.jessberger@dot.gov, (202) 366-1874

Potential Panel Members: For each panel member, provide their name, affiliation, email address and phone.

           Aaron Moss, Traffic Analyst, CDOT, aaron.moss@state.co.us

           Chris Medina, Program Admin Specialist III, VDOT, Chris.Medina@VDOT.Virginia.gov, 804-786-2956

 

Person Submitting The Problem Statement: Name, affiliation, email address and phone.

Kent L. Taylor, NCDOT, kltaylor@ncdot.gov (919) 345-9829