American Association of
State Highway and Transportation Officials
Special Committee on
Research and Innovation
FY2023 NCHRP PROBLEM
STATEMENT
Problem Number:
2023-D-20
Problem Title
Determine
the Accuracy and Bias of Currently Available Portable Technologies for
Obtaining Short Term Traffic Volumes for Segments and Intersections.
Background Information and Need For Research
This
research will enhance the knowledge of the accuracy and bias of short term
traffic counts by documenting the strengths, weaknesses and applications for
(1) technology and sensor selection and (2) array type for short term volume
counts that are used for segment and intersection use. The short-term counting program provides
critical spatial data for a quality traffic monitoring program (TMS) and
provides spatial traffic volume data for a given location. In addition, traffic volume data supports
decision making, and provides engineers and planners with critical information
that enhances safety and mobility for the traveling public.
As sensor
detection technologies continue to mature, traffic count programs often rely on
these new techniques and modern counting technologies and sensors. Therefore, it is necessary to research and
document a most reliable and accurate practices found across different traffic
volume data programs that can inform the industry of these methods in a
documented research findings report.
During
this project, short-term data collection, data quality and availability issues
will be researched, and the accuracy and bias determined when using short-term
data. Methods for technology selection,
sensor choice, array, and the appropriate duration will be compared for
consistency across various agencies and areas of the country. This will help the industry in establishing
and updating their practices for collecting, checking, and validating
short-term data.
Additionally,
short-term counting data has a number of topics that need to be researched and
documented, such as:
• Inconsistency in data quality that
varies across technologies, sensor types and arrays.
• Effect of site conditions on data
quality (weather, arrays, possible occlusion, speed during detection period,
congestion and other site-specific conditions).
• Effect of sensor type and sensor
array, and benefits of one technology over the other.
• Limitations that exist with one
technology over another and documentation of those so agencies can choose the
most appropriate detection method for their given local conditions.
Research
questions to be addressed include:
1. What is typical accuracy and bias of
ADT estimates based on data from existing short term traffic volume locations?
The method of obtaining short term traffic counts will be documented. The reasons ADT estimates vary will be
documented.
2. What methods of data collection,
validation, handling, storage, and QA/QC need to be implemented to obtain the
most accurate and unbiased short term traffic volume counts from existing
technologies at various locations around the US?
3. What challenges exist in obtaining
short term traffic count data (site conditions, traffic flow, traffic volume,
sensor technology)?
Literature Search Summary
No
specific research was found on the accuracy or bias from short term or portable
volume traffic counters through the TRB TRID and other known sources of
research. Closely related work, but not
directly addressing the accuracy or bias of short-term counts, includes the
following:
FHWA. Variability
in Traffic Monitoring Data. Contract DE-AC05-96OR22464, Oak Ridge National
Research Laboratory, August, 1997. https://www.fhwa.dot.gov/ohim/flawash.pdf
Georgia
Institute of Technology for the Georgia Department of Transportation. Accuracy
of Traffic Monitoring Equipment, June 1995.
https://www.fhwa.dot.gov/ohim/atme/atme.htm
FHWA.
This project deals with the duration and frequency of volume counting, but not
on the field data collection efforts agencies utilize.
https://www.fhwa.dot.gov/policyinformation/travel_monitoring/pubs/aadt/
Research Objective
The
objective is to explore the accuracy and bias of different types of short term
portable traffic counts obtained from road tube (single, double and by wheel
path), magnetometer, temporary stick down loop, video, ultrasonic, infrared and
various non-intrusive technologies such as radar, microwave and sound
technologies. Most commonly available
commercial short-term technologies currently in the US should be
considered. In evaluating accuracy and
bias a suitable ground truth method should be used.
Specific
tasks are:
a) Analyze the different count durations
such as consecutive 24 hour, 1 day (ie 24 hours will often split over more than
one calendar day whereas with 1 day is within the same calendar day), 48 hour,
2 day, 72 hour, 3 day and 7 day counts to determine how the count technology
and duration effect the overall accuracy and bias of the short term count. It would be expected that extensive data collection
would be required to obtain the needed data sets for this analysis.
b) Develop recommendations of applications
and limitations of the above referenced technologies to allow DOTs to determine
type of technology and suitable array (number of sensors and spacing of
sensors) to use in a variety of environments (examples include but not limited
to high speed/low speed, occlusion, high volume/low volume, all weather [sunny,
fog, rain and snow], congestion levels [including stop and go], velocity
changes and lane changes).
c) Develop alternatives to mitigate the
equipment and sensor limitations described above.
d) Prepare a final report documenting the
results of this study in a form suitable for a best practice for collecting
accurate and unbiased short term traffic volume counts.
Urgency and Potential Benefits
This need
was first identified by the TRB Traffic Monitoring Committee ACP70 in 2016.
Although there have been advancements in this area since then, the need still
exists and is even more prevalent with advanced technology and the development
of new data sources from vendors, for example, using video recognition with AI
and machine learning technologies.
Being
able to obtain high-quality short term traffic count data equipment is
paramount for traffic volume count programs and allows for safety and facility
improvements to be implemented based on traffic volume data that shows demand
and user facility needs.
Those
benefiting from this research include state, county, MPO, and city traffic
program managers; signal operating agencies; and the public at large (due to
resource saving and increased safety and mobility due to improved data and
decision-making).
Implementation Considerations
The
following state DOT offices will be involved in implementing the results of
this research: Planning, Programming, Traffic Operations, Transportation System
Management and Operations (TSM&O), and Design.
States
will be able to implement the research by adopting lessons learned from other
entities. 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.
Recommended Research Funding and Research
Period
Funding
Requested: $350,000, Research Period: 24 months.
Successful
proposers need to come up with a project plan that fits within the budget
specified and could include vendor provided equipment or equipment provided
from DOTs or local agencies. This
project plan needs to be approved by the NCHRP project manager.
Problem Statement Author(s): For each author,
provide their name, affiliation, email address and phone.
• Liz Stolz, Marlin Engineering, (303)
369-5570, estolz@marlinengineering.com
• Olga Selezneva, Applied Research Associates,
(410) 203-2285, oselezneva@ara.com
• Steven Jessberger, Federal Highway
Administration, (202) 366-5052, steven.jessberger@dot.gov
• Tom Papagiannakis, University of
Texas at San Antonio, (410) 203-2285, Papagiannakis@utsa.edu
• Andrew Nichols, Marshal University,
(304) 696-3203, andrew.nichols@marshall.edu
Potential Panel Members: For each panel
member, provide their name, affiliation, email address and phone.
• Kent Taylor, NC DOT,
kltaylor@ncdot.gov, (919) 345-9829
• Robert Blankenship, AL DOT,
blankenshipr@dot.state.al.us, (334) 242-6393
• Ian Vaagenes, MN DOT,
ian.vaagenes@state.mn.us, (651) 366-3869
• Kurt Matias, NY DOT,
Kurt.Matias@dot.ny.gov, (518) 457-1965
Person Submitting The Problem Statement: Name, affiliation,
email address and phone.
• Kent Taylor, NC DOT,
kltaylor@ncdot.gov, (919) 345-9829