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Traffic management centers
collect traffic and incident information about the transportation
network; this data is then combined with other operational and
control data in order to manage the transportation network and
to produce traveler information. Archiving this data is an effective
way of making it available for operators who want to make improvements
to their particular transportation system.
The data TMCs collect typically
includes:
-
Vehicle traffic volumes
-
Traffic incidents (time
sequence of events, location, cause, number of lanes blocked,
etc)
-
Vehicle speeds
-
Travel time and delay
distribution
-
Current and scheduled
work zones (location, number of lanes closed, scheduled duration,
etc)
-
Vehicle emissions
-
Vehicle classification
(percent trucks)
Archiving these data provides
a cost-effective way to obtain data that can be used by transportation
planners, designers, and researchers alike for many purposes.
Data can be used for facility planning and design, developing
control strategies, congestion tracking, emissions modeling, deployment
of response personnel, and schedule of maintenance and construction.
Traffic management centers in particular can use archived data
to analyze performance measures, determine the optimum ways of
managing crises, and ultimately develop other means of operating
the transportation system at its maximum efficiency.
-
Huge volumes of data
are available at relatively low costs.
-
Allows for better long-term
transportation management and planning.
-
The detailed nature of
ITS-generated data allows for more accurate analysis and makes
possible those applications that were previously too costly
to undertake.
-
Removes temporal sampling
bias from estimates.
-
Allows for the study
of continuous variability in system performance and response.
-
Improves the evaluation
of ITS deployment.
-
Promotes integration
of ITS with traditional information systems.
-
Encourages the use of
data for multiple purposes.
-
Mutual interest in data
generated by ITS will stimulate cooperation among stakeholders,
which could lead to the "main streaming" of ITS into
standard transportation practice, particularly among transportation
planners.
The need for archived data
was initially expressed in the mid-90s at the Highway Performance
Monitoring System Steering Committee on August 7, 1996 and later
at a conference in Irvine, CA in March 1997. In January 1998,
the FHWA sponsored a meeting to discuss the uses of archived data,
the end result of which was a decision to revise the National
Architecture to include a new user service, namely the Archived
Data User Service (ADUS). In September 1999, ADUS was officially
added to the Architecture. In May 2000, the FHWA developed an
ITS
Data Archiving Five-Year Program Description, which explains
the need for a Federal program that addresses the archiving and
multi-agency use of data generated from ITS applications.
Archived data services is
relatively new and only a few state DOTs and associated transportation
organizations have begun to implement this service as part of
their daily operations. Those DOTs and TMCs that regard archived
data as valuable for future planning and operations improvements
have implemented their archiving systems to varying extents. The
Metro District Transportation Management Center in Minneapolis,
MN has been continually archiving traffic data since 1984 and
has used it extensively for traveler information purposes, whereas
the Dallas, TX DOT has archived only a few types of data somewhat
intermittently. Another approach to archiving data was taken by
the TransPort program in Oregon, where a specific type of data
(i.e. loop data) was archived — in an experiment independent of
the ODOT’s normal operations— in order to prove the utility of
archiving data for future applications. TransPort installed 10
mainline inductive loop detector stations and associated on-ramp
detectors at 10 eastbound on-ramps along an 11-mile corridor along
eastbound US 26 in Portland. Vehicle counts, occupancy and speeds
were archived, and it was determined that such simple, directly
measurable variables would be useful in setting standards and
determining widely-applicable performance measures. Still other
DOTs nationwide are archiving several types of data simultaneously,
but most have not gathered a substantial amount of data over a
long enough period of time to use for noteworthy planning and
operations improvements. However, the value inherent in having
such archived data is widely recognized and its planning and operational
benefits highly anticipated. Those DOTs and transportation agencies
that are archiving data have determined that most data users prefer
to access the data in an online format or on CD-ROMs.
Although archived data user services are potentially
a rich resource for improving many transportation decisions, most
notably for enhancing transportation planning and operations,
not many regions are employing ADUS, mainly because this service
requires a significant amount of institutional evolution, particularly
in terms of infrastructure investments. Although ADUS is new to
the ITS Architecture, it is expected that more and more TMCs will
recognize the value of implementing a performance measurement
system based on archived traffic data.
-
The reluctance to share
data among jurisdictions will continue to hinder full ADUS implementation.The
lack of ADUS standardization for both data
-
Data quality and accessibility
slows the integration of different information from multiple
sources.
-
More efficient data checking
methods are needed to ensure accuracy, and reliability, absence
of bias, and validity of estimation methods.
-
Organizations like the
TMC generally do not have the staff needed for both incident
management and data archiving.
-
Data ownership, maintenance,
or control issues may become problematic.
-
The planning community
is not progressing as rapidly as the transit community on ADUS.
This is because the entities that produce the desirable planning
data (e.g. the TMCs) are organizationally separate from the
data users (e.g. the planners).
-
TMCs are not collecting
data explicitly on ITS Safety issues; those who are interested
in safety have to find their own ways to relate ITS-generated
data to the topic of highway safety.
-
Many agencies that collect
data on incidents withhold safety data in order to honor privacy
and liability issues.
-
It is unclear which entity
should bear the cost of the various ADUS applications; whether
it should be borne by the data user or provider (TMC) is still
a major barrier to implementation. Currently, there are some
data users who obtain data by paying the data producers directly;
alternatively, there are some data brokers who make the data
available to interested users at a cost.
-
Costs for implementing
ADUS are needed to:
-
Articulate and communicate
the needs for archived data
-
Save the data
-
Re-format
the archived data into a user-friendly format
-
Re-vamp
the existing software to accommodate archived data
-
Address data quality issues
-
Make archived data accessible
in a timely manner
-
Integrate the archived
data with non-ITS data to meet broader data needs
-
Reconcile data incompatibilities
among different data sources
-
Forge mutually beneficial
partnerships among data-producing agencies and data users
The purposes of having standards
for ADUS are to:
-
Define and promote the
interfaces necessary to implement ADUS in the field.
-
Ensure consistent deployment
of ADUS nationwide.
-
Eliminate duplicate data
collection and storage.
-
Coordinate with other
ITS data dictionary efforts that are relevant to ADUS.
-
Reconcile differences
between the data definitions in pre-existing ITS data dictionaries
and those of ADUS stakeholders.
Standards for ADUS are still
under development, but it is important to note that any standards
developed should take into account that the standards for each
ITS entity will effect ADUS. Close coordination between ADUS and
each ITS user service is thus essential. Aimed at creating “open”
protocol standards that will serve the transportation information
network and be adaptable to different communications architectures,
the National
Transportation Communications for ITS Protocol (NTCIP) is
currently developing standards that will facilitate the use of
ITS devices for data collection.
|
Below
is a diagram of the various ITS Sources that interact with
an archived data management system: |

“Standards Will Promote the Development of Interfaces
for Archived Data Management Systems” From the Strategic Plan
for the Development of ADUS Standards, May 2000.
|
The
diagram below illustrates the flow of data from its collection
stage to its archiving stage: |

"ADUS Standards Take Many Forms and Support
the Various Process of the Data Stream" From the Strategic
Plan for the Development of ADUS Standards, May 2000.
Collected from studies by
the Texas Transportation Institute, Cambridge Systematics, and
PATH.
Portland,
Oregon
Dallas,
Texas
Daltrans is
a component of the Dallas office of the Texas DOT that collects
traffic information from intelligent transportation system. The
Dallas district office currently operates closed circuit TVs (incident
detection and management), changeable message signs (traffic control),
online and media outlets (en-route and pre-trip traveler information),
and lane control signs (traffic management). Daltrans currently
collect video from CCTVs, incident information, current and scheduled
work zones, and point data (volume, occupancy, and speed) from
video.
The following types of
data are currently archived:
-
-
Current and scheduled
work zones
There is no significant
data being archived at this time.
The TXDOT – Fort Worth
is not archiving data as of October 2002, but it has in past years
under the TransVISION project. TransVISION
is a component of the Fort Worth office of the Texas DOT that
collects traffic information from intelligent transportation systems.
TransVISION operates detector surveillance and closed circuit
TVs (incident detection and management), ramp meters/changeable
message signs/lane control signals (traffic control and management),
and online and media outlets (en-route and pre-trip traveler information).
TxDOT – Ft. Worth has developed procedures to track system performance
that rely on archived data but have not regularly implemented
these procedures. TransVISION currently collects point data (volume,
occupancy, speed, percent trucks) from double loops and radar
detectors, video from CCTV, metering rates and ramp queues, incident
information, and current and scheduled work zones.
The following types of
data are currently archived:
-
Video snapshots associated
with incidents
-
-
Current and scheduled
work zones
Archived data are currently
used largely by universities for research purposes, ITS evaluation,
and traffic planning purposes. TransVISION is planning to operate
a local data warehouse for their purposes, as well as share
data with other centers (i.e. The North Central Texas Council of Governments – NCTOG).
Thus far, archived data have been used to evaluate ramp metering
and other research evaluation projects.
The Houston district office
of the TxDOT gathers traffic data largely from two different sources:
1) TranStar,
a multi-governmental facility that is responsible for the planning,
design, operations and maintenance of transportation operations
and traffic emergency management operations within the Greater
Houston Area 2) TTI (Texas Transportation
Institute), an official research agency for the Texas Department
of Transportation and the Texas Railroad Commission. The TxDOT-Houston
currently operates detector and probe vehicle surveillance/closed
circuit TV (incident detection and management), and ramp meters/changeable
message signs/lane control signals/HOV lanes (traffic control
and management). TxDOT-Houston tracks system performance on an
annual basis using probe vehicle data from the AVI traffic monitoring
system. It currently collects point data (volume, occupancy, speed,
percent trucks) from double loops and some VIDs, probe vehicle
travel times from the AVI traffic monitoring system, video from
CCTV, metering rates and ramp queues, incident information, and
current and scheduled work zones.
The following types of
data are currently archived:
-
Anonymous vehicle travel
times
-
Volume, occupancy,
and speed from loops and VIDS since mid-2000 by TTI
Archived data has been
used to evaluate ramp metering as well as overall system performance
at TranStar. TTI-Houston office currently maintains travel time
data from the AVI traffic monitoring system, The TTI-Houston
office has also been archiving loop detector data from the TranStar
database since mid-2000 under agreements with the TxDOT. The
TranStar warehouse will eventually archive numerous data being
generated or collected at TranStar. The data warehouse will
be managed through a relational database, with access through
internal networks or the Internet.
TransGuide
is an Intelligent Transportation System designed by the San Antonio
District of the Texas Department of Transportation (TxDOT). TransGuide
currently operates detector surveillance/closed circuit TV (incident
detection and management), changeable message signs/lane control
signals (traffic control and management), online and media outlets
(en-route and pre-trip traveler information), highway-rail intersection
monitoring. It currently collects point data (volume, occupancy,
speed, percent trucks) from double loops and some VIDs, travel
times from an AVI traffic monitoring system, video from CCTV,
incident information, and current and scheduled work zones.
The following types of
data are currently archived:
-
Traffic volume, occupancy
and speed
-
Probe vehicle travel
time
-
-
-
Current and scheduled
work zones
-
Road and weather conditions
Archived data is largely
used by agencies other than TransGuide, such as state universities
and other research groups. The data is used primarily for research
purposes, ITS evaluation, and traffic planning purposes. This
data is also used in FHWA Mobility Monitoring Study conducted
by TTI/Cambridge Systematics. TransGuide currently maintains
a publicly-accessible FTP site that has the most recent month
of data files in ASCII-text format.
The Georgia DOT currently
operates detector surveillance/closed circuit TV/service patrol
(incident detection and management), changeable message signs/lane
control signals (traffic control and management), online and media
outlets (en-route and pre-trip traveler information), and the
NAVIGATOR
system. The NAVIGATOR
system currently collects point data (volume, occupancy, speed)
from VID, video from CCTV, incident information, and current
and scheduled work zones.
The following types of
data are currently archived:
-
Traffic volume, occupancy,
and speed
Archived data is used
mostly by university researchers (Georgia Tech) for research
on operational strategies, ITS evaluation, and traffic monitoring
and planning purposes. Data is also being used in a FHWA Mobility
Monitoring Study conducted by TTI/Cambridge Systematics. The
GDOT maintains archived data in ASCII-text files at the 15-minute
level; GDOT also provides this data on CD upon request, while
researchers at Georgia Tech maintain the archived data in a
relational database.
The Michigan DOT currently
operates detector surveillance/closed circuit TV/service patrol
(incident detection and management), changeable message signs/lane
control signals (traffic control and management), and online and
media outlets (en-route and pre-trip traveler information). The
Michigan DOT collects point data (volume, occupancy, speed) from
double loop detectors, video from CCTV, incident information,
and current and scheduled work zones.
The following types of
data are currently archived:
-
Traffic volume, occupancy,
and speed
Archived data is shared
with Detroit MPO for traffic planning and analysis purposes;
data is also used in a FHWA Mobility Monitoring Study conducted
by TTI/Cambridge Systematics. The MDOT maintains the most recent
data “online” for a short period (about one week), then permanently
archives them to magnetic trap cartridges.
The Virginia DOT currently
operates detector surveillance/closed circuit TV (incident detection
and management), changeable message signs/lane control signals
(traffic control and management), and online and media outlets
(en-route and pre-trip traveler information). The Virginia DOT
collects point data (volume, occupancy, speed) from double loop/microwave
radar/acoustic detectors, video from CCTV, incident information,
road and weather conditions, and current and scheduled work zones.
The following types of
data are currently archived:
-
Traffic volume, occupancy,
and speed
-
Archived data is used
largely by Virginia Transportation Research Council (VTRC) for
research on operational strategies, ITS evaluation, and traffic
monitoring and planning purposes. Data is also used in a FHWA
Mobility Monitoring Study conducted by TTI/Cambridge Systematics.
VTRC operates and maintains the ITS data archives for the VDOT.
The Montgomery County DOT
currently operates detector surveillance/closed circuit TV/fixed-wing
aircraft (incident detection and management), closed-loop signal
system/emergency vehicle preemption (arterial traffic control
and management), changeable message signs/lane control signals
(traffic control and management), and online and media outlets
(en-route and pre-trip traveler information). The Montgomery County
DOT collects data from sampling and presence loop detectors, video
from CCTV, incident information, and current and scheduled work
zones.
-
The following types
of data are currently archived:
-
Traffic volumes are
transferred to and archived by M-NCPPC
-
Probe vehicle travel
time
-
-
Current and scheduled
work zones
Archived data is used
mostly by M-NCPPC (Maryland National Capital Park
and Planning Commission) for traffic planning and analysis purposes
(i.e. network volume maps). M-NCPPC uses Internet protocols
(TCP/IP) and a custom software product to query the DOT database
in the early morning and retrieve the most recent 24 hours of
5-minute volume data. Once the data has been retrieved, M-NCPPC
loads the data into an Oracle server, does error checking, and
then computes peak hour intersection volumes and other volume
quantities used in planning applications.
The ADOT currently operates
detector surveillance, closed circuit TVs, and an incident response
team (incident detection and management); changeable message signs/lane
control signals (traffic control and management); and online and
media outlets (en-route and pre-trip traveler information). The
ADOT collects point data (volume, occupancy, speed, vehicle classification)
from double loop/passive acoustic detectors, video from CCTV,
incident information, and current and scheduled work zones.
-
The following types
of data are currently archived:
-
Traffic volume, occupancy,
and speed
Archived data is used
primarily for research on operational strategies, ITS evaluation,
and traffic monitoring and planning purposes. Data is also used
in a FHWA Mobility Monitoring Study conducted by TTI/Cambridge
Systematics. The ADOT maintains the original 20-second data
as collected from the detectors; they store recent data on-line
in compressed text formats, and keep old data on CDs. They have
also developed software to provide archived data upon request
in a number of different aggregation levels and formats.
Orange County, CA Caltrans
UCI TMC Orange
County TMC
UC Irvine collects incident, congestion and ramp metering
information. The system support staff analyzes the data to develop
operational strategies and the planning department uses the
data to determine alternative plans for capital improvements.
Data is stored on the server for a year and is backed-up on
tape; this data is available to the public at no cost on the
web.
Minneapolis,
MN Metro District Transportation Management Center
This center uses loop detectors and closed circuit TVs for
incident detection and congestion tracking. They provide an online
map that shows congestion levels every minute and icons indicating
various types of incidents. They also post the data on a server
that can be accessed by organizations providing traffic information;
this is used to provide traffic reports on the radio and television,
SmarTraveler’s telephone traveler information system, and other
traffic web sites. This center has been archiving traffic data
since 1984, and they now store it on the server for one year,
after which time it is transferred to CDs. Anyone in MnDOT
can access the data anytime.
Seattle,
Washington WSDOT
The WSDOT collects freeway detector data and has developed
a CD-based data archive for Seattle freeways. The data is used
for testing and evaluating operational improvements (i.e. ramp
metering and HOV lanes), freeway performance monitoring, pavement
design, and freight performance analysis. The CD is used to hold
three months of 5-minute summary data and the CDs are made available
upon request.
Berkeley,
CA University of California PeMS
PeMS is a freeway performance measurement system that collects
detector data from several Caltrans’ districts including Los Angeles,
Orange County, and Sacramento. The data is archived online (http://transacct.eecs.berkeley.edu)
for anyone who has a password. The data is used for freeway performance
using speeds, estimated travel times, and vehicle volumes.
The ODOT, the City of Portland,
Tri-Met (Portland’s transit agency), Metro (regional government),
and other regional jurisdictions have developed the TransPort
(Transportation Portland) program. This program brings together
the various agencies to develop, operate and evaluate traffic
management, incident response, and traveler information systems
as part of the region’s ATMS. In this experiment, 10 mainline
inductive loop detector stations (with detectors located in each
lane) and associated on-ramp detectors at 10 eastbound on-ramps
were installed along an 11-mile corridor along eastbound US 26
between Helvetia Road and Skyline Road in Portland, Oregon.
The
data recorded by these sensors included:
-
-
occupancy and speed
as measured by the detectors in each lane and on each on-ramp
and are aggregated locally every 20 seconds
These
20-sec data were transmitted to the traffic management center
(TMC) via the regional fiber optics network. Typically ODOT
archives their data at a 15-minute level, but for this experiment
data was requested in its most raw form available. The time
period chosen for this experiment was the week of Monday, October
30 to Friday, November 3, 2000. This experiment showed it is
possible to obtain information assessing the functionality of
the facility using archived data from loop detectors. The information
will assist in determining the best performance measures for
obtaining simple, quick and accurate ideas about the functionality
of the corridor, enhancing decision-making. With simple, directly
measurable variables such as vehicle count, speed, occupancy
and incident information, it is possible to set some standards
and determine some performance measures that can be generated
for the transportation systems around Portland and in that way
keep track of the general performance of the network. The archived
data may be available on the Internet in the future.
Most of the traffic data
sent to the TMC is created by various types of traffic sensors
that include:
Loop Detectors
These are the most commonly used detectors. They sense when
a car enters the pavement over the loop and how long it covers
the loop, thus providing a count of vehicles crossing the loop
and a measure of the time the loop is occupied from which the
vehicle density (vehicles per mile) can be estimated.
Active infrared
Active infrared (or laser range finder technology) provide
presence, speed, volume, occupancy, and classification information
in day and night conditions. The detector senses a portion of
the reflected energy in its field of view; the distance of an
object from the detector is found by measuring the two-way travel
time of the infrared pulse, from the detector to the target and
back.
Passive Infrared
Passive infrared provide volume, occupancy, and presence
information. Passive IR detectors do not transmit energy, but
rather they measure energy emitted by objects in their field
of view. They detect vehicle presence by measuring the difference
in emitted energy (i.e. temperature) from the road and vehicles.
Radar
Radar detection can provide vehicle counts, densities, and
speeds. Vehicle speeds are measured using the Doppler effect (measuring
frequency shifts between the transmitted and received beam caused
by the vehicle in motion); vehicle counts are determined by accumulating
information on each vehicle detected. A second type of radar detector
transmits a signal that is swept over a range of frequencies;
this technique measures the range to the vehicle and thus can
detect presence.
Doppler Microwave
Doppler Microwaves sensors are able to count vehicles,
measure speed and detect vehicle presence. Microwave detectors
fall into two categories: Doppler or radar devices. Radar
devices, also known as pulse microwave, measure the time it
takes for a portion of the microwave radiation to be reflected
from the target area to a receiver. Microwave radar vehicle
detectors transmit electromagnetic energy at the speed of
light in frequency bands between 2.5 to 24.0 GHz.
Pulse Ultrasonic
Pulse Ultrasonic can measure speed, occupancy, presence,
and, in some configurations, queue length. These sensors
operate on the same principles as Doppler radar, except
that they emit sound waves with frequencies between 20 and
200 KHz, which are above the human audible range. They are
pressure waves that travel through the air at about 740
mph at sea level.
Video
Image Detection (VID)
Video image detection systems (VIDS) employ machine vision
technology to automatically analyze traffic data collected
with Closed Circuit Television (CCTV) systems. VID is used
for actuated intersection detection, automated traffic counts,
ramp metering, freeway management and automatic incident detection.
VID can count vehicles, detect vehicle presence, and read
license plates.
GPS
A GPS (Global Positioning System) receiver collects
the real-time latitude and longitude information of a GPS-equipped
vehicle and sends this information to a central computer
for processing. Over the past several years, GPS has become
the preferred AVL system for fleet and travel behavior studies
because it collects accurate and detailed travel times as
well as captures variability in travel behavior across multiple
days.
Cellular Phones
Under manual surveillance, wireless phone users can
call into a Transportation Management Center (TMC) or Traveler
Information Center and report incidents or traffic conditions.
Under automatic surveillance, wireless service providers
automatically collect geo-location data of wireless phones
and forward it to TMCs.
In-vehicle tags
Probe vehicles are equipped with electronic tags that
can track the vehicle’s speed, location, and travel time
along roadways that have a tag reader infrastructure.
The various components of ITS user
services, such as roadside transponders, CCTV, and infrared
sensors, rely upon communication linkages in order to transmit
and receive data. These components communicate with each
other through various mediums, including wireless networks,
fiber optics, radio signals, and wireline connections. These
modes of communication in turn comprise the telecommunications
infrastructure which allows ITS user services to function
efficiently, not only as independent systems, but also as
parts of the larger network of intelligent transportation
systems. The best communications technologies to use for
communicating traffic data will depend on the nature and
volume of the data, distances between where the data is
collected and processed, communication services available
in the area, and their cost. The preferred communication
medium for ITS is fiber optic because of its high capacity
and reliability; however, it is too expensive for many locations.
Leased telephone lines are more commonly used but are less
reliable. Most agencies use a combination of communications
media.
There are two categories
of communications technologies: wireline and wireless.
Wireline Technologies
-
-
-
Fiber optic (multimode
and single mode)
-
-
Cellular (digital
and analog)
-
Cellular digital
packet data
-
-
Digital and trunked
radio systems
The table below compares
the various characteristics of communications technologies.
This chart was created in 1995, and there have since been
many advances, especially in wireless communications.
|
Comparison
of Communications Technologies |

For more information
see the ITS
Decision Telecommunications Report
Quality control of
data is important for ADUS for a number of reasons. Firstly,
it is difficult to detect errors (using traditional manual
techniques) in the large volume of operations data that
ADUS produces. Secondly, archived data users may have very
different data requirements (i.e. accuracy requirements)
than real-time users of that same data. Thirdly, when only
minimal error detection is performed as data are being collected
in real-time, an accumulation of erroneous or missing data
can result.
Data quality has several aspects to consider:
Accuracy –
Different levels of accuracy are needed for different operations
Reliability
– Maintenance practices greatly affect reliability, although
different levels of maintenance are necessary for different
data collection systems to remain useful.
Absence of bias
- This refers to the extent to which the sensor data
reflects the entire facility being monitored.
Validity of estimation methods –
Missing data is often replaced by estimated data, a practice
that may cause some unknowing users to draw erroneous conclusions.
Albert, Luke. An
Evaluation of the Potential of Public/Private Partnerships
for the Management of Archived ITS Data, Texas A &
M University, August 1999. Link
to Report
Archived Data User
Service Self-Evaluation Report, FHWA Nevada DOT, November
2000. Link
to Report
Chen, Chaos. Petty,
Karl. Skabardonis, Alexander. Varaiya, Pravin. Jia, Zhanfeng.
Freeway Performance Measurement System: Mining Loop Detector
Data, UC Berkeley Institute of Transportation Studies,
January 2001. Link to Report
Definging and Measuring
Traffic Data Quality
Link
to Report
Dahlgren, Joy; Garcia,
Reinaldo; Turner, Shawn. Completing the Circle: Using
Archived Operations Data to Better Link Decisions to Performance,
UC Berkeley PATH, 2001. Link
to Report
ITS Data Archiving
Five-Year Program Description, US DOT, March 2000. Link
to Report
Strategic Plan
for the Development of ADUS Standards, Cambridge Systematics,
Inc., May 2000. Link
to Report
Turner, Shawn. Guidelines
for Developing ITS Data Archiving Systems, TTI, September
2001. Link
to Report
Author:
Lauren Smith
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