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IDAS:
A Tool for Integrating ITS Into the Planning Process
by Gene McHale
Intelligent transportation
systems (ITS) have the potential to revolutionize surface transportation, but
listening to all the claims of some ITS proponents, one could begin to believe
that ITS will solve all our transportation problems - and maybe the common cold
too. The transportation planner has to be able to determine the realistic benefits
of particular ITS options, the cost of those options, and the way to get the
greatest benefit for the funds available.
This has been difficult because each jurisdiction has a unique set of conditions
and requirements, and these must be taken into consideration when planning ITS
deployments in conjunction with other types of transportation improvements.
Also, typically in the past, ITS features have been "add-ons" to existing
transportation improvement projects.
However, as ITS become mainstreamed into improvements "tool kits,"
the ability to assess the relative costs and benefits of alternative ITS improvement
strategies is critical. It is for this reason that the ITS Deployment Analysis
System (IDAS) has been developed as a tool to assist transportation planners
and others in the transportation arena.
Background
The transportation planning community has been using travel demand forecasting
models to study alternatives for many years. To forecast travel demand, the
traditional four-step modeling approach, which comprises trip generation, trip
distribution, mode choice, and traffic assignment, is applied.
The four-step models forecast future travel demand on the transportation system
based on a specific set of transportation improvement strategies. It allows
comparison with the "do nothing" or base conditions and with other
sets of improvement strategies. The costs and benefits of these transportation
alternatives are then analyzed using add-on tools such as the Surface Transportation
Efficiency Analysis Model (STEAM), developed by the Federal Highway Administration
(FHWA).
For years, these traditional approaches and their corresponding assessment tools
have served the needs of the planning community. However, these tools are extremely
limited in their ability to evaluate the potential effects of ITS improvements.
For example, the current tools are more than adequate in modeling the effects
of adding an additional lane of highway, but they cannot measure the effects
of a ramp metering system on the freeway.
This is why IDAS was developed. It enables the assessment of ITS improvements
by adding on to the four-step models.
The Tool
In general, the IDAS software is designed to pick up where the traditional four-step
planning models end. In fact, IDAS takes the output from four-step planning
models to establish a base-case scenario. The IDAS user then selects from a
list of ITS components and deploys one or more ITS improvements into the base
case. IDAS then executes its own travel demand model to determine the new travel
patterns that emerge as a result of the ITS improvements. The incremental costs
and benefits resulting from the deployment of the ITS components are then compared
to the base-case scenario and presented to the IDAS user.
This is the overall strategy that serves as the IDAS framework. Within the IDAS
software, this strategy is implemented in a series of modules.
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The Input/Output
Interface inputs the data from the four-step planning models into the
IDAS software. This input establishes the base-case scenario for analysis
and includes files that describe the regional transportation network in
terms of nodes, links, and the number of trips from each origin to each
destination for the forecasted year being analyzed.
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The Alternatives
Generatorprovides the graphical interface for the user to select the ITS components
to deploy on the transportation network. The user selects from a list of
ITS components and "drags and drops" them onto the graphical depiction
of the transportation network. The ITS components are grouped in 12 major
categories as shown in table 1. The user may choose from a total of 69 individual
ITS components. An example of an individual ITS component is the Ramp Metering
Pre-Set Timing option in the Freeway Traffic Management Systems category.
-
The Benefits Modulequantifies the benefits resulting from the deployment of the ITS components.
The default benefit values within IDAS are based on ITS deployments and/or
research studies. The user can change the default values, if desired. It
is within this module that IDAS incorporates an internal travel demand model
to re-evaluate travel patterns based on the addition of the ITS components.
Only benefits attributable to the ITS improvements are reported. Benefits
are calculated using the following submodules:
a. Travel Time/Throughput Submodule.
b. Environment Submodule.
c. Safety Submodule.
d. Travel Time Reliability Submodule.
-
The Cost Moduletracks the estimated costs to deploy the ITS components selected by the
user. Each ITS component within IDAS requires the deployment of one or more
pieces of ITS equipment. The default equipment requirements and their associated
costs may be modified by the user if more customized data is available.
In addition to the equipment costs, the percentage of public versus private
funding, the deployment schedule, and the use of shared equipment are also
factored into the cost analysis.
-
The Alternative
Comparison Modulecompares the benefits and the costs of the ITS component improvements to
the benefits and costs of the base-case scenario, presents the results,
and allows for sensitivity and risk analysis on parameters. Part of this
module is the conversion of all benefits into a monetary value (e.g., the
hourly value of in-vehicle travel time). As with the other modules, the
user may change any of the default parameters in the Alternative Comparison
Module, if desired.
Table 1 - ITS Component
Categories Within IDAS
- Arterial Traffic
Management Systems.
- Freeway Traffic
Management Systems.
- Advanced Public
Transit Systems.
- Incident Management
Systems.
- Electronic Payment
Collection Systems.
- Railroad Grade
Crossings.
- Emergency Management
Systems.
- Regional Multimodal
Traveler Information Systems.
- Commercial Vehicle
Operations.
- Advanced Vehicle
Control and Safety Systems.
- Supporting Deployments.
- Generic Deployments.
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The Project
The development of IDAS was funded with ITS funds from the U.S. Department of
Transportation (DOT) and was managed by the FHWA Office of Operations Research
and Development. The delivery of ITS is the responsibility of the offices of
Travel Management and Metropolitan Planning in FHWA. The contracted team that
conducted the work included the Oak Ridge National Laboratory, Cambridge Systematics
Inc., and ITT Systems. A steering committee, composed of a dozen metropolitan
planning organizations (MPOs), the research community, and DOT, has been active
in the development of IDAS since its inception and continues to provide the
feedback and insight needed from the IDAS "customer community."
IDAS is being developed under the "rapid prototyping" paradigm, using
the following planning organizations as "beta testers" in the development
of the software: Pima Association of Governments (Tucson, Ariz. area), Chicago
Area Transportation Study, and Metropolitan Transportation Commission (San Francisco
Bay area).
MPO Experiences
The three beta test sites continue to use IDAS. In each case, the MPO is using
the IDAS software to analyze a transportation improvement(s) that is currently
being planned in their region.
The Pima Association of Governments (PAG), which began working with the IDAS
team in November 1998, was the first MPO to test the software. PAG studied three
cases for the moderate-sized Tucson transportation network, which included 8,600
directional transportation links and 646 traffic analysis zones. The PAG beta
test cases were as follows:
Pima Association of Governments
(8,600 links, 646 zones)
Option 1: Centrally controlled ramp metering on the I-10 corridor. Ramp
metering for approximately 16 kilometers. Twelve northbound on-ramps were metered.
Option 2: Systemwide transit automated vehicle location (AVL) deployed
on 197 buses.
Option 3: Combined ramp metering and transit AVL.
Preliminary results from
the IDAS software suggested benefit-to-cost ratios of 30.4-to-1, 7.8-to-1, and
12.6-to-1 for options 1, 2, and 3, respectively. As the first beta tester, PAG
identified some bugs in IDAS and made some suggestions for improvements, which
were subsequently incorporated into the software. Overall, they felt that the
IDAS software was a useful tool for planners to use to sketch out the benefits
and costs of ITS improvements.
The other MPOs involved in the beta testing - Chicago Area Transportation Study
(CATS) and Metropolitan Transportation Commission (MTC) - had the opportunity
to use a version of IDAS that was improved by the input from the PAG beta test
results. Again, each of these MPOs decided to use IDAS to test ITS improvements
that were currently under consideration or being planned in their regions. The
beta test case options that were pursued and the size of the transportation
networks are as follows:
Chicago CATS (36,000
links, 1,900 zones)
Option 1: Transit vehicle signal priority along four corridors.
Option 2: Electronic toll payment at 14 locations.
Option 3: Regionwide Internet-based traveler information system.
San Francisco MTC
(31,300 links, 1,099 zones)
Option 1: Telephone and Internet-based traveler information system for
freeways and major arterials.
Option 2: Full traveler information system (e.g., telephone, Internet,
hand-held personal device, and in-vehicle information) on freeways and major
arterials.
Option 3: Option 2 plus full advanced traffic management system (e.g.,
centrally controlled ramp metering, incident detection and response, highway
advisory radio, and freeway variable message signs) on freeways and major arterials.
The size of the Chicago
network presented a challenge to the data processing for the IDAS software,
and the recommendations resulting from the beta testing were extremely helpful
in improving the efficiency with which IDAS handles large data sets.
The results from these beta test cases have shown that IDAS software is a useful
tool for planning-level analyses of ITS deployments.
Release of IDAS
A major "roll-out" of IDAS is planned at the Intelligent Transportation
Society of America (ITS America) Annual Meeting in Boston during the first week
in May 2000. IDAS presentations and demonstrations will be available during
the annual meeting.
Software Distribution
The IDAS software will be distributed and supported by the McTrans Software
Center at the University of Florida. The software will be available by May 2000.
Those interested in purchasing a copy of the IDAS software are referred to the
McTrans Web site at http://mctrans.ce.ufl.edu.
IDAS Training
A two-day training course is currently being developed with ITS funds and is
being managed out of FHWA's National Highway Institute. The training course
is being designed to educate the participants in both the theory behind the
IDAS model and in the use of the software. To meet this goal, the course will
be delivered in a computer lab environment with a combination of lectures and
hands-on use of the IDAS software. A pilot version of the course is scheduled
for delivery in spring 2000, followed by the first round of training, which
will be offered at each of the four FHWA resource centers. The course should
be available to state and local agencies in mid to late summer 2000.
For more information
on IDAS, please visit the ITS Joint Program Office Web site at www.its.dot.gov
or contact the author at gene.mchale@fhwa.dot.gov.
Gene McHale is a
general research engineer on the Advanced Traffic Management Systems (ATMS)
Team within FHWA's Office of Operations Research and Development. His current
responsibilities related to IDAS include the development and maintenance of
the software and the development of the IDAS training course. In addition to
IDAS, McHale is currently involved in the development and maintenance of the
Traffic Software Integrated System (TSIS) suite of traffic analysis tools. Since
joining FHWA in 1995, he has had a variety of duties related to intelligent
transportation systems. He received his bachelor's and master's degrees in systems
engineering from the University of Virginia and is currently a doctoral candidate
in civil engineering at Virginia Tech.
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