Congestion impacts our daily lives, wasting fuel, lengthening trips and threatening business. The U.S. Department of Transportation (USDOT) launched the Integrated Corridor Management (ICM) initiative in 2005 to address these challenges by demonstrating how intelligent transportation systems (ITS) technologies can help transportation system operators and managers efficiently and proactively manage the movement of people and goods in major transportation corridors. The ICM initiative aims to pioneer innovative multimodal and multi-jurisdictional strategies that optimize existing infrastructure to help manage congestion in our nation’s transportation corridors.
In 2006, the USDOT selected eight pioneer sites to act as critical partners in the development, deployment and evaluation of ICM strategies. The pioneer sites include Oakland and San Diego, Calif.; Dallas, Houston and San Antonio, Texas; Montgomery County, Md.; Seattle, Wash.; and Minneapolis, Minn.
Using existing assets such as transit signal priority, ramp metering, real-time parking availability information systems, electronic payment and traveler information technologies, transportation corridor operators and managers can employ an array of ICM strategies to improve the movement of people and goods. With so many choices, agencies are interested in analyzing the potential benefits of the various approaches to help them decide on specific ICM strategies to implement.
The USDOT developed the ICM analysis, modeling and simulation (AMS) methodology to help transportation decision-makers identify the best ICM strategies for their needs under different conditions (such as planned special events, high traffic congestion or major incidents). The approach is unique in that it combines elements of existing models to support comprehensive assessment of ICM strategies not available today through any single tool. Once validated, the USDOT will make the approach available to transportation system managers and operators to help them implement ICM.
The USDOT took the first steps in spring 2008 toward validating the approach and generating initial insights into possible ICM benefits by applying the AMS methodology to a test corridor. Beginning in fall 2008, the USDOT will apply the AMS methodology to analyze the potential benefits of proposed ICM strategies at three of the eight ICM pioneer sites: Dallas, Texas; Minneapolis, Minn.; and San Diego, Calif. The application of AMS to the ICM strategies of these pioneer sites will yield insights that can help other transportation system managers and operators across the country select and apply optimum ICM strategies in their corridors. The USDOT will make the results from the test corridor AMS efforts available to transportation practitioners around the country on the ICM Web site through its knowledge and technology transfer activities.
The ICM AMS Approach
The AMS approach was designed to leverage the strengths of various analysis tools, such as travel demand models, mesoscopic simulation models and microscopic models. The approach was designed to address key gaps in current modeling approaches, including: a) the analysis of traveler responses to traveler information; b) the analysis of strategies related to tolling/high-occupancy toll ( HOT) lanes/ congestion pricing; and c) the analysis of mode shift and transit.
This modeling approach is based on the realization that different tool types have different advantages and limitations. There is no one tool type at this point in time that can successfully address the analysis capabilities required by ICM AMS requirements. No single model available today provides visibility into the cascading impacts of various congestion management strategies, much less combinations of strategies, across the entire network, transportation modes and facility types. The ICM AMS methodology can support corridor management planning, design and operations by integrating the three tool types and combining their capabilities.
The ICM AMS Test Corridor
The analysis team selected the San Francisco Bay Area’s I–880 corridor to serve as the testbed for the AMS methodology after a careful review of more than 20 candidate corridors. This corridor is one of the main arteries in the San Francisco Bay Area, with 38 miles of freeway connecting Silicon Valley with the East Bay. It is a major freight and passenger throughway serving the Port of Oakland, Oakland International Airport and the Oakland Coliseum, as well as a concentration of residential, industrial and commercial properties. The team also selected the I–880 corridor because of the wealth of available corridor data, multitude of transportation modes and facilities (freeways, arterials, high-occupancy vehicle (HOV) lanes, transit, etc.) and the transferability and applicability of results and methods to other corridors.
Operational Conditions of the Test Corridor
The ICM AMS framework provides tools and procedures capable of supporting the analysis of both recurrent and nonrecurrent corridor operational conditions. In the test corridor AMS effort, nonrecurrent congestion conditions entailed combinations of increases of demand and decreases of capacity. Key ICM impacts may be missed in analysis if only “normal” travel conditions are considered. As shown in Figure 3, the different operational conditions of the AMS approach take into account medium- and high-travel demand, combined with assumptions of major and minor incidents.
The relative frequency of nonrecurrent conditions is important to estimate in this process—based on archived data. Figure 3 shows the overall frequency of various operational conditions for the test corridor, including percentage of days in the year categorized by different incident and demand levels. Major incidents were defined as having duration more than 20 minutes, and minor incidents as having duration less than 20 minutes. In the test corridor, major incidents together with high demand, characterize 25 percent of all workdays (red or upper-right cluster in the left part of Figure 3), while 22 percent of all workdays (green or lower-left cluster) feature both low demand and minor incident conditions. The right part of Figure 3 shows that 39 percent of total annual delay (red or upper-right cluster) occurs on the worst 25 percent of days, while 64 percent of annual delay (red and yellow) occurs on the worst 44 percent of days. Conversely, only 14 percent of annual delay (grey and green) occurs on the remaining 39 percent of days.
Performance Measures Used in AMS of the Test Corridor
USDOT is working to establish a continuous improvement cycle to apply to the integrated management and operations of transportation assets in our nation’s multimodal corridors. Figure 4 depicts a process in which by defining clear corridor level performance objectives, archiving operations data and analyzing the impacts of ICM strategies, transportation agencies can improve the performance of their corridors.
Better data leads to better models leads to better investment, and so on.
To be able to compare the impacts of different ICM strategies within a corridor, analysts applied a consistent set of performance measures to the AMS test corridor effort. These performance measures:
- Provide an understanding of travel conditions in the study area;
- Demonstrate the ability of ICM strategies to improve corridor mobility, throughput, reliability and safety based on current and future conditions; and
- Help prioritize individual investments or investment packages within the test corridor for short- and long-term implementation.
To the extent possible, the measures were reported by:
- Mode – Single-occupancy vehicle (SOV), HOV, transit, freight, etc.;
- Facility Type – Freeway, expressway, arterial, local streets, etc.;
- Jurisdiction – Region, county, city, neighborhood and corridor-wide.
The performance measures focused on the following five key areas:
- Mobility – Describes how well the corridor moves people and freight;
- Reliability – Captures the relative predictability of the public’s travel time;
- Safety – Captures the safety characteristics in the corridor, including crashes (fatality, injury and property damage);
- Emissions – Captures the impact on emissions consumption; and
- Fuel Consumption – Captures the impact on fuel consumption.
For the identified ICM strategies, the analysis team prepared planning-level cost estimates, including life-cycle costs (capital, operating and maintenance costs). Costs were expressed in terms of the net present value of various components.
Preliminary AMS of the test corridor suggests the benefits of ICM strategies are greatest under the worst traffic conditions due to heavy demand and/or incidents. In the test corridor AMS, 1 to 4 percent of travelers shifted to transit in the presence of a major incident. Importantly, the test corridor AMS validated the hypothesis that implementation of ICM is not “one size fits all;” effective real-time corridor management requires selective implementation of different ICM strategies, depending on the extent of underlying nonrecurrent congestion (due to incidents, weather and other unexpected events) and on the severity of prevailing travel demand. Dynamically applying ICM strategies in combination across a corridor was shown to reduce congestion and improve the overall productivity of the transportation system.
Figures 5 and 6 present summaries of monetized annual benefits for the ICM strategies modeled in the AMS test corridor effort, using test corridor data, for the major incident operational conditions. The ICM strategies modeled, both individually and in combination, include highway traveler information, transit traveler information, local adaptive ramp metering, HOT lanes and arterial traffic signal coordination. Monetized benefits are combinations of five performance measures, including travel time, reliability of travel time, safety, emissions and fuel consumption.
Information regarding findings on specific ICM strategies can be found in the test corridor summary report titled, “Integrated Corridor Management Analysis, Modeling, and Simulation Results for the Test Corridor.” This report, and other useful resources, are available on the ICM Knowledgebase (www.its.dot.goc/icms/knowledgebase.htm).
Conclusions and Next Steps
Preliminary results of the AMS methodology applied to the test corridor demonstrated the following:
The test corridor modeling validated the ICM concept: Dynamically applying ICM strategies in combination across a corridor is shown to reduce congestion and improve the overall productivity of the transportation system.
The AMS methodology is able to analyze the individual and combination effects of ICM strategies under different operational conditions.
New analysis capabilities were successfully tested and produced intuitive results. These new capabilities include the analysis of: a) mode shift to transit, b) impacts of congestion pricing and c) impacts of traveler information.
The ICM AMS methodology offers the following benefits to corridor managers across the country:
Invest in the right strategies. The methodology offers corridor managers a predictive forecasting capability that they lack today to help determine which combinations of ICM strategies are likely to be most effective under different conditions.
Invest with confidence. AMS allows corridor managers to “see around the corner” and discover optimum combinations of strategies as well as conflicts or unintended consequences inherent in certain combinations of strategies that would otherwise be unknowable before implementation.
Improve the effectiveness/success of implementation. With AMS, corridor managers can understand in advance what questions to ask about their system and potential combinations of strategies to make any implementation more successful.
AMS provides a long-term capability to corridor managers to continually improve implementation of ICM strategies based on experience.
Starting in fall 2008, the USDOT will be working with the three selected pioneer sites (Dallas, Minneapolis and San Diego) to model and analyze the proposed ICM strategies documented in their ICM concepts of operation (the pioneer sites’ ICM concepts of operation documents are available through the ICM Knowledgebase at http://www.its.dot.gov/icms/knowledgebase.htm). The analysis will follow the approach defined in this article and will be tailored to the models, data and strategies available and to be implemented in each corridor. The analysis should be completed by summer 2009.
Vassili Alexiadis is a vice president with Cambridge Systematics Inc., and the principal investigator for the “ICM – Tools, Strategies and Deployment Support” project. Alexiadis is directing the analysis of ICM systems proposed by the stage 2 pioneer AMS sites, and the evaluation of expected benefits to be derived from implementing those ICM systems.
Brian Cronin serves as the RITA ITS joint program office manager for the ICM program. He is the Congestion Program coordinator for the ITS JPO and serves as technical representative for the Montgomery County, Md., and San Antonio, Texas, pioneer sites.
Steve Mortensen is a senior ITS engineer with the FTA Office of Research, Demonstration and Innovation. Mortensen is the technical representative for the Dallas, Texas, Oakland, Calif., and San Diego, Calif., pioneer sites.
Dale Thompson is a transportation research specialist in the Federal Highway Administration’s (FHWA) Office of Operations. He is also the technical representative for the Houston, Texas, Minneapolis, Minn., and Seattle, Wash., pioneer sites.
More Related Information:
Archived Article: Managing Congestion with Integrated Corridor Management