This graphic illustrates the ITS Deployment Analysis System (IDAS) logo.

Case Study 3:  Evaluation of Emissions Impacts of an Incident Management System in Hampton Roads, Virginia

Project Background | ITS Application | Project Goals and Objectives | Existing Agency Technical Capabilities
Additional Data, Technical Assistance, or Training Needs | Analysis Method and Assumptions | IDAS Analysis Results
Recommendations for the Project | Lessons Learned | Project Cost and Schedule
Future Usage of Data and/or Technical Approaches Developed | Contacts

Project Background

The Hampton Roads region is an agglomeration of municipalities located in Southeast Virginia along the southern shores of Chesapeake Bay's entrance to the Atlantic Ocean near the confluence of the James River (See Figure 1). Major cities in the region include Chesapeake, Hampton, Newport News, Norfolk, Portsmouth, and Virginia Beach. Together, these municipalities constitute the nation's 31st largest metropolitan area with a population of over 1.5 million residents in 2000.

Figure 1. Hampton Roads Region

This figure shows a map of the Hampton Roads Region.

The region plays a vital role in national security, as it is the home of numerous military installations. The Norfolk Naval Station is the world's largest and home to 78 naval vessels. Other military installations in the region include Langley Air Force Base and the U.S. Army's Transportation Center.

The area also serves as a major tourist destination. During the summer months, over 2.9 million visitors are estimated to flock to the oceanfront along Virginia Beach. Historic Williamsburg and Jamestown are located in the northwest section of the region.

The demand for travel in the region has increasingly exceeded the capacity of a transportation system that is geographically constrained by numerous bridge and tunnel water crossings. This has resulted in increasing congestion, particularly congestion due to non-recurring incidents on the regional roadways. This congestion has, in turn, contributed to increases in vehicle emissions in a region already facing growing concerns regarding air quality.

In response to these challenges, regional transportation officials have placed an increased focus on improving the operation of transportation facilities through the deployment of ITS technologies. The region's transportation managers, including the Hampton Roads Planning District Commission (HRPDC), have made the implementation and expansion of a regional incident management system a priority for the region.

HRPDC serves as the Metropolitan Planning Organization (MPO) for the Hampton Roads region and represents 16 jurisdictions. One of the duties of HRPDC is the development of the regional long-range transportation plan. During the preparation of this plan in late 1999, planners with HRPDC investigated methods for estimating the emissions benefits of their planned incident management systems to be included in the conformity determinations. The planners felt that it was logical that the incident management system, which was intended to reduce non-recurring congestion, would also have significant emissions benefits. Estimating the quantity of these impacts would prove to be a groundbreaking effort, as few documented results from other agencies' attempts to quantify emissions benefits of similar operational improvements could be obtained.

This case study discusses the HRPDC's efforts to use the ITS Deployment Analysis System (IDAS) software in the analysis and quantification of emissions benefits of their planned incident management system.

Top of Section | Top of Page

ITS Application

The Hampton Roads region has been successful in deploying a number of ITS improvements. The region's incident management system, deployed in conjunction with the Virginia Department of Transportation (VDOT), was initiated in 1993. The system began modestly with Freeway Incident Response being provided on 14 centerline miles of freeway. In 1997, an additional 26 miles of incident response coverage were added; and in 1998, the total coverage was increased to 60 centerline miles. In 1998, incident detection and verification capabilities were also added on 19 centerline miles through the deployment of in-pavement detectors and CCTV camera surveillance. The system is coordinated through the region's traffic management center known as the Hampton Roads Smart Traffic Center.

This graphic illustrates the Hampton Roads Smart Traffic Center logo.

At the completion of Phase III of the deployment project in 2004, the freeway incident management system will include:

In addition to these current projects, the system is anticipated to continue to expand so that by 2021 the system will include:

Figure 2 displays the planned coverage in the year 2021 and the various phases of deployment. The planned 325 miles of incident management coverage will be supplemented by variable message signs, arterial traffic management systems, and traveler information systems. For the purposes of this analysis, however, these additional types of deployments were not included.

Figure 2. Proposed Incident Management Coverage - 2021

This figure shows the proposed incident management coverage in 2021 for the region. It includes: existing incident detection, verification, response and clearance; existing incident response and clearance only with detection and verification in place by 2003; incident detection verification, response, and clearance in place by 2003; 2021 incident detection, verification, response and clearance; and 2021 incident detection and verification only.

Source: HRPDC.

Top of Section | Top of Page

Project Goals and Objectives

As the coverage of the system has expanded, the number of incidents responded to by the incident response team has increased - reaching over 35,000 incidents in 2000. As such, the program is generally perceived as a success by local officials and the public. Therefore, it was not the primary goal of this analysis to justify the current program through the comprehensive analysis of all the program's benefits. Instead, this analysis was focused only on identifying and quantifying the emissions benefits of the system.

A significant investment had been made in the incident management system, but to date, no attempt had been made to quantify the likely emissions reductions resulting from the system. Planners with HRPDC felt the system provided emissions benefits through the reduction in incident related congestion. The objective of this study was to quantify these emissions benefits. A particular focus was placed on nitrous oxide (NOx), as levels of these emissions were a concern in the region.1 It was the objective of this analysis to estimate the emissions reductions and include them as part of the conformity determination on the long-range transportation plan under development.

Oversight for conformity determination of the plan was provided by the Interagency Consultation Group (ICG), which included representatives of the Environmental Protection Agency (EPA), FHWA, and VDOT's Air Quality and Environmental Bureaus. It was the responsibility of HRPDC to present a logical justification for the quantity of emissions benefits for their ITS improvements that would be approved by the ICG.

Top of Section | Top of Page

Existing Agency Technical Capabilities

As the regional MPO, HRPDC maintains the regional travel demand model, based on the MinUTP software package, which is the standard tool for evaluating transportation system improvements in the region. HRPDC has several staff that are responsible for the model application and are familiar with its capabilities and limitations.

Additionally, several HRPDC staff had recently completed a workshop on the use and application of the IDAS software tool. This training was jointly sponsored by HRPDC and VDOT several months prior to the conduct of the study. The IDAS analysis of the incident management system was internally performed by HRPDC staff, with oversight and comment provided by the ICG.

It is important to note that although HRPDC was responsible for conducting the travel demand forecasting for the analysis of the long-range transportation plan, they did not directly generate regional emissions estimates at the time. Emissions were estimated by passing travel demand model results to an emissions expert retained by VDOT. The travel demand model data was post-processed before being incorporated in the emissions estimating software to produce the final quantification of emissions.

Top of Section | Top of Page

Additional Data, Technical Assistance, or Training Needs

Early in the analysis process, HRPDC staff evaluated the methodology and default assumptions used by IDAS to better understand the analysis process. Supplementary data collection was initiated to further research emissions impacts of incident management systems observed in other regions to provide opportunities for customization of the IDAS methodology to the local conditions.

The ITS Library within the IDAS software and the User's Manual were first studied to identify data sources used in developing the IDAS methodology. The reference citations were used to find copies of the actual evaluation reports summarizing the experience from other regions related to emissions impacts of previously deployed incident management systems. Studies of these reports, however, proved unsuccessful in identifying more in-depth emissions information that could be used to customize the default figures in the IDAS model to better calibrate the methodology to the local conditions and validate the results.

Additional literature reviews were then conducted to uncover any emissions impact information related to incident management systems that may have been omitted from the IDAS ITS Library or released more recently than the software. Table 1 summarizes the findings identified by the HRPDC researchers related to the impacts of incident management systems.

Table 1. Benefits in Delay, Fuel Consumption, and Emissions for 
Incident Management Systems in Different Locations

Location

 Previous Incident Duration Time (Minutes) Improved Incident Duration Time (Minutes) Incident Clearance Time Reduction (Percent) Reduced Fuel Consumption Reduced Emissions
Hampton Roads     40    
Hampton Roads 
I-64 MIS
(Completed 6/99)		     25(1)    
Brooklyn, NY 90 31 66    
North Virginia      48(1)    
Pittsburgh, PA 34.0 25.7 24 38% 38% (HC)
Seattle, WA 173.5 152.9 12    
Baltimore, MD 68.2 44.7 35 5.85 million 
gallons yearly		 19 kg/yr (HC)
829 kg/yr (CO)
153 kg/yr (NOx)
Atlanta, GA 64 41 23    
Boston, MA     45    
San Francisco, CA         32 kg/day (HC) 322 kg/day (CO)
798 kg/day (NOx)
Houston, TX         91 kg/day (HC)
San Antonio, TX     20 2,600 gallons per major incident  
Detroit, MI       42%(1)  
Toronto, ON 86 30 65    

(1) These delay reductions are study estimates. All other delay reductions are the result of completed projects.

Source: HRPDC.

Although a number of evaluations of incident management systems were identified, the researchers were frustrated to find little information related specifically to emissions issues. Many evaluations had identified the reduction of incident duration attributable to incident management systems, but few studies had quantified the resulting reduction in emissions related to the easing of incident congestion. Additionally, much of the limited information that was available was presented in a format that had little use outside of the particular region where the data was collected. HRPDC realized that few documented studies of the emissions impacts of incident management systems were available to provide methodological guidance.

Top of Section | Top of Page

Analysis Method and Assumptions

The first step in the IDAS analysis of the emissions impacts of the incident management system in the Hampton Roads region was to identify the alternatives for analysis and the general structure of the evaluation. Due to the focused nature of the study (only emissions impacts), time constraints, and the experimental nature of the analysis, only three options were initially selected for analysis. These analysis options included:

  1. Control Alternative - A representation of the 2021 model network without any incident management related improvements;
  2. Run 1 - A representation of the 2021 model network with only those incident management improvements that are currently in operation or are planned for deployment in the near term (by October 2003); and
  3. Run 2 - A representation of the 2021 model network with all existing and near-term deployments included in Run 1, plus additional incident management coverage identified in the long-range plan for deployment prior to 2021.

These alternatives were selected to specifically identify the emissions levels in future years without the incident management system, with the current system, and with the planned system. By comparing the various alternatives, the incremental emissions benefits of the incident management system could, therefore, be identified.

A baseline future forecast for the year 2021 was selected from the regional MinUTP travel demand model to represent the travel demand and network characteristics generally consistent with the time horizon of the long-range plan. A daily model was also selected to be consistent with the operating plans for the incident management system.

Outputs from MinUTP analysis of the 2021 conditions were imported into the IDAS software to create the control alternative (no incident management). This control alternative was then run in the IDAS software and the network performance statistics such as vehicle miles of travel (VMT), and vehicle hours of travel (VHT) were compared with similar metrics from the regional travel demand model to validate the results. The IDAS-generated metrics were found to be generally consistent with the MinUTP-generated performance measures.

The two incident management options (Run 1 and Run 2) were then created by adding the appropriate incident management components to the appropriate roadways. The IDAS ITS components deployed included:

These two components were used to represent the various levels of incident management intensity on the various roadways, which included freeways, HOV facilities, and a limited number of major arterials.

The Run 1 Option was developed first by deploying the appropriate roadways with existing or near-term incident management deployments. Once complete, this option was copied as the Run 2 Option and additional incident management deployments added to represent the proposed build out of the system in 2021.

During the creation of the analysis options, HRPDC investigated several options for modifying the default assumptions used in IDAS related to the emissions impacts of incident management systems. Table 2 presents the default incident clearance and emissions impacts in IDAS.

Table 2. IDAS Default Impact Assumptions

Type of Incident Reduction in Incident Duration on Affected Links Reduction in Emissions 
on Affected Links
Implementation of incident detection, verification, response, and clearance 40% 42%
Implementation of incident detection and verification only 9% 15%

The default emissions impacts represent the amount in which the IDAS software modifies the standard emissions rate for links where incident management components are deployed. HRDPC was not 100 percent comfortable with the assumption that all categories of emissions would be impacted similarly, so additional research was conducted to learn how the impact might vary among the emissions categories. Data on the quantifiable impacts observed in other regions proved difficult to find, however, so the default impacts were not customized for this analysis.

The IDAS analysis software is targeted towards generating estimates of a wide range of performance measures (e.g., travel time, accidents, fuel use, etc.) for various ITS components and producing comparisons of the benefits and costs on an annualized basis. However, the analysis conducted by HRPDC solely focused on the daily incremental emissions impacts. Therefore, many of the default values and assumptions typically used in a comprehensive IDAS analysis, such as annualization factors and the dollar values of impacts, were not applicable to this study and could be ignored.

Top of Section | Top of Page

IDAS Analysis Results

The three different options were run through the IDAS analysis and the results were compared. The results showed a substantial decrease in the daily emissions for hydrocarbons (HC) and NOx in the region for the two options containing incident management improvement when compared with the control alternative. Table 3 presents the emissions estimated for the three options segmented by various facility types.

Table 3. IDAS Comparison of Emission Reductions

Functional Class Control Alternative HC (tons/day)
Run 1		 HC (tons/day)
Run 2		 Control Alternative NOx (tons/day)
Run 1		 NOx (tons/day)
Run 2
Centroids 5.618 5.618 5.618 6.707 6.707 6.707
Collector 3.623 3.623 3.623 4.570 4.570 4.570
Freeway 14.160 10.275 9.442 25.655 19.193 17.584
HOV 3.076 2.610 1.784 4.576 3.834 2.654
Major Arterials 10.630 10.576 10.458 14.315 14.260 14.071
Minor Arterials 11.144 11.144 11.144 14.619 14.619 14.619
Ramp 0.275 0.275 0.275 0.464 0.464 0.464
Total 48.526 44.121 42.344 70.906 63.647 60.669
Difference from Total   -4.405 -6.182   -7.259 -10.237
Percent Difference   -9.1% -12.7%   -10.2% -14.4%

As expected, the option representing the proposed full build out of the future incident management system (Run 2) was estimated to have even greater reductions than the option only representing the current and near-term deployments (Run 1). Since the Run 2 option represents a greater incident management coverage on the regional roadway system, it is logical that the emissions benefits are more substantial given the analysis methodology.

HRPDC was pleased that the analysis showed a reduction in emissions resulting from the deployment of incident management systems; however, there were some concerns that the magnitude of the benefits (nine to 14 percent reductions) was significantly greater than had been previously estimated for other more traditional types of transportation improvements.

In an attempt to validate the IDAS results, sketch planning techniques were applied to generate a second set of estimates of emissions impacts using findings of impacts from other regions. An evaluation of incident management systems in the San Francisco Bay Area was referenced (see Table 1), which identified an emissions reduction on a per incident basis attributable to improved incident management systems. An estimate of the number of incidents occurring within the future coverage of the Hampton Roads incident management system was also developed. Multiplying these factors suggested that the incident management system would result in a reduction in NOx emissions of 6.8 tons per day and a reduction of HC emissions of 2.7 tons per day. The results of this simplified sketch analysis were 38 percent lower for HC and 6 percent lower for NOx than the IDAS analysis results.

Top of Section | Top of Page

Recommendations for the Project

HRPDC presented the results of their analysis to the ICG to gain approval of their estimates of emissions benefits for their incident management system. HRPDC worked with the ICG to justify the reasonableness of the results and include these reductions in the conformity determination. Since this analysis represented the first time an attempt had been made to estimate emissions benefits for these types of incident management systems in the Hampton Roads region, intense scrutiny was placed on HRPDC's proposal and several iterations of negotiations were conducted in an attempt to achieve consensus.

Ultimately, the ICG chose not to accept the proposal, citing three general concerns with the analysis approach:

  1. Emissions impacts in the region were not historically estimated directly from outputs of the MinUTP travel demand model. A post-processor was typically applied to the model outputs before the emissions analysis was conducted. The IDAS analysis used outputs directly from the model and was, therefore, inconsistent with other regional emissions analysis.
  2. The identical impact applied by IDAS to all emission classes (HC, NOx, CO) was not perceived as being sufficiently sensitive to the many factors that impact these emissions (i.e., the emissions impacts would be expected to vary more greatly across the emissions classes due to a change in incident duration caused by incident management systems). Attempts by HRPDC to identify additional observed impacts from other regions further supporting this methodology or providing sufficient justification to modify the impacts were, unfortunately, unsuccessful.
  3. Direct changes in roadway volumes and speeds resulting from the deployment of incident management components are not calculated in IDAS, since travel demand models typically do not consider non-recurring delay (caused by incidents). This limitation concerned the ICG as the reductions in emissions could not be compared and validated with predicted changes in these performance measures.

Based on these concerns and the need to complete the analysis within a constrained time period, a second analysis was conducted - this time employing a more traditional approach using an analysis methodology that had been recently been developed to analyze a proposed light-rail system in the region. The emissions benefits generated using this traditional approach were accepted by the ICG for inclusion in the conformity determination. However, the benefits that were ultimately estimated for the incident management system were less than five percent of the magnitude of those originally proposed.

Top of Section | Top of Page

Lessons Learned

Lessons learned in the application of the IDAS tool to estimate emissions impacts associated with incident management systems include:

  1. HRPDC discovered that there is a great interest in this new avenue of estimating the emissions impacts of ITS improvements. Their analysis has generated numerous inquiries from other agencies regarding their methodology.
  2. The IDAS software provides an innovative tool for estimating these impacts with the limitation that it is based on previous evaluation results. In situations where few real-world results are available - as in the case of emissions impacts of incident management systems - the analysis may not be sensitive to specific impacts. Supplemental data may be beneficial to enhance the IDAS default data.
  3. The estimation of emissions impacts related to operational improvements is an emerging field of study. In many cases, there may be little previous analysis or results to serve as precedent.
  4. The lack of quantifiable results from other regions makes the presentation of findings difficult, as few comparisons are available to help others understand the impacts.
  5. The introduction of a new analysis procedure into a consensus-driven policy environment can be a difficult process and often requires a significant time period for validation and full acceptance.
  6. A thorough review of the assumptions and methodologies used in IDAS is extremely valuable in explaining and negotiating the use of IDAS with others.

Top of Section | Top of Page

Project Cost and Schedule

The analysis of the potential emissions impacts of Hampton Roads' incident management system was completed under a constrained schedule of approximately three months from October to December 1999.

The work was largely completed internal to HRPDC with oversight and comment provided by the ICG. HRPDC estimated that two months of staff time (full time equivalents) were required to complete the analysis. Significant tasks included conducting the background research, developing the IDAS alternatives, running the analysis and interpreting the results, developing presentations and reports, and negotiating findings.

Top of Section | Top of Page

Future Usage of Data and/or Technical Approaches Developed

Although HRPDC was unsuccessful in using this innovative approach for estimating the emissions benefits of their incident management system, the agency has continued to use IDAS in the analysis of subsequent ITS deployments.

HRPDC is currently conducting a study of a large-scale arterial traffic management system (ATMS), which will include the coordination of approximately 200 signal systems and the deployment of numerous traffic surveillance cameras and variable message signs. HRPDC is planning to use the IDAS software to evaluate this ATMS deployment. The software is likewise being considered for an upcoming analysis of the benefits of a planned traveler information system in the region.

This graphic illustrates the ITS Deployment Analysis System (IDAS) logo.

This is one of four case studies describing the application of the ITS Deployment Analysis System (IDAS) software program. These case studies illustrate innovative approaches in conducting ITS planning and program development.

Top of Section | Top of Page

Contacts

This work was performed under contract with:

This graphic illustrates the U.S. Department of Transportation Federal Highway Administration logo.

Federal Highway Administration
Planning and Environment
Office of Metropolitan Planning and Programs
400 7th Street, S.W.
Washington, D.C. 20590

The Case Study was prepared by:

This graphic illustrates the Cambridge Systematics, Inc. logo.

Cambridge Systematics, Inc.
1300 Clay St., Suite 1010
Oakland, CA 94611
Telephone: (510) 873-8700
Fax: (510) 873-8701
Web: http://www.camsys.com

For further information, please contact:

This graphic illustrates the Hampton Roads logo.

Camelia Ravanbakht, Ph.D., or
Keith Nichols
Hampton Roads Planning District Commission
723 Woodlake Drive
Chesapeake, Virginia 23320
Telephone: (757) 420-8300
Fax: (757) 523-4881
E-mail: cravan@hrdpc.org
knichols@hrpdc.org
Web: http://www.hrpdc.org

Top of Section | Top of Page