Model Minimum Inventory of Roadway Elements—MMIRE
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DEFINITION OF AND RATIONALE FOR MMIRE
The concept of MMIRE includes a listing of roadway inventory and traffic elements critical to safety management and the proposed coding for each of these critical elements. No such listing now exists. These high-priority inventory and traffic variables are linked to and then used with crash data elements in making decisions concerning implementing safety treatments and in developing knowledge about the safety effects of treatments, roadway designs and traffic operations (e.g., signal phasing). While crash data alone can be used by a State or local roadway safety agency to answer some questions (e.g., the identification of locations for treatment), they are not sufficient in many cases. Without sound inventory and traffic data, the safety professional’s ability to make critical programmatic decisions is greatly reduced. Examples where sound inventory and traffic data are needed include:
- Identification of locations that would benefit most from safety treatments. Safety treatment dollars are limited, and should be used on locations that will most benefit from treatments. While these problem-location-identification decisions can, and often are, made on the basis of crash frequency alone, such a process does not allow the safety engineer to identify those sites that are most likely to benefit from safety treatment. To meet these criteria, the site must not just have the highest frequency of crashes, but have an elevated crash risk when compared to similar sites. More specifically, the identification of high priority intersections by crash frequency alone would lead to a listing including primarily (or only) intersections with high traffic volumes. To identify both those high and lower volume intersections that will benefit most from treatment, one needs to identify those that have higher crash frequencies or rates when compared to similar intersections based on intersection characteristics (e.g., entering volumes on all legs, number of approach lanes, signalized versus unsignalized, presence of left turn lanes and signal phases). Without an inventory file that includes both the locations of all intersections within a system and characteristics of each of these intersection legs, one cannot conduct such analyses since the needed group of similar intersections cannot be identified. Even if the safety engineer decided not to use such a robust problem-identification process, but did want to compare intersections on the basis of crash rates (i.e., crashes per entering vehicle) rather than just crash frequencies, they could not even complete this less-robust process without approach volumes from both crossing roadways—data that are not available in most State and local agencies. This is particularly true when the crossing roadway is not a State-system road (i.e., is a county or local road).
Development of knowledge about roadway treatment effects. As has been documented in various publications, including the NCHRP “Series 500” Implementation Guides for the AASHTO Strategic Highway Safety Plan efforts1, accurate estimates of the treatment effect (i.e., accident modification factors—AMFs) of many commonly used safety treatments are unknown or are based on poor data and research methods. The safety professional and the safety research community are continually trying to evaluate critical treatments. However, conducting a sound evaluation requires much more than just comparing the before and after crash experience on the treated site. Current state-of-the-practice methods require the use of a reference group of similar untreated sites. Even less than optimum evaluations require a comparison group of similar sites. Without a good inventory system, these groups cannot be defined.
1 See http://safety.transportation.org/guides.aspx.
Use of the new generation of safety management tools. For the past few years, FHWA and AASHTO have been developing a set of new cutting-edge analytical tools and resources to aid the roadway designer and the safety engineer in their design, operations, and treatment decisions. These include FHWA’s Interactive Highway Safety Design Model (IHSDM)2 and SafetyAnalyst3, AASHTO’s Series 500 Data and Analysis Guide(3), and the Highway Safety Manual4. IHSDM is a CAD-based system, comprised of multiple modules that allows the user to predict the expected safety performance of roadway design and redesign alternatives. Currently, only the rural two-lane version has been developed. However, similar tools are being developed for both suburban and urban arterials and rural multilane roadways. These tools will be included in the first edition of the Highway Safety Manual, a compilation of safety knowledge and safety analysis tools being developed by the Transportation Research Board with funding from AASHTO. FHWA’s Safety Analyst is a package of safety management tools that will assist the user in efforts ranging from screening the roadway network to identify sites for improvement to analyzing the sites and choosing the most appropriate treatments, and evaluating the effects of the treatment. This set of tools will be completed and released in 2008. AASHTO’s Series 500 Guides5 are compilations of current knowledge about low-cost safety treatments aimed at reducing specific crash types (e.g., run-off- road crashes, unsignalized intersection crashes, crashes involving drinking drivers) The final Guide in this series, A Guide for Addressing Safety Data and Analysis in Developing Emphasis Area Plans, contains analytical techniques to assist the safety engineer and other safety professionals in planning how to reduce each of 22 crash types covered in the Series 500 Guides.(3) What is important to note is that all of these new tools require good inventory and traffic flow data for use. Without such data, the safety professional cannot take full advantage of the safety decision tools.
- Development of knowledge about roadway elements and designs that increase or decrease crash risk. While the study of changes in crash risk or crash injury risk due to changes in roadway elements is usually conducted by researchers rather than safety engineers, the knowledge gained from such analyses leads to improved design standards and operating procedures—outcomes that do affect how the engineers do their jobs. Such studies cannot be completed without detailed information on the roadway characteristics and traffic flows on roadway segments with and without crashes. At this point, very little is known about the true effects on crash risk of such elements as curvature or grade on multilane rural and suburban roads, driveway density, access control policies, and many others. The lack of this knowledge affects sound safety decisions, and this lack results from the fact that complete inventory data that can be linked with crashes is unavailable in most States and local jurisdictions.
Almost all State highway agencies and some local transportation agencies currently have roadway inventory and traffic flow data in their files. These data were often the result of expanding data collection efforts required by FHWA’s Highway Performance Monitoring System (HPMS)6 for sample sections of roadways to the full State system of roadways. Although HPMS has been the driving force behind the collection of roadway inventory and traffic data by State departments of transportation (DOTs), it cannot be considered the model for safety inventory data because:
- It is based on the need for data on highway condition, performance, use, and operating characteristics of highways and is not driven by safety considerations.
- It requires complete inventory data of only basic (universe) variables, while other variables are captured only for certain sample sections of roadways (e.g., lane width, shoulder width).
- The format of certain variables, even those captured on only sample sections, is not conducive to safety use (e.g., horizontal curvature data specifies the total curve length within the sample for certain curve classes, but not the location of the individual curves within the section).
While the data elements in many States’ current inventory systems are an expansion of the HPMS sample elements to all roads in the full State system and capture such variables as lane width, shoulder width and type, speed limit, and other cross sectional variables, very few State systems capture curvature or grade data, intersection inventory data, roadside inventory data, or other data elements critical to safety.
FHWA and AASHTO initiated efforts to develop a “Draft Model Highway Data Dictionary” for subsequent use in the development of the Transportation Safety Information Management System (TSIMS). The data dictionary is viewed as a starting point for developing a comprehensive, uniform set of roadway characteristic data attributes.7 However, it cannot be considered a model for a sound safety inventory database due to some limitations in the explanatory descriptions of the items, missing critical safety elements (e.g., clear-zone width), and in the classification of the priority of the elements.
|7For more information, refer to http://tsims.aashtoware.org/ContentManagement/PageBody.asp?PAGE_ID=3&CONTENT_ID= 23.|
In summary, there is no current listing of critical safety-related inventory and traffic data elements––no MMIRE. In contrast, the U.S. Department of Transportation’s (USDOT’s) National Highway Traffic Safety Administration, working with the Governors’ Highway Safety Association and safety data advocates across the Nation, have developed a listing of and definitions for critical crash data elements over the past decade—the Model Minimum Uniform Crash Criteria (MMUCC).8 Although not an official national standard, this data element guideline has become the de facto standard that is used by almost all State agencies when they reexamine and modify their crash report form. What is needed is a companion for MMUCC— thus the birth of MMIRE.
Three final background points are noted concerning what MMIRE is envisioned to be. First, since the development of the concept in the Council and Harkey White Paper,(1) it has been strongly recommended that like MMUCC (but unlike HPMS), the collection of MMIRE elements will be voluntary rather than mandatory. Like MMUCC, MMIRE is envisioned as a tool to be used by State and local agencies in their safety data improvement efforts. The only MMIRE-related requirement currently being discussed concerns States applying for Federal safety-data improvement grants under Section 2006(e)—“State Traffic Safety Information System Improvements” in the new Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users (SAFETEA-LU) legislation. The language in that section indicates that the USDOT Secretary will define model data elements for use in safety analyses, and that States applying for the grants will need to certify that they have adopted the model elements or will use the grant funds to work toward adopting and using them. While not known at this time, it is anticipated that elements in MMIRE, like MMUCC, ultimately will be included in the listing of these model data elements.
Second, it also has been recommended strongly from inception that MMIRE efforts be continually reviewed by the data collectors and users—the State and local DOTs. The White Paper(1) suggested that the listing of proposed elements be vetted by review committees of State and local agency safety and inventory engineers and users. The vetting effort should include strong participation from appropriate individuals and committees in AASHTO, because their endorsement and support will be critical to gaining State agency acceptance. As described below, this vetting process has begun with the convening of State and local data experts in a MMIRE review workshop. It is anticipated that FHWA will continue that vetting process in further reviews.
Third, the choice of elements considered for MMIRE and the priority assigned are based on the need for that element in safety efforts. There are clearly other variables collected in HPMS and other files that are used for nonsafety analyses (e.g., pavement depth). These may well be key variables for other purposes, but were not included (or recommended) in MMIRE unless they were felt to be important for safety uses.
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