MIRE MIS

MIRE MANAGEMENT INFORMATION SYSTEM

FEASIBILITY OF A MODEL INVENTORY 

OF ROADWAY ELEMENTS (MIRE) 

MANAGEMENT INFORMATION SYSTEM

Quality data are the foundation for making sound decisions 

regarding the design, operation, and safety of roadways. Safety 

programs such as the Federal Highway Administration’s (FHWA’s) 

Highway Safety Improvement Program (HSIP) and more advanced 

analysis tools such as the Highway Safety Manual (HSM) (1) 

and Safety Analyst (2) rely on crash, roadway, and traffic data 

to conduct effective analyses for problem identification and 

evaluation. Robust data can help agencies improve safety by 

making more effective and efficient use of safety funds, which will 

help save lives and reduce serious injuries.

National leadership recognizes the importance of a robust data 

system for safety. The current transportation legislation, Moving 

Ahead for Progress in the 21st Century (MAP-21), requires States to 

have a safety data system in place to perform analyses supporting 

the strategic and performance-based goals in the Strategic 

Highway Safety Plan (SHSP) and HSIP [23 U.S.C. 148 (c) (2)] (3). 

MAP -21 defines safety data as crash, roadway, and traffic data 

on a public road [23 U.S.C. 148 (a) (9)] (3). The Model Inventory 

of Roadway Elements (MIRE) provides guidance to transportation 

agencies on collecting safety-related roadway and traffic data (4).

The FHWA developed MIRE as a recommended listing and 

data dictionary of roadway and traffic data elements critical 

to supporting highway safety management programs and 

tools. MIRE consists of 202 roadway and traffic data elements 

grouped under three major categories: 1) roadway segments, 

2) roadway alignments, and 3) roadway junctions. The next 

step in the effort to expand the use of MIRE involved examining 

the feasibility of collecting and integrating these data elements 

FHWA SAFETY 

PROGRAM

http://safety.fhwa.dot.gov

FHWA-SA-13-020

U.S. Department of Transportation

Federal Highway Administration
into a management information system (MIS). 

It is envisioned that States would ultimately 

integrate roadway data with crash data and 

other safety-related data for a complete safety 

information system.

The Model Inventory of Roadway Elements 

(MIRE) is a recommended listing and data 

dictionary of roadway and traffic data 

elements to support safety. 

2

OBJECTIVES

The objective of the MIRE MIS project was to test 

the feasibility of converting the MIRE listing into 

an MIS. The project team conducted this effort 

through the exploration, development, and 

documentation of:

› Mechanisms for data collection.

› Processes for data handling and storage.

› Details of data file structure.

› Methods to assure the integration of MIRE data 

with crash data and other data types.

› Performance measures to assess and assure 

MIRE data quality and MIS performance.

The project team undertook several tasks to 

achieve these objectives. This report provides an 

overview of these tasks, highlighting the results 

and lessons learned that are most applicable to 

agencies wanting to improve their roadway and 

traffic data to support their safety programs.

BACKGROUND RESEARCH

The project team began by assessing States’ and 

local agencies’ current data systems, and 

problem identification and prioritization 

processes on both State-owned and locallyowned roads. Establishing this information as a 

baseline provided an understanding of the 

challenges States face in integrating various 

types of data (crash, roadway, traffic data, etc.). 

The project team gathered information during 

site visits with several State and local 

departments of transportation (DOTs), and 

included the status of the agencies’ data (crash 

roadway, and traffic); how agencies utilize those 

data for their safety programs (network 

screening, project prioritization, etc.); the 

structure of their database files; and any 

innovative data collection methodologies they 

employ.

In addition to 

obtaining such 

information on 

site visits, the 

project team 

conducted 

additional 

research to 

further explore 

MIRE data 

collection 

methodologies. 

The MIRE Element 

Collection 

Mechanisms and Gap Analysis report provides 

an assessment of State highway agencies’ 

roadway inventory data collection practices, 

documentation of current and emerging 

MIRE element data collection mechanisms, 
Feasibility of a MIRE Management Information System 3

identification of gaps in current practices, 

and recommendations for filling those gaps to 

support the MIRE MIS effort (5).

The MIRE Element Collection Mechanisms 

and Gap Analysis report provides 

methodologies and recommendations 

that can help States determine how best 

to collect additional or improved roadway 

data to implement a roadway inventory 

system, such as a safety MIS, to help 

support their safety programs through 

data-driven decision-making.

DATA COLLECTION

Collecting additional roadway safety data can 

be a large undertaking. Based on the results of 

this effort, the research team developed several 

recommendations to help States implement a 

MIRE MIS. States should consider using other 

available information systems as sources of data. 

Integrating the available data systems and data 

needs within the agency will help minimize the 

data collection and processing efforts of various 

internal departments. States should also 

standardize data collection methods to ensure 

quality and simplify transfer between information 

systems. While multiple technologies are 

available to assist States in data collection, 

public and private sectors should explore the 

development of automated techniques for 

extracting inventory feature data from advanced 

collection techniques into a usable database 

format. These steps can help States develop the 

MIRE into a safety MIS to help support their safety 

programs through data-driven decision-making. 

The project 

team further 

explored 

mechanisms 

for collecting 

MIRE data 

through three 

major tasks: 

1) a pilot data collection effort where MIRE data 

were collected in two States; 2) a white paper 

that explores the use of a “collective information” 

approach for obtaining transportation safety 

data; and, 3) development of a MIRE data 

collection guidebook. The following sections 

provide more details on each of these efforts.

MIRE Pilot Data Collection

The project team conducted a MIRE pilot data 

collection effort to test the feasibility of collecting 

MIRE data for two lead agencies, New Hampshire 

and Washington State. Both pilot projects relied 

heavily on the use of Geographic Information 

Systems (GIS) to collect, analyze, and store MIRE 

data. Many transportation agencies already 

collect and store roadway attributes within a GIS. 

Often the data structure is designed for a specific 

purpose, which may make it difficult for all 

departments within an agency to use the data.

The MIRE Pilot data collection effort 

demonstrated the feasibility of collecting 

MIRE data elements. The methodologies 

and lessons learned can assist State and 

local transportation agencies collect and 

maintain MIRE data.

The pilot projects 

utilized existing 

roadway data from 

multiple sources, 

supplemented 

by manual data 

collection efforts to 

collect additional 

MIRE data for 

use in building 

a statewide 

intersection 

inventory in 

both states. The MIRE MIS Lead Agency Data 

Collection Report documents the methods used 

to examine existing roadway data within an 

agency, to collect additional MIRE data, and to 
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develop an intersection inventory, as well as the 

data collection tools used, challenges faced, 

and lessons learned (6).

The results of this effort were:

› Determination of the level of effort 

and resources needed to develop an 

intersection inventory.

› Development of an intersection inventory for 

over 10,000 intersections in New Hampshire 

and 15,000 intersections in Washington State.

› Development of automated GIS tools for 

importing existing GIS data.

› Identification of readily available sources of 

information and imagery that aid in developing 

and verifying MIRE data elements.

› Development of multiple data collection 

interfaces and toolbars based on a GIS 

platform that aid in the data collection and 

execution of the data models.

The lessons learned from this effort were:

› Develop a detailed work plan that outlines 

a clear vision and approach for the 

data collection.

› Maintain constant contact/feedback between 

the agency and the data collection team/ 

contractor. The agency should have one 

dedicated champion/point of contact for the 

data collection effort.

› MIRE is intended as guidance, and 

accommodating individual State’s 

existing information systems and needs 

requires flexibility.

› A common Linear Referencing System (LRS) 

will simplify the process of integrating existing 

data sources.

› Use of existing and customized GIS tools is 

a cost-effective approach to building an 

intersection inventory.

› Many of the basic intersection elements an 

agency would be interested in can be derived 

from readily available sources.

Collective Data White Paper

One of the biggest challenges in using an MIS for 

highway safety is the lack of roadway inventory 

data. This is particularly true for local roads. Most 

transportation agencies are resourceconstrained and do not have the staff or 

available funds to collect and maintain this 

information. However, a few transportation 

agencies have discovered that smart phones 

and other mobile devices may present an 

opportunity to cost-effectively collect data. The 

prevalence of these GPS-enabled mobile 

devices present a feasible option for acquiring 

roadway inventory data through crowdsourcing 

of collective information. Crowdsourcing is the 

process of assembling data or collecting 

information on a subject using a large, disperse, 

and potentially uncontrolled group of people. 

The Exploration 

of the 

Application 

of Collective 

Information to 

Transportation 

Data for Safety 

White Paper

explores the 

application 

of collective 

information in 

transportation 

data, particularly 

in the collection and management of MIRE data 

(7). Transportation agencies could use any 

number of individuals to collect this information, 

such as contractors, maintenance crews, 

volunteer organizations, and the general public.

The collective information white paper 

is a starting point for discussions on 

the application and feasibility of using 

collective information for transportation 

safety data. It also identifies potential 

next steps and future applications of 

this concept.
Feasibility of a MIRE Management Information System 5

The results of the effort to develop a MIRE 

MIS structure can help other agencies 

interested in developing a MIS for their 

safety data using readily available tools 

and resources.

The project team first developed a conceptual 

model of a potential MIRE MIS, and then 

expanded on that by developing a logical 

database model based on the MIRE Version 1.0 

specification. The project team then expanded 

the structure to incorporate supplemental 
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The Development of a Structure for a MIRE 

Management Information System report 

documents the effort, including details on the 

structure, obstacles, and lessons learned (9).

PERFORMANCE MEASURES

Performance measures are tools for measuring 

data quality and establishing goals for data 

improvement. The primary quality characteristics 

for safety data include:

› Timeliness

› Accuracy

› Completeness

› Uniformity

› Integration

› Accessibility

The Performance 

Measures for 

Roadway Inventory 

Data report 

documents the 

result of an effort 

to build upon a 

previous publication 

by the National 

Highway Traffic 

Safety Administration 

(NHTSA), the Model 

Performance 

Measures for State Traffic Records Systems (10, 

11) focusing on expanding the measures for 

roadway data. The Performance Measures for 

Roadway Inventory Data report also provides 

suggestions for data-related business practices 

that can lead to improvements in roadway data.

The results of the FHWA performance 

measure effort provide data managers 

and collectors with refined techniques for 

assessing and improving the quality of the 

roadway and traffic data inventory data 

they collect and maintain.

datasets mentioned in MIRE Version 1.0 that are 

not part of the 202 MIRE element listing. Data 

provided by one of the Lead Agency States, New 

Hampshire, was then imported into the system 

along with data from the MIRE Pilot Data 

Collection effort to create a working MIS.

The development 

of the prototype 

helped identify 

several key 

challenges that 

a State will need 

to address in the 

implementation of 

a safety MIS. The 

project team also 

developed several 

implementation 

scenarios to help agencies that are considering 

implementation of a safety MIS.

The results of this effort were:

› Development of a logical database model 

based on the MIRE 1.0 specification.

› Development of a prototype MIS for one of the 

Lead Agency States.

› Identification of lessons learned and 

implications for further development 

and implementation.

The lessons learned from this effort were:

› Data in the systems need to be of a high 

quality for the MIS to be most functional.

› The ability to correlate data from disparate 

systems to the relevant roadway elements is a 

critical success factor.

› Cooperation of the different organizations 

is essential.

› Development of a safety MIS is feasible with 

tools and resources readily available to most 

agencies agencies.
Feasibility of a MIRE Management Information System 7

SUMMARY

Integrating quality roadway and traffic data 

with crash data can help agencies make better 

decisions and more effective use of limited funds 

to improve safety, and meet Federal Legislative 

requirements. The MIRE MIS effort provides 

lessons on how to collect, integrate, manage, 

and measure data for improved safety decisionmaking.

Better data help lead to better decisions, 

which ultimately can save lives!

Project Outcomes and Products

The MIRE MIS effort yielded several products 

and reports that will be valuable in helping 

practitioners improve their roadway data 

to support a data-driven safety program. 

These include:

Data Collection:

› MIRE Element Collection Mechanisms and 

Gap Analysis report.

› MIRE MIS Lead Agency Data Collection report.

› Exploration of the Application of Collective 

Information to Transportation Data for Safety 

White Paper.

› MIRE Data Collection Guidebook.

Structure of the MIS:

› Development of a Structure for a MIRE 

Management Information System report.

Performance Measures:

› Performance Measures for Roadway Inventory 

Data report.

These documents can be found at 

http://safety.fhwa.dot.gov/rsdp.
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REFERENCES

1. The Highway Safety Manual. Transportation 

Research Board, URL: 

http://www.highwaysafetymanual.org/.

2. Safety Analyst. American Association of State 

Highway and Safety Officials, Washington, 

DC, 2013. URL: http://www.safetyanalyst.org/.

3. MAP-21 - Moving Ahead for Progress in the 

21st Century: Guidance on State Safety Data 

Systems. Federal Highway Administration, 

Washington, DC, December 2012. URL: 

http://www.fhwa.dot.gov/map21/guidance/

guidesafetydata.cfm.

4. Lefler, Nancy; Forrest Council; David 

Harkey; Daniel Carter; Hugh McGee; and 

Michael Daul. Model Inventory of Roadway 

Elements—MIRE, Version 1.0. FHWAHRT-10-048, Federal Highway Administration, 

Washington, DC, October 2010. URL: 

http://safety.fhwa.dot.gov/tools/data_tools/

mirereport/mirereport.pdf.

5. Mallela, Jagannath; Suri Sadasivam; and 

Nancy Lefler. MIRE Element Collection 

Mechanisms and Gap Analysis. FHWASA-11-49, Federal Highway Administration, 

Washington, DC, September 2012.

6. Fiedler, Rebecca; Nancy Lefler; Jagannath 

Mallela; Dale Abbott; David Smelser; and 

Rachel Becker. MIRE MIS Lead Agency Data 

Collection Report. FHWA-SA-13-008, Federal 

Highway Administration, Washington, DC, 

February 2013.

7. Eccles, Kim; Greg Bosworth; and Nancy Lefler. 

Exploration of the Application of Collective 

Information to Transportation Data for 

Safety White Paper. FHWA-SA-13-006, Federal 

Highway Administration, Washington, DC, 

January 2013.

8. Mallela, Jag; Nancy Lefler; and Hugh McGee. 

MIRE Data Collection Guidebook. FHWASA-13-009, Federal Highway Administration, 

Washington, DC, 2013. (publication pending)

9. Altobello, Michael; Michael Thurber; Nancy 

Lefler; Hugh McGee; and Barbara Hilger 

DeLucia. Development of a Structure 

for a MIRE Management Information 

System. FHWA-SA-13-007, Federal 

Highway Administration, Washington, DC, 

January 2013.

10. Council, Forrest; Jonathan Soika; Nancy 

Lefler; Robert Pollack; and Carol Tan. 

Performance Measures for Roadway 

Inventory Data. FHWA-SA-12-036, Federal 

Highway Administration, Washington, DC, 

February 2013.

11. Model Performance Measures for State 

Traffic Records Systems. National Highway 

Traffic Safety Administration, Washington, DC, 

February 2011.

This project was performed by Nancy X. Lefler, Hugh McGee, Rebecca Fiedler, Kimberly Eccles, Dale Abbott, 

and Michael Altobello from Vanasse Hangen Brustlin, Inc.; Jag Malella from Applied Research Associates; and 

Barbara Hilger Delucia from Data Nexus Inc.

FOR MORE INFORMATION 

Visit: http://safety.fhwa.dot.gov/rsdp/

FHWA, OFFICE OF SAFETY

Robert Pollack

Federal Highway Administration

Office of Safety Programs

robert.pollack@dot.gov

Carol Tan, Ph.D.

Federal Highway Administration

Office of Safety Research and Development

carol.tan@dot.gov