Ohio Department of Transportation’s

Intersection 

Inventory 

SAFETY DATA CASE STUDY 

FHWA-SA-22-068 

Federal Highway Administration Office of Safety 

Roadway Safety Data Program 

http://safety.fhwa.dot.gov/rsdp
ii SAFETY DATA CASE STUDY FHWA-SA-22-068

Notice 

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iii SAFETY DATA CASE STUDY FHWA-SA-22-068

1. Report No.

FHWA-SA-22-068

2. Government Accession

No.

3. Recipient's Catalog No.

4. Title and Subtitle

Ohio Department of Transportation’s Intersection Inventory

5. Report Date

November 2022

6. Performing Organization Code

7.Author(s)

Ian Hamilton

8. Performing Organization Report No.

9. Performing Organization Name and Address

Vanasse Hangen Brustlin, Inc (VHB)

940 Main Campus Drive

Raleigh, NC 27606

10. Work Unit No.

11. Contract or Grant No.

DTFH61-16-D-00052

12. Sponsoring Agency Name and Address

Federal Highway Administration Office of Safety

1200 New Jersey Ave., SE

Washington, DC 20590

13. Type of Report and Period

Case Study, August 2019-August 2022

14. Sponsoring Agency Code

FHWA

15. Supplementary Notes

The contract manager for this report was Sarah Weissman Pascual. Jerry Roche and Joe Hausman provided editorial review

and support for technical content.

16. Abstract

The Federal Highway Administration (FHWA) originally published the Model Inventory of Roadway Elements – MIRE

1.0 guidance on a set of recommended safety data elements for State departments of transportation (DOTs) in 2010. These

elements could support a variety of network and site-specific safety analyses, as well as support the methods introduced in

the First Edition of the American Association of State Highway and Transportation Officials’ Highway Safety Manual. In

2017, FHWA updated and expanded the MIRE guidance and introduced the concept of MIRE Fundamental Data Elements

(FDEs). These MIRE FDEs include data elements for roadway segments, intersections, and interchange/ramps on non-local

paved roads, as well as smaller subsets for local paved and unpaved roads.

This case study presents an effort by the Ohio Department of Transportation (ODOT) to 1) develop a digital inventory of

intersection locations on all public roads in the State, and 2) collect MIRE FDEs at those intersections to support statewide

safety screening and analysis. The intersection inventory will serve several important purposes for ODOT, including

meeting Federal data requirements and substantially improving data analysis capabilities. ODOT’s data integration with

existing and future data analysis systems and work with FHWA’s Applications of Enterprise Geographic Information

Systems for Transportation (AEGIST) pooled fund study will expand intersection safety analysis capabilities throughout

the agency.

17. Key Words:

Intersections, MIRE, FDE, integration, safety,

AEGIST

18. Distribution Statement

No restrictions.

19. Security Classif. (of this report)

Unclassified

20. Security Classif. (of this

page) Unclassified

21. No. of Pages

17

22. Price

Technical Documentation Page
iv SAFETY DATA CASE STUDY FHWA-SA-22-068

Acronyms 

Acronym Description

AADT Annual Average Daily Traffic

AASHTO American Association of State Highway and Transportation Officials

AEGIST Applications of Enterprise GIS for Transportation

DOT Department of Transportation

ETL extract, transform, and load

FDE Fundamental Data Elements

FHWA Federal Highway Administration 

GCAT GIS Crash Analysis Tool

GIS geographic information systems 

HSIP Highway Safety Improvement Program

HSM Highway Safety Manual

LBRS Location Based Response System

LRS linear referencing system

MIRE Model Inventory of Roadway Elements

NHTSA National Highway Traffic Safety Administration

ODOT Ohio Department of Transportation

R&H Roads and Highways

SQL Structured Query Language

TRCC Traffic Records Coordinating Committee
v SAFETY DATA CASE STUDY FHWA-SA-22-068

Table of Contents

Introduction........................................................................................................................ 1

Background ........................................................................................................................ 3

Data Development ............................................................................................................ 6

Future Considerations ...................................................................................................... 8

Conclusions......................................................................................................................... 8

References ........................................................................................................................10

List of Figures

Figure 1. Graphic. Example of ODOT’s intersection inventory basemap. ................. 6

Figure 2. Graphic. ODOT’s data governance committee ............................................8

Figure 3. Graphic. Roadway safety management process.............................................8

List of Tables

Table 1. MIRE 2.0 FDEs..................................................................................................... 2

Table 2. Intersection data elements................................................................................ 4

Table 3. Intersection approach data elements............................................................... 5
vi SAFETY DATA CASE STUDY FHWA-SA-22-068

Executive Summary

The Federal Highway Administration (FHWA) originally published the Model Inventory of 

Roadway Elements – MIRE 1.0 guidance on a set of recommended safety data elements for State 

departments of transportation (DOTs) in 2010. These elements could support a variety of 

network and site-specific safety analyses, as well as support the methods introduced in the First 

Edition of the American Association of State Highway and Transportation Officials’ Highway 

Safety Manual. In 2017, FHWA updated and expanded the MIRE guidance and introduced the 

concept of MIRE Fundamental Data Elements (FDEs). These MIRE FDEs include data elements 

for roadway segments, intersections, and interchange/ramps on non-local paved roads, as well 

as smaller subsets for local paved and unpaved roads.

This case study presents an effort by the Ohio Department of Transportation (ODOT) to 

1) develop a digital inventory of intersection locations on all public roads in the State, and

2) collect MIRE FDEs at those intersections to support statewide safety screening and analysis.

The intersection inventory will serve several important purposes for ODOT, including meeting

Federal data requirements and substantially improving data analysis capabilities. ODOT’s data

integration with existing and future data analysis systems and work with FHWA’s Applications

of Enterprise Geographic Information Systems for Transportation (AEGIST) pooled fund study

will expand intersection safety analysis capabilities throughout the agency.
1 SAFETY DATA CASE STUDY FHWA-SA-22-068

Introduction 

The Federal Highway Administration (FHWA) originally published guidance on a set of 

recommended safety data elements for State departments of transportation (DOTs) in 2010. 

The Model Inventory of Roadway Elements (MIRE), Version 1.0 (Lefler et al., 2010) provided a list of 

202 potential data elements representing roadway, intersection, interchange, and traffic 

characteristics. These elements could support a variety of network and site-specific safety 

analyses, as well as support the methods introduced in the First Edition of the American 

Association of State Highway and Transportation Officials’ (AASHTO’s) Highway Safety Manual

(HSM; 2010).

In 2017, FHWA updated and expanded the MIRE guidance to include 205 data elements (Lefler 

et al., 2017). The MIRE 2.0 guidance also introduced the concept of MIRE Fundamental Data 

Elements (FDEs). These MIRE FDEs include 37 data elements for roadway segments, 

intersections, and interchange/ramps, primarily for non-local paved roads (table 1). Local paved 

roads and unpaved roads require fewer MIRE FDEs (9 and 5 data elements, respectively), but 

MIRE requires annual average daily traffic (AADT) estimates for all public paved roads. Per 23 

CFR §924.11, “States shall have access to a complete collection of the MIRE FDEs on all public 

roads by September 30, 2026.” FHWA also requests States to report progress (i.e., percent of 

MIRE FDEs collected) annually as part of routine Highway Safety Improvement Program (HSIP) 

reporting. 

This case study presents an effort by the Ohio Department of Transportation (ODOT) to:

1) develop a digital inventory of intersection locations on all public roads in the State, and

2) collect MIRE FDEs at those intersections to support statewide safety screening and

analysis.

The purpose is to provide a potential roadmap for other States as they prepare their 

intersection inventories to meet the 2026 deadline and support safety programs intended to 

reduce fatalities and serious injuries on all public roads.
2 SAFETY DATA CASE STUDY FHWA-SA-22-068

Table 1. MIRE 2.0 FDEs.

Data Element

(In MIRE 2.0 Order)

NonLocal 

Paved 

Roadway 

Segment

Non-Local 

Paved 

Intersection

Non-Local 

Paved 

Interchange/ 

Ramp 

Local 

Paved 

Roads

Local 

Unpaved 

Roads

Type of Government Ownership X X X X 

Route Number X 

Route/Street Name X 

Begin Point Segment Descriptor X X X 

End Point Segment Descriptor X X X 

Segment Identifier X X X 

Segment Length X 

Direction of Inventory X 

Functional Class X X X X 

Rural/Urban Designation X X 

Federal Aid/Route Type X 

Access Control X 

Surface Type X X 

Number of Through Lanes X X 

Median Type X 

AADT X X X 

AADT Year X X 

One/Two-Way Operations X 

Unique Junction Identifier X 

Location Identifier for Road 1 

Crossing Point X 

Location Identifier for Road 2 

Crossing Point X 

Intersection/Junction Geometry X 

Intersection/Junction Traffic Control X 

Unique Approach Identifier X 

Unique Interchange Identifier X 

Interchange Type X 

Ramp Length X 

Ramp AADT X 

Year of Ramp AADT X 

Roadway Type at Beginning Ramp 

Terminal X 

Location Identifier for Roadway at 

Beginning Ramp Terminal X 

Roadway Type at Ending Ramp 

Terminal X 

Location Identifier for Roadway at 

Ending Ramp Terminal X 
3 SAFETY DATA CASE STUDY FHWA-SA-22-068

Background 

ODOT’s Needs

ODOT had several data systems that supported intersection-related data management prior to 

the MIRE 2.0 guidance release. However, no single dataset met the need for a complete 

intersection inventory. For instance, ODOT’s roadway inventory group could produce an 

inventory where digital centerlines overlapped, but this dataset did not necessarily reflect the 

physical layout and spatial relationships of roads. ODOT also maintained an inventory of traffic 

signals, but this inventory lacked several MIRE FDEs and did not include the non-signalized 

intersections. 

With the advent of MIRE 2.0, ODOT began a scoping process to support a comprehensive 

intersection inventory. These discussions included transportation safety, roadway engineering, 

planning, traffic demand modeling and forecasting, and geometric design groups. ODOT focused 

on intersection data as a planning-level resource (e.g., general traffic control and number of 

approaches) rather than an inventory of engineering-level detail (e.g., turn lane lengths and 

taper); this approach is consistent with the intention of MIRE and HSM methods.

Developing Requirements

Safety, planning, and traffic demand modeling comprised the critical partners in the intersection 

inventory’s development. This team determined the requirements of the new dataset based on 

the DOT’s collective planning needs. This involved sorting data elements best captured at the 

intersection-level (i.e., data that represent the entire intersection area), as well as the 

intersection approach-level (i.e., data that will vary by approach leg).

Table 2 and table 3 document the intersection elements collected at the intersection- and 

intersection approach-level. ODOT developed Structured Query Language (SQL)-based 

extract, transform, and load (ETL) processes to import intersection data into the agency’s 

various analysis platforms. This included enterprise platforms for safety analysis and traffic 

demand modeling.
4 SAFETY DATA CASE STUDY FHWA-SA-22-068

Table 2. Intersection data elements.

Date Element

MIRE 

2.0 

Number

Data Type/

Domain Values

Intersection Identifier 110* N/A

Configuration 116*

1 T-Intersection

2 Y-Intersection

3 Cross-Intersection (four legs)

4 Roundabout

5 Five or More Legs and Not Circular

6 Other Circular Intersection

7 Midblock Pedestrian Crossing

8 Restricted Crossing U-turn Intersection

9 Median U-turn Intersection 

10 Displaced Left-turn Intersection 

11 Jughandle Intersection

12 Continuous Green T Intersection 

13 Quadrant Intersection

14 Single Point Urban Interchange

99 Other

Traffic Control 121*

1 Uncontrolled

2 Yield Sign

3 Two-Way Stop 

4 All-Way Stop

5 Two-Way Stop with Flasher

6 All-Way Stop with Flasher

7 Signalized

8 Roundabout

9 Pedestrian Hybrid Beacon

10 Railroad Crossing, Gates, and Flashing Lights

11 Railroad Crossing, Flashing Lights Only

12 Railroad Crossing, Stop-sign Controlled

13 Railroad Crossing, Crossbucks Only 

99 Other

Number of Circulatory Lanes 124 Numerical

* MIRE FDE
5 SAFETY DATA CASE STUDY FHWA-SA-22-068

Table 3. Intersection approach data elements.

Date Element MIRE 2.0 

Number

Data Type/ 

Domain Values

Intersection Identifier 128* N/A

Unique Identifier 129* N/A

Mode 132

1 Vehicle Only or Shared Use

2 Pedestrians Only

3 Bicycles Only

4 Pedestrians and Bicycles

5 Railroad

9 Other

Traffic Control 144*

1 Uncontrolled

2 Yield Sign

3 Two-Way Stop 

4 All-Way Stop

5 Two-Way Stop with Flasher

6 All-Way Stop with Flasher

7 Signalized

8 Roundabout

9 Pedestrian Hybrid Beacon

10 Railroad Crossing, Gates, and 

Flashing Lights

11 Railroad Crossing, Flashing

Lights Only

12 Railroad Crossing, Stop-sign 

Controlled

13 Railroad Crossing, Crossbucks

Only 

99 Other

Annual Average Daily Traffic (AADT) 130 Numerical

AADT Year 131 Numerical

Number of Exclusive Left-Turn Lanes 136 Numerical

Number of Shared Left-Through Turn Lanes N/A Numerical

Number of Exclusive Through Lanes 134 Numerical

Number of Shared Left-Through-Right Lanes N/A Numerical

Number of Shared Left-Right Lanes N/A Numerical

Number of Shared Right-Through Turn Lanes N/A Numerical

Number of Exclusive Right-Turn Lanes 140 Numerical

One-Way Street Outbound Approach 

Indicator N/A Coded Indicator

*MIRE FDE
6 SAFETY DATA CASE STUDY FHWA-SA-22-068

Data Development

ODOT developed its intersection inventory from an all-roads basemap using geographic 

information systems (GIS) tools. ODOT populated these data through a combination of derived 

data from existing data systems, as well as custom data collection performed by a third-party 

contractor.

Basemap

ODOT maintains two linear referencing systems (LRS), one that represents all routes in Ohio 

from end to end statewide, and a second that is based on county-routes. The latter breaks 

individual routes (e.g., Interstate 75) at county boundaries. ODOT maintains roadway, traffic, 

asset, and crash data using the county-route LRS, and this served as the basemap for the 

intersection inventory. The combination of LRS route IDs and mileposts provides the location 

reference for each intersection, and the approaching routes to each intersection provide a 

basemap reference for all approach information. This all-roads basemap format allows for ready

compatibility between ODOT’s crash and supporting safety data (figure 1).

Figure 1. Graphic. Example of ODOT’s intersection inventory basemap.

Source: FHWA
7 SAFETY DATA CASE STUDY FHWA-SA-22-068

Attribute Data Development

ODOT estimated that there are 290,000 public intersections in the State prior to attribute data 

collection. The DOT and State Traffic Records Coordinating Committee (TRCC) acquired data 

collection funding through National Highway Traffic Safety Administration (NHTSA) 405(c) 

funds. ODOT did not use HSIP funds for the intersection data collection effort, although MIRE 

data collection and improvements are eligible for HSIP. After an open invitation to bid for thirdparty contractor support, ODOT conducted a pilot effort collecting data on five percent of all 

public intersections in the State. This allowed ODOT to assess the sufficiency of the vendor’s 

proposed methods.

Some data elements could be derived from existing ODOT datasets, such as AADT, AADT 

year, and approach location. Others, such as traffic control and turn-lane presence, required 

additional data collection or validation. Since the LRS may not be a perfect representation of 

intersections in a physical space, ODOT required collectors to validate the presence of an 

intersection at the confluence of two or more LRS routes; in other words, ODOT required its 

vendor to confirm that the flagged intersection location represented an “exchange of traffic 

between two roadways” (ODOT, 2020, p.7). This could include grade separation or other 

circumstances where potential traffic conflicts may not be present. ODOT did not collect 

intersection or approach information for these locations.

ODOT pursued the remaining statewide collection after the success of the pilot effort. To 

address so many locations in a systematic and efficient manner, ODOT prioritized data 

collection in counties that were fully incorporated in the State’s Location Based Response 

System (LBRS) at the start of the intersection collection effort in 2020. The LBRS is a program 

that ingests local road data into the State LRS and improves location referencing for all public 

roadways (FHWA, 2014), and all counties are anticipated to be incorporated into the LBRS 

program by 2023 (ODOT, 2022). ODOT will receive collected data for all valid intersection 

locations at project completion (anticipated fall 2022), as well as documentation regarding the 

collection methods and a data glossary with definitions.
8 SAFETY DATA CASE STUDY FHWA-SA-22-068

Conclusions

Intersection inventories are an 

important component of a State’s 

safety data system. These data are 

part of the MIRE FDE requirements, 

and they are applicable to a State’s 

ability to conduct safety analysis and 

implement Parts B and C of the HSM. 

Part B includes the roadway safety 

management process (figure 3).

The LRS is the foundation for 

ODOT’s intersection inventory. This 

approach allows the intersection 

inventory to adapt to changes in the 

network and ODOT can maintain 

1 https://gisintransportation.com/

Figure 3. Graphic. Roadway safety management process 

(FHWA, 2013). 

Source: FHWA

Future Considerations 

The intersection inventory will serve several 

important purposes for ODOT, including 

meeting Federal data requirements (23 CFR § 

924.11) and substantially improving data 

analysis capabilities. Although the intersection

inventory effort began before ODOT adopted 

its formal data governance framework (Albee 

et al., 2020), the Data Governance Committee 

and associated working groups will manage

the future of the inventory (figure 2). This

includes establishing the inventory’s role in © ODOT

future safety analysis tools as ODOT plans Figure 2. Graphic. ODOT’s data governance

future beyond AASHTOWare Safety committee.

AnalystTM, integration with the State’s GIS 

Crash Analysis Tool (GCAT), and LRS migration to Esri’s Roads & HighwaysTM (R&H) platform.

ODOT is also working with FHWA’s Applications of Enterprise GIS for Transportation 

(AEGIST) pooled fund study to refine its GIS approach. 1 This includes a strategic roadmap for 

intersection data maintenance within ODOT’s broader GIS data ecosystem and application of 

new methods (e.g., intersection polygons). 
9 SAFETY DATA CASE STUDY FHWA-SA-22-068

these data long-term (i.e., future R&H integration). The location information generated by the 

intersection of unique routes will allow ODOT to link crash and other asset data to specific 

intersections locations.

This information will allow ODOT to conduct more systemic-based analysis (i.e., focused on 

addressing risk factors with proven safety countermeasures) and implement predictive safety 

models (i.e., safety performance functions) to support the roadway safety management process. 

ODOT’s integration with existing and future data analysis systems (e.g., GCAT, Safety 

AnalystTM, or a future safety management system) and work with FHWA’s AEGIST program will 

expand safety analysis capabilities throughout the agency. 
10 

References

Albee, M., Hamilton, I., Chestnutt, C. (2020). Data Governance Ohio’s People, Processes, 

and Technology, Report No. FHWA-SA-20-059, Washington, D.C. 

https://rosap.ntl.bts.gov/view/dot/58089. 

 American Association of State Highway and Transportation Officials. (2010). Highway 

Safety Manual: 1st Edition, Washington, D.C.

http://www.highwaysafetymanual.org/Pages/default.aspx. 

 Federal Highway Administration. (2014, June 6). Ohio Location Based Response System 

State and Local Data Integration, Report No. FHWA-SA-14-036. Washington, D.C.

https://safety.fhwa.dot.gov/rsdp/downloads/ohio_case_study.pdf. 

 Federal Highway Administration. (2013). Quantifying Safety in the Roadway Safety 

Management Process, Report No. FHWA-SA-13-010, Washington, D.C. 

https://rosap.ntl.bts.gov/view/dot/49412/dot_49412_DS1.pdf?. 

 Lefler, N., Council F., Harkey, D., Zhou, Y., Carter, D., McGee, H., and Daul M. (2010). 

Model Inventory of Roadway Elements – MIRE 1.0, Report No. FHWA-SA-10-018, 

Washington, D.C. https://rosap.ntl.bts.gov/view/dot/41410.

 Lefler, N., Zhou, Y., Carter, D., McGee, H., Harkey, D., and Council, F. (2017). Model 

Inventory of Roadway Elements – MIRE 2.0, Report No. FHWA-SA-17-048, Washington, 

D.C. https://rosap.ntl.bts.gov/view/dot/49568.

 ODOT. (2020). Invitation to Bid. Invitation No. 393021. 

 ODOT. (2022). “ODOT Location Based Response System” (website). 

https://www.transportation.ohio.gov/programs/technical-services/transportationinformationmanagement/lbrs#:~:text=The%20Location%20Based%20Response%20System,reducing

%20redundant%20data%20collection%20activities. 

 Phone Interview on May 27, 2022, with Brent Bogard (ODOT), Ian Kidner (ODOT),

and Derek Troyer (FHWA).

 23 CFR § 924.11 - Implementation. (n.d.). Code of Federal Regulations. 

https://www.ecfr.gov/current/title-23/chapter-I/subchapter-J/part-924/

section-924.11.
11 

Contact

Ohio Department of Transportation

Brenton Bogard

brenton.bogard@dot.ohio.gov