Florida Department of Transportation

Data Governance to 

Data-Driven Safety 

Analysis 

Florida’s SAFE STRIDES 2 Zero

SAFETY DATA CASE STUDY 

FHWA-SA-22-004 

Federal Highway Administration Office of Safety 

Roadway Safety Data Program 
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SAFETY DATA CASE STUDY FHWA-SA-22-004

Notice 

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SAFETY DATA CASE STUDY FHWA-SA-22-004

1. Report No.

FHWA-SA-22-004

2. Government Accession 

No.

3. Recipient's Catalog No.

 

4. Title and Subtitle

Data Governance to Data-Driven Safety Analysis

Florida’s SAFE STRIDES 2 Zero

5. Report Date

March 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, Suite 500 

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, January 2020-June 2022

14. Sponsoring Agency Code

FHWA

15. Supplementary Notes

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

technical content.

16. Abstract

Data governance makes data more accessible by implementing standards and assigning responsibilities to each role in the 

data collection, management, and analysis process. These responsibilities extend to executive leadership in addition to 

transportation professionals, data managers, and data stewards. This case study documents how the Florida Department of 

Transportation’s (FDOT’s) multi-year data governance effort has enabled the Agency to embark upon a robust program of 

safety data collection, integration, and analysis. The State Traffic Roadway and Intersection Data Evaluation System 

(STRIDES) 2 Zero (S2Z) program and the System Analysis and Forecast Evaluation (SAFE) subprogram represent a 

comprehensive safety management approach. The S2Z program aligns traffic safety and operations data applications to 

standardize FDOT’s approach to data-driven safety analysis. The SAFE subprogram overhauls FDOT’s network screening 

process to enable predictive methods. This programmatic enhancement supports project selection, improves program 

effectiveness, and helps reduce fatalities and serious injuries on Florida’s roads.

17. Key Words: 

Data governance, data integration, safety, highway 

safety manual

18. Distribution Statement

No restrictions.

19. Security Classif. (of this report)

Unclassified

20. Security Classif. (of this 

page) Unclassified

21. No. of Pages

 16 

22. Price

Technical Documentation Page
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SAFETY DATA CASE STUDY FHWA-SA-22-004

Acronyms

Acronym Description

AADT annual average daily traffic

AASHTO American Association of State Highway and Transportation Officials

ARBM All Roads Base Map

BCR benefit-cost ratio

CARS Crash Analysis and Reporting System

DDSA data-driven safety analysis

DHSMV Department of Highway Safety and Motor Vehicles

DOT department of transportation

EB empirical Bayes

EEC excess expected crashes

ETL extract, transform, and load

FHWA Federal Highway Administration

FDOT Florida Department of Transportation

GIS geographic information systems

HPMS Highway Performance Monitoring System

HSM Highway Safety Manual

RCI Roadway Characteristic Inventory

ROADS Reliable, Organized, Accurate Data Sharing

ROI return on investment

S2Z STRIDES 2 Zero

SAFE System Analysis and Forecast Evaluation

SHS State Highway System

SPF safety performance function

SQL Structured Query Language

STRIDES State Traffic Roadway and Intersection Data Evaluation System

TEOO Traffic Engineering and Operations Office

TSMCA Traffic Signal Maintenance and Compensation Agreement
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SAFETY DATA CASE STUDY FHWA-SA-22-004

Table of Contents

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

Data Governance and Safety Data.............................................................................................. 2

Safety Data, S2Z, and Roadway Safety Management ............................................................... 3

Challenges ...................................................................................................................................... 8

Next Steps...................................................................................................................................... 9

Conclusions .................................................................................................................................... 9

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

List of Tables 

Table 1. Sample comparison of candidate and sister signalized intersection locations........ 7

List of Figures

Figure 1. Graphic. FDOT’s governance structure..................................................................... 2

Figure 2. Graphic. FDOT’s ROADS component model. .......................................................... 3

Figure 3. Graphic. Illustration of FDOT’s data and application integration needs................ 5

Figure 4. Graphic. Diagram illustrating predicted, expected, observed, and ........................ 6

Figure 5. Graphic. Sample SAFE annual report of candidate locations.................................. 8
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SAFETY DATA CASE STUDY FHWA-SA-22-004

Executive Summary

Data governance makes data more accessible by implementing standards and assigning responsibilities 

to each role in the data collection, management, and analysis process. These responsibilities extend to 

executive leadership in addition to transportation professionals, data managers, and data stewards. This 

case study documents how the Florida Department of Transportation’s (FDOT’s) multi-year data 

governance effort has enabled the Agency to embark upon a robust program of safety data collection, 

integration, and analysis. The State Traffic Roadway and Intersection Data Evaluation System (STRIDES) 

2 Zero (S2Z) program and the System Analysis and Forecast Evaluation (SAFE) subprogram represent 

a comprehensive safety management approach. The S2Z program aligns traffic safety and operations 

data applications to standardize FDOT’s approach to data-driven safety analysis. The SAFE subprogram 

overhauls FDOT’s network screening process to enable predictive methods. This programmatic 

enhancement supports project selection, improves program effectiveness, and helps reduce fatalities 

and serious injuries on Florida’s roads.
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SAFETY DATA CASE STUDY FHWA-SA-22-004

Introduction 

In 2019, the Federal Highway Administration (FHWA) completed the second U.S. Roadway 

Safety Data Capabilities Assessment (FHWA, 2019a). This nationwide survey documented the 

safety data processes, policies, and procedures of all 50 States plus Washington D.C. and 

Puerto Rico. This survey highlighted the state-of-the-practice with respect to all phases of safety 

data collection, management, integration, and analysis. It also revealed that State Departments 

of Transportation (DOTs) were eager to improve their capacity for data management and 

integration.

This case study presents how the Florida Department of Transportation’s (FDOT’s) Traffic 

Engineering and Operations Office (TEOO) used agency-wide data governance to support its 

roadway safety management process. FDOT’s State Traffic Roadway and Intersection Data 

Evaluation System (STRIDES) 2 Zero (S2Z) program, including the System Analysis and Forecast 

Evaluation (SAFE) subprogram, represents a comprehensive safety management approach. 

FDOT’s enterprise data capabilities support the S2Z program and data-driven safety analysis 

(DDSA) of the State’s signalized intersections. Future enhancements to the S2Z program will 

apply DDSA to improve safety at unsignalized intersections and roadway segments.

Purpose and Need 

FDOT began a review of its enterprise data strategy in 2014. This effort revealed several critical 

needs with respect to the Agency’s approach to data, and FDOT organized the Reliable, 

Organized, Accurate Data Sharing (ROADS) initiative to address gaps in the Agency’s strategy. 

The ROADS program formalized FDOT’s data governance structure with the intent of making 

data more reliable, shareable, and integrated across business units and tools within FDOT. In 

2019, FDOT’s TEOO began the S2Z program to improve the DOT’s network screening 

process using enterprise data. For TEOO, this means moving from a more reactive hot spot 

screening approach to using predictive safety models. With full implementation of S2Z by 2025, 

FDOT will be able to evaluate safety improvements and monitor program performance

consistently across the Agency’s seven districts. 

Target Audience

The target audience for this case study is:

• Executive Leadership 

• Data Governance Committees

• Information Technology Staff

• Data Managers, Analysts, and Stewards

• Traffic Safety Managers

• Subject Matter Experts in Planning and Engineering
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SAFETY DATA CASE STUDY FHWA-SA-22-004

Data Governance and Safety Data

During its preliminary evaluation in 2014, FDOT identified five problems that needed to be 

addressed in the Agency’s revised data strategy (Christian, 2020):

1. It was difficult to know which data were available. 

2. Data were difficult to access; this includes both the number of data systems, as well as 

the security procedures related to them.

3. There was no standardized approach to data entry. Most districts adopted geographic 

information systems (GIS) as the entry point, but there was no central planning, so each 

solution was unique.

4. There was no enterprise-level view of data. Business units and districts focused on their 

own issues, and there was only ad-hoc collaboration to improve performance or reduce 

risk.

5. Users wanted a single source of truth (i.e., a “one-stop shop”) for FDOT’s data. FDOT 

needed to identify authoritative data sources.

FDOT established the ROADS program in response to these needs. The ROADs program 

developed FDOT’s formal data governance structure in 2015. This structure defines four roles: 

an executive team, enterprise data stewards, data stewards, and data custodians (figure 1).

Figure 1. Graphic. FDOT’s governance structure.

© FDOT
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SAFETY DATA CASE STUDY FHWA-SA-22-004

These roles have responsibilities assigned to them, with the ROADS executive team ultimately 

responsible for the direction and execution of data governance within FDOT. This includes 

implementation of the ROADS Component Model, which aligns enterprise-level data 

governance and change management with practical applications of data management (figure 2).

A more detailed summary of FDOT’s data governance roles and responsibilities can be found in 

the 2020 FHWA case study, FDOT Data Governance Initiative: Managing Vital Data Assets.

FDOT’s data governance initiative is ongoing, and FDOT’s data warehouse now supports 

enterprise data for safety analysis, road and asset inventories, Highway Performance Monitoring 

System (HPMS) reporting, and pavement condition. It is this foundation that supports the S2Z 

program and FDOT’s state-of-the-practice safety management process. 

Safety Data, S2Z, and Roadway Safety Management

Although S2Z is a roadway safety management program, data development and integration 

comprised the initial step in FDOT’s eight-step strategy: 

Figure 2. Graphic. FDOT’s ROADS component model. 

© FDOT
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SAFETY DATA CASE STUDY FHWA-SA-22-004

1. Develop an extract, transform, and load (ETL) process for extracting roadway and 

crash data. 

2. Classify roadway sites into different categories. 

3. Develop safety performance functions (SPFs).

4. Calculate predicted and expected crashes (FHWA, 2019b). 

5. Identify safety countermeasures. 

6. Collect additional roadway site data. 

7. Select candidate sites and their comparison sites. 

8. Summarize SAFE analysis results. 

Through this program, enterprise data will allow FDOT to implement a predictive DDSA 

program for all roads on the State Highway System (SHS).

Data Development

FDOT integrated data from several internal and external sources (e.g., the Florida Department 

of Highway Safety and Motor Vehicles, or DHSMV) to develop SPFs and conduct network 

screening. These data also support the roadway safety management process outlined in the 

American Association of State Highway and Transportation Officials’ (AASHTO) Highway 

Safety Manual (HSM). This approach used a formal, customized ETL process (figure 3). 

An ETL process copies data from an origin database and translates it into a format that is 

compatible with a destination database. FDOT developed its initial S2Z database architecture in 

2019. In 2020, FDOT developed a Structured Query Language (SQL) systems ETL process for 

data available to the DOT’s Central Office. This included data from:

• Crash Analysis and Reporting System (CARS).

• Roadway Characteristic Inventory (RCI).

• All Roads Base Map (ARBM) for intersection legs.

• Traffic Signal Maintenance and Compensation Agreement (TSMCA) data for traffic 

signals. 

FDOT and its university partners also collected intersection data to support specific analyses. 

They will collect segment-level geometric and non-motorized-vehicle infrastructure data as 

well. FDOT initially collected data through a manual, desktop-based effort. Future data 

collection efforts will include imagery-based machine learning applications, drone data from 

traffic studies, and other contextual studies. These data will be integrated with FDOT’s existing 

data to support the SAFE subprogram.
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SAFETY DATA CASE STUDY FHWA-SA-22-004

SAFE 

The SAFE subprogram is just one component of the overall S2Z initiative. This subprogram uses 

FDOT’s data to implement many of the best practices outlined in the AASHTO HSM. Prior to 

SAFE, FDOT relied on a hot spot approach based on crash frequency to identify locations with 

a safety need. SAFE is developing SPFs for intersections and segments in two phases. Phase I 

focused on intersections, and Phase II will focus on segments and midblock crossings. SAFE 

standardizes FDOT’s approach to facility type categories, countermeasure selection, and 

economic appraisal. FDOT completed its signalized intersection approach in 2020, and this 

serves as an example of the SAFE methodology for analyses of other facility types.

FDOT used S2Z data to categorize intersections based on similar land use context, number of 

legs, and traffic control devices present. For instance, FDOT has several land use categories 

that could apply to three- or four-leg signalized intersections for SPF development:

Figure 3. Graphic. Illustration of FDOT’s data and application integration needs. 

© FDOT
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SAFETY DATA CASE STUDY FHWA-SA-22-004

• C1: Natural

• C2: Rural

• C2T: Rural Town

• C3R: Suburban Residential

• C3C: Suburban Commercial

• C4: Urban General

• C5: Urban Center

• C6: Urban Core

With these highly stratified and homogenous facility types, FDOT applies an SPF based on 

major and minor-leg annual average daily traffic (AADT). FDOT uses the empirical Bayes (EB) 

method to calculate expected crashes. Comparing observed crashes to expected crashes 

determines excess expected crashes (EECs). If the EEC at a particular site is positive (i.e., more 

observed crashes than expected crashes), then the site presents an opportunity for safety 

improvement (figure 4).

These SPFs assess the expected and observed safety performance at each signalized intersection 

on the SHS. FDOT compares peer sites that perform well and poorly. These “candidate” sites 

(i.e., sites that experience more crashes than expected) and “sister” sites (i.e., similar 

comparison sites that experience fewer crashes than expected) can inform FDOT’s selection of 

potential safety countermeasures at candidate sites. For instance, a candidate and sister site may 

Figure 4. Graphic. Diagram illustrating predicted, expected, observed, and excess crashes.

© Kentucky Transportation Center 
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SAFETY DATA CASE STUDY FHWA-SA-22-004

have similar major- and minor-leg AADT, but differences at each site may indicate the need for 

specific treatments (table 1).

Table 1. Sample comparison of candidate and sister signalized intersection 

locations.

Characteristic Candidate Location Sister Location

Number of Legs 4 4 

Land Use Category C4 C4

Major AADT 59,000 55,332 

Minor AADT 25,733 25,733 

Observed Fatal and Suspected 

Serious Injury Crashes 4 1 

Retroreflective Backplates 

Present No Yes

Lighting Present Yes Yes

High Visibility Crosswalk 

Present No Yes

Advance Street Name Plaque No Yes

FDOT posts network screening results to the project website (figure 5). These reports list

candidate and sister sites identified in the network screening process, potential 

countermeasures for candidate sites, and the economic appraisal results (e.g., benefit-cost ratio, 

or BCR) for countermeasures at the candidate site. As the S2Z program grows and data are 

collected, FDOT will refine its methods and approach to improve the program’s return on 

investment (ROI). 
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SAFETY DATA CASE STUDY FHWA-SA-22-004

Challenges

S2Z and SAFE represent the state-of-the-practice in safety data collection and DDSA. Although 

the program is still in its early stages with activities planned into 2025, there are a few notable 

challenges in FDOT’s experience for peer DOTs to consider. Data governance has played a key 

role in enabling safety- and operations-specific data development. Without this foundation in 

place, TEOO would have to spend additional resources to locate, aggregate, and standardize 

data. Furthermore, FDOT is a highly decentralized DOT with major points of control and 

decision making at the district level. This has not only been an important consideration in data 

governance and data collection, but as FDOT continues its S2Z program, district involvement 

will be critical to supplement data and implement the DDSA program across the entire agency. 

Figure 5. Graphic. Sample SAFE annual report of candidate locations.

© FDOT
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SAFETY DATA CASE STUDY FHWA-SA-22-004

Next Steps

FDOT will continue to collect and integrate data into its S2Z database and associated 

applications. The additional data will support analyses (and countermeasure selection) for all 

intersections, segments, and midblock crossings on the SHS. Integrating FDOT’s data and 

applications will support dynamic analysis, visualization, and reporting for stakeholders. This 

could include dynamic SAFE reports for tracking candidate locations, monitoring project status 

at these locations, and evaluating ROI at the district-level. By standardizing and centralizing 

safety data, FDOT plans to help districts fund projects based on consistent methodology and 

statutory requirements. This includes trainings for engineers and other stakeholders, as well as 

annual SPF calibration and updates to the S2Z program.

Conclusions

Data governance makes data more accessible by implementing standards that improve data 

awareness and interoperability throughout a DOT. Accessible and usable data are the result of 

effective data governance and management. This case study documents how FDOT’s multi-year 

data governance effort has enabled the TEOO to enhance its safety analysis methodology 

through integrated data and DDSA. This is an example of how data can be used to standardize 

best practices for roadway safety management, improve program ROI, and reduce fatalities and 

serious injuries on public roads. 
10 

Contact 

Florida Department of Transportation 

Alan El-Urfali, State Traffic Services Program Engineer 

Alan.El-Urfali@dot.state.fl.us 

References

 Christian, C. (2020). FDOT Data Governance Initiative: Managing Vital Data Assets, 

Report No. FHWA-HIF-20-064, Washington, D.C. Available online:

https://rosap.ntl.bts.gov/view/dot/50671. 

El-Urfali, A., Ponce, J. (2020). SAFE STRIDES 2 Zero [Presentation]. Available online: 

https://www.fdot.gov/traffic/trafficservices/safestrides2zero/presentations. 

 Federal Highway Administration. (2019a). Second U.S. Roadway Safety Data Capabilities 

Assessment, Report No. FHWA-SA-19-018, Washington, D.C. Available online: 

https://rosap.ntl.bts.gov/view/dot/55617. 

 Federal Highway Administration. (2019b). Safety Data and Analysis: Observed, Predicted 

and Expected Crashes [Video]. YouTube. Available online: 

https://www.youtube.com/watch?app=desktop&v=fTzz5bv7Ko8. 

 Florida Department of Transportation. (2020). STRIDES 2 Zero (SAFE) [Presentation]. 

Available online: 

https://www.fdot.gov/traffic/trafficservices/safestrides2zero/presentations. 

 Florida Department of Transportation. (2021). “SAFE STRIDES 2 Zero” (website). 

Available online: https://www.fdot.gov/traffic/trafficservices/safestrides2zero/overview.