Roadway Safety Data Program
 

UTAH DEPARTMENT OF TRANSPORTATION
 

SAFETY DATA PROCESSES AND GOVERNANCE PRACTICES
 

CASE STUDY 

FHWA-SA-15-060 

Prepared for
 

Federal Highway Administration
 

Office of Safety
 

Roadway Safety Data Program
 

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

November 2015 

 

UTAH DOT CASE STUDY 

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UTAH DOT CASE STUDY 

ACKNOWLEDGEMENTS 

The FHWA Office of Safety Data Management Systems and Processes Project team would like to 

thank the following individuals who graciously provided information needed to develop this case 

study. 

Name Title Department Email/Phone # 

Michael Butler Contract Administrator 

Consultant Services 

Utah Department 

of Transportation 

michaelbutler@utah.gov 

801-965-4419 

W. Scott Jones Safety Programs 

Engineer 

Utah Department 

of Transportation 

wsjones@utah.gov 

801-965-4285 

Stan Burns Director for Asset 

Management 

Utah Department 

of Transportation 

sburns@utah.gov 

801-965-4150 

Chris Meredith Cartography and GIS Utah Department 

of Transportation 

cmeredith@utah.gov 

(801) 965-4915 

Steve Quinn Engineering Technology 

Services Manager 

Utah Department 

of Transportation 

squinn@utah.gov 

801-887-3631 

Becky Hjelm GIS Manager Utah Department 

of Transportation 

bhjelm@utah.gov 

801-964-4456 

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UTAH DOT CASE STUDY 

ACRONYMS 

Table 1. Acronyms 

Acronym Description 

AASHTO American Association of State Highway and Transportation Officials 

AGRC Automatic Geographic Reference Center 

CDIP Crash Data Improvement Program 

DBP Data Business Plan 

DOT Department of Transportation 

FHWA Federal Highway Administration 

GIS Geographic Information System 

LRS Linear Reference System 

UDOT Utah Department of Transportation 

UGate UDOT’s Geospatial Data Portal 

UMIP Utah Mapping and Information Partnership 

UPlan UDOT’s data sharing portal 

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UTAH DOT CASE STUDY 

TABLE OF CONTENTS
 

TABLE OF CONTENTS.............................................................................. 4
 

INTRODUCTION......................................................................................... 6
 

STATE SAFETY DATA PROCESSES AND GOVERNANCE 

PRACTICES .................................................................................................. 8
 

DATA MANAGEMENT AND GOVERNANCE.......................................................8
 

Data Collection ...........................................................................................................8
 

Data Management and Governance.........................................................................8
 

Interagency Partnerships and Collaboration...........................................................9
 

SAFETY DATA ANALYSIS TOOLS.......................................................................10
 

UPlan..........................................................................................................................11
 

Linear Bench .............................................................................................................12
 

Report Auto Generator ...........................................................................................13
 

Crash Data Analysis Tool.........................................................................................14
 

Other Safety Analysis Tools ....................................................................................16
 

APPLICABILITY TO OTHER STATES................................................... 19
 

FUNDING RESOURCES ........................................................................... 20
 

REFERENCES.............................................................................................. 21
 

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UTAH DOT CASE STUDY 

LIST OF TABLES
 

Table 1. Acronyms.............................................................................................................3
 

Table 2. Utah’s Safety Analysis Options ......................................................................16
 

LIST OF FIGURES 

Figure 1. UPlan ...............................................................................................................12
 

Figure 2. Linear Bench Application ..............................................................................13
 

Figure 3. Report Auto Generator, Cost Estimate ......................................................14
 

Figure 4. Example Treatment Options Report for the New Crash Data Analysis
 

Tool ...................................................................................................................................15
 

Figure 5. View of Detailed Analysis in the Crash Data Analysis Tool ......................16
 

Figure 6. FHWA Systemic Safety Tool.........................................................................17
 

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UTAH DOT CASE STUDY 

INTRODUCTION
 
 

The purpose of this case study is to highlight innovative data management strategies at Utah 

Department of Transportation (UDOT) that support the use of technology to benefit safety 

programs. In addition to highlighting forward-thinking strategies for safety data management, 

data analysis, and reporting, the case study documents the need for a formal data business plan 

and data governance. Exploring data management practices and the use of innovative tools 

within UDOT provides safety data management examples of: 

•	 The importance and usefulness of a robust and well-managed data collection program. 

•	 Providing access to integrated data for a variety of purposes. 

•	 How to use integrated data to develop advanced safety analysis capabilities and at the 

same time support tools for planning, performance measures, and target-setting 

processes. 

•	 The importance of collaboration and sharing current data strategies and challenges with 

data stakeholders. 

UDOT has recognized the need for quality data to support planning, performance measures 

and decision making for many years and has emerged as a leader in data collection, data sharing, 

and development of innovative tools for data analysis and reporting. Through the annual 

Strategic Direction reports and complimenting Efficiencies and Accomplishments reports, 

UDOT updates their goals and strategies based on current needs while supporting the overall 

vision, mission, and goals of the Department. UDOT staff and management do not hesitate to 

try new ideas and invest in data-driven tools to make the best use of available funding for safety, 

asset management and other program areas. Their accomplishments in data collection methods 

and development of tools and reports have inspired many other state DOT’s to try similar 

strategies. 

One of the prominent research projects recently completed pertaining to the topic of 

enhancing data management/data governance practices is NCHRP 666: Target-Setting Methods 

and Data Management to Support Performance-Based Resource Allocation by Transportation Agencies 

(2010). NCHRP 666 provides systematic guidance for establishing data management (and data 

governance) programs within an organization. The following six steps from NCHRP 666 can be 

adapted for safety data programs1

: 

1 NCHRP Report 666: Target-Setting Methods and Data Management to Support Performance-Based Resource 

Allocation by Transportation Agencies (2010), http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_rpt_666.pdf. 

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UTAH DOT CASE STUDY 

1. Establishing a need for safety data management/governance 

2. Establishing goals for safety data management 

3. Assessing the current state of safety data program systems 

4. Establishing safety data governance programs 

5. Leverage Technology for safety data management 

6. Linking safety data to planning, performance measures, and target processes 

This case study demonstrates how UDOT excels in two of those steps: leveraging technology 

for safety data management; and linking safety data to planning, performance measures, and 

target processes. 

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Data Collection 

 

 

Data Management and Governance 


 

UTAH DOT CASE STUDY 

STATE SAFETY DATA PROCESSES AND GOVERNANCE 

PRACTICES 

DATA MANAGEMENT AND GOVERNANCE 

UDOT has an innovative data collection program that has vastly improved procedures for 

managing assets and roadway inventory. As a result, they have been the focus of several case 

studies and have earned recognition from transportation organizations such as AASHTO. 

UDOT has developed a geospatial data portal called “UGate” that supports many data-driven 

tools for project prioritization, planning, analysis, and reporting. Currently, there is no formal 

data business plan for safety or enterprise data, but UDOT staff takes initiative on data 

management projects by applying innovative ideas. The resulting products and tools such as 

UPlan, Linear Bench, and Report Auto Generator that are highlighted in this case study 

demonstrate the value in quality data and confirm the need for investment in improved data 

management practices such as an enterprise data business plan. 

UDOT is very good at understanding user needs and providing the data and tools needed to 

manage programs that support the Department’s initiatives. They readily share information and 

coordinate with other business areas (including Information Technology (IT)) in data 

management issues and potential projects. Data management, IT, asset management, safety, and 

planning staff work together to be strategic, collaborative, and innovative. 

Utah’s data collection project (featured in the FHWA-SA-14-078 Case Study: “Collection and 

Use of Roadway Asset Data in Utah Roadway Safety Data and Analysis”) expands UDOT’s 

asset and roadway feature inventory, allows for better planning and budgeting, improves 

coordination among divisions, and greatly improves the traffic and safety division’s data analysis 

capabilities. The Request for Proposal (RFP) they used to solicit the contract is available, and 

lessons learned and successes from that project have been well documented and presented at 

various conferences and webinars. The data collection effort was coordinated with several 

business areas in the organization to meet as many needs as possible. These include 

incorporating advanced imagery (hi-resolution photo and LiDAR), data extraction of specified 

inventory, and pavement data imaging and tools for analysis. 

UDOT manages and shares data in a centralized data system that supports many innovative 

tools and applications for planning, safety data analysis, target-setting processes, and tracking 

performance measures. They consolidate all of their main systems (including those that 

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Interagency Partnerships and Collaboration 

 


 

UTAH DOT CASE STUDY 

specifically support safety programs) in a centralized data portal known as UGate. Data in 

UGate is integrated, downloadable, and accessible. Most information is available to the public. 

At UDOT, data is available for viewing and analysis using web based applications and online 

maps (UPlan) or available for download in various formats such as Shapefile (ArcGIS), Excel or 

KMZ (for display in Google Earth). UGate also supports several analysis tools used by traffic 

and safety engineers for project prioritization, planning and reporting. 

UDOT exposes data in tools, applications, and reports to improve quality. This in turn 

demonstrates the need for data governance and data management improvements. For example, 

when developing a tool, a systems engineering process occurs to evaluate data needs and 

linkages to ensure it meets end-user needs. If a problem arises during development that will be 

an obstacle for the functionality desired of the tool, UDOT finds a way to troubleshoot the 

problem and is able to obtain support for that work. Web applications (i.e., an online map) also 

help with data quality because maps and visual web tools make poor data quality and other data 

management issues easier for business owners to see. This often triggers support for activities 

and projects to improve quality. 

The expansion of technology at UDOT has made data governance and data business planning a 

higher priority need for the Department. They are currently developing UGate 2.0, which will 

allow for more in-depth analysis of data to support safety and other program areas. The 

process of developing UGate 2.0 resembles a data governance framework because Utah is 

taking a close look at all priority systems and data and evaluating how they will fit into the 

UGate framework. UDOT is also in the process of organizing a data governance board to 

review technology expenditures, stewardship roles and other data governance matters. 

Specific to safety data, UDOT evaluated their process for the Crash Data Improvement 

Program (CDIP) in 2011 to assess their current situation and develop recommendations for 

improvement. Since then, UDOT’s Highway Safety Office has implemented specific 

performance measures for safety, which they track and report to National Highway Traffic 

Safety Administration (NHTSA) every year as part of the Highway Safety Plan (HSP). One 

example of an area where they have made significant progress is electronic reporting of 

crashes. UDOT reports that they submit all of their crashes electronically and they are 

receiving 60% of all crash reports within a week of the incident. The electronic submission of 

crash data greatly improves accessibility to the data and allows for automated quality checks 

and tracking for performance measures. 

UDOT uses an external department for technology delivery that (for a fee) handles technical 

details such as data item definitions or physical database locations, storage and structures. 

Although these services come at a cost, it is helpful to have information technology 

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UTAH DOT CASE STUDY 

professionals handle the system architecture and database functionality so UDOT staff can 

focus on improving or developing data collection and analysis capabilities to support program 

areas. 

UDOT creates and manages a common Linear Referencing System (LRS) from centerline data 

compiled by an outside agency called the Automatic Geographic Reference Center (AGRC). 

AGRC aggregates all geospatial data from state and local governments and provides UDOT 

with the centerline and associated data. UDOT then creates and manages the LRS which they 

share back to AGRC. The partnership between UDOT and AGRC is part of the Utah Mapping 

and Information Partnership (UMIP), which includes several agencies that coordinate to 

consolidate, improve, and provide access to common datasets. 

An important partnership project between UDOT and AGRC is a pooled fund study to update 

the LRS to meet the FHWA requirement of establishing and maintaining an All Roads Network 

of Linear Referenced Data (ARNOLD) including a LRS that incorporates all public roads in the 

State. The pooled funds study supports data collection that leads to faster centerline updates 

using new imagery data. The LRS is a baseline for the data collection effort linking several data 

systems including: assets, roadway inventory, pavement, traffic, and crash data needed for safety 

analysis. Working with the AGRC is a successful partnership for UDOT that contributes to 

management and maintenance of the LRS, connections with other data and collaboration with 

outside agencies. 

SAFETY DATA ANALYSIS TOOLS 

UDOT’s data management practices and data collection contracts have resulted in a single 

reliable source of integrated data (called UGate Data Portal) to support various tools and 

applications. Although there is no formal process or governance in place for the development 

and use of tools, the data portal was nevertheless developed as a result of collaboration among 

several business areas. UDOT staff leading the effort have focused on making sure there is 

ample current and reliable data available through the UGate Data Portal. Some of the ways 

they accomplish this are through promoting their comprehensive data collection program, 

finding the best ways to utilize all data they collect (mostly via innovative tools), and showing 

their executive and managers how the data and tools have created efficiencies or allowed for 

better management of safety program resources. Because data resources are centralized and 

there are many options for analysis and reporting, most staff at UDOT are aware of their 

options and support the data portal and its capabilities. Rather than using a formal process for 

developing tools, UDOT develops tools either in-house or in partnership with contractors 

designed meet specific needs identified for a business area. They recognize a need for a more 

formal process to ensure they meet all program area needs consistently and effectively with 

ample quality data to support them. UDOT is always exploring possibilities for optimal use of 

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UTAH DOT CASE STUDY 

their available data and tools and this section describes several tools that currently support 

safety analysis, planning, and decision-making processes. 

UPlan 

Utah was one of the lead states working with the AASHTO Innovation Initiative to develop a 

web based decision-support, mapping, and informational tool for completing complex planning 

and project development tasks. The purpose and goals of the program are available online at 

http://aii.transportation.org/Pages/UPlan.aspx. The main benefits of the program are data 

visibility and similar formats for sharing data through ArcGIS online (an ESRI Product) maps. 

This leads to better coordination between business areas and different agencies, and also 

improves data quality. The original UPlan design inspired the Geospatial Data Collaboration 

effort that was part of the Every Day Counts Accelerating Innovation initiative. Several states 

have adopted and deployed maps built in ArcGIS online for sharing state agency data in a webbased portal of collaborative information that supports a number of business areas. 

UDOT uses an interactive map to accurately locate and link crash data to the LRS. The data is 

then available in UGate (the data portal) and shared via UPlan and other safety analysis tools. In 

the UPlan portal for Zero Fatalities, UDOT codes safety data by performance measures and 

roadway segments link to statistics such as severe crash rate, crash rate per mile, and safety 

ratings. A public use for this is to easily locate the safest routes in a simple but interactive web 

map application. Utah provides this information in UPlan and makes it available through public 

information requests. Data presented on the website is downloadable and if internal staff or 

other agencies need more detail, they can request access to use less limited crash data for their 

analyses. UPlan also provides open access to several other web based maps and applications 

that are of interest to the public and coordinating agencies. Figure 1 shows the Portal. 

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Figure 1. UPlan Map Portal 

Source: http://uplan.maps.arcgis.com/home/ 

Linear Bench 

 

 

 

 

 


 

UTAH DOT CASE STUDY 

Linear Bench is a tool used to view and analyze data that is accessible to UDOT staff. The too 

is designed for ease-of-use and allows the user to choose a road segment and data sets to 

generate a straight-line diagram, tabular report or map display with the selected characteristics. 

The data used in Linear Bench builds upon the data collection efforts and combines available 

data sources to allow for detailed analysis, decision making, and reporting capabilities that could 

support a number of different business area needs. The safety area can use this tool for 

detailed analyses of project areas or specific road segments because it can bring in any available 

assets or features and display them in a variety of formats. 

Viewing data sets together using the Linear Bench tool (Figure 2) can trigger response and 

action. For instance, analyzing crash scores, Annual Average Daily Traffic (AADT), and 

pavement data together could uncover the need for a site visit to check pavement surface 

condition. Linear Bench is a useful way to inventory roadway assets before visiting a project 

site, which saves time and resources as well as improving safety for UDOT employees. 

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UTAH DOT CASE STUDY 

Figure 2. Linear Bench Application 

Source: https://www.udot.utah.gov/ugate/f?p=111:2:0::NO::: 

Report Auto Generator 

The Report Auto Generator uses a download parameter in Linear Bench to set up a bid 

estimate (Figure 3) using Excel and connections to an export of data for a given segment of 

road. The tool saves time and effort and increases accuracy. One benefit of the Report Auto 

Generator is that it utilizes information accessed through the Data Portal to populate most 

parts of the form, so users do not have to look for and compile data to create a bid estimate. 

Another benefit is a notification feature that encourages coordination on projects across 

departments. When a bid estimate is created using this tool, there is an option to notify one or 

more interested parties either within or outside the department by email. The email 

notification provides enough detail to make sure interested parties don’t overlap work in the 

same area and allows for coordination of work efforts. 

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UTAH DOT CASE STUDY 

Systematic instructions allow any user to generate a cost estimate as long as they know how to 

identify a few details associated with the project. Prompts will guide a user to: 

• Name the project file, 

• Decide if they want to include guardrail data, 

• Identify a region, 

• Identify project as an Overlay or Mill and Fill 

• Identify additional specifications including details on repair and fill type, asphalt type 

• Notify other departments if desired (great for project coordination) 

There is a video tutorial describing the details on how to use this tool and the data and tool is 

open and available for anyone to use. 

Figure 3. Report Auto Generator, Cost Estimate 

Source: https://drive.google.com/a/utah.gov/file/d/0B_k-MpCWnQUEZlc3bHV2Vzk2TEE/edit?pli=1 

Crash Data Analysis Tool 

Former UDOT engineers who helped build the Report Auto Generator are developing the 

Crash Data Analysis Tool. This tool uses crash and incident location data combined with asset 

inventory data related to safety and damage value/cost estimates to easily display where funding 

for safety improvements should happen. Currently the tool shows analysis on a user defined 

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UTAH DOT CASE STUDY 

segment of road and reports in spreadsheet format but it is still in development. There are 

plans to transition into an online dashboard that will be expanded to perform both user defined 

and network level analysis. The following screenshots show how the tool will allow a user to 

identify an area of interest (currently restricted to a segment of roadway) and return a report 

that analyzes treatment types, options, and benefits displayed as dollar amounts. Figure 4 is a 

summary of treatment options where the red indicates treatments that would result in the 

highest return on investment in safety data improvements. Figure 5 shows some of the detailed 

summaries of crash mitigation options. The major benefit of this tool is the speed and ease of 

performing analyses. Normally, a safety analyst or traffic engineer would have to manually 

collect data (often in the field) possibly taking weeks or longer to research and gather data for 

this type of analysis. The reports shown in the images below were generated using business 

intelligence tools and took less than five minutes to complete. 

Figure 4. Example Treatment Options Report for the New Crash Data 

Analysis Tool 

Source: Michael Butler, Contract Administrator, UDOT 

15
Figure 5. View of Detailed Analysis in the Crash Data Analysis Tool 

Source: Michael Butler, Contract Administrator, UDOT 

Other Safety Analysis Tools 

UDOT has a few other options for safety data analysis and planning as shown in Table 2. The 

table describes the methods and quantifies the data and effort to use it. 

Table 2. Utah’s Safety Analysis Options 

Analysis Methods Description Data and Effort 

FHWA Systemic 

Safety Tool 

Uses crash data to identify appropriate target crash types and 

risk factors and then uses those risk factors to prioritize 

potential sites for implementation of target countermeasures 

Low 

United States Road 

Assessment Program 

(usRAP) Tools

Software tools that use predictive models and limited crash 

data to characterize crash risk . The primary product includes 

a program of highway infrastructure improvements prioritized 

on a benefit -cost basis. A limited selection of roadway 

variables is required in order to identify potential hazardous 

conditions. 

Medium 

Utah Crash 

Prediction Model 

Uses a predictive Bayesian crash model to screen, diagnose, 

select, appraise, prioritize, and evaluate statewide highway 

safety projects. Results are integrated within a GIS 

framework to better visualize the model results 

High 


 

UTAH DOT CASE STUDY 

Source: Systemic Safety Analysis - Utah’s Approach, PowerPoint by Scott Jones, Utah DOT for 2014 Systemic Safety 

Implementation Peer Exchange 

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UTAH DOT CASE STUDY 

The FHWA Systemic Safety Tool uses an initial 

screening measure to determine which crash 

types represent the bulk of crashes to help 

UDOT focus further analysis in areas that need 

more attention. UDOT does not use this tool 

to analyze specific crashes or to determine 

countermeasures at specific locations. Figure 6 

demonstrates an example of results from 

running the tool. As shown, the tool produced 

a prioritized list of areas needing attention based 

on the data. 

UDOT uses the United States Road Assessment 

Program data model to create a risk-based 

assessment of the entire state roadway system. 

United States Road Assessment Program 

analyzes roadway characteristics such as 

barriers, rumble strips, lane widths, access 

points, speeds, AADT, and more on a given 

road to identify risks. UDOT calibrates the 

model using existing crash data and the tool 

produces outputs in the form of “star ratings” 

showing the relative safety of each of the state 

roads. This tool also helps produce a “safer roads

investment plan” which is a list of recommended projects UDOT could pursue to reduce the 

risk of serious injuries and fatalities. The most innovative aspect of this tool is the 

incorporation of Google Street View to allow more options for data collection on roadways 

that might not be covered in UDOT’s data collection coverage (on state roads only). The 

benefit is that data collection options are available to agencies so they can run safety analysis 

models on non-state roads when needed. There are plans to expand the model to the Federal 

aid system following initial deployment and testing on the state system. 

The Utah Crash Prediction Model is a powerful and flexible model (currently only pertaining to 

the state road system) that can run any combination of variables together and output a list of 

road segments accordingly. The Bayesian model runs a comparison of actual crash history 

versus the expected crashes, which enables UDOT to not only see where crashes are 

occurring most frequently, but also to see where infrastructure changes are likely to make a 

difference to reduce fatal and serious injury crashes. Locations with the largest difference 

between actual and expected crashes should represent best opportunities for affecting positive 

change. 

Figure 6. FHWA Systemic Safety Tool 

Source: W. Scott Jones, Safety Programs Engineer, UDOT 

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UTAH DOT CASE STUDY 

UDOT’s tools and technology are innovative, inspire other DOTs, and keep their managers 

excited about investing in data collection and technology. To keep the technology and data 

collection momentum going and better manage future efforts, UDOT recognizes that structure 

for data management needs to be in place. 

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APPLICABILITY TO OTHER STATES
 

UDOT is innovative, creative, and proactive when it comes to implementing new strategies. 

This is part of their organization’s culture and accompanies UDOT’s strategy of coordinating 

with business areas and IT and incorporating user needs and ideas into the development of data 

and information systems. UDOT’s ideas, strategies, and lessons learned from the development 

of UGate, the data collection project, and from the development and deployment of tools for 

analysis, planning, and performance measures can be greatly beneficial to other states. A few 

lessons learned from UDOT related to safety data management and technology follow: 

•	 Costs for data collection and management need to relate to the hidden cost of not 

having linked data or not being able to make data driven decisions. UDOT feels strongly 

that there must be a way to show a return on the investment in data. 

•	 Even though it is sometimes hard to develop and implement new ways of managing and 

reporting data, the change in culture at UDOT has been a good thing; people are 

working together more effectively now than in the past. 

•	 Always think about ways to collect data once for use by many groups. 

•	 Make an effort to consolidate tools, reports, and data in centralized locations while 

making sure they meet the needs of as many business areas as possible. 

•	 Ability to display all of this information in UPlan was very beneficial for consolidating 

efforts and to show the value of sharing data in a centralized portal. 

•	 Keep working on ideas and strategies to utilize Business Intelligence (BI) tools. They 

help with data analysis, reporting and with justification of the investment in data 

management improvements. 

•	 Involve all the parties that use the data (safety, asset, etc.) and consider all areas of 

UDOT. This helps secure buy-in and support across the board. 

•	 Having the right people in the room helps with decision-making. 

•	 Make sure to inform managers and executives on cost savings and other benefits
 

achieved through more efficient processes.
 

•	 It takes people with passion. UDOT was committed to getting the job done so they 

proceeded with ideas and strategies and handled any problems as they arose. 

Other states can benefit from following UDOT’s example of open and collaborative 

development of data and information systems. 

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FUNDING RESOURCES 

UDOT utilizes funding from multiple sources. To raise business area interest in sharing 

resources for data management, one strategy is to talk to entities that have a need or use for 

data and analysis tools and show them what is possible. Another method is to show upper 

management how investment in data system improvements (UGate 2.0) would help manage 

data and information, by speeding up access to and analysis of data. 

Most of UDOT’s IT budget is through State funds in a transportation bill, which are earmarked 

funds for IT expenditures. In some cases, using State funds for the maintenance program is 

justified. For example, UDOT used state funds for about a third of the LiDAR in the data 

collection project because it creates efficiencies for the maintenance program such as time and 

cost savings by not having to survey in the field. 

UDOT uses Federal funds for eligible programs; these may include Highway Safety 

Improvement Program (HSIP), State Planning and Research (SP&R), or occasionally the Surface 

Transportation Program (STP). 

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REFERENCES
 
 

Collection and Use of Roadway Asset Data in Utah, Roadway Safety Data and Analysis, Case 

Study, FHWA-SA-14-078, Prepared for FHWA Office of Safety, Roadway Safety Data Program, 

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

Final UDOT CDIP Report, FHWA Office of Safety, by Data Nexus, Inc., November 28, 2011 

Interview with UDOT for FHWA Safety Data Systems and Processes for Literature Review and 

Synthesis Report, February 2015 

Phone, interviews, and email conversations with: 

• Michael Butler, Contract Administrator Consultant Services, UDOT 

• W. Scott Jones, Safety Programs Engineer, UDOT 

• Stan Burns, Director for Asset Management, UDOT 

• Chris Meredith, Cartography and GIS, UDOT 

• Steve Quinn, Engineering Technology Services (ETS) Manager, UDOT 

• Becky Hjelm, GIS Manager, UDOT 

• Robert Hull, Former Safety Program Engineer, UDOT 

Systemic Safety Analysis – Utah’s Approach, 2014 Systemic Safety Implementation Peer 

Exchange, Scott Jones, Utah DOT (“UDOT”), PowerPoint 

UDOT Data Portal: data.udot.utah.gov 

UDOT Data Portal News, September, 2013, Google UDOT Routes with Linear Bench 

Explorer, Frank Pisani, Becky Hjelm 

UDOT Efficiencies and Accomplishments, http://www.udot.utah.gov/main/ 

UDOT 2015 Strategic Direction, www.udot.utah.gov/go/strategicdirection 

UGate: UDOT’s LRS-based Data Warehouse, UGateCase Study, Gistic Research 

AASHTO Innovation Initiative – UPlan: http://aii.transportation.org/Pages/UPlan.aspx 

FHWA Office of Safety Roadway Safety Data Program Toolbox: Noteworthy Practices 

Database link, http://safety.fhwa.dot.gov/rsdp/ 

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UTAH DOT CASE STUDY 

Anita Vandervalk, Dena Snyder, Kim Hajek, Talena Adams, and Lisa Smith from Cambridge 

Systematics, Inc. performed this project. 

FHWA, Office of Safety 

Stuart Thompson. P.E. 

Federal Highway Administration 

202-366-8090 

Stuart.Thompson@dot.gov 

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