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Market Analysis of Collecting Fundamental Roadway Data Elements to Support the Highway Safety Improvement Program

Cover - Background Report: Guidance for Roadway Safety Data to Support the Highway Safety Improvement Program

Market Analysis of Collecting Fundamental Roadway Data Elements to Support the Highway Safety Improvement Program

Final Report

June 2011
FHWA-SA-11-40

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Notice

 
This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The U.S. Government assumes no liability for the use of the information contained in this document.
 
The U.S. Government does not endorse products or manufacturers. Trademarks or manufacturers' names appear in this report only because they are considered essential to the objective of the document.
 
Quality Assurance Statement
 
The Federal Highway Administration (FHWA) provides high-quality information to serve Government, industry, and the public in a manner that promotes public understanding. Standards and policies are used to ensure and maximize the quality, objectivity, utility, and integrity of its information. FHWA periodically reviews quality issues and adjusts its programs and processes to ensure continuous quality improvement.

 

 

Acknowledgements

The project team would like to thank the following individuals who served as members on the Federal Highway Administration (FHWA) Office of Safety Technical Working Group for this effort.  Their contributions helped shape the guidance that States will be receiving on the fundamental roadway safety data elements to support their Highway Safety Improvement Programs.

Office of Safety Technical Working Group

Robert Pollack, FHWA Office of Safety
Jeff Miller, FHWA Office of Safety
Mike Griffith, FHWA Office of Safety
Erin Kenley, FHWA Office of Safety
Ed Rice, FHWA Office of Safety
Lincoln Cobb, FHWA Office of Safety Research and Development
Ray Krammes, FHWA Office of Safety Research and Development
Joe Hausman, FHWA Office of Highway Policy Information
Greg Schertz, FHWA Federal Lands
Christine Thorkildsen, FHWA New York Division
Greg Piland, FHWA Illinois Division
Jerry Roche, FHWA Iowa Division
David Harkey, University of North Carolina Highway Safety Research Center
Forrest Council, University of North Carolina Highway Safety Research Center

 

Technical Documentation Page

1. Report No. FHWA

FHWA-SA-11-40

2. Government Accession No.

3. Recipient’s Catalog No.

4. Title and Subtitle

Market Analysis of Collecting Fundamental Roadway Data Elements to Support the Highway Safety Improvement Program

5. Report Date

June 2011

6. Performing Organization Code

7. Authors

Nancy Lefler, Rebecca Fiedler, Hugh McGee, Robert Pollack, and Jeff Miller

8. Performing Organization Report No.

9. Performing Organization Name and Address

Vanasse Hangen Brustlin, Inc. (VHB)
8300 Boone Boulevard, Suite 700
Vienna, VA 22182-2626

10. Work Unit No.

11. Contract or Grant No.

DTFH61-05-D-00024 (VHB)

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 Covered

Final Report, April 2010 - June 2011

14. Sponsoring Agency Code

FHWA

15. Supplementary Notes:

The contract manager for this project was Robert Pollack. 

16. Abstract

Quality data are the foundation for making important decisions regarding the design, operation, and safety of roadways.  Using roadway and traffic data together with crash data can help agencies to make decisions that are fiscally responsible and to improve the safety of the roadways for all users.  The Federal Highway Administration (FHWA) Office of Safety has established a fundamental set of roadway and traffic data elements that States should be collecting to support the activities conducted under their Highway Safety Improvement Programs (FDE/HSIP).  The objective of this effort was to conduct a market analysis of the potential cost to States in developing a statewide location referencing system and collecting the FDE/HSIP in all public roadways.  This effort also investigated potential methodologies that could be applied to estimate the benefits in terms of safety of collecting this additional roadway information.  This report provides the results of this effort and provides suggestions for future research.   

17. Key Words

Safety data, economic analysis, HSIP, roadway data, traffic data, intersections, ramps

18. Distribution Statement

No restrictions.

19. Security Classif. (of this report)

Unclassified

20. Security Classif. (of this page)

Unclassified

21. No. of Pages:

41

22. Price

Form DOT F 1700.7 (8-72) - Reproduction of completed pages authorized

 

Conversion Table

 

Acronyms

Term Definition
AADTAnnual Average Daily Traffic
CFRCode of Federal Regulations
DOTDepartment of Transportation
EMSEmergency Medical Services
FDE/HSIPFundamental Data Elements for HSIP
FHWAFederal Highway Administration
FMCSAFederal Motor Carrier Safety Administration
GISGeographic Information System
HCMHighway Capacity Manual
HPMSHighway Performance Monitoring System
HSIPHighway Safety Improvement Program
HSMHighway Safety Manual
IHSDMInteractive Highway Safety Design Model
LIDARLight Detection and Ranging
LRSLocation Referencing System
MIREModel Inventory of Roadway Elements
MIRE MISMIRE Management Information Systems
NCHRPNational Cooperative Highway Research Program
NHSNational Highway System
NHTSANational Highway Traffic Safety Administration
SAFETEA-LUThe Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users
SHSPStrategic Highway Safety Plan
TRB SHRP 2Transportation Research Board Strategic Highway Research Program 2
TRCCTraffic Records Coordinating Committee
TWGTechnical Working Group
U.S.United States

 

Table of Contents

 


Executive Summary

Quality data are the foundation for making important decisions regarding the design, operation, and safety of roadways.  By incorporating roadway and traffic data into safety analysis procedures, States can better identify safety problems and prescribe solutions to support their Highway Safety Improvement Programs (HSIP) and implement their Strategic Highway Safety Plans (SHSP).  Furthermore, a new generation of safety analysis tools and methods are being developed to help identify safety issues and provide recommendations for improvements.  These safety analysis tools, such as the Highway Safety Manual (HSM) and related SafetyAnalyst and Interactive Highway Safety Design Model (IHSDM) software, all require quality roadway, traffic, and crash data to achieve the most accurate results.  Using roadway and traffic data together with crash data can help agencies to make decisions that are fiscally responsible and to improve the safety of the roadways for all users.

While HSIP guidance provides information on how safety data should be used, there is no additional detail on the specific data elements that State and local agencies should be collecting, maintaining, and using to support their HSIPs and SHSPs.  In response to this gap, the Federal Highway Administration (FHWA) held a series of information gathering sessions in 2009 and 2010 and convened a Technical Working Group (TWG) from 2010 through 2011 to determine a minimum set of roadway and traffic data elements that States should be collecting; what data States are capable of collecting given the current economic environment; and the importance of using roadway and traffic data to support the States’ HSIPs.

States should have a common statewide location referencing system, such as a geographic information system (GIS) or a linear referencing system, on all public roads.  These systems will enable States to identify high crash locations on all their public roads.  As States expand their inventories, these common statewide systems will enable States to link these locations with additional data systems, such as roadway and traffic data.

States should also be collecting a set of minimum roadway and traffic data elements that are fundamental to support their HSIPs. This set of elements is herein referred to as the Fundamental Data Elements for HSIP (FDE/HSIP).    

The FDE/HSIP are based on the minimum required elements needed to use enhanced safety analysis tools and methods, including the HSM and related software SafetyAnalyst.  They are a subset of the Model Inventory Roadway Elements (MIRE) and duplicate many of the Highway Performance Monitoring System (HPMS) full extent elements that States are already required to collect (1).  These FDE/HSIP elements include segment, intersection, and ramp data elements and were determined to be the basic set of data elements an agency would need to conduct enhanced safety analysis to support States’ HSIPs.

While the FDE/HSIP were selected in part based on the basic data requirements of existing tools such as such as the HSM and related SafetyAnalyst, they are not exclusive to these tools. The FHWA recognizes that many States are developing analysis tools in-house that will help to support their HSIPs.  The FDE/HSIP are a basic set of elements an agency would need to conduct effective, enhanced safety analysis independent of the specific analysis tools used or methods applied.  All States should be moving towards using analysis tools and having the FDE/HSIP available to utilize these tools, regardless of whether they are the tools developed through Federal efforts or they are developed in-house.

The objective of this effort was to conduct a market analysis of the potential cost to States in developing a statewide location referencing system and collecting the FDE/HSIP on all public roadways.  The primary theory is that collecting additional roadway and traffic data and integrating those data into the safety analysis process will improve an agency’s ability to locate problem areas and apply appropriate countermeasures, hence improving safety.  This effort also investigated potential methodologies that could be applied to estimate the benefits in terms of safety of collecting this additional roadway information.

A literature review was conducted to identify resources to help develop a methodology for analysis of the cost and benefits of collecting roadway data to improve highway safety.  The literature review showed there were no established methodologies to estimate the benefit of collecting roadway data elements for safety.  An alternate approach was developed to conduct the market analysis.  The costs for data collection were gathered from several vendors and one State department of transportation (DOT) that had been investigating a similar effort.  The numbers of fatalities and injuries that would need to be reduced in order to exceed the costs (for a 1:1 and 2:1 ratio) were estimated to determine the benefits.  That is, this analysis identified the benefit required to obtain cost effectiveness.

The cost estimations developed for this analysis reflect the additional costs that States would incur based on what is not already being collected through HPMS or not already being collected through other efforts.  At the time of this analysis, the FHWA did not know the extent of data collection practices for all States beyond HPMS requirements.  In order to accommodate a range of data collection practices among the States, the methodology for the analysis was conservatively based on the assumption that all data collection beyond HPMS requirements would be new collection.  Therefore, this analysis of the additional cost to States is most likely greater than the actual cost that would be incurred.  Individual cost estimates would vary by the circumstances in each State.

Costs

A summary of the additional costs identified includes the following three sets of data elements:

The costs were collected from a variety of vendors and were broken down into a per-mile basis for segments, per intersection, and per ramp.  The summary of data collection costs is shown in Table 1.

Table 1. Summary of Average Data Collection Costs in Addition to HPMS Requirements
(2010 U.S. Dollars)

Data Collection Elements

Per Mile

Per Intersection

Per Ramp

Location Referencing System on
Non-Federal-aid Highways

Total

$40

 

 

21 FDE/HSIP on
 Federal-aid Roadways
(all FDE/HSIP minus HPMS elements)

Elements

$60

$130

$100

Traffic Data

--

$590

$400

22 FDE/HSIP Total

$60

$720

$500

All FDE/HSIP on
Non-Federal-aid Roadways

Elements

$70

$130

$100

Traffic Data

$460

$590

$400

All Elements – Total

$530

$720

$500

Benefits

There are no established methodologies for estimating the safety benefits of collecting roadway data elements.  It was not feasible at the time this analysis was conducted to develop a direct estimate of the safety benefits of collecting roadway inventory data.  In lieu of a traditional cost-benefit estimate, a “cost effectiveness” approach was taken. 

For the purposes of this analysis, work was conducted to determine what safety benefits would need to be realized from data collection in order to exceed the costs of collection. The needed benefits were calculated by developing an estimate of the number of fatalities and injuries that would need to be reduced in order to exceed a 1:1 ratio and a 2:1 ratio of benefits to costs. These estimates were developed for two scenarios:

Scenario 1:

Scenario 2:

For both Scenarios, the first two initiatives would involve developing a statewide relational location referencing system on all public roads, and collecting the FDE/HSIP on all Federal-aid highways.  Scenario 2 adds a third initiative of collecting the FDE/HSIP in all non-Federal-aid roads. 

The analysis period for this effort was established to be 2012 – 2031.  The costs were aggregated out to the State level, and then the estimated needed reductions in fatalities and injuries were determined based on the costs for each scenario. Both the costs and benefits were estimated across the analysis period and discounted to reflect 2010 U.S. dollars. The results of the analysis are shown in Table 2.  

For Scenario 1, the average annual cost of data collection for an average State (based on HPMS mileage) is $6.3 million for initial collection and $3.4 million for maintenance over the analysis period of 2012 – 2031 (in 2010 U.S. dollars).  Using a base of $6,339,701 as the comprehensive cost of a fatality and $516,947 as the comprehensive cost for an injury, a reduction of  0.6 fatalities and 41.0 injuries is required to achieve a greater than 1:1 benefit to cost ratio (2).  For Scenario 2, 2.5 fatalities and 163.7 injuries are needed to achieve greater than a 1:1 benefit.  Scenario 2 includes collecting the FDE/HSIP on both Federal-aid and non-Federal-aid roads.

Table 2. Summary of Analysis for Average State
Analysis Period 2012 – 2031
Average Annual Costs and Needed Benefits
(Millions of 2010 U.S. Dollars)

Scenario

Cost During Collection

Cost During Maintenance

Estimated Fatalities
Needed to Achieve >1:1

Estimated Injuries
Needed to Achieve >1:1

Estimated Fatalities Needed to Achieve- >2:1

Estimated Injuries
Needed to Achieve >2:1

1

$6.3

$3.4

0.6

41.0

1.2

81.6

2

$23.8

$12.8

2.5

163.7

5.0

325.9

Note - Costs are accumulated throughout the entire analysis period; benefits are realized after the data collection is complete.

Future Research

This effort was a preliminary attempt to quantify the costs and benefits of collecting roadway and traffic data for safety.  The primary theory driving the analysis is that collecting additional roadway and traffic data and integrating those data into the safety analysis process will improve an agency’s ability to locate problem areas and apply appropriate countermeasures, hence improving safety.  Based on the work conducted for this effort, including a thorough literature review, it was determined that there are no established methodologies for quantifying the benefits of investing in safety data improvements.  Additional research needs to be conducted to build upon the analysis provided in this report to work towards filling that knowledge gap by developing guidance on the methodologies that can be applied to determine the benefits of investing in data systems and processes for achieving a data-driven safety program.  Developing such methodologies would be the crucial next step to help the FHWA Office of Safety achieve its goal to reduce highway fatalities by providing decision makers the tools they need to make informed decisions through an evidenced-based approach to safety implementation.

Introduction

Quality data are the foundation for making important decisions regarding the design, operation, and safety of roadways.  By incorporating roadway and traffic data into safety analysis procedures, States can better identify safety problems and prescribe solutions to support their Highway Safety Improvement Programs (HSIPs) and implement their Strategic Highway Safety Plans (SHSPs).  Furthermore, a new generation of safety analysis tools and methods are being developed to help identify safety issues and to provide recommendations for improvements.  These safety analysis tools, such as the Highway Safety Manual (HSM) and related software SafetyAnalyst and Interactive Highway Safety Design Model (IHSDM), all require quality roadway, traffic, and crash data to achieve the most accurate results. Using roadway and traffic data together with crash data can help agencies to make decisions that are fiscally responsible and to improve the safety of the roadways for all users.

The Federal Highway Administration (FHWA) has developed guidance for States on implementing their HSIPs.  While HSIP guidance provides information on how safety data should be used, there is no additional detail on the specific data elements that State and local agencies should be collecting, maintaining, and using to support their HSIPs and SHSPs.  The FHWA Model Inventory of Roadway Elements (MIRE) provides a recommended listing of roadway inventory and traffic elements critical to safety management. The MIRE Version 1.0 report includes over 200 roadway and traffic data elements (3). Due to the economic climate, it may not be feasible for States to collect all of the MIRE elements and integrate them into their existing programs.  There remains a need for information on the fundamental roadway and traffic elements that departments of transportation (DOTs) should be collecting to support their HSIPs.

In response to this need, the FHWA held a series of information gathering sessions in 2009 and 2010 and convened a Technical Working Group (TWG) from 2010 through 2011. The purpose of the information gathering sessions and TWG was to determine which set of roadway and traffic data elements States should be collecting, what data States are capable of collecting given the current economic environment, and the importance of using roadway and traffic data to support the States’ HSIPs.

States should have a common statewide location referencing system, such as a geographic information system (GIS) or a linear referencing system, on all public roads.  This will enable States to locate high crash locations on all public roads.  As States expand their inventories, these common statewide systems will enable States to link these locations with additional data systems, such as roadway and traffic data.

States should also be collecting a set of minimum roadway and traffic data elements that are fundamental to support a State’s HSIP on all public roads. This set of elements is herein referred to as the Fundamental Data Elements for HSIP (FDE/HSIP).  The FDE/HSIP include segment, intersection, and ramp data elements and were determined to be the basic set of data elements that an agency would need to conduct enhanced safety analyses to support a State’s HSIP.

Objective

The objective of this effort was to conduct a market analysis of the potential cost to States in developing a statewide location referencing system and collecting the FDE/HSIP on all public roadways.  The primary theory is that collecting additional roadway and traffic data and integrating those data into the safety analysis process will improve an agency’s ability to locate problem areas and apply appropriate countermeasures, hence improving safety.

Background

The following sections provide additional background on the use of safety data in the HSIP, the MIRE elements, and the FDE/HSIP, as each relates to this effort.

Use of Safety Data in the HSIP

Graphic. Logo for the Highway Safety Improvement Program. Includes the slogan: "Data Driven Decision"In 2009, 33,808 people died in motor vehicle traffic crashes in the U.S.  According to the U.S. DOT, the total societal cost of crashes exceeds $230 billion annually (4).  The Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users (SAFETEA-LU), which was signed into law on August 10, 2005, established the HSIP as a core Federal-aid program.  The overall objective of the HSIP is to significantly reduce the occurrence of fatalities and serious injuries resulting from crashes on all public roads.  The FHWA established a formalized HSIP process to ensure that the HSIP is carried out in an organized, systematic manner where the greatest benefits are achieved. 

The 23 Code of Federal Regulations (CFR) Part 924 states that “The HSIP shall include a data-driven SHSP and the resulting implementation through highway safety improvement projects.”  Further, it defines a SHSP as “a comprehensive, data-driven safety plan developed, implemented, and evaluated in accordance with 23 U.S.C. 148”(5).

While the formalized HSIP process detailed in 23 CFR Part 924 addresses the use of safety data in the HSIP, there is no additional detail on the specific data elements that agencies should be collecting, maintaining, and using to support their HSIPs and development and implementation of their SHSPs.  This was highlighted by the Government Accountability Office (GAO) Report 09-035 on the HSIP.  The report, titled Highway Safety Improvement Program, Further Efforts Needed to Address Data Limitations and Better Align Funding with States’ Top Safety Priorities regarding the HSIP, contained recommendations regarding data needs to help fill identified gaps (6).  These recommendations, which the FHWA accepted for action, include the following:

There still remains a need for guidance for the fundamental roadway and traffic data elements that States should be collecting to support their HSIP.

Model Inventory of Roadway Elements

Graphic. Image of the cover for the Model Inventory of Roadway Elements (MIRE) Version 1.0 Report.MIRE, the Model Inventory of Roadway Elements, is a recommended listing of roadway inventory and traffic elements critical to safety management (3).  MIRE is intended as a guideline to help transportation agencies improve their roadway and traffic data inventories.  It provides a basis for what can be considered a good/robust data inventory and helps agencies move towards the use of performance measures.

There are a total of 202 elements that comprise the MIRE listing.  These elements are divided among three broad categories: roadway segments, roadway alignment, and roadway junctions.  There are many benefits to State and local transportation agencies in expanding their inventories through the collection of MIRE elements.  Having these additional data can help better identify where the safety problems are, what those problems are, and how best to treat them.  Additional information on MIRE, including the full listing of elements, can be found at http://www.mireinfo.org.

MIRE is intended as guidance and provides a comprehensive listing of the data elements to support the HSIP.  However, due to the economic climate, it may not be feasible for States to collect all of the MIRE elements and integrate them into their existing programs.

Fundamental Data Elements for HSIP (FDE/HSIP)

While MIRE provides a comprehensive listing of roadway and traffic data elements, it may not be feasible for States to collect all of the 200+ MIRE elements and integrate them into their existing programs.  State departments of transportation (DOTs), particularly highway safety agencies, are facing increasing demands and decreasing resources. Additionally, the 23 CFR 924 provides only general information on how safety data should be used; it does not provide details on specific data elements (5).  There remains a need for information on a minimum set of fundamental roadway and traffic elements that DOTs should be collecting to support their HSIPs.

In order to address the States’ safety data improvements challenges, the FHWA held a series of information gathering sessions and convened a TWG. The purpose of the TWG was to determine the roadway and traffic data elements that States should be collecting, what States are capable of collecting given the current economic environment, and the importance of using roadway and traffic data in the safety analysis process. 

States should have a common statewide location referencing system, such as geographic information system (GIS) or a linear referencing system, on all public roads.  This will enable States to locate high crash locations on all public roads in the State.  As States expand their inventories, this common system will enable States to link these locations with additional data systems, such as roadway and traffic data.

States should also be collecting a set of minimum roadway and traffic data elements on all public roads that are fundamental to support a State’s HSIP - the FDE/HSIP.  These are based on the elements needed to apply HSM roadway safety management (Part B) procedures using network screening analytical tools (such as SafetyAnalyst), are a subset of MIRE, and duplicate many of HPMS full extent elements that States are already required to collect on Federal-aid Highways. The FDE/HSIP are comprised of roadway segment, intersection, and ramp elements as shown in Table 3.

The FDE/HSIP are a basic set of elements an agency would need to conduct effective, enhanced safety analysis independent of the specific analysis tools used or methods applied.  While the FDE/HSIP were selected in part based on the basic data requirements of existing tools such as the HSM and related SafetyAnalyst, they are not exclusive to these tools. The FHWA recognizes that many States are developing analysis tools in-house that will help to support their HSIPs.  All States should be moving towards using analysis tools and having the FDE/HSIP available to utilize these tools, regardless of whether they are the tools developed through Federal efforts or they are developed in-house.

Table 3. FDE/HSIP Elements.

FDE/HSIP Elements

Definition


Roadway Segment

Segment ID*

Unique segment identifier.

Route Name*

Signed numeric value for the roadway segment.

Alternate Route Name*

The route or street name, where different from route number.

Route Type*

Federal-aid/NHS route type.

Area Type*

The rural or urban designation based on Census urban boundary and population.

Date Opened to Traffic

The date at which the site was opened to traffic.

Start Location*

The location of the starting point of the roadway segment.

End Location*

The location of the ending point of the roadway segment.

Segment Length*

The length of the segment.

Segment Direction

Direction of inventory if divided roads are inventoried in each direction.

Roadway Class*

The functional class of the segment.

Median Type

The type of median present on the segment.

Access Control*

The degree of access control.

Two-Way vs. One-Way Operation*

Indication of whether the segment operates as a one- or two-way roadway.

Number of Through Lanes*

The total number of through lanes on the segment. This excludes turn lanes and auxiliary lanes.

Interchange Influence Area on Mainline Freeway

The value of this item indicates whether or not a roadway is within an interchange influence area.

AADT*

The average number of vehicles passing through a segment from both directions of the mainline route for all days of a specified year.

AADT Year*

Year of AADT.


Intersection

Intersection ID

A unique junction identifier.

Location

Location of the center of the junction on the first intersecting route (e.g., route-milepost).

Intersection Type The type of geometric configuration that best describes the intersection/junction.
Date Opened to Traffic The date at which the site was opened to traffic.

Traffic Control Type

Traffic control present at intersection/junction.

Major Road AADT

The Annual Average Daily Traffic (AADT) on the approach leg of the intersection/junction.

Major Road AADT Year

The year of the Annual Average Daily Traffic (AADT) on the approach leg of the intersection/junction.

Minor Road AADT

The Annual Average Daily Traffic (AADT) on the approach leg of the intersection/junction.

Minor Road AADT Year

The year of the Annual Average Daily Traffic (AADT) on the approach leg of the intersection/junction.

Intersection Leg ID

A unique identifier for each approach of an intersection.

Leg Type

Specifies the major/minor road classification of this leg relative to the other legs in the intersection.

Leg Segment ID

A unique identifier for the segment associated with this leg.


Ramp/Interchange

Ramp ID*

An identifier for each ramp that is part of a given interchange. This defines which ramp the following elements are describing.

Date Opened to Traffic

The date at which the site was opened to traffic.

Start Location

Location on the roadway at the beginning ramp terminal (e.g., route-milepost for that roadway) if the ramp connects with a roadway at that point.

Ramp Type

Indicates whether the ramp is used to enter or exit a freeway, or connect two freeways.

Ramp/Interchange Configuration

Describes the characterization of the design of the ramp.

Ramp Length

Length of ramp.

Ramp AADT*

AADT on ramp.

Ramp AADT Year

Year of AADT on ramp.

*HPMS full extent elements required on all Federal-aid highways and ramps located within grade-separated interchanges, i.e., NHS and all functional systems excluding rural minor collectors and locals.

In 2011, the FHWA Office of Safety released a guidance memorandum on the fundamental data elements that States should be collecting and incorporating into their safety analyses to support their HSIPs and indicate on what roadways they should be collecting data.  In addition to the memorandum, the FHWA Office of Safety has also developed the Background Report: Guidance for Roadway Safety Data to Support the Highway Safety Improvement Program, to support the guidance set forth in memorandum and act as a counterpart to this analysis (7).  The Background Report provides additional detail on FDE/HSIP, existing and emerging data collection methodologies, estimated costs of collection (based on the results of this market analysis), potential funding sources, and model performance measures.

Literature Review

The literature review for this research effort focused on identifying literature pertaining to the costs and benefits of collecting data.  This extensive search looked at sources both within the transportation industry and expanded to fields outside of transportation including forestry, medicine and health, ecology, water resources, and mining.  Literature from these fields was reviewed for any pertinent methodologies or findings that could be helpful to this research effort.  The findings from the review were used to help develop a methodology for conducting a market analysis of the cost and benefits of collecting roadway data to improve highway safety.  Most of the literature did not contain information directly relevant to developing a methodology for this type of cost-benefit analysis; however, there were a few resources that provided useful information, and these are summarized in the following paragraphs.

The Colorado DOT conducted a study evaluating the statewide economic benefits of future transportation investments.  The research investigated the benefits of additional transportation spending above what is needed to maintain current transportation performance levels.  The researchers were able to quantify certain benefits related to transportation improvements, including reduced congestion, pavement quality, safety improvements, and general system improvements.  Other benefits (e.g., quality of life, new jobs, and better access to recreation) that they were unable to quantify for the economic analysis were still determined to have a positive impact (8).

Several reports provided information on the cost of collecting roadway data.  A 1998 report from the FHWA investigated the cost and quality issues associated with collecting and managing highway safety data (9).  In 2009, a North Carolina DOT research effort collected asset management data on 95 miles of roadway to determine the capabilities and limitations of automated roadway data collection systems.  Various vendors were used to collect a sampling of pavement, roadside, geotechnical, and bridge elements (10).  In a similar effort, the Transportation Research Board (TRB) Strategic Highway Safety Research Program (SHRP2) conducted a roadway data collection “rodeo” where vendors used mobile data collection units to collect over 100 roadway data elements. Information from the vendors who participated in both of these data collection efforts was used to help develop cost estimates for the market analysis (11).

A recent study by Li et al. presents a methodology for a benefit-cost analysis of improving highway segment safety hardware over its life cycle.  The researchers established a safety index by assessing the risk of vehicle crashes with safety-related attributes on the roadway segment.  An annual potential for safety improvements associated with improvements to the hardware was calculated and compared to the number of collisions on the segment with and without hardware upgrades.  The methodology outlined in this report relies on a sufficient amount of historical data, including vehicle crashes, highway system preservation, traffic operations, and expenditures, as well as data processing and analysis capabilities.  This methodology was too specific for the purpose of developing this market analysis but presented a vision on how future data efforts could be quantified, comparing locations without data and locations with data (12).

A full list of all of the literature reviewed for this project, including a brief summary of each resource, can be found in Appendix A.

Methodology

Overview

Based on the results of the literature review, communications with States, discussions with experts, and review of the Office of Management and Budget (OMB) guidance (13), an appropriate methodology was developed to meet the objectives of this effort given the available information.  

The literature review showed there were no established methodologies to estimate the benefit of collecting roadway data elements for safety. No one State was identified that has collected the exact list of FDE/HSIP on all public roadways within the State.  Therefore, an analysis of collecting all 37 FDE/HSIP to determine the safety benefits was not feasible at the time this investigation was conducted.

An alternate approach was developed to conduct the market analysis.  The costs for data collection were provided from several vendors and one State DOT that had been investigating conducting a similar effort. The number of fatalities and injuries that would need to be reduced in order for the monetized benefits to exceed the costs was estimated to determine the benefits.  The methodology developed is a hybrid of a benefit-cost analysis and a cost effectiveness analysis.

The cost estimations developed for this analysis reflect the additional costs that States would incur based on what is not already being collected through HPMS or not already being collected through other efforts.  At the time of this analysis, the FHWA did not know the extent of data collection practices for all States beyond HPMS requirements.  In order to accommodate a range of data collection practices among the States, the methodology for the analysis was conservatively based on the assumption that all data collection beyond HPMS requirements would be new collection.  Therefore, this analysis of the additional cost to States is most likely greater than the actual cost that would be incurred.  Individual cost estimates would vary by the circumstances in each State.

A location referencing system is already required under HPMS for all Federal-aid highways. In addition, 16 of the 38 FDE/HSIP are also already required for collection under the HPMS for the full extent of Federal-aid highways (1).  Full extent accounts for all Federal-aid highways and ramps located within grade-separated interchanges (i.e., NHS and all functional systems excluding rural minor collectors and locals). Table 3 indicates which of the 38 FDE/HSIP are HPMS full extent elements.

Data Collection Costs

The additional costs identified include the following three sets of data elements:

In order to conduct the analysis, costs were obtained from 12 data collection vendors from around the country. Costs were obtained from the vendors on a per-mile basis along segments, a per-intersection basis for intersections, and a per-ramp basis for ramps.  The costs for developing a location referencing system were estimated per mile.  For the case of traffic counts on segments, an estimate of one count per mile was used to estimate to generate a per mile cost.  These costs included data collection and reduction for integration into a State’s existing system.

Vendors were identified based on the list of vendors involved in the North Carolina and the Transportation Research Board Strategic Highway Research Program 2 (TRB SHRP2) data collection rodeos which were both conducted in 2008.  These rodeos were conducted to test the capabilities of roadway data collection technologies.  Many of the rodeo vendors only collected roadway inventory elements and not traffic counts, so the project team also identified several companies that collect traffic counts to obtain cost estimates.  The (non-traffic) roadway elements are collected using different methods than the traffic data, and, therefore, the costs for each were calculated separately.

The majority of vendors estimated that they would use digital data collection vans to collect the roadway inventory data.  For traffic count data, vendors provided cost estimates based on 48-hour classification counts for segment traffic data, peak hour manual counts for intersections, and technology similar to segment counts to collect ramp data.  The costs provided were averaged to develop estimates.

The analysis was based on information provided by vendors and reflects the methods and costs that would be used if the collection was contracted.   There are other methods of collecting some of these data elements, including extracting the data from existing plans or visual imagery such as aerials or Google Earth.  Some of these methods may be lower in costs, particularly if the cost of agency personnel are not included as part of the costs.

In addition, several State DOTs were contacted to obtain estimates of what the costs would be to collect these “in-house” rather than contract the data collection out to a vendor.  Since the data collection was very specific to this list of FDE/HSIP, the majority of States contacted could not provide an estimate of costs.  Only one State that was considering conducting a similar effort provided cost information. However, that State was only considering the collection on intersections.  The analysis was conducted using the estimates provided by the vendors, acknowledging that these are conservative estimates, and there may be more cost effective methods available (but information for those methods was not available).

Benefits

For the purposes of this analysis, the benefits were calculated by developing an estimate of the benefits needed to exceed a 1:1 ratio and a 2:1 ratio of benefits to costs.  The first step in the analysis was to calculate the cost of a fatality and the cost of an injury.  The 2008 comprehensive cost of a fatality used in the analysis was $6,339,701 and $516,947 for an injury, based on information provided by the National Highway Traffic Safety Administration (NHTSA) (2).  The injury costs reflect a Maximum Abbreviated Injury Scale (MAIS) Level 3 injury.  MAIS injuries are on a scale of 0-5, with 5 being the most severe non-fatal injury.  MAIS Level 3 was chosen as a “mid-point” in this scale.

The future cost of a fatality and injury were forecasted out 20 years to 2031 and then discounted to reflect 2010 dollar values.  A discount rate of 7.0 percent was used.  The benefit estimation assumed that the benefits would not be realized until the data collection is complete: 2021 for Federal-aid and 2022 for non-Federal-aid roads.
An average of the costs of a fatality and the cost of an injury from 2021 through 2032 was calculated.  This calculation provided the cost of a fatality and the cost of an injury, represented in 2010 dollars.

In order to determine the balance of the number of fatalities and injuries that should be used in calculating the benefits, a ratio of the number of fatalities to injuries was calculated using 2009 crash data.  In 2009 there were 33,808 total fatalities and 2,217,000 total injuries (14), equating to a fatality to injury ratio of approximately 1:66.  Using that ratio, the number fatalities and injuries needed to exceed a 1:1 ratio and a 2:1 ratio of benefits to cost was developed for each State, and for each scenario.

Classification of Roadway Ownership

Costs were aggregated to a State level to estimate the reduction in crashes (fatalities and serious injuries) needed to exceed the costs.  The first step in the analysis was to develop a classification of roadway ownership for each State.  Three States were analyzed: an “average” State, a small State (information from Rhode Island was used to represent a small State), and a large State (information from California was used to represent a large State).  To calculate the costs for each State, the mileage, number of intersections, and number of ramps was determined for the Federal-aid and non-Federal-aid roadways.  The mileage was obtained from the FHWA Office of Highway Policy Information (OHPI) (15).  The mileage for the “average” State was calculated using the U.S total (including Washington, DC) and dividing by 51.

There is not yet an estimate of intersections or ramps available through the OHPI.  Therefore, the project team contacted States directly to obtain estimates of the number of intersections and ramps in each State.  In addition to a large State and a small State, Missouri and Ohio were contacted to obtain estimates for the “average” State.  Missouri and Ohio were chosen to represent the “average” State based on their land mass, roadway mileage, and geographic locations.

All of the States except California were able to provide the total number of intersections and ramps in the State.  In California, the total number of intersections was estimated based on the total number of miles in the State. The distribution of mileage of Federal-aid and non-Federal-aid roadways was used to estimate the same distribution for intersections.  This assumes there is the same density of intersections per mile on each roadway set.

The number of ramps provided by the States was applied to the Federal-aid roadways with the justification that there would most likely not be ramps on non-Federal-aid roads.  The distribution of roadway ownership by State, mileage, intersections, and ramps is shown in Table 4.

Table 4. Breakdown of Roadway Ownership.

State

Mileage Federal-aid

Mileage Non-Federal-aid

Intersections Federal-aid

Intersections Non-Federal-aid

Ramps Federal-aid

Ramps Non-Federal-aid

Average State

19,430

57,390

70,430

208,020

4,450

0

Rhode Island

1,750

4,600

27,560

72,440

380

0

California

55,230

103,490

132,370

248,030

14,660

0

Aggregated Costs

The aggregated costs were developed for two scenarios:

For both Scenarios, the first two initiatives involve developing a statewide relational location referencing system on all public roads, and collecting the FDE/HSIP on all Federal-aid highways.  Scenario 2 adds a third initiative of collecting the FDE/HSIP in all non-Federal-aid roads. 

The base cost for mileage, intersections, and ramps was then disaggregated annually.  The time frames include five years for segments, seven years for intersections, and nine years for ramps on Federal-aid roads; and six, eight, and ten years respectively for non-Federal-aid roadways.  These time frames were selected as reasonable intervals for State and local agency collection of the FDE/HSIP data.

For this analysis, data collection was estimated to begin in 2012 and continue for nine years to 2020 for Federal-aid roadways, and continue for ten years to 2021 for non-Federal-aid roadways.  The analysis assumes an equal distribution of costs over the data collection period.

In addition to the costs of initial data collection, the costs to maintain the data were also calculated.  That is, the costs to update the data as conditions change.  For segment data, it was assumed that five percent of the roadway mileage would be updated annually.  These updates would not be done by re-collecting the data, but rather based on updates from construction/design plans.  It was approximated that updating the inventory would take two hours per mile by an employee earning $20.00 an hour (approximately $40,000 per year).

The intersection inventory would be updated on a three-year cycle for signalized intersections and a five-year cycle for unsignalized intersections.  This assumes that traffic volumes will not change dramatically at unsignalized intersections.  A split of 20 percent of signalized intersections and 80 percent of unsignalized intersections was used to determine the number of signalized and unsignalized intersections.  In addition, the cost of inventory updates was also included in the maintenance costs.

The analysis assumes that a ramp inventory would be updated on a six-year cycle, with counts and inventory updates collected on one-sixth of the ramps per year.

The costs for coding and locating crashes on non-Federal-aid roads was also calculated since States would now have the information they need to locate crashes, which they would not have had previously.  National statistics were obtained from NHTSA to estimate a ratio of fatal crashes to injury crashes (14).  The number of fatal crashes on non-Federal-aid roads was obtained from the NHTSA Fatality Analysis Reporting System (FARS) (16). The ratio of fatal to injury crashes was applied to the number of fatal crashes on non-Federal-aid highways to obtain an estimate of injury crashes on non-Federal-aid highways. Costs for locating and coding these additional crashes were then applied. It was assumed that five crashes could be coded per hour at a cost of $20/hour. These costs only pertain to the costs of coding and locating fatal and injury crashes.  The number of property damage only crashes on non-Federal-aid roads could be not reasonably estimated; therefore, they were not included.

These assumptions on data collection cycles, maintenance, and crash coding were based on standard practices obtained through discussions with several States.

Once the costs for collection, maintenance, and coding of the data were determined, they were summed to establish a total cost per year out to 2032.  This timeframe would allow for the total 10-year data collection period (for non-Federal-aid roads) and an additional 10 years of implementation.  These costs were then discounted using a 7.0 percent discount rate per the OMB guidance to bring the costs back to 2010 values (13).  Once the costs were all in the same value year, an annual average cost during the data collection period and an annual average cost during the maintenance period was calculated.

Results

The results of the analysis are shown in the following sections.

Costs

The additional costs identified include the following three sets of data elements:

Table 5 provides the calculated average cost per mile, per intersection, and per ramp for each of the sets of elements.

Table 5. Summary of Average Data Collection Costs in Addition to HPMS Requirements.
(2010 U.S. Dollars)

Data Collection Elements

Per Mile

Per Intersection

Per Ramp

Location Referencing System on
Non-Federal-aid Highways

Total

$40

 

 

22 FDE/HSIP on
 Federal-aid Roadways
(all FDE/HSIP minus HPMS elements)

Elements

$60

$130

$100

Traffic Data

--

$590

$400

22 FDE/HSIP Total

$60

$720

$500

All FDE/HSIP on
Non-Federal-aid Roadways

Elements

$70

$130

$100

Traffic Data

$460

$590

$400

All Elements – Total

$530

$720

$500

Benefits

The benefits, in terms of the number of fatalities and injuries that would need to be reduced in order to achieve a greater than 1:1 and greater than 2:1 benefit to cost ratio, were determined for each State and for each scenario.  

The future cost of a fatality and injury were forecasted out to 2031 and then discounted to reflect 2010 dollar values.  The costs were then averaged across the analysis period to provide the cost of a future fatality and the cost of an injury represented in 2010 dollars.

For Scenario 1, this resulted in an average future cost of approximately $2.2 million for a fatality and $0.2 million for an injury in 2010 dollars. Since the benefit estimation assumed that the benefits would not be realized until the data collection is complete (2021 for Federal-aid and 2022 for non-Federal-aid roads), the estimates varied slightly for Scenario 2. For Scenario 2, the average future cost was approximately $2.1 million for a fatality and $0.2 million for an injury in 2010 dollars.

In order to determine the balance of the number of fatalities and injuries that should be used in calculating the benefits, a ratio of the number of fatalities to injuries was calculated using 2009 crash data.  In 2009 there were 33,808 total fatalities and 2,217,000 total injuries, equating to a fatality to injury ratio of approximately 1:66 (14).  Using that ratio, the number fatalities and injuries needed to exceed a 1:1 ratio and a 2:1 ratio of benefits to costs was developed for each State, and for each scenario.

The results of the analysis are presented in the following sections.

Scenario 1

The summary of the average annual costs and required benefits for Scenario 1 are shown in Table 6.  For an average State, 0.6 fatalities and 41.0 injuries would need to be reduced per year in order to achieve a greater than 1:1 benefit to cost ratio.  This increases to 1.2 fatalities and 81.6 injuries that would need to be reduced per year to achieve a greater than 2:1 benefit to cost ratio for an average State.  This ranges from 0.5 fatalities for a small State to 2.5 fatalities for a large State.

Table 6. Summary Average Annual Cost and Needed Benefit for Scenario 1.
(Millions of 2010 U.S. Dollars)

State

Cost  of Collection

Cost  of Maintenance

Cost of a Fatality

Cost of an Injury

Needed Fatalities

Needed Injuries

Benefit > 1:1 

Average State

$6.3

$3.4

$2.2

$0.2

0.6

41.0

Small State

$2.4

$1.3

$2.2

$0.2

0.2

15.5

Large State

$12.6

$6.7

$2.2

$0.2

1.2

80.8

Benefit > 2:1

Average State

$6.3

$3.4

$2.2

$0.2

1.2

81.6

Small State

$2.4

$1.3

$2.2

$0.2

0.5

30.8

Large State

$12.6

$6.7

$2.2

$0.2

2.5

160.8

Note - Costs are accumulated throughout the entire analysis period; benefits are realized after the data collection is complete.

Scenario 2

The summary of the average annual costs and required benefits for Scenario 2 are shown in Table 7.  For an average State, 2.5 fatalities and 163.7 injuries would need to be reduced per year in order to achieve a greater than 1:1 benefit to cost ratio.  This increases to 5.0 fatalities and 325.9 injuries that would need to be reduced to achieve a greater than 2:1 benefit to cost ratio for an average State.  This ranges from 1.7 fatalities for a small State to 7.3 fatalities for a large State.

Table 7. Summary Average Annual Cost and Needed Benefit for Scenario 2.
(Millions of 2010 U.S. Dollars)

State

Cost of Collection

Cost of Maintenance

Cost of a Fatality

Cost of an Injury

Needed Fatalities

Needed Injuries

Benefit > 1:1

Average State

$23.8

$12.8

$2.1

$0.2

2.5

163.7

Small State

$8.2

$4.5

$2.1

$0.2

0.9

57.3

Large State

$36.0

$17.7

$2.1

$0.2

3.7

241.1

Benefit > 2:1

Average State

$23.8

$12.8

$2.1

$0.2

5.0

325.9

Small State

$8.2

$4.5

$2.1

$0.2

1.7

114.0

Large State

$36.0

$17.7

$2.1

$0.2

7.3

479.9

Note - Costs are accumulated throughout the entire analysis period; benefits are realized after the data collection is complete.

While this report provides estimates for an the average, small and large State, the FHWA Office of Safety has developed a spreadsheet tool to help States better estimate the cost to collect FDE/HSIP for their specific State. This spreadsheet takes into account collection costs spread over a specified time frame, ongoing costs to maintain the additional data, and other factors involved in the collection and maintenance of data.  It also provides States an estimate of how many fatalities and injuries would need to be reduced in order to exceed the data collection costs using the methodology laid out in this report.

Summary

The purpose of this effort was to conduct a market analysis of the development of a statewide common location referencing system and the collection of the FDE/HSIP on all public roads.  The primary theory is that collecting additional roadway and traffic data, and integrating those data into the safety analysis process, will improve an agency’s ability to locate problem areas and apply appropriate countermeasures, hence improving safety.

A literature review was conducted to identify resources to help develop a methodology for analysis of the cost and benefits of collecting additional roadway data to improve highway safety.  The literature review showed there were no established methodologies to estimate the benefit of collecting roadway data elements for safety.  An alternate approach was developed to conduct the market analysis.  The costs for data collection were gathered from vendors and State DOT.  For benefits, an estimate of how many fatalities and injuries would need to be reduced in order exceed the costs (for a 1:1 and 2:1 ratio) were developed.  That is, this analysis identified the benefit required to obtain cost effectiveness.

The additional costs identified include the following three sets of data elements:

The costs were collected from a variety of vendors and a State DOT, and were broken down into per mile (for segments), per intersection, and per ramp costs.

When the costs were aggregated out to the State level, the estimated reduction in fatalities and injuries were determined based on the costs for each Scenario.   Table 8 shows the range of data collection costs and estimated required benefits for the average State for both scenarios.  For Scenario 1, the total cost of data collection for an average State (based on HPMS mileage) is $6.3 million for initial collection, and $3.4 million for maintenance over the analysis period of 2012 – 2031 (in 2010 U.S. dollars).  A reduction of 0.6 fatalities and 41.0 injuries is required to achieve a greater than 1:1 benefit to cost ratio.  This increases in Scenario 2, which also includes collecting the FDE/HSIP on all non-Federal-aid roads.  For Scenario 2, 2.5 fatalities and 163.7 injuries are needed to achieve greater than a 1:1 benefit.

Table 8. Summary of Market Analysis for Average State.
Analysis Period 2012–2031
Average Annual Costs and Needed Benefits
(Millions of 2010 U.S. Dollars)

Scenario

Cost During Collection

Cost During Maintenance

Estimated Fatalities
Needed to Achieve >1:1

Estimated Injuries
Needed to Achieve >1:1

Estimated Fatalities Needed to Achieve- >2:1

Estimated Injuries
Needed to Achieve >2:1

1

$6.3

$3.4

0.6

41.0

1.2

81.6

2

$23.8

$12.8

2.5

163.7

5.0

325.9

Note - Costs are accumulated throughout the entire analysis period; benefits are realized after the data collection is complete.

The work conducted for this project was a preliminary attempt to quantify the costs and benefits of collecting roadway and traffic data for safety.  The primary theory driving the analysis is that collecting additional roadway and traffic data and integrating those data into the safety analysis process will improve an agency’s ability to locate problem areas and apply appropriate countermeasures, hence improving safety.  Based on the work conducted for this effort, including a thorough literature review, it was determined that there are no established methodologies for quantifying the benefits of investing in safety data improvements.  Additional research needs to be conducted to build upon the analysis provided in this report to work towards filling that knowledge gap by developing guidance on the methodologies that can be applied to determine the benefits of investing in data systems and processes for achieving a data-driven safety program.  Developing such methodologies would be the crucial next step to help the FHWA Office of Safety achieve its goal to reduce highway fatalities by providing decision makers the tools they need to make informed decisions through an evidenced-based approach to safety implementation.


References

  1. Federal Highway Administration, Office of Highway Policy Information, Highway Performance Monitoring System, Accessed online August 2010. https://www.fhwa.dot.gov/policyinformation/hpms.cfm.
  2. Unpublished values provided by National Highway Traffic Safety Administration.
  3. Lefler, N; F. Council; D. Harkey; D. Carter; H. McGee; and M. Daul. Model Inventory of Roadway Elements - MIRE, Version 1.0. Federal Highway Administration, FHWA-HRT-10-048, Washington, DC, October 2010.
  4. Facts & Statistics, FHWA Safety Program, Federal Highway Administration, Accessed May 10, 2011, http://safety.fhwa.dot.gov/facts_stats/.
  5. Federal Highway Administration, Federal-Aid Policy Guide, Title 23 - Code of Federal Regulations, Subchapter J – Highway Safety. Accessed online June 16, 2011, https://www.fhwa.dot.gov/legsregs/directives/cfr23toc.htm.
  6. Government Accountability Office (GAO), Report 09-035: Highway Safety Improvement Program, Further Efforts Needed to Address Data Limitations and Better Align Funding with States’ Top Safety Priorities Regarding the HSIP, November 2008.
  7. Lefler, N; R. Fiedler; H. McGee; R. Pollack; and J. Miller. Background Report: Guidance for Roadway Safety Data to Support the Highway Safety Improvement Program.  Federal Highway Administration, FHWA-SA-11-39, publication pending.
  8. Pickton, Todd, et al. Statewide Economic Benefits of Transportation Investment, Colorado Department of Transportation, 2007.
  9. Pfefer, Ronald C., et al. Highway Safety Data: Costs, Quality, and Strategies for Improvement Research Report, Federal Highway Administration, 1998.
  10. Kim, Y. Richard, et al. Asset Management Inventory and Data Collection, North Carolina Department of Transportation, 2009.
  11. Fay, Charles Sr., SHRP 2 Roadway Projects - Safety Symposium 2010 (presentation), Transportation Research Board Strategic Highway Research Program 2, 2010.
  12. Li, Zongzhi, et al. Project-Level Life-Cycle Benefit-Cost Analysis Approach for Evaluating Highway Segment Safety Hardware Improvements, Transportation Research Record (2160), 2010.
  13. Office of Management and Guidance. Circular A-94,  https://www.whitehouse.gov/omb/circulars_a094/.
  14. National Highway Traffic Safety Administration Traffic Safety Facts: Highlights of 2009 Motor Vehicle Crashes, http://www-nrd.nhtsa.dot.gov/Pubs/811363.pdf.
  15. Highway Statistics, 2008. Table HM-14 Federal Aid Highway Length – 2008 Miles by Ownership. FHWA Office of Policy, October 2009.
  16. Fatality Analysis Reporting System (FARS). National Highway Traffic Safety Administration. http://www-fars.nhtsa.dot.gov/Main/index.aspx.

 

Appendix A: Literature Matrix

Source

Author(s)

Publication

Year

Summary


Transportation Sources

Colorado DOT

Todd Pickton, Janet Clements, Robert W. Felsburg

Statewide Economic Benefits of Transportation Investment

2007

Evaluates statewide economic benefits of future transportation investment in CO using data and benefits studies from other states.

Colorado DOT

Jim Mascolo, Ginger Pelz, Doug Magee

2008 Safety Engineering Annual Report

2008

Report was identified but could not be located.  

County Road Association of Michigan and Michigan DOT

County Road Association of Michigan and Michigan DOT

PASER Cooperative Road Condition Survey Demonstration Project

2001

Description of GPS/GIS asset management data collection effort.

FHWA

Ronald C. Pfefer, Richard A. Raub, Roy E. Lucke

Highway Safety Data: Costs, Quality, and Strategies for Improvement Research Report

1998

Identifies costs of collecting, reporting, and managing safety data.

Florida DOT

Iskandaria Masduki, Margaret Armstrong, Amy Finley, Rebecca Augustyniak, Kea Herron

Applying Instructional Design Practices to Evaluate and Improve the Roadway Characteristics Inventory (RCI) Training Curriculum

2010

Evaluates FDOT's training program for district data collection technicians on the Roadway Characteristics Inventory (RCI) methods. Focuses on an instructional design strategy to improve the training and reduce its cost.

NC Department of Transportation

Y. Richard Kim, Joseph E. Hummer, Mohammed Gabr, David Johnston, B., Shane Underwood, Daniel J. Findley and Christopher M. Cunningham

Asset Management Inventory and Data Collection

2009

Results of an effort in NC to collect asset management data on 95 miles on roadway.

NCHRP (Project 8-36, Task 22)

Cambridge Systematics

Working Paper #1: Economic Benefits of Transportation Investment

2002

Presents basic information on how safety improvements save lives and the related economic benefit. No discussion on data collection or project selection

NCHRP (Project 8-36, Task 22)

Cambridge Systematics

Working Paper #3: Community and Social Benefits of Transportation Investment

2002

Discusses safety improvements of specific treatments. No information presented that adds to current knowledge that would assist in this effort.

NHTSA

L. Blincoe, A. Seay, E. Zaloshnja, T.Miller, E. Romano, S.Luchter, R.Spicer

The Economic Impact of Motor Vehicle Crashes, 2000

2002

Report presents analysis results of motor vehicle crash costs in the US in 2000.

SHRP 2

Charles Fay, Sr.

SHRP 2 Roadway Projects - Safety Symposium 2010 (presentation)

2010

This presentation reviewed an ongoing SHRP2 projects on roadway data collection. It provided a list of vendors who participated in their data collection rodeo.

TR News, Number 254

Bradley J. Overturf

A Roadway Photolog Goes High-Definition: Connecticut Expands User Network, Realizes Cost Savings

2008

The Connecticut Department of Transportation (DOT) has created a high definition image inventory of the State's entire roadway network, accessible for desktop computer viewing by users throughout the agency. The DOT's photolog director traces the development and capabilities of the pioneering system, which has saved the state approximately $2 million.

Transportation Research Record (1719)

James P. Hall, Tschangho John Kim, Michael I. Darter

Cost-Benefit Analysis of Geographic Information System Implementation: Illinois Department of Transportation

2000

Paper presents an investigation of the costs and benefits of geographic information system (GIS) implementation in the Illinois DOT. Addresses the need to determine the organizational impact and cost-effectiveness of the technology to achieve the greatest benefit.

Transportation Research Record (2160)

Zongzhi Li, Samuel Labi, Matthew Karlaftis, Konstantinos Kepaptsoglou, Montasir Abbas, Bei Zhou, Sunil Mandanu

Project-Level Life-Cycle Benefit-Cost Analysis Approach for Evaluating Highway Segment Safety Hardware Improvements

2010

Presents a methodology for a benefit-cost analysis of improving highway segment safety hardware over its life cycle. Calculates the annual potential for safety improvements associated with the upgrading of hardware by reductions in fatal, injury, and PDO collisions.

TRB Research E-Circular (E-C077)

James P. Hall

Enhancing the Value of Data Programs: A Peer Exchange

2005

Summarizes the proceedings from a peer exchange forum, organized to raise awareness of data programs, share best practices and ideas for addressing data gaps and other emerging problems.

University of Arkansas

Kelvin C.P. Wang, Weiguo Gong, Zhiqiong Hou

Networked Sensor System for Automated Data Collection and Analysis

2008

This research describes the development of a real-time multi-functional system for roadway data acquisition and analysis with multiple sensors. This system, Digital Highway Data Vehicle (DHDV), combined the technologies of laser illumination based digital imaging, inertial profiling and GPS mapping into an integrated system to accomplish the multiple tasks of survey and management for roadway data.

University of South Florida

Linjun Lu, Jian John Lu, Pei Sung Lin, Zhenyu Wang, Hongyun Chen

Developing and Interface Between FDOT's Crash Analysis Reporting System and the Safety Analyst

2009

This research presents a method to convert information from FDOT's Crash Analysis Reporting (CAR) System to a format that can be used in the SafetyAnalyst software. Other databases were also investigated, such as the Roadway Characteristics Inventory (RCI), for their compatibility with SafetyAnalyst.

Volpe National Transportation Systems Center, FHWA

S.C. Dresley, A. Lacombe

Value of Information and Information Services

1998

This report describes and, where possible, quantifies the value of information and information services for transportation agencies. It evaluates the various means of accessing information, and the important role of the information professional.

VTT Tiedotteita--Research Notes

Maila Herrala

The Value of Transport Information

2007

The objectives of this research were to identify the attributes affecting the value of transport information, and to specify the valuation methods applied.

Washington State DOT, Transportation Data Office

 

Better Decisions Through Better Data

2007

Discusses how WSDOT collects roadway, traffic, and collision data.


Other Industry Sources

American Journal of Medicine

S.J. Wang, B. Middleton, L.A. Prosser, et.al

A Cost-Benefit Analysis of Electronic Medical Records in Primary Care

2003

The purpose of this study was to estimate the net financial benefit or cost of implementing electronic medical record systems in primary care.

American Society of Mechanical Engineers

Steve Adam, Joseph T. Hlady

Data is an Asset that Should be Managed

2007

Illustrates how data can be viewed as an asset rather than an expenditure. The intent of this is not as an accounting strategy, but as a way to illustrate how data shows asset characteristics.

American Statistical Association

C. Sims

Can we measure the benefits of data programs?

1984

Article was identified but could not be located.  

Australia New Zealand Land Information Council

Price Waterhouse Economic Studies & Strategies Unit

Australian Land and Geographic Data Infrastructure Benefits Study

1995

Examines the economic gains from developing, maintaining, improving and providing access to land and geographic data infrastructure at a national level. Also determines and prioritizes the steps data supplying organizations in Australia should take to maximize potential infrastructure benefits.

Canadian Journal of Fisheries and Aquatic Sciences, 67

E.P. Fenichel, G.J.A. Hansen

The Opportunity Cost of Information: An economic framework for understanding the balance between assessment and control in sea lamprey management

2010

Research using sea lamprey population management to show how the optimal allocation of resources between assessment and control depends on the total budget, the relative cost of each management activity, the marginal reduction in uncertainty associated with increased assessment, and the marginal effectiveness of increased treatment.

Clinical Trials; London (Periodical)

Reza Rostami, Meredith Nahm, Carl F. Pieper

What can we learn from a decade of database audits?

2009

Reviewed a decade of internal data quality audits performed at Duke Clinical Research Institute. Results indicate higher quality data achieved from a series of small audits rather than a single large database audit.

Computer Technology Review

Fred Moore

The Value of Data

2002

Focuses on the determination of the monetary value of data.

Decision Sciences Institute

Grant O. Alexander

Development of an Instrument for Measuring Information and Information Technology's Costs and Economic Value

1997

Literature review of the measurement of business value of information and information systems, specifically, the issues of information and information technology's costs, benefits, and economic value.

Economics Bulletin

Daniel Sgroi

Irreversible investment and the value of information gathering

2003

This report develops a model in which a firm has to decide whether to undertake an irreversible investment.

Fisheries

G.J.A. Hansen, M.L. Jones

The Value of Information in Fishery Management

2008

Article illustrates the importance of accounting for all aspects of the value of information using examples drawn from three critical areas of fishery management. Authors discuss how experts have judged the value of assessment programs in the past, and provide suggestions as to how these methods could be expanded to examine the value of information in a more holistic manner.

Institute for Geoinformation, Technical University Vienna

Alenka Krek, Andrew U. Frank

The Production of Geographic Information - The Value Tree

2000

Investigates how organizations collect raw geographic data and turn it into usable geographic information. The corresponding economic theory gives guidelines for fixing the transfer prices between the participants, which determines their share of the value produced.

International Journal of Technology, Policy, and Management

Pieter W.G. Bots, Fred A. B. Lohman

Estimating the Added Value of Data Mining: A Study for the Dutch Internal Revenue Service

2003

Addresses how the added value of data mining for an organization can be defined and measured before major investments in data warehousing systems are made.

International Pipeline Conference 2004

Bruce Dupuis, Jason Humber

Pipeline Integrity: Establishing Data Management Value

2004

Paper addresses the process needed to determine the value of data management to support pipeline integrity.

Journal of AHIMA

M. Mercer

Data warehousing improves care, demonstrates return on investment

2001

Article was identified but could not be located.  

Journal of Applied Corporate Finance

Margaret Armstrong, William Bailey, Benoit Couet

The Option Value of Acquiring Information in an Oilfield Production Enhancement Project

2005

Article presents a case study of an oil production enhancement where Bayesian analysis is used in a real options framework to determine if the cost of collecting additional data is justified.

Journal of Health Services Research & Policy

Susan Griffin, Karl Claxton, Mark Sculpher

Decision Analysis for Resource Allocation in Health Care

2008

Addresses the use of economic evaluation to inform resource allocation decisions within health care systems about which interventions to reimburse and whether additional research should be funded.

Journal of Information Technology

Bert van Wegen, Robert De Hoog

Measuring the Economic Value of Information Systems

1996

Paper outlines an approach that combines the information commodity approach, activity-based costing, and graph modeling to determine the value of information systems for information management.

Journal of Mechanical Design Transactions of the ASME

J. M. Ling, J. M. Aughenbaugh, C.J.J Paredis

Managing the collection of information under uncertainty using information economics

2006

Introduces the principles of information economics to guide decisions on information collection. Investigates how designers can bound the value of information in the case of distributions with unknown parameters by using imprecise probabilities to characterize the current state of information.

Mining Technology: IMM Transactions Section A

Sean Dessureault

Justification Techniques for Information Technology Infrastructure in Mining

2004

The Black-Scholes option pricing method (BSOPM) is used to value the investment in a data warehouse for the mining industry.

NASA Airspace Systems Program

Thomas B. Sheridan

Strategy for Optimum Acquisition of Information

2006

Brief tutorial on optimizing acquisition of data (example presented - whether to add an instrument to an aircraft to optimize performance given how much it cost).

Nursing Management; Chicago

Bernadette M. Billinger

Should your data collection expand or shrink?

2000

Addresses the issue of expanding data collection and how to evaluate how useful and cost-effective it is in hospital areas. Three guidelines - know what you're collecting, ask the right question, focus your efforts

Pennsylvania State University

Damon Jones, Brian K. Bumbarger, Mark T. Greenberg, et al

The Economic Return on PCCD's Investment in Research-based Programs: A Cost-Benefit Assessment of Delinquency Prevention in Pennsylvania

2008

This report considers the cost-effectiveness potential for seven research-based programs funded by the Pennsylvania Commission on Crime and Delinquency (PCCD).

Photogrammetric Engineering and Remote Sensing

S. DeBruin, G.J. Hunter

Making the Trade-off Between Decision Quality and Information Cost

2003

Paper discusses how to compare if using additional or different imagery to improve decision quality may be justified by its cost. Compares competing factors using a cost-benefit analysis.

Principles of Microeconomics, 2nd edition (McGraw-Hill)

Robert H. Frank, Ben S. Bernanke

The Economics of Information

2003

Chapter on basic economic principles to help identify situations where additional information is most likely to prove helpful.

Resources for the Future

Molly K. Macauley

The Value of Information: A Background Paper on Measuring the Contribution of Space-Derived Earth Science Data to National Resource Management

2005

Describes a general framework for conceptualizing the value of information and illustrates how the framework might be used to value information from earth science data collected from space.

Society

Stuart Nagel

Determining When Data is Worth Gathering

1978

Brief analysis that investigates how to determine how much data is "excessive" when it comes to gathering data for federal agencies.

STEPHEN (Science & Technology Policy Asian Network)

M.A.T De Silva

Typology of S&T Statistics and Methods for Data Collection for Output and Input Indicators

Discusses a few data collection methods, and the development of output indicators (productivity, rate of return).

Studies in Health and Technology Informatics

I. Shabtai, M. Leshno, O. Blondheim, et.al

The value of information for decision-making in the healthcare environment

2007

Ealuates the contribution of information technology (IT) to improving the medical decision-making processes at the point of care of internal medicine and surgical departments and to evaluate the degree to which IT investments are worthwhile.

Swedish University of Agriculture Sciences, Dept. of Forest Resource Management

Karl Duvemo

The Influence of Data Uncertainty on Planning and Decision Processes in Forest Management

2009

Focuses on how uncertainty in forest data affects the outcome of management planning and decision making.

The Australian Society for Medical Research

Access Economics

Exceptional Returns: the Value of Investing in Health R&D in Australia

2003

His research shows that every dollar invested in health R&D in Australia has historically be recouped many times over, and that it makes an exceptional investment with high returns.

Trends in Ecology and Evolution

R. E. Johannes

The Case for Data-less Marine Resource Management: Examples from Tropical Nearshore Finfisheries

1998

Paper discusses the case for data-less management of finfisheries since there are too few researchers to do the work and it is usually not cost-effective.

US Dept. of State

Christopher Dauer

Insurers uptight about NAIC overhaul of data collection

1995

Insurance brokers express concern over the NAIC's intention to make data retrieval files more specific. One concern was how much the data files would cost.

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