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Development of Roundabout Crash Prediction Models and Methods (2019)

Chapter: Chapter 4 - Data Collection Approach and Findings

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Suggested Citation:"Chapter 4 - Data Collection Approach and Findings." National Academies of Sciences, Engineering, and Medicine. 2019. Development of Roundabout Crash Prediction Models and Methods. Washington, DC: The National Academies Press. doi: 10.17226/25360.
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Suggested Citation:"Chapter 4 - Data Collection Approach and Findings." National Academies of Sciences, Engineering, and Medicine. 2019. Development of Roundabout Crash Prediction Models and Methods. Washington, DC: The National Academies Press. doi: 10.17226/25360.
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Suggested Citation:"Chapter 4 - Data Collection Approach and Findings." National Academies of Sciences, Engineering, and Medicine. 2019. Development of Roundabout Crash Prediction Models and Methods. Washington, DC: The National Academies Press. doi: 10.17226/25360.
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Suggested Citation:"Chapter 4 - Data Collection Approach and Findings." National Academies of Sciences, Engineering, and Medicine. 2019. Development of Roundabout Crash Prediction Models and Methods. Washington, DC: The National Academies Press. doi: 10.17226/25360.
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Suggested Citation:"Chapter 4 - Data Collection Approach and Findings." National Academies of Sciences, Engineering, and Medicine. 2019. Development of Roundabout Crash Prediction Models and Methods. Washington, DC: The National Academies Press. doi: 10.17226/25360.
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Suggested Citation:"Chapter 4 - Data Collection Approach and Findings." National Academies of Sciences, Engineering, and Medicine. 2019. Development of Roundabout Crash Prediction Models and Methods. Washington, DC: The National Academies Press. doi: 10.17226/25360.
×
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Suggested Citation:"Chapter 4 - Data Collection Approach and Findings." National Academies of Sciences, Engineering, and Medicine. 2019. Development of Roundabout Crash Prediction Models and Methods. Washington, DC: The National Academies Press. doi: 10.17226/25360.
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Suggested Citation:"Chapter 4 - Data Collection Approach and Findings." National Academies of Sciences, Engineering, and Medicine. 2019. Development of Roundabout Crash Prediction Models and Methods. Washington, DC: The National Academies Press. doi: 10.17226/25360.
×
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Suggested Citation:"Chapter 4 - Data Collection Approach and Findings." National Academies of Sciences, Engineering, and Medicine. 2019. Development of Roundabout Crash Prediction Models and Methods. Washington, DC: The National Academies Press. doi: 10.17226/25360.
×
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Suggested Citation:"Chapter 4 - Data Collection Approach and Findings." National Academies of Sciences, Engineering, and Medicine. 2019. Development of Roundabout Crash Prediction Models and Methods. Washington, DC: The National Academies Press. doi: 10.17226/25360.
×
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Suggested Citation:"Chapter 4 - Data Collection Approach and Findings." National Academies of Sciences, Engineering, and Medicine. 2019. Development of Roundabout Crash Prediction Models and Methods. Washington, DC: The National Academies Press. doi: 10.17226/25360.
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42 Data Collection Approach and Findings This chapter presents the approach to the data collection, including data sources, database development, data reduc- tion procedures, and the final database attributes and char- acteristics from which the crash prediction models were developed. 4.1 Data Collection Approach The following describes the overarching data collection approach, including quality control and assurance as well as how roundabout sites were identified for the database. Sub- sequent sections provide more information regarding the specific data and data sources. 4.1.1 Quality Control and Quality Assurance Accurate and complete data are critical for crash prediction model development. There are often challenges in working with crash and volume data from multiple sources as well as challenges to ensuring geometric data is collected consistently and accurately across different sites. To overcome the above concerns about data quality, this project developed a data reduction procedures guide (see Appendix B) and established and implemented a quality control procedure. These are discussed below. 4.1.1.1 Data Reduction Procedures Guide A data reduction procedures guide was developed and used to ensure that the data were collected consistently and accurately. The core procedures described include • Procedures for defining the roundabout functional area and roundabout-related crashes. These procedures built off the findings in the literature review. • Procedures used to link each roundabout in an elec- tronic database with its physical location on a road map. The Modern Roundabout database (http://roundabout. kittelson.com) and public agency roundabout inventories were used within this procedure. • Procedures used to measure supplemental data from sec- ondary data sources (e.g., measurements of roundabout geometric elements from Google Earth aerial imagery). The Data Reduction Procedures Guide and Roadway Safety Database Organization Paper include definitions for each data attribute in each database assembled for this project. 4.1.1.2 Quality Control Procedure The quality control procedure focused on verifying the accuracy of the data obtained from supplemental data sources, such as measurements from Google Earth™ aerial imagery, information used from crash reports, and informa- tion extracted from as-built plans. Multiple sources of traffic volume and crash data were not available for the same sites, and therefore there was no readily feasible way to cross-check or verify the accuracy of data provided by the public agencies. The quality control for the supplemental data sources included the following activities: • Periodic requests of two research team members to inde- pendently collect data for the same data attribute at the same roundabout site to compare their findings. • Reexamination of the supplemental resources used for each observation and confirmation of the reasonableness of the data collected. • Review of the data attributes collected for consistency; observations with significant inconsistencies will be con- sidered for deletion. This consistency check is most impor- tant for data provided by the agencies (e.g., similar AADT on both major road approaches). • Review of the crash data, aerial imagery, and agency records or database inventories to confirm the observations in the C H A P T E R 4

43 database were not influenced by interim or long-term activities like work zones or construction activities. 4.1.2 Identifying Roundabout Sites The Modern Roundabout database (in addition to round- about inventories received from public agencies during the outreach conducted as part of the literature review) was used to identify roundabout sites for data collection. The data attributes included in the Modern Roundabout database are listed below. • Site identification number; • Intersecting street names; • City, state, and county; • Status (existing, planned, removed, unknown); • Latitude and longitude; • Number of approaches; • Type (single-lane roundabout, multilane roundabout, mini roundabout, unknown); • Functional class of intersecting roadways; • Year built; • Inscribed circle diameter; and • Notes (e.g., unique characteristics of site, links to addi- tional information). Of the information included in the database, the location information (i.e., intersecting street names, city, state, county, latitude, and longitude) is the most reliable and consistently present set of attributes across the roundabout sites. At the time the database was pulled for use in this project, there were 2,456 roundabouts in the database. The steps below were used to identify specific roundabout sites for the project database. 1. Identify public agencies able to provide the following for their roundabout intersections: – Minimum of 5 years of crash data, with crashes reflect- ing severity on KABCO scale; and – Major and minor street annual average daily traffic (AADT) that ideally corresponds to the years of crash data. 2. Identify roundabouts in the jurisdictions identified in Step 1. These roundabouts are identified as the candidate sites. 3. Roundabouts within the candidate sites group that were opened to traffic in 2009 to present were dropped from the group due to their limited years of operation and, therefore, likely limited crash experience. 4. Roundabouts within the candidate sites group with- out a known construction year were also dropped from consideration. 5. Roundabouts within the candidate sites group were orga- nized into different databases based on the safety perfor- mance factor (SPF) they are expected to be used to estimate (e.g., the single-lane roundabout database was created separately from the multilane roundabout database, AADT by approach/movement were in a separate database from those having just a digital summary of the crash attributes, and AADT by major/minor street). Roundabouts with right-turn bypass lanes were categorized as either a single- lane or multilane roundabout depending on the number of circulating lanes and were flagged by a variable indi- cating a presence of a right-turn bypass on one or more approaches. Roundabouts with variable circulating lanes were categorized as a multilane roundabout with a vari- able indicating that the number of circulating lanes varies within the intersection. 6. Traffic volume, crash, and geometric data were collected for the resulting candidate sites. 7. Descriptive characteristics of the attributes in the result- ing databases were developed and assessed during the data collection process to ensure that sufficient variability across each attribute is present to allow for estimating the effects of the different data attributes on crashes. 8. In some cases, follow-up with some jurisdictions was needed to obtain AADT and crash data from less- (or previously non-) responsive jurisdictions to try to expand the pool of potential sites. These efforts added additional sites to the databases to increase the desired variability and database characteristics. 4.1.3 Exploratory Analysis Exploratory analysis was conducted during the data col- lection activities to monitor the characteristics of the data attributes in each database and begin to explore the relation- ships between the data attributes expected to affect crashes and the crash data. Monitoring the characteristics of the data attributes in the databases helped identify the range of variability in each data attribute. The other purpose of the exploratory analysis was to look for potential relationships between the data attributes within the databases. The characteristics of the final database are presented further below in Section 4.5. 4.2 Desired Data Attributes based on Candidate SPFs and CMFs In Chapter 3 this report described a crash prediction frame- work to inform design decisions and to inform planning or network screening decisions. Table 4-1 summarizes the result- ing candidate SPFs from the crash prediction framework along with their purpose (i.e., intended application for practitioners). The above candidate SPFs, combined with the potential crash modification factors (CMFs) identified, formed the

44 basis for creating the data collection plan. Table 4-2 summa- rizes the candidate variables (i.e., desired data attributes) and the associated SPFs. The numbers in the right-hand columns of Table 4-2 correspond to the SPF identification numbers (ID #) in Table 4-1. The purpose of Table 4-2 was to begin assessing which data attributes are potentially applicable to the candidate SPFs. 4.3 Data Sources The data attributes associated with the candidate SPFs and CMFs were organized into four basic categories: (1) crash data, (2) traffic volume data, (3) roadway inventory data, and (4) speed data. The following subsections discuss sources used to acquire data for this project. 4.3.1 Crash and Traffic Volume Data Three general sources are available for crash and traffic volume data: (1) state and local agencies with roundabouts; (2) the Highway Safety Information System (HSIS), avail- able at http://www.hsisinfo.org/; and (3) recently completed roundabout research studies. Each of these potential sources is discussed below. It is important to note, the candidate SPFs summarized in Table 4-1 have different crash and traf- fic volume data needs. The approach-level predictive models ID # SPF Purpose Crash Severities Crash Type Design Decisions: Option A – Approach Level 1 Entering-Circulating Design Decisions Total, Fatal/Injury, PDO Entering-Circulating 2 Exiting-Circulating Design Decisions Total, Fatal/Injury, PDO Exiting-Circulating 3 Approach Design Decisions Total, Fatal/Injury, PDO Approach 4 Downstream Design Decisions Total, Fatal/Injury, PDO Downstream 5 Other Design Decisions Total, Fatal/Injury, PDO Other Design Decisions: Option B – Intersection Level 6 One Circulating Lane, Three Approaches Design Decisions Total, Fatal/Injury, PDO 7 One Circulating Lane, Four Approaches Design Decisions Total, Fatal/Injury, PDO Traditional Intersection Crash TypesA 8 Two Circulating Lanes, Three Approaches Design Decisions Total, Fatal/Injury, PDO 9 Two Circulating Lanes, Four Approaches Design Decisions Total, Fatal/Injury, PDO Design Decisions: Option C - Surrogate-Based Model – Approach Level 10 Surrogate-Based Model Design Decisions Total Crashes – Planning and Network Screening: Intersection Level 11 Urban/Suburban, Single-Lane Roundabout Planning and Network Screening Total, Fatal/Injury, PDO – 12 Urban/Suburban, Multilane Roundabout Planning and Network Screening Total, Fatal/Injury, PDO – 13 Rural, Single-Lane Roundabout Planning and Network Screening Total, Fatal/Injury, PDO – 14 Rural, Multilane Roundabout Planning and Network Screening Total, Fatal/Injury, PDO – NOTES: “–“ Indicates model would not be used to predict speci‚ic crash types. PDO = property damage–only A Traditional intersection crash types include rear-end, sideswipe, single-vehicle, and other similar crash types traditionally recorded by public agencies within their respective crash reports and databases. Traditional Intersection Crash TypesA Traditional Intersection Crash TypesA Traditional Intersection Crash TypesA Table 4-1. Summary of candidate SPFs for NCHRP 17-70.

45 Data Attribute Applicable SPFs – Design DecisionsA Applicable SPFs – Planning and Network ScreeningA Roadway Inventory Data Area Type (urban/suburban, rural) – 11,12,13,14 Opening DateB – 11,12,13,14 Ramp Terminal Intersection (“yes” or “no” per site)C – 11,12,13,14 Number of Circulating Lanes All SPFs Number of Entering Lanes per Approach All SPFs Number of Exiting Lanes per Approach All SPFs Number of Approaches All SPFs Entry Width (ft) – Measured at Yield Line 1,5,6,7,8,9 – Angle to Next Leg (deg) 1,5,6,7,8,9 – Inscribed Circle Diameter (ft) 2,5,6,7,8,9 – Circulating Width (ft) 2,6,7,8,9 – Approach Half-Width (ft) 3,6,7,8,9 – Lane Width (ft) – Measured 25 ft back from Yield Line 1,3,5,6,7,8,9 – Central Island Diameter (ft) 1,6,7,8,9 – Intersection Sight Distance 1,3,6,7,8,9 – Presence of Right-Turn Bypass Lane 4,6,7,8,9 – Radius of Right-Turn Bypass Horizontal Curve (ft) 4,6,7,8,9 – Radius of Exiting Vehicle Path Adjacent to Right-Turn Bypass Lane (ft) 4,6,7,8,9 – Distance from Circulating Roadway to Gore Point of Merge with Right-Turn Bypass Lane (ft) 4,6,7,8,9 – Lane Width (ft) – Measured at Gore Point of Merge with Right-Turn Bypass Lane 4,6,7,8,9 – Number of Luminaires within 200 ft of the Roundabout 1,2,3,4,5,6,7,8,9 – Presence and Type of Lane Use Markings 1,2,3,6,7,8,9 – Speed Data Entering Vehicle Speed (mph) 1,3,10 – Posted Speed on Approach (mph) 1,3,5,6,7,8,9 11,12,13,14 Circulating Vehicle Speed (mph)D 1,10 – Trafic Volume Data (Ideally Corresponds to Years of Crash Data) Total Entering Vehicle AADT All SPFs Vehicle AADT by Approach 6,7,8,9 – Vehicle AADT by Approach and Movement (e.g., entering, circulating, conŠlicting) 1,2,3,4,5,10 – Table 4-2. Summary of data attributes and applicable SPFs. (continued on next page)

46 needed crash reports and AADT by approach and movement, while the intersection-level models needed a digital summary of the crash attributes and AADT by major and minor street approach. 4.3.2 Roadway Inventory Data Roadway inventory data were available to varying degrees from state and local agency roundabout inventories, previous roundabout research databases, and as-built plans. Potential sources included agency roundabout inventories and research roundabout databases, as-built plans, and Google Earth aerial imagery. Google Earth aerial imagery was used as the primary source for roadway inventory data (i.e., roundabout geomet- ric features), which is furthered described below. The research team used the Modern Roundabout database, state and local agency roundabout inventories, and previous roundabout research databases as sources for roundabout location information and historic AADT data. Road inventory data was obtained from aerial imagery. The roadway inventory data collected for NCHRP 17-70 was gathered using Google Earth aerial imagery. The research team established data reduction procedures that were used through the data collection activities. A key topic for those procedures was presenting consistent methods for measuring dimensions from Google Earth aerial imagery to obtain the roadway inventory data listed in Table 4-2. A similar approach was developed and used successfully as part of NCHRP Project 17-45, “Enhanced Safety Pre- diction Methodology and Analysis Tool for Freeways and Interchanges.” 4.3.3 Speed Data Posted speed limit, entering vehicle speed, and circulating vehicle speed are the speed-related data attributes identified as candidate CMFs in Table 4-2. Potential sources for each of these data are discussed below. 4.3.3.1 Posted Speed Limit This data attribute is not included in the Modern Round- about database, roundabout inventories or databases main- tained by the public agencies, or the databases assembled in previous research projects. Posted speed limit data were collected through three primary sources: (1) Google Street View™, (2) crash data (some agencies have a field that includes posted speed), and (3) GIS-databases maintained by the pub- lic agency with jurisdiction of the roadways. 4.3.3.2 Entering Vehicle Speed and Circulating Vehicle Speed For this project, entering vehicle speed and circulating vehicle speed were defined consistent with NCHRP Report 672 (Rodegerdts et al., 2010) methodology for conducting fastest path speed performance checks for a given roundabout design. Within NCHRP Report 672, entry speed is the maximum theoretical speed a motorist is able to travel when making the movement from the entry approach into the circulatory road- way without regard to pavement markings. This is a maxi- mum desirable theoretical free-flow speed (i.e., it is controlled by the geometry of the roundabout and not the level of traf- fic volume or need to yield to a vehicle in the roundabout). Data Attribute Applicable SPFs – Design DecisionsA Applicable SPFs – Planning and Network ScreeningA NOTES: A Numbers correspond to the SPF identiication numbers (ID #) in Table 4-1. B Opening date variable was used in evaluating the effect of driver learning curve on crash frequency and severity. C Ramp terminal variable was used to try to detect a correlation between crash frequency or severity and roundabouts at ramp terminal intersections vs. nonramp terminal intersections. D Used to estimate the variation in vehicle speed as the difference between entering vehicle speed and circulating vehicle speed. Crash Data (Minimum 5 Years) Total Number of Crashes All SPFs Crashes by Severity (KABCO Scale) All SPFs Crashes by Traditional Intersection Types (e.g., rear-end) 6,7,8,9 – Crashes by Roundabout-Speciic Type (e.g., entering-circulating) 1,2,3,4,5,10 – Crash Location within (or on approach) to Roundabout 1,2,3,4,5,10 – Table 4-2. (Continued).

47 Therefore, this speed is not reached by a motorist if a con- flicting vehicle is in the roundabout and the entering vehicle must slow or stop to yield the right-of-way. This is consistent with how NCHRP Report 672 defines entering vehicle speeds in the context of roundabout design. It suggests a maximum theoretical entry speed of 25 mph for single-lane roundabout entries and a maximum theoretical entry speed of 30 mph for multilane roundabout entries. There are three options for obtaining entering vehicle speed and circulating vehicle speed data: (1) collect the data in the field as part of NCHRP 17-70, (2) use the speed data collected in NCHRP Report 572 (Rodegerdts et al., 2007), and (3) estimate the entering vehicle and circulating vehicle speed using the methods in NCHRP Report 672. A third option was used for a subset of the roundabouts in the database. The results from this work are described in Chapter 6, Section 6.5. This approach to estimating speed at the roundabouts was used for the following reasons. • The methodology documented in NCHRP Report 672 was validated through the NCHRP Report 572 research. Apply- ing the methodology results in a reasonable estimate of vehicle speed through a given roundabout. • The methodology documented in NCHRP Report 672 is what many practitioners use today as part of the round- about design process. Therefore, practitioners that are going to use the crash prediction models from this project to further guide their design decisions will already be using the speed estimating methodology (i.e., Fastest Path Check) from NCHRP Report 672. As a result, it would be relatively easy for practitioners to input this information into a crash prediction model. • One of the purposes of this project’s crash prediction models was to enable practitioners to use them to design new roundabouts. Practitioners using the models for pro- posed roundabouts will not have field-measured speed data for the roundabout. By using Option 3 above, these models will be more directly applicable to the context in which most practitioners will be using them. • Collecting speed data at specific roundabouts (Option 1 above) is expensive and does not reflect the type of data most practitioners will have available when using this project’s crash prediction models. • Applying the NCHRP Report 572 speed data (Option 2 above) may not result in substantially different findings than what is documented in NCHRP Report 572 due to the limited speed data collected. Furthermore, the sample size from NCHRP Report 572 research is limited. Chapter 6, Section 6.7.1, of NCHRP Report 672 presents the approach to estimating vehicle speeds through a roundabout based on its geometric characteristics. 4.4 Database Development The Data Reduction Procedures Guide and the Roadway Safety Database Organization White Paper were two critical documents used to develop the final database. Each is described in more detail below and is contained in an appendix (Appen- dixes B and C, respectively). (Appendixes can be found online by searching the TRB website for “NCHRP Research Report 888”.) 4.4.1 Data Reduction Procedures The following two documents were developed over the course of this project to summarize the data reduction pro- cedures used: • The Data Reduction Procedures Guide and • The Roadway Safety Database Organization White Paper. Together, these two documents describe the following the key topic areas: • Procedures for defining roundabout functional area and roundabout-related crashes, • Procedures used to link each roundabout in an electronic database with its physical location on a road map, and • Procedures to measure geometric data for the roundabouts from aerial imagery. An overview of the development of each and its content are provided below. 4.4.1.1 Data Reduction Procedures Guide The purpose of the Data Reduction Procedures Guide was to create consistency in how data attributes were collected for this project. The Data Reduction Procedures Guide focused on the process used to collect the roadway inventory and speed data attributes shown in Table 4-3. The Data Reduction Procedures Guide was developed using similar roundabout research such as NCHRP Report 572: Roundabouts in the United States and NCHRP Report 672: Roundabouts: An Informational Guide, 2nd edition. It also drew on a similar data reduction guide for NCHRP 17-45. The Data Reduction Procedures Guide was developed using a subset of the candidate roundabout sites used to test and refine the procedures. Some of the data attributes were relatively straightforward to capture from aerial imagery (e.g., number of legs); in these instances, the Data Reduction Procedures Guide served as a resource to clarify and confirm how those data attributes should be collected. Other data attributes, particularly those requiring measurements, were more complex to gather (e.g., inscribed circle diameter). In those instances, detailed step-by-step descriptions were

48 provided for how the measurements were taken. Most of the data attributes discussed in the Data Reduction Procedures Guide included figures to illustrate the written descriptions. 4.4.1.2 Roadway Safety Database Organization White Paper The Roadway Safety Database Organization White Paper documented the database framework that was used to develop this project’s databases. The Roadway Safety Data- base Organization White Paper included the variable names for each data attribute being collected. It also included a brief description of each data attribute. Therefore, the Roadway Safety Database Organization document repeated in brevity the detailed information regarding the roadway inventory and speed data contained in the Data Reduction Procedures Guide and provided additional information about variables used to record attributes such as roundabout location, traffic volume, crash data, and the start and end of evaluation periods. 4.4.1.3 Data Collection and Reduction Approach The data collection and reduction activities were organized into the following basic set of activities: 1. Identify specific candidate roundabout sites and basic characteristics of those sites. 2. Request crash and traffic volume data from focus states and agencies. 3. Request crash and traffic volume HSIS data. 4. Establish databases to be populated with data collected. 5. Organize crash and traffic volume data received for the candidate sites within the database. 6. Obtain traffic volume data for candidate sites where not provided directly by agency. Number of Luminaires within 250 ft of Roundabout Google Earth Aerial Imagery and AutoCAD Entry Width (ft) – Measured at Yield Line Google Earth Aerial Imagery and AutoCAD Angle to Next Leg (deg) Google Earth Aerial Imagery and AutoCAD Inscribed Circle Diameter (ft) Google Earth Aerial Imagery and AutoCAD Circulating Width (ft) Google Earth Aerial Imagery and AutoCAD Approach Half-Width (ft) Google Earth Aerial Imagery and AutoCAD Number of Access Points (i.e., Driveways) within 250 ft of Roundabout Google Earth Aerial Imagery and AutoCAD Posted Speed (mph) Google Earth Street View Entering Vehicle Speed (mph) Google Earth Aerial Imagery, NCHRP Report 672 Methodology, and AutoCAD Software Circulating Vehicle Speed (mph) Data Attribute Anticipated Source and Tools Area Type (urban/suburban, rural) U.S. Census Data Opening Year Public Agency Data or Google Earth Historical Imagery Ramp Terminal Intersection (“Yes” or “No” per Site) Google Earth Aerial Imagery Number of Circulating Lanes Google Earth Aerial Imagery Number of Legs Google Earth Aerial Imagery Number of Entering Lanes per Leg Google Earth Aerial Imagery Number of Exiting Lanes per Leg Google Earth Aerial Imagery Presence of Right-Turn Bypass Lane Google Earth Aerial Imagery Presence and Type of Lane Use Markings Google Earth Aerial Imagery Table 4-3. Summary of roadway inventory and speed data attributes.

49 7. Confirm opening years for roundabouts with unknown opening dates. 8. Identify the roundabout sites for geometric data collection. 9. Conduct the geometric data collection for roundabout sites. 10. Identify the roundabout sites for leg-level detailed speed, crash, and traffic volume data reduction. 11. Reduce and organize the data for the subset of sites to be used in the leg-level crash prediction models (referenced in item 10). 12. Identify the subset of roundabouts with well-established opening dates to use in identifying effects of driver learn- ing curve and obtain additional years of data (if needed). 4.5 Final Database Attributes and Characteristics The following section summarizes the basic characteristics of the final database, including the range of geometric, traffic, and crash data collected. More detailed summaries of the data used to create each model can be found in Chapter 5, Crash Prediction Model Development Approach. 4.5.1 Final Database Attributes The final database contains the following attributes for each site: • Overall site variables: – Opening date; – Area type; – State; – Whether the site is a ramp terminal; – Number of legs; – Number of circulating lanes; – Whether the site has a hybrid number of circulating lanes (e.g., there are two circulating lanes at some approaches but only one at others); – Presence of driveway access on any leg; – Inscribed circle diameter; and • Variables collected by leg: – Street names; – Number of circulating lanes; – Number of entering lanes; – Number of exiting lanes; – Right-turn bypass lane presence; – Presence and type of lane use markings; – Number of luminaires within 250 ft of the roundabout; – Entry width; – Angle to the next leg; – Circulatory roadway width; – Approach half-width; – Number of accesses within 250 ft of the roundabout; – Posted speed limit; and – AADT volumes for each study year. 4.5.2 Final Database Characteristics The following section summarizes the basic characteristics of the final database, including the range of geometric, traffic, and crash data collected. More detailed summaries of the data used to create each model can be found in Chapter 5. 4.5.2.1 Sites by State Figure 4-1 summarizes the number of sites by state in the final database. These states present a diverse range of conditions. Col- lectively, the three states with the greatest number of sites 0 10 20 30 40 50 60 70 80 CA FL KS MI MN NC NY ON PA WA WI # of Sites St at e Figure 4-1. Number of sites by state/province.

50 (i.e., Florida, Wisconsin, and Washington) make up approxi- mately 57% of the database. 4.5.2.2 Sites by Candidate SPF Figure 4-2 summarizes the number of sites by candi- date SPF. The candidate SPFs with the most sites include those focused on single-lane roundabouts with four legs (i.e., SPF #7) and urban/suburban single-lane sites (i.e., SPF #11). Conversely, SPFs covering rural multilane sites (i.e., SPF #14) and multi- lane sites with three legs (i.e., SPF #8) have the fewest number of sites. 4.5.2.3 Geometric Data Characteristics Table 4-4 summarizes the overall geometric characteristics of sites in the final database. 1SPFs are #6 = One Circulating Lane, Three Legs #7 = One Circulating Lane, Four Legs #8 = Two Circulating Lanes (or Hybrid), Three Legs #9 = Two Circulating Lanes (or Hybrid), Four Legs #11 = Urban/Suburban, Single-Lane Roundabout #12 = Urban/Suburban, Multilane Roundabout #13 = Rural, Single-Lane Roundabout #14 = Rural, Multilane Roundabout 0 50 100 150 200 14 13 12 11 9 8 7 6 # of Sites SP F # Figure 4-2. Number of sites by candidate SPF1. Number of Roundabouts with Three Legs 104 Number of Roundabouts with Four Legs 251 Presence of Right-Turn Bypass Lane Yes = 44 No = 311 Data Attributes (Geometry, Area Type, Opening Year) Number of Sites Total Number of Single-Lane Roundabout Sites 235 Total Number of Multilane Roundabout Sites 120 Area Type (urban/suburban, rural) Urban/Suburban = 250 Rural = 105 Ramp Terminal Intersection Yes = 30 No = 325 Table 4-4. Geometric data summary.

51 Table 4-5 summarizes descriptive statistics for the geomet- ric measurements completed by the project team for various roundabout types. 4.5.2.4 Traffic Volume Characteristics Table 4-6 summarizes the overall traffic volume character- istics of sites in the final database, based on average AADTs at each site for each leg. Multilane sites generally exhibit higher volumes than single-lane sites. 4.5.2.5 Crash Characteristics Table 4-7 provides an overall summary of the average crash frequency at all sites, all single-lane sites, and all multi- lane sites. Data Attributes/Statistic Median Value Maximum Value Minimum Value Interquartile RangeA Multilane Roundabouts Inscribed Circle Diameter (ft) 171 426 97 150–193 Entry Width – Two-lane Entries (ft) 28 48 20 27–31 Entry Width – Single-lane Entries (ft) 20 32 13 18–23 Approach Half-width (ft) 26 131 9 18–34 Luminaires (#)B 3 [12] 8 [21] 0/0 2–4 [8–14] Access Points (#)B 0 [2] 8 [20] 0/0 0–1 [0–5] Single-lane Roundabouts Inscribed Circle Diameter (ft) 122 259 58 104–137 Entry Width (ft) 18 46 11 16–21 Circulatory Width (ft) 20 60 13 18–22 Approach Half-width (ft) 18 61 8 13–22 Luminaires (#)B 2 [7] 8 [24] 0 [0] 1–3 [4–10] Access Points (#)B 1 [3] 8 [22] 0 [0] 0–2 [1–7] 4-Legged Roundabouts Angle to Next Leg 90 170 37 85–94 3-Legged Roundabouts Angle to Next Leg 109 193 47 91–152 A Interquartile range is the range between the 25th and 75th percentile values for the given measurement. B Number of luminaires and access points are reported on a per-leg basis and per-site basis (i.e., the total number for all legs of a single site) as follows: leg [site]. Table 4-5. Geometric measurements summary. Roundabout Size Highest AADT/leg Lowest AADT/leg Median AADT/leg Interquartile RangeA Single-Lane Sites 19,733 55 5,100 2,702–8,028 Multilane Sites 28,927 307 7,900 4,219–13,107 A Interquartile range is the range between the 25th and 75th percentile values for the given measurement. Table 4-6. Traffic volumes summary.

52 Multilane sites generally have more crashes per year than do single-lane sites. The spread of crash frequencies is also greater for multilane sites, whereas 75% of all single-lane sites have an average crash frequency of approximately 2.0 crashes per year or less, compared to 75% of all multilane sites having 7.1 crashes per year or less. 4.6 References and Bibliography Bagdade, J., B. Persaud, K. McIntosh, J. Yassin, C. Lyon, C. Redinger, J. Whitten, and W. Butch. 2011. Evaluating the Performance and Safety Effectiveness of Roundabouts. Michigan Department of Trans- portation Report No. RC-1566, Lansing, Mich. Dixon, K., and J. Zheng. 2013. Developing Safety Performance Measures for Roundabout Applications in the State of Oregon. Final Report, SPR 733, Oregon Department of Transportation, Salem, Oregon, and FHWA- OR-RD-13-08, Federal Highway Administration, Washington, D.C. Qin, X., A. Bill, M. Chitturi, and D. A. Noyce. 2013. Evaluation of Roundabout Safety. Submitted for Presentation and Publication to the 92nd Annual Meeting of the Transportation Research Board, Washington, D.C. Rodegerdts, L., M. Blogg, E. Wemple, E. Myers, M. Kyte, M. Dixon, G. List, A. Flannery, R. Troutbeck, W. Brilon, N. Wu, B. Persaud, C. Lyon, D. Harkey, and D. Carter. 2007. NCHRP Report 572: Round- abouts in the United States. Transportation Research Board of the National Academies, Washington, D.C. Rodegerdts, L., J. Bansen, C. Tielser, J. Knudsen, E. Myers, M. Johnson, M. Moule, B. Persaud, C. Lyon, S. Hallmark, H. Isebrands, R. B. Crown, B. Guichet, and A. O’Brien. 2010. NCHRP Report 672: Roundabouts: An Informational Guide, 2nd edition. Transportation Research Board of the National Academies, Washington, D.C. Srinivasan, R., J. Baek, S. Smith, C. Sundstrom, D. Carter, C. Lyon, B. Persaud, F. Gross, K. Eccles, A. Hamidi, and N. Lefler. 2011. NCHRP Report 705: Evaluation of Safety Strategies at Signalized Intersections. Transportation Research Board of the National Acad- emies, Washington, D.C. Turner, S. A., A. P. Roozenburg, and A. W. Smith. 2009. Roundabout Crash Prediction Models. NZ Transport Agency Research Report 386. Wellington, New Zealand. Crash Frequency AttributeA All Sites Single-Lane Sites Multilane Sites Median Crash Frequency 1.4 1.0 3.2 Minimum Crash Frequency 0.0 0.0 0.0 Maximum Crash Frequency 43.5 8.5 43.5 Interquartile RangeB 0.5–3.3 0.5–2.0 1.2–7.1 A Data summarized is the average crash frequency per site. B Interquartile range is the range between the 25th and 75th percentile values for the given measurement. Table 4-7. Crash data summary—all sites, single-lane sites, and multilane sites.

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TRB’s National Cooperative Highway Research Program (NCHRP) Research Report 888: Development of Roundabout Crash Prediction Models and Methods provides crash prediction models that quantify the expected safety performance of roundabouts for motorized and non-motorized road users. Safety performance factors (SPF) and crash modification factors (CMF) are predictive models that estimate expected crash frequencies. These models are used to identify locations where crash rates are higher than expected, to estimate safety benefits of a proposed project, and to compare the safety benefits of design alternatives. SPF and CMF models may help identify and prioritize locations for safety improvements, compare project alternatives by their expected safety benefits, and guide detailed design decisions to optimize safety. Research indicates that roundabouts provide substantial reductions in crashes, and this report determines SPF and CMF specifications for roundabouts.

The report includes appendices to the contractor's final report and a Powerpoint presentation.

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