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Federal Highway Administration
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Federal Highway Administration Research and Technology
Coordinating, Developing, and Delivering Highway Transportation Innovations
| REPORT |
| This report is an archived publication and may contain dated technical, contact, and link information |
 |
| Publication Number: FHWA-HRT-17-079 Date: July 2018 |
Publication Number: FHWA-HRT-17-079 Date: July 2018 |
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The Federal Highway Administration (FHWA) is exploring the use of alternate, non-traditional data sets. Access to relevant data is critical to understanding when traditional data sets seem to have been exhausted and to finding novel ways to mitigate the consequences of crashes. This study examines alternate data sources to increase understanding of precipitating events and predisposing crash factors. Models were developed for crashes occurring on horizontal curves and unsignalized intersections along rural two-lane roads to create crash profiles.
This technical report forms part of the series of low-cost in-house efforts to make full use of existing data resources to understand the roadway departure problem. The first report, Photographic Data Extraction Feasibility and Pilot Study in Support of Roadside Safety and Roadway Departure Research, sought to understand the roadway departure problem by repurposing existing data and blending it with emerging data sources.(1) Its purpose was to provide additional detail on roadside hardware and potentially identify previously unreported roadside conditions in the repurposed data. The intended audience is comprised of current data scientists, transportation researchers, and decisionmakers from State and Federal departments of transportation.
Monique R. Evans, P.E., CPM
Director, Office of Safety Research
and Development
Notice
This document is disseminated under the sponsorship of the U.S. Department of Transportation (USDOT) 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.
Technical Report Documentation Page
| 1. Report No.
FHWA-HRT-17-079 |
2. Government Accession No.
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3 Recipient's Catalog No.
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| 4. Title and Subtitle
Understanding the Causative, Precipitating, and Predisposing Factors in Rural Two-Lane Crashes |
5. Report Date
July 2018 |
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| 6. Performing Organization Code
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| 7. Author(s)
Richard Porter, Scott Himes, Anusha Musunuru, Thanh Le, Kim Eccles, Kara Peach, Ivana Tasic, Milan Zlatkovic, Kailash Tatineni, and Brendan Duffy |
8. Performing Organization Report No.
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9. Performing Organization Name and Address
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10. Work Unit No. (TRAIS)
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| 11. Contract or Grant No.
DTFH61-12-C-00033 |
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| 12. Sponsoring Agency Name and Address
U.S. Department of Transportation |
13. Type of Report and Period Covered
Technical Report; October 2012–September 2017 |
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| 14. Sponsoring Agency Code
HRDS-20 |
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| 15. Supplementary Notes
The Federal Highway Administration Contracting Officer’s Technical Manager for this project was Dr. Ana Eigen (HRDS-20). |
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| 16. Abstract
The overall objectives of this study were to (1) identify and explore alternative safety data sources and analysis perspectives and (2) demonstrate the potential utility of these alternative approaches in increasing understanding of precipitating events and predisposing factors for crashes occurring on horizontal curves and at unsignalized intersections along rural two-lane roads. Generalized conceptual crash model frameworks were developed, informed by a review of supporting published literature on conceptual crash models and contributing factors, alternative approaches to accident analysis, and the role of constraints in systemic approaches to accident analysis. The frameworks proved useful from several perspectives, including (1) identifying and organizing all factors that influence the likelihood of a crash and defining the event sequences that lead to a crash, (2) providing terminology that will encourage clear communication across accident analysis disciplines as research on crash causation continues, (3) visualizing the nature by which a certain factor influences the likelihood of a crash or by which an event directly causes a crash, and (4) identifying data needs (versus data availability) for studying the precipitating events, system constraints, predisposing factors, and target groups associated with a specific crash type. After marrying the conceptual crash model framework with available data, a study was conducted to determine whether crash causal types, or similar crashes grouped together based on their key precipitating events, could be developed from data, photographs, and narratives developed from detailed, on-scene crash investigations available in the National Motor Vehicle Crash Causation Survey. This was followed by a set of three additional studies primarily focused on alternative safety data sources and analysis perspectives related to predisposing factors. Enhanced data collection and subsequent analysis were demonstrated for three high-priority crash scenarios on rural two-lane roads: “straight crossing path crashes” at unsignalized intersections, combination “control loss/no vehicle action” and “road edge departure/no maneuver” single-vehicle crashes on horizontal curves, and “opposite direction/no maneuver crashes” on horizontal curves. Findings demonstrate that expanding beyond traditional databases used for crash-based evaluations can provide further insight into these crashes. One follow-on analysis in the final part of the study indicated that the alternative approaches to estimating disaggregate measures of exposure, kriging, and quasi-induced demand techniques show some promise and should be considered in future research. |
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| 17. Key Words
conceptual crash models, rural two-lane, single-vehicle crashes, multi-vehicle crashes |
18. Distribution Statement
No restrictions. This document is available to the public through the National Technical Information Service, Springfield, VA 22161. |
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| 19. Security Classification (of this report) Unclassified |
20. Security Classification (of this page) Unclassified |
21. No. of Pages
275 |
22. Price
N/A |
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| Form DOT F 1700.7 (8-72) | Reproduction of completed page authorized |
