Bayesian Approach to Developing Context-Based Crash Modification Factors for Medians on Rural Four-Lane Roadways

Rural four-lane roadways provide important transportation accessibility and mobility to populations in rural areas. It is a challenge for practitioners to determine cross-section types when both benefits and costs need to be considered. Crash Modification Factors (CMFs) are developed to evaluate the safety effectiveness of alternative designs. However, safety effectiveness could vary significantly across contexts. Thus, this study aims to estimate CMFs for alternative cross sections of rural four-lane roadways under different contexts characterized by traffic volume, truck percentage, and access point density. Using Georgia state-wide crash data, this study developed Safety Performance Functions (SPFs) to predict crash frequencies for different contexts. Considering linearity and independence assumptions of traditional negative binomial SPFs, this study adopts Bayesian generalized negative binomial modeling approaches to relax those assumptions and only follows the Bayes rule to form SPFs for CMF estimation. This study focuses on four typical cross-sections including: (1) non-traversable medians; (2) two-way-left-turn lanes; (3) 4-ft flush medians; and (4) undivided roadways with double-yellow lines (the base cross-section design). The results show that CMFs vary significantly across different contexts. Compared with the base cross-section design, safety benefits of the other three designs can be either positive or negative under different traffic or road conditions. For example, 4-ft flush medians are found to have positive safety benefits (CMF?<?1) under lower average daily traffic volumes (e.g., = 6,000) and negative benefits (CMF?>?1) under greater average daily traffic volumes (e.g., = 15,000). The findings suggest that, to enhance roadway safety, practitioners should vary cross-section designs for different rural contexts.

• Record URL:
  https://doi.org/10.1177/03611981211007141
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/03611981
• Supplemental Notes:
  • The authors are responsible for the views, facts, and validity of the information presented in this study. © National Academy of Sciences: Transportation Research Board 2021.
• Authors:
  • Li, Xiaobing
  • Liu, Jun
  • Yang, Chenxuan
  • Barnett, Timothy
• Publication Date: 2021-9

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Photos; References; Tables;
• Pagination: pp 1316-1330
• Serial:
  • Transportation Research Record: Journal of the Transportation Research Board
  • Volume: 2675
  • Issue Number: 9
  • Publisher: Sage Publications, Incorporated
  • ISSN: 0361-1981
  • EISSN: 2169-4052
  • Serial URL: http://journals.sagepub.com/home/trr

Subject/Index Terms

• TRT Terms: Bayes' theorem; Binomial distributions; Crash modification factors; Crash risk forecasting; Four lane highways; Geometric design; Highway safety; Medians; Rural highways; Two way left turn lanes
• Identifier Terms: Safety Performance Functions
• Geographic Terms: Georgia
• Subject Areas: Design; Highways; Planning and Forecasting; Safety and Human Factors;

Filing Info

• Accession Number: 01764328
• Record Type: Publication
• Report/Paper Numbers: TRBAM-21-00190
• Files: TRIS, TRB, ATRI
• Created Date: Feb 4 2021 11:00AM