Safety Performance Functions for Horizontal Curves

Statistics from the Fatality Analysis Reporting System (FARS) indicate that more than 25 percent of fatal crashes occur at horizontal curves, with most of these crashes being roadway departures. In the United States, the average crash rate for horizontal curves is about three times higher when compared to crash rates of other types of roadway segments. Although researchers and practitioners agree that curvature plays a role in crash frequency, crash rate, and crash severity, Safety Performance Functions (SPFs) for horizontal curves have not been thoroughly investigated or widely implemented. The Highway Safety Manual (HSM) provides SPFs of various facility types for segments and intersections, but no specific SPFs for curved segments are presented. Rather, curves are handled by applying an Adjustment Factor (AF) to estimate the predicted crash frequency of a curved segment. Unfortunately, not all the SPF models within the HSM have AFs for horizontal curves. Recent studies have been implemented to develop AFs for curved segments of certain facility types to begin filling this gap. However, applying a horizontal curve AF to an existing segment SPF assumes that the underlying prediction model of a tangent segment only needs to be adjusted to appropriately estimate a horizontal curve’s influence on the segment’s safety performance. This method may not be the best way to assess the safety performance of horizontal curves. A more thorough investigation may reveal that common geometric attributes used to estimate the safety performance of tangent segments have a different degree of influence on the safety performance of horizontal curves. For example, length has been shown to be an important attribute for predicting crashes on a tangent segment; however, for predicting crashes at a horizontal curve, the length of curve may have less influence and attributes such as curve radius and deflection angle may have stronger influence. Taking this possibility further, the attributes most important for predicting the safety performance of a horizontal curve may differ due to setting (rural vs. urban), facility type (2-lane vs. freeway), or other factors such as lane width, shoulder with, and roadside elements. Research is needed to better understand the attributes that most influence the safety performance of horizontal curves. Ultimately, this research will lead to the development of SPFs for horizontal curves along a variety of facility types so that the safety performance of most facility types can be predicted more comprehensively by utilization of three categories of SPFs: one for tangent segments, one for horizontal curves, and one for intersections. Horizontal curves are mentioned in the HSM for some facility types and addressed with a Crash Modification Factor (CMF), which is now referred to as an AF, but no specific SFPs were proposed for curved segments. Recent studies demonstrate that the application of curve CMFs/AFs within the HSM could not properly reflect this roadway element in the safety prediction for some locations and the development of additional CMFs/AFs and SPFs could be beneficial in safety studies (Banihashemi 2015, 2016; Harwood and Bauer 2015; Wu, Lord, and Geedipally 2017, Silva 2017). Moreover, some initiatives have shown that horizontal curves are an important roadway element and need to be addressed separately using a SPF (Anarkooli et al. 2019; Aram 2010; Bauer and Harwood 2014; Findley et al. 2012; Gooch, Gayah, and Donnell 2016; Khan et al. 2013; Miaou and Lum 1993; Montella 2009; Saito et al. 2015; Saleem and Persaud 2017; Vogt and Bared 1998; Xin et al. 2019). A common limitation in previous studies is the lack of a comprehensive sample of horizontal curves. The horizontal curve features were not always available in a roadway database, causing some researchers to collect data by identifying horizontal curves manually, resulting in the use of a small set of horizontal curves for SPF development. However, there is now an opportunity to use horizontal curve features from automated data collection methods to address this gap in knowledge and practice through this proposed research. The objectives of this research include: (1) Investigate a wide variety of roadway and traffic attributes to better understand which attributes, or combination of attributes, have strong correlation with the safety performance of horizontal curves for various facility types. (2) Explore the impact new data sources might have on the predictive results of horizontal curve SPFs. Potential data sources could include, but are not limited to: measured operation speed (e.g., INRIX data), continuous pavement friction measurement (e.g., SCRIM), and curve advisory speed and other curve data (e.g., CARS). (3) Evaluate various SPF model forms to determine which have the best fit for various facility types. Consideration should be given to the SPF models described in the SPF Development Guide (Srinivasan and Bauer 2013). (4) Develop horizontal curve SPFs for a variety of facility types, including rural and urban freeways, rural and urban multilane divided roadways, rural and urban multilane undivided roadways, and rural and urban 2-lane undivided roadways.

Language

  • English

Project

  • Status: Proposed
  • Funding: $350000
  • Contract Numbers:

    Project 17-117

  • Sponsor Organizations:

    National Cooperative Highway Research Program

    Transportation Research Board
    500 Fifth Street, NW
    Washington, DC  United States  20001

    American Association of State Highway and Transportation Officials (AASHTO)

    444 North Capitol Street, NW
    Washington, DC  United States  20001

    Federal Highway Administration

    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590
  • Project Managers:

    Deng, Zuxuan

  • Start Date: 20220608
  • Expected Completion Date: 0
  • Actual Completion Date: 0

Subject/Index Terms

Filing Info

  • Accession Number: 01845545
  • Record Type: Research project
  • Source Agency: Transportation Research Board
  • Contract Numbers: Project 17-117
  • Files: TRB, RIP
  • Created Date: May 17 2022 11:30AM