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Evaluating Opportunities Using Predicted Crash Frequency with CMF Adjustment - Missouri Case Study

Summary from Crash Modification Factors in Practice: Using CMFs to Quantify Safety in the Value Engineering Process

(The Missouri case study begins on Page 22 of the full report, after background information about the use of crash modification to quantify safety in the value engineering process.)

Publication Year: 2013


Background

The following case study illustrates how the Predicted Crash Frequency with CMF Adjustment method has been used to explicitly consider the safety impacts of opportunities during the Value Engineering (VE) process. Specifically, it focuses on the quantification of safety in the evaluation phase when safety is a project factor and crash frequency is the related performance measure. Information for the case study was provided by the Missouri Department of Transportation (MoDOT).

MoDOT integrates data-driven decision-making in many of their planning and design practices, including the VE process. While not part of their VE policy, MoDOT encourages the use of the AASHTO Highway Safety Manual to better understand the safety implications of design-related decisions.

Project Description

MoDOT Southeast District proposed a roadway improvement project on a rural, two-lane section of Route 34 in Bollinger County, MO. The existing 2.8-mile study section is characterized by a narrow cross-section with several horizontal curves and relatively unforgiving roadside. The proposed project involved resurfacing, lane and shoulder widening, horizontal realignment, installation of centerline rumble strips, and roadside improvements. The project was also listed on the district's VE work plan, which is created by the District Value Engineering Coordinator (DVEC) to identify priority projects for VE study. Suggested selection criteria are provided at the following link to aid the DVEC in selecting projects for the VE work plan: http://epg.modot.org/files/c/c0/130_VE_Project_Selection_Criteria.doc.

Findings

Safety Performance Function (SPFs) can be used to predict crashes for baseline conditions and CMFs can be applied to adjust the baseline estimate to reflect specific conditions of interest. This is useful for quantifying and comparing the safety performance of scenarios with different design features and can aid in the decision-making process. Specifically, this approach can help an agency to better understand the potential safety impacts of individual design elements and changes proposed as part of a VE study when safety is a project factor and crash frequency and/or severity is the performance measure. In this case, Southeast District of MoDOT used the Predicted Crash Frequency with CMF Adjustment in order to quantify the safety impacts of road widening in conjunction with horizontal realignment, centerline rumble strips, and roadside improvements. Two alternative alignments (original proposed design and VE proposed design) were compared to the existing conditions. While the two alternative designs provide nearly identical levels of safety based on total predicted crashes, the VE proposed design would reduce project costs. The use of the Predicted Crash Frequency with CMF Adjustment demonstrated that the proposed improvements could result in a substantial reduction in crashes compared to existing conditions. It also showed that the VE proposed design would provide a similar level of safety to the original proposed design while providing additional benefits. Recall that non-calibrated SPFs may overestimate or underestimate the predicted crash frequency, but provide a reasonable estimate of the percent difference in crashes among alternatives. As such, it is desirable to use a calibrated SPF if it is necessary to estimate the change in predicted crash frequency or conduct a formal economic analysis.

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Contact

Karen Scurry
FHWA Office
609-637-4207
Karen.Scurry@dot.gov

Publication Year: 2013

View more information about CMFs on the web at: http://safety.fhwa.dot.gov/.
Additional practices in the CMFs in Practice Series:

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