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15 Chapter 2. Survey of Practitioners Initially, the project team envisioned gathering the NCHRP Project 17-78 panelâs opinion on the model and application-related factors. Based on the kickoff call, the project team agreed to expand and conduct a survey of a broader group of practitioners. In the kickoff call, it was proposed that the project team focus more on application-related factors. The project team identified a list of practitioners for the survey by contacting FHWA Office of Safety and AASHTOâs Senior Engineering Program Manager for Safety. These practitioners included members of the AASHTO Safety Management subcommittee, AASHTO HSM2 Steering Committee, and FHWA HSM Pooled Fund Group. Following are the details of the survey, including the results. Twenty practitioners responded to the survey. The first page of the survey provided the following background about the survey, and this shown below: CrashÂ predictionÂ modelsÂ (CPMs),Â alsoÂ calledÂ safetyÂ performanceÂ functions,Â areÂ modelsÂ usedÂ toÂ predictÂ crashÂ frequencyÂ basedÂ onÂ siteÂ characteristics.Â TheyÂ mayÂ comeÂ withÂ orÂ withoutÂ crashÂ modificationÂ factorsÂ (CMFs)Â thatÂ adjustÂ theÂ predictionÂ toÂ accountÂ forÂ siteÂ conditionsÂ thatÂ areÂ differentÂ fromÂ theÂ baseÂ conditionÂ ofÂ theÂ model.Â ManyÂ CPMsÂ areÂ presentedÂ inÂ PartÂ CÂ ofÂ theÂ HighwayÂ SafetyÂ Manual.Â YouÂ areÂ invitedÂ toÂ shareÂ yourÂ experienceÂ asÂ aÂ userÂ ofÂ crashÂ predictionÂ modelsÂ (CPMs)Â byÂ respondingÂ thisÂ shortÂ questionnaire,Â needingÂ approximatelyÂ 10Â minutes.Â YourÂ responseÂ willÂ helpÂ directÂ theÂ NCHRPÂ 17â78Â projectÂ teamÂ toÂ addressÂ theÂ priorityÂ needsÂ ofÂ safetyÂ practitioners.Â BriefÂ BackgroundÂ TheÂ NCHRPÂ 17â78Â project,Â recentlyÂ launched,Â hasÂ threeÂ mainÂ objectives:Â Â 1. DevelopÂ guidanceÂ forÂ theÂ quantificationÂ ofÂ theÂ reliabilityÂ ofÂ crashÂ predictionÂ modelsÂ (includingÂ crash modificationÂ factorsÂ (CMFs),Â crashÂ modificationÂ functionsÂ andÂ safetyÂ performanceÂ functionsÂ (SPFs)) forÂ practitionerÂ use. 2. DevelopÂ guidanceÂ forÂ userÂ interpretationÂ ofÂ modelÂ reliability. 3. DevelopÂ guidanceÂ forÂ theÂ applicationÂ ofÂ CPMsÂ accountingÂ for,Â butÂ notÂ limitedÂ toÂ assumptions,Â data ranges,Â andÂ intendedÂ andÂ unintendedÂ uses. TheÂ projectÂ teamÂ willÂ greatlyÂ benefitÂ fromÂ theÂ feedbackÂ fromÂ usersÂ ofÂ crashÂ predictionÂ models,Â likeÂ yourself.Â YourÂ responsesÂ willÂ helpÂ usÂ inÂ identifyingÂ theÂ dayâtoâdayÂ needsÂ andÂ highÂ priorityÂ gapsÂ inÂ understandingÂ andÂ communicatingÂ reliabilityârelatedÂ factorsÂ orÂ aspects,Â andÂ willÂ beÂ instrumentalÂ inÂ developingÂ pragmaticÂ andÂ neededÂ guidanceÂ toÂ practitioners,Â likeÂ yourself.Â Â The second page asked the respondents to indicate whether a particular issue regarding CPMs were âVery concerningâ, âSomewhat concerningâ, âNeutralâ, âNot very concerningâ, or âNot a concernâ. The respondents were asked to respond to seven issues. Following is the list of questions along with the summary of the results.
16 PotentialÂ ConcernsÂ inÂ ApplyingÂ CPMsÂ WhenÂ youÂ useÂ aÂ CPMÂ toÂ whatÂ levelÂ doesÂ eachÂ ofÂ theseÂ potentialÂ issuesÂ concernÂ you?Â Â "Concern"Â inÂ thisÂ usageÂ refersÂ toÂ yourÂ levelÂ ofÂ trustÂ inÂ theÂ resultsÂ ofÂ theÂ CPMÂ predictionsÂ forÂ yourÂ ownÂ useÂ asÂ wellÂ asÂ yourÂ concernsÂ aboutÂ theÂ easeÂ ofÂ communicatingÂ theÂ reliabilityÂ andÂ resultsÂ ofÂ theÂ CPMÂ toÂ yourÂ colleagues,Â managers,Â andÂ theÂ public.Â SomeÂ ofÂ theseÂ potentialÂ concernsÂ mayÂ notÂ beÂ applicableÂ toÂ youÂ becauseÂ yourÂ dataÂ doesÂ notÂ presentÂ thatÂ typeÂ ofÂ concernÂ orÂ youÂ haveÂ otherÂ waysÂ ofÂ handlingÂ it.Â InÂ thoseÂ cases,Â markÂ yourÂ answerÂ asÂ "NotÂ aÂ concern".Â
17 Table 3. Results of Practitioner Survey. Issue Number of Responses Very concerning Somewhat concerning Neutral Not very concerning Not a concern Did not Answer Using CPMs that were developed in another location but calibrated for your local jurisdiction 0 7 2 4 7 0 Using crash modification factors that were not included in the original CPM but are consistent with the base conditions of the CPM 1 4 4 9 1 1 Using crash modification factors that were not included in the original CPM and are inconsistent with the base conditions of the CPM 7 7 4 1 1 0 Using a CPM that does not represent the characteristics of your project (e.g., using a 4-lane road CPM to predict crashes for a 6-lane road project) 13 6 0 0 1 0 Using input values that are uncertain (e.g., estimated AADTs based on old counts, crashes with unverified locations, etc.) 4 9 6 1 0 0 Using a CPM for a project whose characteristics lie outside the range of values of the CPM development (e.g., AADT volumes higher than the maximum value documented for the CPM) 7 8 3 2 0 0 Using a CPM to estimate rare crash types, such as fatal crashes or pedestrian crashes 6 5 4 5 0 0 Finally, the respondents were asked to answer the following question in their own words (the answers are provided below the question): Question:Â AreÂ thereÂ anyÂ otherÂ concernsÂ youÂ haveÂ whenÂ communicatingÂ theÂ reliabilityÂ orÂ applicationÂ ofÂ CPMsÂ (data,Â valuesÂ usedÂ forÂ variables,Â estimatesÂ calculated,Â andÂ toÂ yourÂ decisionÂ toÂ adoptÂ orÂ notÂ toÂ adoptÂ aÂ givenÂ CPMÂ andÂ CMFs)Â toÂ yourÂ colleagues,Â managers,Â orÂ theÂ public?Â PleaseÂ describe.Â
18 Answers: ï· The biggest difficulty is explaining what a CPM is and why one would use a CPM instead of pure naive prediction. If they do accept it, they tend to overrate the reliability of the CPM. Some prefer whatever predictive method gives the results they want, regardless of which is most accurate or applicable. ï· Communicating the value of CPM (or SPF) that predict a very low number of crashes, such as those for very specific conditions, e.g., pedestrians, bicycles, rail road crossings, specific geometric conditions, etc. ï· Any CMF that has a broad range of standard deviation, especially those that are not statistically significant. I don't put much trust in those CMFs. ï· Too many input parameters. ï· It is important to interpret the data and describe what the data represents. Typically, we describe these predictions as planning level estimates for what we expect safety to look like in some future scenario based on the specific variables that were captured in a specific CPM. This can be difficult to explain, because there are so many variables that can affect future safety performance, and these can be difficult to estimate. ï· Very few people (including myself) use CPM and CMFs on a daily basis. It is hard to develop expertise. When getting outside of this group, explaining and justifying numbers can be difficult. It is more difficult when you disagree with how someone else's numbers were computed and why you disagree. ï· Results that show a crash reduction of less than one crash. Hard to make the case for investing in a project. We have low numbers of crashes in VT. Another issue is with calibration. We have not calibrated the HSM type models. Results are thus potentially unreliable. ï· Still some concern about how sensitive the development of the SPF is to the available data components. What attributes (and to what accuracy) are most needed versus what attributes are less "needed" to achieve usable functions/models. ï· Yes. We want to use the CPMs but there are many uncertainties as mentioned in the questions above. With limited experience, it's difficult to confidently assess the reliability of the CPMs and the results they produce. Summary of Survey Responses The survey provided valuable information about the importance of the different application-related factors. Those issues that were rated as âVery Concerningâ by multiple respondents were considered important enough for further examination in this research project. These issues included the following: ï· Using crash modification factors that were not included in the original CPM and are inconsistent with the base conditions of the CPM. ï· Using a CPM that does not represent the characteristics of your project (e.g., using a 4-lane road CPM to predict crashes for a 6-lane road project). ï· Using input values that are uncertain (e.g., estimated AADTs based on old counts, crashes with unverified locations, etc.) ï· Using a CPM for a project whose characteristics lie outside the range of values of the CPM development (e.g., AADT volumes higher than the maximum value documented for the CPM). ï· Using a CPM to estimate rare crash types, such as fatal crashes or pedestrian crashes.