1. HSM: Another Tool for Safety Management in Wyoming Excellence in Transportation

2. Acronym Soup • WYDOT – Wyoming Department of Transportation • HSM – Highway Safety Manual • ITE – Institute of Traffic Engineers • SMS – Safety Management System • CARE – Critical Analysis Reporting Environment • CMF – Crash Modification Factor (AMF in HSM) • B/C – Benefit-Cost Ratio • NPV – Net Present Value • SPF – Safety Performance Function • RTM – Regression-to-the-mean • ARF – Accident Reduction Factor (CRF in HSM) • AADT – Annual Average Daily Traffic

3. Early Stages • Started before the Highway Safety Manual was finally approved or published • Highway Safety, Traffic, Road Design, and District Operations people did attend a one-day introductory training at an ITE meeting in May, 2010 • Plan is to incorporate the quantitative processes into WYDOT’s Safety Management System

4. The WYDOT SMS Process Pavement Project Recommendations Updates to CMFs, Guidance Effectiveness Studies Theme Studies Feedback Loop District Inputs Bridge Project Recommendations Project Deployment Safety Issue Identification / quantification Safety Project Definition Safety Project Prioritization Project Planning CARE Intersection Magic Safety Analyst Etc. Prioritized safety project stack Projects consolidated with other programs Deployed & Operational Prioritized opportunities to analyze Candidate Safety Projects Benefits and costs; B/C Network Safety Index STIP, etc. Includes all Safety Projects • For all Safety work • Done in advance Excellence in Transportation

5. Highway Safety Manual • Crash modification factors • Project planning input • Process to calibrate for state Excellence in Transportation

6. Where the HSM fits in to Project Definition Safety Project Definition step Methods for estimating safety effectiveness (of a remedy / set of remedies) Select appropriate remedy(ies) Needs for each Part C – Predictive Method (with calibrated SPF, HSM CMFs) Appropriate SPF, calibration, multiple data sets, and CMF (limited) Identify expected improvements (CMF) Un-calibrated SPF and CMFs (HSM, Part D, others) Appropriate SPF, multiple data sets, and CMF Observed crash frequency and CMFs (HSM, Part D, others) Historical crash data and CMF, doesn’t address RTM Calculate lifecycle benefits (NPV) In decreasing order of reliability; from HSM training (4.56) Also, calculate lifecycle cost, project B/C ratio Excellence in Transportation 6

7. Which Method to use? • Use HSM Part C – Predictive Method • Pros: Most reliable (according to HSM) • Cons: Needs lots of data sets (WYDOT does not have several); needs calibration (extensive process) • Use un-calibrated SPF • Pros: Still reliable (according to HSM) • Cons: Needs lots of data sets (WYDOT does not have several); • Use observed (historic crashes) • Pros: Needs least amount of additional data; familiar to people (similar to previous use of ARF) • Cons: Least reliable (according to HSM) Excellence in Transportation

8. Applying CMF – Using observed crash frequency Specific Site being analyzed Observed crashes Select remedies Expected change in crash counts Identify CMF* Expected benefits of remedy(ies) * Generally studies refer to Crash / Accident Reduction Factors which translate to CMF Excellence in Transportation 8

9. Applying CMF – HSM Part C Predictive Method Calibrate each SPF Determine C for each SPF Select appropriate SPF Determine SPF for site (based on facility) Determine volume for site Adjust SPF (based on site) Expected average crash frequency for the site Identify site characteristics (delta from baseline) Up to 18 parameters Select Remedy(ies) Find corresponding CMF for the remedy(ies) Apply CMF From HSM lists (Part C, Part D) Engineering judgement Difference = expected benefits of remedy(ies) 9 Excellence in Transportation

10. HSM Part C – Expected average crash frequency(example; 2-lane rural highway segment) Expected change in average crash frequency for specific site given selected remedies = SPF for rural 2-lane AADT x Length + (365*10-6) x e-0.312 X Adjust for shoulder width, type … horizontal curve (3 factors) … superelevation … grade … driveway density … centerline rumble strips … passing lanes … 2-way left turn lanes Adjust for lane width … automatic speed enforcement … roadside rating hazard … lighting CMF(lw) X CMF(swt) X CMF(hc) X CMF(se) X CMF(gr) X CMF(dd) X CMF(crs) X CMF(pl) X CMF(2lt) X CMF(rd) X CMF(l) X CMF(ase) X … for selected remedies 1 - ( CMF1 X CMF2 ) Excellence in Transportation

11. HSM Core Data Needs for Segments • NOTES: • However, need projected future traffic volumes • Data identified as coming from Pathways log. • Roadway width will catch many of these, but not all. Should we modify number of lanes table for this? • DCE’s agreed to gather this data in FY 2011, specifics to be determined? Excellence in Transportation

12. Observations & Conclusions • HSM Predictive method requires too much effort at this point • To obtain missing data sets, to perform SPF calibration • HSM “Observed Crash Frequency” method can readily be used in WYDOT’s SMS approach • Easier to combine multiple remedies • Decision needed regarding “expected” crash rates • Not all WYDOT remedies are covered by HSM Part C CMFs • Can also use Part D CMFs but with caveats • Need additional data • Expected future traffic volumes (or at least growth rate) • In order to calculate lifecycle crash reduction • Roadside data • In order to support some of the CMFs (e.g. way left turn lanes, passing lanes, though partially available in the # lanes table) Excellence in Transportation

13. Going Forward • Who should attend HSM training? • Finalize the starting remedies to consider for now • Identify appropriate CMF values to use for each remedy • Work with District Traffic Engineers • Document logic for selection of values • DiExSys is continuing research (Highway Safety) • Terrain (flat/rolling/mountainous) might be a sufficient surrogate for roadside hazard rating • Address need for future traffic volume data • Other possibilities • Prototype HSM calculation of expected average crash frequency for different segments using available data sets • Determine need/ability to get missing data sets Excellence in Transportation