Session #2 Overview of HSM Crash Prediction Methodology (Parts C & D)

1. Highway Safety Manual Session #2 Overview of HSM Crash Prediction Methodology (Parts C & D)

2. Describe purpose and principles Parts C &D of the HSM • Describe the content in Parts C & D • Describe HSM Crash Prediction Methodology • Describe Safety Performance Functions • Describe Crash Modification Factors Overview - HSM Crash Prediction Methodology Learning Outcomes:

3. Overview - HSM Crash Prediction Methodology

4. Overview - HSM Crash Prediction Methodology PREDICTIVE METHODS – Roadway Segments and Intersections Rural Two-Lane Roads Chapter 10 Rural Multilane Highways Chapter 11 Urban and Suburban Arterials Chapter 12 • Safety Performance Functions • Crash Modification Factors • Calibration for local conditions Part C Common Procedures

5. Overview - HSM Crash Prediction Methodology HSM Predictive Method can be used to: • Identify sites with the most potential for reducing crash frequency • Identify contributing factors to crashes • Calculate the safety effect of various design alternatives • Estimate potential crash frequency on highways • Estimate the potential effects on crash frequency of planning, design, operations, and policy decisions • Assist in review & documentation of design exceptions, variances and waivers

6. Overview - HSM Crash Prediction Methodology Predictive Method for Roadway Segments or Intersections Crash Prediction = SPF x (CMF1 x CMF2 x ….) x C ‘Safety Performance Function’ ‘Crash Modification Factors’ ‘Local Calibration Factor’

7. Crash Prediction Methodology What are Safety Performance Functions? Mathematical Regression Models for Roadway Segments and Intersections: • Developed from data for a number of similar sites • Developed for specific site types and “base conditions” • Function of only a few variables, primarily AADT • Used to calculate the predicted crash frequency (crashes/year) for a set of base geometric and traffic control conditions

8. Overview - HSM Crash Prediction Methodology Represent change in expected number of crashes as exposure (e.g., AADT) changes Constructed using data from multiple sites Used to identify sites with potential for safety improvement, countermeasure selection, and project evaluation Safety Performance Function

9. Crashes per unit time 1.2 1.0 0.8 0.6 0.4 0.2 1000 2000 3000 4000 5000 Average Daily Traffic Safety Performance Function (SPF) Plot of similar sites based on Traffic Volume and Crash Data X X X X X X X X X X X X X SPF = Best Fit Line XX XXX X X X X X X

10. Overview - HSM Crash Prediction Methodology SPFs by Facility Type & Site Type

11. Overview - HSM Crash Prediction Methodology Example Safety Performance Functions Nspf-rs = AADT x L x 365x10-6 x e(-0.312) Rural Two-Lane Intersection SPF: Rural Two-Lane Roadway Segment SPF: N (spf-int) = e [a + b ln(AADTmaj) + c ln (AADTmin)] Where a, b and c vary for intersection type and severity

12. Overview - HSM Crash Prediction Methodology Basic Analysis Steps for Applying the Predictive Method Process • Determine data needs • Divide locations into homogeneous segments or intersections • Identify and apply the appropriate SPF • Apply CMFs to calculated SPF values • Apply local calibration factor

13. Overview - HSM Crash Prediction Methodology STEP 1. Determine Data Needs • Study limits • Facility type • Study period • Site conditions (geometry, traffic control, etc.) • Traffic volume (vehicles/day)

14. Overview - HSM Crash Prediction Methodology Presence (and type) of intersections Number of lanes Cross section dimensions (LW, SW) Alignment change (Horiz, Vertical) Change in roadside conditions Change in traffic volume STEP 2. Divide Locations into Homogeneous Segments or Intersections

15. Overview - HSM Crash Prediction Methodology STEP 3. Identify and Apply the Appropriate SPF Chapter 10 for 2-lane Rural Highway SPFs Chapter 11 for Multilane Rural Highway SPFs Chapter 12 for Urban Arterial SPFs

16. Overview - HSM Crash Prediction Methodology STEP 4. Apply CMFs to Calculated SPF Values • Review applicable SPF “base conditions” • Determine how study site differs from “base conditions” • Select appropriate CMFs for road type and typical features from Part C • Multiply SPF value by applicable CMFs

17. Overview - HSM Crash Prediction Methodology SPF Base Conditions for Rural 2-Lane Road Intersections 90o angle (00 skew) No left turn lanes No right turn lanes No lighting Road Segments 12-ft lane widths 6-ft shoulder widths Roadside Hazard Rating = 3 5 driveways per mile Tangent, flat alignment (<3%) No centerline rumble strips No passing lanes No two-way left turn lanes No lighting No automated speed enforcement

18. Overview - HSM Crash Prediction Methodology SPF Base Conditions for Rural Multilane Highways Intersections 90o angle (00 skew) No left turn lanes No right turn lanes No lighting Road Segments 12-ft lane widths 8-ft shoulder widths 30-ft median (4D) No lighting No automated speed enforcement

19. Overview - HSM Crash Prediction Methodology SPF Base Conditions for Urban and Suburban Arterials Intersections No left-turn lanes Permissive left-turn signal phasing No right-turn lanes Right-turn on red permitted No lighting No automated enforcement No bus stops, schools or alcohol sales establishments near intersection Road segments No on-street parking No roadside fixed objects 15-ft median (4D) No lighting No automated speed enforcement

20. Overview - HSM Crash Prediction Methodology STEP 5. Apply Local Calibration Factor (C) • Adjust HSM SPF-derived crash estimates to reflect local conditions • Provide method to address for local variations such as: • Climate, • Driver populations, • Animal populations, • Crash Reporting Thresholds, and • Crash Reporting System Procedures

21. Overview - HSM Crash Prediction Methodology Calibration Procedure: Part C – Appendix A Typically done by specialty group or under contract Five steps: • Identify facility types • Select calibration sites • Obtain data • Apply the predictive method • Compute calibration factors

22. Overview - HSM Crash Prediction Methodology Replace Default Crash Statistics with Local Values • All facilities: • Crash severity and collision type • Ratio of nighttime to total crashes • Ratio of driveway-related crashes to total crashes (segments) • Urban and suburban facilities: • Pedestrian adjustment factor • bicycle adjustment factor

23. Overview - HSM Crash Prediction Methodology Can use Empirical Bayes (EB) Method to Combine Predicted and Observed Crash Frequency • Reduces effects of regression-to-the-mean • Improves reliability of the crash frequency estimate • Both SPF and crash data must be available • See HSM Part C Appendix

24. Overview - HSM Crash Prediction Methodology Apply Site-Specific Empirical Bayes (EB) Method Determine if EB Method applies Determine if crash data are available Apply the EB Method Adjust the estimated expected crashes to future years if appropriate

25. Overview - HSM Crash Prediction Methodology Does the EB Method Apply? • “Do nothing” sites • Basic number of through lanes intact but with minor cross section changes • Minor changes in horizontal alignment • Rural 2-lane highway with passing lanes or short 4-lane sections added • Any combination of the above

26. Overview - HSM Crash Prediction Methodology EB Method Application and Formula 10-26 Expected Crash Frequency: Nexpected= w x Npredicted+ (1.00 – w) x Nobserved Weighted Adjustment (w):

27. Overview - HSM Crash Prediction Methodology Calculation of Weighted Adjustment (w): weight adjustment for observed crashes w = 1 / [ 1 + k x (∑ N predicted)] where k is overdispersion parameter (unique to each SPF) and ∑ N predicted is predictive model estimate for all study years

28. Overview - HSM Crash Prediction Methodology Project Level EB Method • Apply method • Repeat for next site • Sum crash estimates • N (total) = ∑ N (all rs) + ∑ N (all int) • Repeat if evaluating alternate designs • Compare results

29. Overview - HSM Crash Prediction Methodology Predictive Method Limitations • Potential effect of many but not all geometric or traffic control features • Non-geometric factors are considered in a general sense • Potential interactions between geometric & traffic control features are independent of each other

30. Overview - HSM Crash Prediction Methodology HSM Part D: Crash Modification Factors (CMFs)

31. Overview - HSM Crash Prediction Methodology PART D: CRASH MODIFICATION FACTORS

32. Overview - HSM Crash Prediction Methodology . A value which quantifies the change in crash frequency at a site as a result of implementing a specific treatment or countermeasure CMF

33. Overview - HSM Crash Prediction Methodology What are Crash Modification Factors? • Functions or factors that adjust the calculated SPF predicted value for base conditions to actual or proposed conditions • Accounts for the difference between base conditions and site specific conditions • CMF = 1.0: Meets base conditions or the treatment has no effect on the expected crash frequency • CMF < 1.0: The treatment reduces the expected crash frequency • CMF > 1.0: The treatment increases the expected crash frequency

34. Overview - HSM Crash Prediction Methodology Npredicted = Nspf x (CMF1r … CMFxr) C CMF application to the SPF Base Model Where: Npredicted = predicted average crash frequency for an individual roadway for a specific year (crashes per year) Nspf = predicted average crash frequency for base conditions (crashes per year) CMF1 ... CMFx = Crash Modification Factors for individual design elements C = calibration factor

35. Overview - HSM Crash Prediction Methodology May apply to all crashes, or specific subsets of crashes (e.g., run-off-road, night, wet weather, multi-vehicle, etc.) Same treatment in different contexts or highway types may have differing effects and result in different CMF values Multiple CMFs may be applied to same location CMF is one value, but our knowledge of effects suggests we expect a distribution of results (variance when applied in multiple locations) A crash modification function may apply Important Concepts about CMFs

36. Crash Modification Function(Example: Part C CMF for Horizontal Curves) CMF3r =(1.55 x LC) + (80.2 / R) – (0.012 x S)(1.55 x LC) Overview - HSM Part D where LC is length of curve (mi) R is radius of curve (ft) S = 1.0 if spiral curve present; 0 if no spiral

37. Overview - HSM Crash Prediction Methodology Example Format and Description of CMFs in Part D • CMFs may differ based on crash severity or type

38. Overview - HSM Crash Prediction Methodology N predicted = Nspf x [CMF1 X CMF2X…] Use of Multiple CMFs • CMFs are Independent of other effects • Part C CMFs • (CMF1, CMF2,….CMFn) • Derived from SPF data • Can use all applicable CMFs • Part D CMFs • Derived from data separate from the SPF data • Limit multiple use to 3 or less

39. Overview - HSM Crash Prediction Methodology Standard Errors for Part D CMFs Standard Error Font 0.10 or less Bold (reliable & stable) Between 0.10 – 0.20 Normal Between 0.20 – 0.30 Italic (less reliable) • Standard errors > 0.10 User should consider the range over which a change in crash frequency could occur. • Standard errors for CMFs in Part D are ≤ 0.30 • Standard errors > 0.10 rounded to nearest 0.10

40. www.cmfclearinghouse.org

41. www.cmfclearinghouse.org

42. www.cmfclearinghouse.org

43. HSM Part C - Calculation Tool Excel spreadsheet facilitates crash prediction calculations and delivers results in an organized format!

44. Highway Safety Manual • Important HSM Tools: • HSM Spreadsheets • Facilitates HSM calculations • Developed by Oregon State University • http://safetyperformance.org/resources/nchrp-17-38/ • HSM User Discussion Forum • Submit questions/concerns to HSM Panel members for answers • http://www.highwaysafetymanual.org/Pages/default.aspx

45. Overview - HSM Crash Prediction Methodology • Described purpose and principles Parts C &D of the HSM • Described the content in Parts C & D • Described HSM Crash Prediction Methodology • Described Safety Performance Functions • Described Crash Modification Factors Learning Outcomes:

46. Overview - HSM Crash Prediction Methodology Questions and Discussion?