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A PRIORITISATION SCHEME FOR THE SAFETY MANAGEMENT OF CURVES Presented by: Neil Jamieson

A PRIORITISATION SCHEME FOR THE SAFETY MANAGEMENT OF CURVES Presented by: Neil Jamieson Research Leader, Tyre-Road Interactions Opus Central Laboratories. Why focus on curves?. Answer. Loss of control on curves are the largest cause of injury crashes on NZ rural State Highways! In 2009:

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A PRIORITISATION SCHEME FOR THE SAFETY MANAGEMENT OF CURVES Presented by: Neil Jamieson

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  1. A PRIORITISATION SCHEME FOR THE SAFETY MANAGEMENT OF CURVES Presented by: Neil Jamieson Research Leader, Tyre-Road Interactions Opus Central Laboratories

  2. Why focus on curves?

  3. Answer Loss of control on curves are the largest cause of injury crashes on NZ rural State Highways! In 2009: • Amounted to 1309 reported injury crashes • Corresponds to: • 49% of reported injury crashes on rural SH’s • 36% of allreported injury crashes • 1210 (92%) occurred on moderate or easy curves • 471 (36%) occurred in wet

  4. Collective and personal risk metrics For a curve defined as: • Collective risk = Fatal Crashes + Serious & Minor Injury Crashes on CurveNumber of Years of Data • Personal risk or crash rate is a measure of the likelihood of an individual road user being involved in a crash as they enter a curve i.e. Personal Risk = Fatal Crashes + Serious & Minor Injury Crashes on Curve (No. of years of data × 365 days × AADT)/108

  5. Curve radius & collective risk

  6. Curve radius & personal risk

  7. Previous safety management of curves • Relied on T10 specification, which aimed to equalise personal risk across SH network through investigatory skid resistance levels (IL’s). • Prior to October 2010, curves < 250mR were managed to a skid resistance level that was 25% greater than for all other curves on SH network (IL=0.5 c.f. IL=0.4). • Curves ≥ 250mR (85 km/h curves) treated the same as straights (event free). • Too simplistic for “safe system approach”!

  8. Potential for reducing SH crash numbers

  9. Solution for more effective safety management • All curves < 400mR identified • Crash rate calculated using a predictive model which has as inputs: • curve speed (derived from geometry) • curve length • approach gradient (averaged over 100 m prior to curve) • difference between approach speed and curve speed • Risk ranking of “high”, “medium” or “low” assigned to each curve on basis of predicted crash rate. Slides which follow expand on the above three steps

  10. Locating start of curve Start of curve  “Point where radius < 800m” Circular Arc Spiral Spiral CS CS Straight Straight Tangent Point Tangent Point Typical Right Hand Curve

  11. Estimation of curve radius Curve Radius  Averaged over tightest 30m of the curve Curve included if <400mR Circular Arc Spiral Spiral CS CS Superelevation  (crossfall)  Averaged over tightest 30mR Straight Straight Tangent Point Tangent Point Typical Right Hand Curve

  12. Locating end of curve Circular Arc Spiral End of curve  Radius > 800m Spiral CS CS Straight Straight Tangent Point Tangent Point Typical Right Hand Curve

  13. Poisson linear/log-linear model Curve Crash Rate = (108⁄365)×L1×exp(L2) L1 & L2 are linear combinations of transforms of road characteristics as follows: L1: a constant square root of curve length L2: OOCC (i.e. difference between approach & curve speeds) curve speed skid resistance approach gradient log 10 (ADT) year NZTA administration region

  14. Predicted effects on curve crash rates - ADT

  15. Predicted effects on curve crash rates - SCRIM

  16. Predicted effects on curve crash rates – curve length

  17. Predicted effects on curve crash rates – approach gradient

  18. Predicted effects on curve crash rates – speed difference

  19. Observed & modelled crash numbers

  20. Predicted crash rate distribution

  21. Default risk ratings of curves and IL’s

  22. Moderations to default curve risk ratings • High risk curves >250mR lowered to low if speed difference less than 15km/h • High risk curves >250mR lowered to medium if speed difference below 20km/h • Medium risk curves (<250mR) raised to high if speed difference greater than 35km/h • High risk curves <250mR lowered to medium risk if speed difference <20km/h

  23. Actual injury crash rates versus risk rating

  24. Implications for NZ’s rural SH network • Superseded T10:2002 • 11800 curves (<250mR) • Approximately 1041 km’s (9.3% of network) , IL=0.5 • T10:2010 (curve risk rating incorporated) • ≈ 17000 curves (≤400mR) • Equates to 2620 km’s (23.4% of network) • 505 km (4.5% of network) low risk (IL=0.40 or 0.45) • 1365 km (12.2% of network) medium risk (IL=0.50) • 750 km (6.7% of network) high risk (IL=0.55)

  25. Concluding Remarks • Extending <250mR curves (T10:2002 site cat 2 curves) to include transition spiral increases length of network managed to an IL=0.5 from 1041 kms (9.3% of network) to 1699 kms (15.6% of network). However, B/C ≈ 10. • Applying curve risk rating procedure to extended curves gives B/C≈ 26. • Targeted skid resistance management of curves seen as a very cost-effective safety measure. • Curve table incorporated in RAMM to assist industry.

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