hsm tables, case studies, and sample...

HSM Tables, Case Studies,

and Sample Problems

Table of Contents

Chapter 10 Tables: HSM Default Tables – Local Values (Michigan) ................................ 1 Chapter 11 Tables: HSM Default Tables – Local Values (Michigan) ................................ 5 Chapter 12 Tables: HSM Default Tables – Michigan Values Not Available ................. 10 Sample Problem 3-1: .................................................................................................................. 17 Sample Problem 4-1: .................................................................................................................. 20 Case Study 7-1: ............................................................................................................................ 28 Case Study 9-1: ............................................................................................................................ 35 Case Study 10-1: .......................................................................................................................... 53 Case Study 11-1: .......................................................................................................................... 69 Chap 10 Sample Problem 1:...................................................................................................... 83 Chap 10 Sample Problem 2:...................................................................................................... 86 Chap 10 Sample Problem 3:...................................................................................................... 91 Chap 10 Sample Problem 4:...................................................................................................... 94 Chap 10 Sample Problem 5:...................................................................................................... 97 Chap 10 Sample Problem 6:...................................................................................................... 97 Chap 11 Sample Problem 1:...................................................................................................... 99 Chap 11 Sample Problem 2:.................................................................................................... 101 Chap 11 Sample Problem 3:.................................................................................................... 104 Chap 11 Sample Problem 4:.................................................................................................... 107 Chap 11 Sample Problem 5:.................................................................................................... 108 Chap 11 Sample Problem 6:.................................................................................................... 109 Chapter 10 Sample Problems - Data Entry Tables ............................................................. 111

HSM Chapter 10 Sample Problem 5 .......................................................................... 115 HSM Chapter 10 Sample Problem 6 .......................................................................... 116

Chapter 11 Sample Problems - Data Entry Tables ............................................................. 117 HSM Chapter 11 Sample Problem 4 .......................................................................... 120 HSM Chapter 11 Sample Problem 5 .......................................................................... 121

Chapter 12 Sample Problems - Data Entry Tables ............................................................. 122 HSM Chapter 10 Sample Problem 5 .......................................................................... 126 HSM Chapter 12 Sample Problem 6 .......................................................................... 127

HSM Chapter 10 Worksheets (Sample) ............................................................................... 128

HSM Chapter 10 Tables

Chapter 10 Tables

1

Chapter 10 Tables: HSM Default Tables – Local Values (Michigan) Table 10-3: Distribution for Crash Severity Level on Rural Two-Lane Two-Way Roadway Segments plus Michigan Derived Values

Crash severity level

Percentage of total roadway segment crashes

HSM-Provided Values Locally-Derived Values (Michigan)

Fatal 1.3 0.5

Incapacitating Injury 5.4 1.8

Non-incapacitating Injury 10.9 3.3

Possible Injury 14.5 5.3

Total Fatal Plus Injury 32.1 10.9

Property Damage Only 67.9 89.1

TOTAL 100.0 100.0

Note: HSM-provided crash severity data based on HSIS data for Washington (2002-2006). Locally-Derived Values provided courtesy of the Michigan Department of Transportation (MDOT).

Table 10-4: Default Distribution by Collision Type for Specific Crash Severity Levels on Rural Two-Lane Two-Way Roadway Segments plus Michigan Derived Values

Collision type

Percentage of total roadway segment crashes by crash severity level


Total fatal and injury

Property damage only

TOTAL (all severity levels

combined)

Total fatal and injury

Property damage

only

TOTAL combined

SINGLE-VEHICLE CRASHES

Collision with animal 3.8 18.4 12.1 11.5 74.8 67.7

Collision with bicycle 0.4 0.1 0.2 0.7 0.0 0.0

Collision with pedestrian 0.7 0.1 0.3 1.3 0.0 0.2

Overturned 3.7 1.5 2.5 15.5 2.5 4.0

Ran off road 54.5 50.5 52.1 26.7 11.2 12.9

Other single-vehicle crash 0.7 2.9 2.1 2.9 1.3 1.5

Total single-vehicle crashes 63.8 73.5 69.3 58.7 89.9 86.5

MULTIPLE-VEHICLE CRASHES

Angle collision 10.0 7.2 8.5 6.1 1.2 1.7

Head-on collision 3.4 0.3 1.6 9.0 0.3 1.3

Rear-end collision 16.4 12.2 14.2 16.4 4.2 5.5

Sideswipe collision 3.8 3.8 3.7 5.7 2.4 2.8

Other multiple-vehicle collision 2.6 3.0 2.7 4.2 2.0 2.3

Total multiple-vehicle crashes 36.2 26.5 30.7 41.3 10.1 13.6

TOTAL CRASHES 100.0 100.0 100.0 100.0 100.0 100.0

Note: HSM-provided values based on crash data for Washington (2002-2006); includes approximately 70 % opposite-direction sideswipe and 30% same-direction sideswipe collisions. Locally-Derived Values provided courtesy of the Michigan Department of Transportation (MDOT).

Table 10-5: Default Distribution for Crash Severity Level at Rural Two-Lane Two-Way Intersections Michigan Derived Values

Collision type

Percentage of total crashes


3ST 4ST 4SG 3ST 4ST 4SG

Fatal 1.7 1.8 0.9 0.5 0.7 0.2

Incapacitating injury 4.0 4.3 2.1 2.8 4.0 2.5

Non-incapacitating injury 16.6 16.2 10.5 5.5 6.8 5.7

Possible injury 19.2 20.8 20.5 9.8 12.0 15.1

Total fatal plus injury 41.5 43.1 34.0 18.6 23.5 23.5

Property damage only 58.5 56.9 66.0 81.4 76.5 76.5

TOTAL 100.0 100.0 100.0 100.0 100.0 100.0

Note: Locally-Derived Values provided courtesy of the Michigan Department of Transportation (MDOT).


Chapter 10 Tables

2

Table 10-6: Default Distribution for Collision Type and Manner of Collision at Rural Two-Way Intersections plus Michigan Derived Values

Collision type

Percentage of total crashes by collision type: HSM Default Values

Three-leg stop-controlled intersections

Four-leg stop-controlled intersections

Four-leg signalized intersections

Fatal and

Injury

Property damage

only Total

Fatal and

injury

Property damage

only Total

Fatal and

injury

Property damage

only Total


Collision with animal 0.8 2.6 1.9 0.6 1.4 1.0 0.0 0.3 0.2

Collision with bicycle 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

Collision with pedestrian 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

Overturned 2.2 0.7 1.3 0.6 0.4 0.5 0.3 0.3 0.3

Ran off road 24.0 24.7 24.4 9.4 14.4 12.2 3.2 8.1 6.4

Other single-vehicle crash 1.1 2.0 1.6 0.4 1.0 0.8 0.3 1.8 0.5

Total single-vehicle crashes 28.3 30.2 29.4 11.2 17.4 14.7 4.0 10.7 7.6


Angle collision 27.5 21.0 23.7 53.2 35.4 43.1 33.6 24.2 27.4

Head-on collision 8.1 3.2 5.2 6.0 2.5 4.0 8.0 4.0 5.4

Rear-end collision 26.0 29.2 27.8 21.0 26.6 24.2 40.3 43.8 42.6

Sideswipe collision 5.1 13.1 9.7 4.4 14.4 10.1 5.1 15.3 11.8

Other multiple-vehicle collision

5.0 3.3 4.2 4.2 3.7 3.9 9.0 2.0 5.2

Total multiple-vehicle crashes 71.7 69.8 70.6 88.8 82.6 85.3 96.0 89.3 92.4

TOTAL CRASHES 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Collision type

Percentage of total crashes by collision type: Locally Derived Values (Michigan)

Three-leg stop-controlled intersections

Four-leg stop-controlled intersections


Fatal and Injury

Property damage

only Total

Fatal and

injury

Property damage

only Total

Fatal and

injury

Property damage

only Total


Collision with animal 3.9 39.4 32.8 1.5 28.8 22.3 0.2 4.4 3.4

Collision with bicycle 1.0 0.1 0.3 1.2 0.1 0.4 1.9 0.3 0.6

Collision with pedestrian 1.5 0 0.3 1.5 0 0.4 4.7 0.1 1.2

Overturned 9.6 2.6 3.9 3.1 1.4 1.8 0.3 0.3 0.3

Ran off road 18.8 17.7 17.9 8.5 11.8 11 3.7 5.0 4.7

Other single-vehicle crash 2.9 2.5 2.6 1.5 1.7 1.6 1.1 0.6 0.7

Total single-vehicle crashes 37.7 62.3 57.8 17.3 43.8 37.5 11.9 10.7 10.9


Angle collision 16.7 7.7 9.4 41.6 18.1 23.8 33.0 21.2 24.0

Head-on collision 8.9 1.5 2.9 9.0 2.6 4.1 14.6 6.1 8.1

Rear-end collision 26.6 15.7 17.7 20.7 17.4 18.1 31.9 37.5 36.3

Sideswipe collision 4.5 6.9 6.4 4.7 8.3 7.4 2.7 11.5 9.4

Other multiple-vehicle collision 5.6 5.9 5.8 6.7 9.8 9.1 5.9 13.0 11.3

Total multiple-vehicle crashes 62.3 37.7 42.2 82.7 56.2 62.5 88.1 89.3 89.1

TOTAL CRASHES 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0



Chapter 10 Tables

3

Table 10-8: CMF for Lane Width on Roadway Segments (CMFra)

Lane Width (ft) AADT (veh/day)

< 400 400 to 2000 > 2000 9 1.05 1.50 9.5 1.04 1.40 10 1.02 1.30 10.5 1.02 1.18 11 1.01 1.05 11.5 1.01 1.03 12 1.00 1.00 1.00

Table 10-9: CMF for Shoulder Width on Roadway Segments (CMFwra)

Shoulder Width (ft)

AADT (veh/day)

< 400 400 to 2000 > 2000

0 1.10 1.50

1 1.09 1.40

2 1.07 1.30

3 1.05 1.23

4 1.02 1.15

5 1.01 1.08

6 1.00 1.00

7 0.99 0.94

8 0.98 0.87

Table 10-10: Crash Modification Factors for Shoulder Types and Shoulder Widths on Roadway Segments (CMFtra) Shoulder

Type

Shoulder width (ft)

0 1 2 3 4 5 6 7 8

Paved 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Gravel 1.00 1.00 1.01 1.01 1.01 1.02 1.02 1.02 1.02

Composite 1.00 1.01 1.02 1.02 1.03 1.04 1.04 1.05 1.06

Turf 1.00 1.01 1.03 1.04 1.05 1.07 1.08 1.10 1.11

Note: The values for composite shoulders in this exhibit represent a shoulder for which 50 percent of the shoulder width is paved and 50 percent of the shoulder width is turf.

Table 10-11: Crash Modification Factors (CMF5r) for Grade of Roadway Segments Approximate Grade (%)

Level Grade ( ≤ 3% ) Moderate Terrain ( 3% < grade ≤ 6% ) Steep Terrain ( >6% )

1.00 1.10 1.16

Table 10-12: Nighttime Crash Proportions for Unlighted Roadway Segments plus Michigan Derived Values

Roadway Type

HSM Default Values Locally Derived Values (Michigan)

Proportion of total nighttime crashes by severity level

Proportion of crashes that occur at night

Proportion of total nighttime crashes by severity level


Fatal and Injury pinr PDO ppnr pnr Fatal and Injury pinr PDO ppnr pnr

2U 0.382 0.618 0.370 0.270 0.650 0.463

Note: HSM-provided values based on HSIS data for Washington (2002-2006). Locally-Derived Values provided courtesy of the Michigan Department of Transportation (MDOT).


Chapter 10 Tables

4

Table 10-13: CMF for Installation of Left-Turn Lanes on Intersection Approaches (CMF2i)

Intersection type Intersection traffic control

Number of approaches with left-turn lanes a

1 2 3 4

Three-leg intersection Minor road stop control b 0.56 0.31 0.31 0.31

Four-leg intersection Minor road stop control b 0.72 0.52 0.52 0.52

Traffic signal 0.82 0.67 0.55 0.45

Table 10-14: CMF for Installation of Right-Turn Lanes on Intersection Approaches (CMF3i)

Intersection type Intersection traffic control

Number of approaches with left-turn lanes a

1 2 3 4

Three-leg intersection Minor road stop control b 0.86 0.74 0.74 0.74

Four-leg intersection Minor road stop control b 0.86 0.74 0.74 0.74

Traffic signal 0.96 0.92 0.88 0.85 a Stop-controlled approaches are not considered in determining the number of approaches with left-turn lanes b Stop signs present on minor road approaches only.

Table 10-15: Nighttime Crash Proportions for Unlighted Intersections

Intersection Type

Proportion of crashes that occur at night, pni

HSM Provided Values Locally-Derived Values (Michigan)

3ST 0.260 0.248

4ST 0.244 0.208

4SG 0.286 0.188

Note: Locally-Derived Values provided courtesy of the Michigan Department of Transportation (MDOT). Notes for Tables 8 & 9 for AADT 400 – 2000 See HSM for determining values


Chapter 11 Tables

5

Chapter 11 Tables: HSM Default Tables – Local

Values (Michigan) Table 11-4: Distribution of Crashes by Collision Type and Crash Severity Level for Undivided Roadway Segments

Collision type

Proportion of crashes by collision type and crash severity level


Total Fatal and

injury

Fatal and

injury a PDO Total

Fatal and injury

Fatal and

injury a PDO

Head-on 0.009 0.029 0.043 0.001 0.045 0.108 0.138 0.022

Sideswipe 0.098 0.048 0.044 0.120 0.155 0.062 0.061 0.189

Rear-end 0.246 0.305 0.217 0.220 0.205 0.266 0.188 0.184

Angle 0.356 0.352 0.348 0.358 0.149 0.180 0.184 0.138

Single 0.238 0.238 0.304 0.237 0.321 0.242 0.299 0.349

Other 0.053 0.028 0.044 0.064 0.125 0.143 0.130 0.188

SV run-off-rd, Head-on, Sideswipe 0.270


Table 11-6: Distribution of Crashes by Collision Type and Crash Severity Level for Divided Roadway Segments

Collision type



Total Fatal and

injury Fatal and injury a

PDO Total Fatal and


PDO

Head-on 0.006 0.013 0.018 0.002 0.009 0.018 0.033 0.006

Sideswipe 0.043 0.027 0.022 0.053 0.120 0.059 0.055 0.139

Rear-end 0.116 0.163 0.114 0.088 0.136 0.195 0.143 0.118

Angle 0.043 0.048 0.045 0.041 0.046 0.086 0.143 0.034

Single 0.768 0.727 0.778 0.792 0.626 0.605 0.604 0.633

Other 0.024 0.022 0.023 0.024 0.063 0.036 0.022 0.072




Chapter 11 Tables

6

Table 11-9: Distribution of Intersection Crashes by Collision Type and Crash Severity

Collision type



Total Fatal and


PDO Total Fatal and

injury

Fatal and

injury a PDO

Three-leg intersections with minor road stop control

Head-on 0.029 0.043 0.052 0.020 0.050 0.103 0.146 0.028

Sideswipe 0.133 0.058 0.057 0.179 0.096 0.049 0.051 0.115

Rear-end 0.289 0.247 0.142 0.315 0.293 0.299 0.198 0.291

Angle 0.263 0.369 0.381 0.198 0.161 0.194 0.206 0.147

Single 0.234 0.219 0.284 0.244 0.307 0.266 0.300 0.324

Other 0.052 0.064 0.084 0.044 0.093 0.089 0.099 0.095


Four-leg intersections with minor road stop control

Head-on 0.016 0.018 0.023 0.015 0.056 0.094 0.120 0.038

Sideswipe 0.107 0.042 0.040 0.156 0.099 0.049 0.034 0.124

Rear-end 0.228 0.213 0.108 0.240 0.238 0.216 0.149 0.248

Angle 0.395 0.534 0.571 0.292 0.320 0.426 0.466 0.268

Single 0.202 0.148 0.199 0.243 0.180 0.124 0.128 0.207

Other 0.052 0.045 0.059 0.054 0.107 0.091 0.103 0.115



Head-on 0.054 0.083 0.093 0.034 0.087 0.146 0.204 0.067

Sideswipe 0.106 0.047 0.039 0.147 0.101 0.029 0.018 0.125

Rear-end 0.492 0.472 0.314 0.505 0.380 0.318 0.159 0.403

Angle 0.256 0.315 0.407 0.215 0.250 0.333 0.404 0.222

Single 0.062 0.041 0.078 0.077 0.058 0.049 0.065 0.060

Other 0.030 0.042 0.069 0.022 0.124 0.125 0.150 0.123


NOTE: a Using the KABCO scale, these include only KAB crashes. Crashes with severity level C (possible injury) are not included. Locally-Derived Values provided courtesy of the Michigan Department of Transportation (MDOT).

Table 11-10: Summary of CMFs in Chapter 11 and the Corresponding SPFs Applicable SPF CMF CMF Description CMF Equations and Exhibits

Undivided Roadway Segment SPF

CMF1ru Lane Width on Undivided Segments Equation 11-12, Table 11-11 and Figure 11-8

CMF2ru Shoulder Width and Shoulder Type Equation 11-14, Figure 11-9, Tables 11-12 and 11-13

CMF3ru Sideslopes Table 11-14

CMF4ru Lighting Equation 11-15, Table 11-15

CMF5ru Automated Speed Enforcement See text

Divided Roadway Segment SPF

CMF1rd Lane Width on Divided Segments Equation 11-16, Table 11-16, Figure 11-10

CMF2rd Right Shoulder Width on Divided Roadway Segment Table 11-17

CMF3rd Median Width Table 11-18

CMF4rd Lighting Equation 11-17, Table 11-19

CMF5rd Automated Speed Enforcement See text

Three- and Four-Leg Stop-Controlled Intersection SPFs

CMF1i Intersection Angle Tables 11-20, 11-21

CMF2i Left-Turn Lane on Major Road Tables 11-20, 11-21

CMF3i Right-Turn Lane on Major Road Tables 11-20, 11-21

CMF4i Lighting Tables 11-20, 11-21


Chapter 11 Tables

7

Table 11-11: CMF for Lane Width on Undivided Roadway Segments (CMFRA)

Lane Width (ft)

AADT (veh/day)

< 400 400 to 2000 > 2000

9 1.04 1.38

9.5 1.03 1.31

10 1.02 1.23

10.5 1.02 1.14

11 1.01 1.04

11.5 1.01 1.02

12 1.00 1.00 1.00

Note: The collision types related to lane width to which this CMF applies include run-off-the-road, head-on crashes, and sideswipes.

Table 11-12: CMF for Collision Types Related to Shoulder Width (CMFWRA)

Shoulder Width (ft)

AADT (veh/day)

< 400 400 to 2000 > 2000

0 1.10 1.50

1 1.09 1.40

2 1.07 1.30

3 1.05 1.23

4 1.02 1.15

5 1.01 1.08

6 1.00 1.00 1.00

7 0.99 0.94

8 0.98 0.87

Note: The collision types related to shoulder width to which this CMF applies include single-vehicle run-off-the-road and multiple-vehicle head-on, opposite-direction sideswipe, and same-direction sideswipe crashes.

Table 11-13: CMF for Collision Types Related to Shoulder Types and Shoulder Widths (CMFTRA)

Shoulder Type

Shoulder width (ft)

0 1 2 3 4 5 6 7 8 9 10

Paved 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Gravel 1.00 1.00 1.01 1.01 1.01 1.02 1.02 1.02 1.02 1.03 1.03

Composite 1.00 1.01 1.02 1.02 1.03 1.04 1.04 1.05 1.06 1.07 1.07

Turf 1.00 1.01 1.03 1.04 1.05 1.07 1.08 1.10 1.11 1.13 1.14

Table 11-14: CMF for Side Slope on Undivided Roadway Segments (CMF3ru) 1:2 or Steeper 1:3 1:4 1:5 1:6 1:7 or Flatter

1.18 1.15 1.12 1.09 1.05 1.00

Table 11-15: Night-time Crash Proportions for Unlighted Roadway Segments

Roadway Type


Proportion of total night-time crashes by severity level




Fatal and injury, pinr PDO, ppnr pnr Fatal and injury, pinr PDO, ppnr pnr

4U 0.361 0.639 0.255 0.190 0.534 0.290



Chapter 11 Tables

8

Table 11-16: CMF for Lane Width on Divided Roadway Segments (CMFRA)

Lane Width (ft)

AADT (veh/day)

< 400 400 to 2000 > 2000

9 1.03 1.25

9.5 1.02 1.20

10 1.01 1.15

10.5 1.01 1.09

11 1.01 1.03

11.5 1.01 1.02

12 1.00 1.00 1.00

Note: The collision types related to lane width to which this CMF applies include run-off-the-road, head-on crashes, and sideswipes.

Table 11-17: CMF for Right Shoulder Width on Divided Roadway Segments (CMF2rd)

Average Shoulder Width (ft) CMF

0 1.18

1 1.16

2 1.13

3 1.11

4 1.09

5 1.07

6 1.04

7 1.02

8 1.00

9 1.00

10 1.00

Table 11-18: CMF for Median Width on Divided Roadway Segments without a Median Barrier (CMF3rd) Median Width (ft) CMF

10 1.04

20 1.02

30 1.00

40 0.99

50 0.97

60 0.96

70 0.96

80 0.95

90 0.94

100 0.94

Table 11-19: Night-time Crash Proportions for Unlighted Roadway Segments

Roadway Type






Fatal and injury, pinr PDO, ppnr pnr Fatal and injury, pinr PDO, ppnr pnr

4D 0.323 0.677 0.426 0.232 0.718 0.533



Chapter 11 Tables

9

Table 11-22: Crash Modification Factors (CMF2i) for Installation of Left-Turn Lanes on Intersection Approaches

Intersection Type Crash Severity Level

Number of Non-Stop-Controlled Approaches with Left-turn Lanesa

One Approach Two Approaches

Three-leg minor-road stop controlb

Total 0.56 -

Fatal and Injury 0.45 -

Four-leg minor-road stop controlb

Total 0.72 0.52

Fatal and Injury 0.65 0.42 a Stop-controlled approaches are not considered in determining the number of approaches with left-turn lanes

b Stop signs present on minor-road approaches only

Table 11-23: Crash Modification Factors (CMF3i) for Installation of Right-Turn Lanes on Intersection Approaches

Intersection Type Crash Severity Level

Number of Non-Stop-Controlled Approaches with Right-turn Lanesa

One Approach Two Approaches

Three-leg minor-road stop controlb

Total 0.86 -

Fatal and Injury 0.77 -

Four-leg minor-road stop controlb

Total 0.86 0.74

Fatal and Injury 0.77 0.59 a Stop-controlled approaches are not considered in determining the number of approaches with right-turn lanes

b Stop signs present on minor-road approaches only

Table 11-24: Night-time Crash Proportions for Unlighted Intersections

Roadway Type






Fatal and injury, pini PDO, ppnr pni Fatal and injury, pinr PDO, ppnr pni

3ST 0.276 0.148

4ST 0.273 0.106

Note: Locally-Derived Values provided courtesy of the Michigan Department of Transportation (MDOT). Notes for Tables 11-11, 11-12 and 11-16 for AADT 400 – 2000 see HSM.

HSM Chapter 12 Tables: HSM Default Tables – Michigan Values Not Available

Chapter 12 Tables

10

Chapter 12 Tables: HSM Default Tables – Michigan

Values Not Available Table 12-3: SPF Coefficients for Multiple-Vehicle Non-driveway Collisions on Roadway Segments

Road type

Coefficients use in Eqn. 12-10 Overdispersion parameter (k)

Intercept AADT

(a) (b)

Total crashes

2U -15.22 1.68 0.84

3T -12.40 1.41 0.66

4U -11.63 1.33 1.01

4D -12.34 1.36 1.32

5T -9.70 1.17 0.81

Fatal-and-injury crashes

2U -16.22 1.66 0.65

3T -16.45 1.69 0.59

4U -12.08 1.25 0.99

4D -12.76 1.28 1.31

5T -10.47 1.12 0.62

Property-damage-only crashes

2U -15.62 1.69 0.87

3T -11.95 1.33 0.59

4U -12.53 1.38 1.08

4D -12.81 1.38 1.34

5T -9.97 1.17 0.88

Table 12-4: Distribution of Multiple-Vehicle Non-driveway Collisions for Roadway Segments by Manner of Collision Type

Collision type

Proportion of crashes by severity level for specific road types

HSM-Provided Values

2U 3T 4U 4D 5T

FI PDO FI PDO FI PDO FI PDO FI PDO

Rear-end collision 0.730 0.778 0.845 0.842 0.511 0.506 0.832 0.662 0.846 0.651

Head-on collision 0.068 0.004 0.034 0.020 0.077 0.004 0.020 0.007 0.021 0.004

Angle collision 0.085 0.079 0.069 0.020 0.181 0.130 0.040 0.036 0.050 0.059

Sideswipe, same direction 0.015 0.031 0.001 0.078 0.093 0.249 0.050 0.223 0.061 0.248

Sideswipe, opposite direction 0.073 0.055 0.017 0.020 0.082 0.031 0.010 0.001 0.004 0.009

Other multiple-vehicle collision 0.029 0.053 0.034 0.020 0.056 0.080 0.048 0.071 0.018 0.029

Source: HSIS data for Washington (2002-2006)

Collision type

Locally-Derived Values

2U 3T 4U 4D 5T


Rear-end collision

Head-on collision

Angle collision

Sideswipe, same direction

Sideswipe, opposite direction


Note: HSM-Provided values based on HSIS data for Washington (2002-2006)


Chapter 12 Tables

11

Table 12-5: SPF Coefficients for Single-Vehicle Collisions on Roadway Segments

Road type


Intercept AADT

(a) (b)

Total crashes

2U -5.47 0.56 0.81

3T -5.74 0.54 1.37

4U -7.99 0.81 0.91

4D -5.05 0.47 0.86

5T -4.82 0.54 0.52


2U -3.96 0.23 0.50

3T -6.37 0.47 1.06

4U -7.37 0.61 0.54

4D -8.71 0.66 0.28

5T -4.43 0.35 0.36


2U -6.51 0.64 0.87

3T -6.29 0.56 1.93

4U -8.50 0.84 0.97

4D -5.04 0.45 1.06

5T -5.83 0.61 0.55

Table 12-6: Distribution of Single-Vehicle Collisions for Roadway Segments by Collision Type

Collision type

Proportion of crashes by severity level for specific road types

HSM-Provided Values

2U 3T 4U 4D 5T


Collision with animal 0.026 0.066 0.001 0.001 0.001 0.001 0.001 0.063 0.016 0.049

Collision with fixed object 0.723 0.759 0.688 0.963 0.612 0.809 0.500 0.813 0.398 0.768

Collision with other object 0.010 0.013 0.001 0.001 0.020 0.029 0.028 0.016 0.005 0.061

Other single-vehicle collision 0.241 0.162 0.310 0.035 0.367 0.161 0.471 0.108 0.581 0.122


Collision type


2U 3T 4U 4D 5T


Collision with animal

Collision with fixed object

Collision with other object

Other single-vehicle collision

Table 12-8: Pedestrian Crash Adjustment Factor for Roadway Segments

Road type

Pedestrian Crash Adjustment Factor (fpedr)

HSM-Provided Values Locally-Derived Values

Posted Speed 30 mph or Lower

Posted Speed Greater than 30 mph



2U 0.036 0.005

3T 0.041 0.013

4U 0.022 0.009

4D 0.067 0.019

5T 0.030 0.023

Note: These factors apply to the methodology for predicting total crashes (all severity levels combined). All pedestrian collisions resulting from this adjustment factor are treated as fatal-and-injury crashes and none as property-damage-only crashes. Source: HSIS data for Washington (2002-2006)


Chapter 12 Tables

12

Table 12-9: Bicycle Crash Adjustment Factor for Roadway Segments

Road type

Bicycle Crash Adjustment Factor (fbiker)






2U 0.018 0.004

3T 0.027 0.007

4U 0.011 0.002

4D 0.013 0.005

5T 0.050 0.012

Note: These factors apply to the methodology for predicting total crashes (all severity levels combined). All pedestrian collisions resulting from this adjustment factor are treated as fatal-and-injury crashes and none as property-damage-only crashes. Source: HSIS data for Washington (2002-2006)

Table 12-10: SPF Coefficients for Multiple-Vehicle Collisions at Intersections

Intersection type


Intercept AADTmaj AADTmin

(a) (b) (c)

Total crashes

3ST -13.36 1.11 0.41 0.80

3SG -12.13 1.11 0.26 0.33

4ST -8.90 0.82 0.25 0.40

4SG -10.99 1.07 0.23 0.39


3ST -14.01 1.16 0.30 0.69

3SG -11.58 1.02 0.17 0.30

4ST -11.13 0.93 0.28 0.48

4SG -13.14 1.18 0.22 0.33


3ST -15.38 1.20 0.51 0.77

3SG -13.24 1.14 0.30 0.36

4ST -8.74 0.77 0.23 0.40

4SG -11.02 1.02 0.24 0.44

Table 12-11: Distribution of Multiple-Vehicle Collisions for Intersections by Collision Type

Collision type

Proportion of crashes by severity level for specific intersection types

HSM-Provided Values

3ST 3SG 4ST 4SG

FI PDO FI PDO FI PDO FI PDO

Rear-end collision 0.421 0.440 0.549 0.546 0.338 0.374 0.450 0.483

Head-on collision 0.045 0.023 0.038 0.020 0.041 0.030 0.049 0.030

Angle collision 0.343 0.262 0.280 0.204 0.440 0.335 0.347 0.244

Sideswipe 0.126 0.040 0.076 0.032 0.121 0.044 0.099 0.032


0.065 0.235 0.057 0.198 0.060 0.217 0.055 0.211


Collision type


3ST 3SG 4ST 4SG


Rear-end collision

Head-on collision

Angle collision

Sideswipe


Note: HSM-Provided values based on HSIS data for California (2002-2006)


Chapter 12 Tables

13

Table 12-12: SPF Coefficients for Single-Vehicle Crashes at Intersections

Intersection type


Intercept AADTmaj AADTmin

(a) (b) (c)

Total crashes

3ST -6.81 0.16 0.51 1.14

3SG -9.02 0.42 0.40 0.36

4ST -5.33 0.33 0.12 0.65

4SG -10.21 0.68 0.27 0.36


3ST -- -- -- --

3SG -9.75 0.27 0.51 0.24

4ST -- -- -- --

4SG -9.25 0.43 0.29 0.09


3ST -8.36 0.25 0.55 1.29

3SG -9.08 0.45 0.33 0.53

4ST -7.04 0.36 0.25 0.54

4SG -11.34 0.78 0.25 0.44

Note: Where no models are available, the equation used is Nbisv(FI) = Nbisv(TOTAL) x fbisv

Table 12-13: Distribution of Single-Vehicle Crashes for Intersections by Collision Type

Collision type

Proportion of crashes by severity level for specific intersection types

HSM-Provided Values

3ST 3SG 4ST 4SG


Collision with parked vehicle 0.001 0.003 0.001 0.001 0.001 0.001 0.001 0.001

Collision with animal 0.003 0.018 0.001 0.003 0.001 0.026 0.002 0.002

Collision with fixed object 0.762 0.834 0.653 0.895 0.679 0.847 0.744 0.870

Collision with other object 0.090 0.092 0.091 0.069 0.089 0.070 0.072 0.070

Other single-vehicle collision 0.039 0.023 0.045 0.018 0.051 0.007 0.040 0.023

Noncollision 0.105 0.030 0.209 0.014 0.179 0.049 0.141 0.034

Source: HSM-Provided values base on HSIS data for California (2002-2006)

Collision type


3ST 3SG 4ST 4SG


Collision with parked vehicle


Collision with fixed object

Collision with other object


Noncollision

Table 12-14: SPF for Vehicle-Pedestrian Collisions at Signalized Intersections

Intersection type


Intercept AADTtot AADTmin/AADTmaj PedVol nlanesx

(a) (b) (c) (d) (e)

Total crashes

3SG -6.60 0.05 0.24 0.41 0.09 0.52

4SG -9.53 0.40 0.26 0.45 0.04 0.24


Chapter 12 Tables

14

Table 12-15: Estimates of Pedestrian Crossing Volumes Based on General Level of Pedestrian Activity

General Level of Pedestrian Activity

Estimate of PedVol (pedestrians/day) for Use in Equation 12-29

3SG Intersections 4SG Intersections

High 1,700 3200

Medium-high 750 1500

Medium 400 700

Medium-low 120 240

Low 20 50

Table 12-16: Pedestrian Crash Adjustment Factors for Stop-Controlled Intersections Intersection Type Pedestrian Crash Adjustment Factor (fpedi)

3ST 0.021

4ST 0.022

Table 12-17: Bicycle Crash Adjustment Factors for Intersections Intersection Type Bicycle Crash Adjustment Factor (fbikei)

3ST 0.016

3SG 0.011

4ST 0.018

4SG 0.015

Table 12-19: Values of fpk Used in Determining the CMF for On-Street Parking

Road Type

Type of Parking and Land Use

Parallel Parking Angle Parking

Residential/ Other

Commercial or Industrial/ Institutional

Residential/ Other

Commercial or Industrial/ Institutional

U 1.465 2.074 3.428 4.853

3T 1.465 2.074 3.428 4.853

4U 1.100 1.709 2.574 3.999

4D 1.100 1.709 2.574 3.999

5T 1.100 1.709 2.574 3.999

Note: These factors apply to the methodology for predicting total crashes (all severity levels combined). All bicycle collisions resulting from this adjustment factor are treated as fatal-and-injury crashes and none as property-damage-only crashes. Source: HSIS data for Washington (2002-2006)

Table 12-22: CMFs for Median Widths on Divided Roadway Segments without a Median Barrier (CMF3r) Median Width (ft) CMF

10 1.01

15 1.00

20 0.99

30 0.98

40 0.97

50 0.96

60 0.95

70 0.94

80 0.93

90 0.93

100 0.92


Chapter 12 Tables

15

Table 12-23: Nighttime Crash Proportions for Unlighted Roadway Segments

Road Type


Proportion of Total Nighttime Crashes by Severity Level

Proportion of Crashes that

Occur at Night

Proportion of Total Nighttime Crashes by Severity Level

Proportion of Crashes that

Occur at Night

Fatal and Injury (pinr) PDO (ppnr) (pnr) Fatal and Injury

(pinr) PDO (ppnr) (pnr)

2U 0.424 0.576 0.316

3T 0.429 0.571 0.304

4U 0.517 0.483 0.365

4D 0.364 0.636 0.410

5T 0.432 0.568 0.274

Table 12-24: Crash Modification Factor (CMF1i) for Installation of Left-Turn Lanes on Intersection Approaches Intersection Type

Intersection traffic control Number of approaches with left-turn lanes a

One approach Two approaches Three approaches Four approaches

3ST Minor-road STOP controlb 0.67 0.45 -- --

3SG Traffic signal 0.93 0.86 0.80 0.80

4ST Minor-road STOP controla 0.73 0.53 -- --

4SG Traffic signal 0.90 0.81 0.73 0.66 a STOP-controlled approaches are not considered in determining the number of approaches with left-turn lanes. b Stop signs present on minor-road approaches only.

Table 12-25: Crash Modification Factor (CMF2i) for Type of Left-Turn Signal Phasing Type of Left-Turn Signal Phasing CMF2i

Permissive 1.00

Protected/permissive or permissive/protective 0.99

Protected 0.94

Note: Use CMF2i = 1.00 for all un-signalized intersections. If several approaches to a signalized intersection left-turn phasing, the values of CMF2i for each approach are multiplied together

Table 12-26: Crash Modification Factor (CMF3i) for Installation of Right-Turn Lanes on Intersection Approaches Intersection Type

Intersection traffic control Number of approaches with right-turn lanes a

One approach Two approaches Three approaches Four approaches

3ST Minor-road STOP controlb 0.86 0.74 -- --

3SG Traffic signal 0.96 0.92 -- --

4ST Minor-road STOP controla 0.86 0.74 -- --

4SG Traffic signal 0.96 0.92 0.88 0.85 a STOP-controlled approaches are not considered in determining the number of approaches with left-turn lanes. b Stop signs present on minor-road approaches only.

Table 12-27: Nighttime Crash Proportions for Unlighted Intersections

Intersection Type

Proportion of crashes that occur at night, pni


3ST 0.238 0.300

4ST 0.229 0.310

3SG 0.235 0.320

4SG 0.235 0.330


Chapter 12 Tables

16

Table 12-28: Crash Modification Factor (CMF1p) for the Presence of Bus Stops Near the Intersection Number of Bus Stops within 1,000 ft. of the Intersection CMF1p

0 1.00

1 or 2 2.78

3 or more 4.15

Table 12-29: Crash Modification Factor (CMF2p) for the Presence of Schools Near the Intersection Number of Schools within 1,000 ft. of the Intersection CMF2p

No school present 1.00

School present 1.35

Table 12-30: Crash Modification Factor (CMF3p) for the Number of Alcohol Sales Establishment near the Intersection

Number of Alcohol Sales Establishments within 1,000 ft. of the Intersection CMF3p

0 1.00

1-8 1.12

9 or more 1.56

HSM Module 3: Crash Modification Factors

Sample Problem 3-1

17

Sample Problem 3-1: Effectiveness of treatments on two-lane rural highway segment

Brief Description of the Project/Case

This analysis of a roadway segment involves County Road 63. The segment under review extends from CR 637 to CR 345. The roadway is a two-lane facility in a rural setting. Currently, the roadway segment consists of 12’ lanes with 4’ paved shoulders. What will be the likely change in expected run-off-the-road crashes and total crashes if the County narrows the lane widths to 11’ and widens the shoulder widths to 5’?

The 2008 traffic count indicates that the average annual daily traffic (AADT) for the segment was 4,494 vehicles per day. Table 3-1 summarizes the crash history for the segment. Table 3-1. Crash History for Segment

Year Run-off-the-road, head-on, and sideswipe

crashes

Total segment crashes

2006 10 26

2007 13 19

2008 10 17

Total 33 (11 .00 per year, 53.2% of total crashes)

62 (20.67 per year)

Step 1. Calculate the existing CMF for 12’ lanes Student Notes


Sample Problem 3-1

18

To adjust the lane width CMF for total crash assessment (based on proportion of crashes), use HSM Equation 13-3, p. 13-18.

Run-off-the-road, Head-on, & Sideswipe Crashes

Total Crashes

CMF = 1.00 (per Table 13-2) CMF = (1.00 – 1.00) x 0.532 + 1.00 (per Equation 13-3) CMF = 1.00

For lane width CMFs - use Table 13-2, p. 13-4 of the HSM. The percentage of run-off-the-road, head-on, and sideswipe crashes is 53.2% per Table 3-1 of this sample problem. (If local crash type % values are unknown, HSM Table 10-6 provides defaults.)

Step 2. Calculate the CMF for proposed 11’ lanes


Total Crashes


Step 3. Calculate the treatment corresponding to the change in lane width for run-off-the-road crashes and total crashes

𝐶𝑀𝐹𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡 =𝐶𝑀𝐹11′𝑙𝑎𝑛𝑒

𝐶𝑀𝐹12′𝑙𝑎𝑛𝑒


Total Crashes

𝐶𝑀𝐹𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡 =1.05

1.00= 1.05 𝐶𝑀𝐹𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡 =

1.027

1.00= 1.027

Where CMFfor 11’ from Step 2 CMFfor 12’ from Step 1

Step 4. Apply the treatment CMF to the expected number of crashes


Total Crashes

1.05 × 11.00 = 11.55 crashes/year

1.027 × 20.67 = 21.23 crashes/year

Use results from Step 3 and Table 3-1

Step 5. Change in expected crashes due to proposed lane width changes


Total Crashes

11.55 – 11.00 = 0.55 crashes/year (So an increase of 0.55 crashes/year)

21.23 – 20.67 = 0.56 crashes/year (So an increase of 0.56 crashes/year)


Step 6. Calculate the existing CMF for 4’ paved shoulders

To adjust the paved shoulder width CMF for total crash assessment (based on proportion of crashes), use HSM Equation 13-3, p. 13-18.


Total Crashes


For paved shoulder width CMFs - use Table 13-7, p. 13-11 of the HSM. The percentage of run-off-the-road, head-on, and sideswipe crashes is 53.2% per Table 3-1.

Step 7. Calculate the CMF for proposed 5’ paved shoulders and 4,494 vpd


Sample Problem 3-1

19


Total Crashes


Step 8. Calculate the treatment corresponding to the change in shoulder width for run-off-the-road crashes and total crashes


Total Crashes

𝐶𝑀𝐹𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡 =1.075

1.15= 0.935 𝐶𝑀𝐹𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡 =

1.04

1.08= 0.963

𝐶𝑀𝐹𝑇𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡 =𝐶𝑀𝐹

5′𝑠ℎ𝑙𝑑

𝐶𝑀𝐹4′𝑠ℎ𝑙𝑑

Where CMFfor 5’ from Step 7 CMFfor 4’ from Step 6

Step 9. Apply the treatment CMF to the expected number of crashes


Total Crashes

0.935 × 11.00 = 10.29 crashes/year

0.963 × 20.67 = 19.91 crashes/year


Step 10. Calculate the change in crashes due to proposed shoulder width changes.


Total Crashes

10.29 – 11.00 = -0.71 crashes/year (So a decrease of 0.71 crashes/year)

19.91 – 20.67 = -0.76 crashes/year (So a decrease of 0.76 crashes/year)


Step 11. Total change in expected crashes due to lane and shoulder width changes


Total Crashes

∆ Crashes = 0.55 – 0.71 = -0.16 (So an overall decrease of 0.16

crashes/year)

∆ Crashes = 0.56 – 0.76 = -0.20 (So an overall decrease of 0.20

crashes/year )

11.00 – 0.16 = 10.84 expected crashes following treatment

20.67 - 0.20 = 20.47 expected crashes following treatment

Use results from Step 5 and Step 10

SUMMARY The proposed changes will slightly decrease the run-off-the-road, head-on, and sideswipe crashes as well as total crashes.

HSM Module 4: Predictive Method Process

Sample Problem 4-1

20

Sample Problem 4-1: Design Exception Case Study

Brief Description of the Project/Case Student Notes

The intersection of a four-lane undivided rural highway with minor road

(STOP-controlled) currently does not have turn lanes and the lane width

and shoulder width adhere to AASHTO policies.

As a possible way of improving safety at the intersection, an agency is

considering narrowing the paved lane and shoulder widths so that they can

maintain existing right-of-way widths and potentially add left and/or right

turn-lanes on the mainline approaches.

Using the predictive methodologies included in the HSM Vol. 2 (Part C)

Chapter 11: Multilane Rural Highways, evaluate the impact of the

proposed alternative designs on expected crash frequency for the year

2009.

Step 1 – Identify data needs for the facility

Existing Road (study segment length of 0.38 miles):

Mainline (major road)

AADT of 30,000 vpd in 2009 (assume does not change at intersection) 66’ cross-section (4 lanes + 2 shlds) [Lane Widths = 12’, Paved Shlds = 8’] Design Speed = 50 mph No lighting or automated speed enforcement No turn lanes and no intersection skew Roadside slope = 1:7 Intersecting Highway (minor road)

AADT of 5,000 vpd in 2009 (assume does not change at intersection) Lane Widths = 11’, No Shoulders (graded or paved) Design Speed = 50 mph Proposed Design “A”:

Mainline (major road) changes

Lane Widths reduced from 12’ to 11’ (does not meet policy and so requires an exception) Shoulder widths reduced from 8’ to 6’ (does not meet policy and so requires an exception) Add left-turn lanes in each direction (10’ wide, 500’ in length)


Sample Problem 4-1

21

Proposed Design “B”:

Mainline (major road) changes

Lane Widths reduced from 12’ to 10’ (does not meet policy) Shoulder widths reduced from 8’ to 3’ (does not meet policy) Add left-turn lanes and right-turn-lanes in each direction (10’ wide, 500’ in length)

Step 2 – Divide locations into homogeneous segments or

intersections

For this study, all alternatives apply to one intersection location so this can

be perceived as a single homogeneous segment site and a single

homogeneous intersection site.

Step 3 – Apply the appropriate SPF

It is appropriate to compute the SPF values for segments and intersections

and then add them together. Since this location has modifications that

directly influence lane and shoulder widths (safety influences captured

during segment analysis), it is important to include this step.

𝑁𝑝𝑟𝑒𝑑𝑖𝑐𝑡𝑒𝑑 = 𝑁𝑠𝑝𝑓 × (𝐶𝑀𝐹1𝑥 × 𝐶𝑀𝐹2𝑥 × 𝐶𝑀𝐹𝑦𝑥) × 𝐶𝑥

For all designs, the same SPF will be used but some of the CMF values will

change due to the various proposed designs. Since this location is

consistent for all candidate designs, the calibration factor will be the same

for all designs.

Predicted Segment Crashes for Base Conditions:

Using Equation 11-7, the segment SPF for base conditions can be

determined as follows:

𝑁 𝑠𝑝𝑓𝑠𝑒𝑔𝑚𝑒𝑛𝑡

= 𝑒[𝑎+𝑏×ln(𝐴𝐴𝐷𝑇)+ ln(𝐿)]


Sample Problem 4-1

22

The variables are defined from Table 11-3 for the various severity levels:

𝑁 𝑠𝑝𝑓 𝑡𝑜𝑡𝑎𝑙𝑠𝑒𝑔𝑚𝑒𝑛𝑡 𝑐𝑟𝑎𝑠ℎ𝑒𝑠

= 𝑒[−9.653+1.176×ln(30,000)+ ln(0.38)] = 4.49

Predicted Intersection Crashes for Base Conditions:

Using Equation 11-11, the intersection SPF for base conditions can be

determined as follows:

𝑁𝑠𝑝𝑓 = 𝑒[𝑎+𝑏×ln(𝐴𝐴𝐷𝑇𝑚𝑎𝑗)+𝑐×ln(𝐴𝐴𝐷𝑇𝑚𝑖𝑛)]

The variables are defined from Table 11-7 for the various severity levels:

𝑁 𝑠𝑝𝑓 𝑡𝑜𝑡𝑎𝑙𝑖𝑛𝑡 𝑐𝑟𝑎𝑠ℎ𝑒𝑠

= 𝑒[−10.008+0.848×ln(30,000)+0.448×ln(5,000)] = 12.80


Sample Problem 4-1

23

Step 4 – Apply CMFs as needed

Segment Base Conditions (Undivided Roadway):

Lane Width = 12’

Shoulder Width = 6’

Shoulder Type = Paved

Side Slopes = 1V:7H or flatter

No lighting or automated speed enforcement

CMFs will be needed for any conditions that do not meet these base

conditions, so for the proposed designs the lane width and shoulder width

CMF values are required.

Lane Width CMF (applicable for run-off-road, head-on, & sideswipe):

So, LW=11’ has CMFRA=1.04, LW=10’ has CMFRA=1.23 (related crashes)

𝑪𝑴𝑭𝟏𝒓𝒖 = (𝑪𝑴𝑭𝑹𝑨 − 𝟏. 𝟎) × 𝒑𝑹𝑨 + 𝟏. 𝟎

For 11’ lanes:

𝑪𝑴𝑭𝟏𝒓𝒖 = (𝟏. 𝟎𝟒 − 𝟏. 𝟎) × 𝟎. 𝟐𝟕 + 𝟏. 𝟎 = 𝟏. 𝟎𝟏𝟎𝟖


Sample Problem 4-1

24

For 10’ lanes:

𝑪𝑴𝑭𝟏𝒓𝒖 = (𝟏. 𝟐𝟑 − 𝟏. 𝟎) × 𝟎. 𝟐𝟕 + 𝟏. 𝟎 = 𝟏. 𝟎𝟔𝟐𝟏

Shoulder Width CMF (applicable for run-off-road, head-on, & sideswipe):

So, SW=8’ has CMFWRA=0.87, LW=3’ has CMFWRA=1.225 (related crashes)

Since the shoulder is paved, this will have a CMFTRA value of 1.00 for all

cases.

Apply Shoulder CMF values for each segment scenario:

𝑪𝑴𝑭𝟐𝒓𝒖 = (𝑪𝑴𝑭𝑾𝑹𝑨 × 𝑪𝑴𝑭𝑻𝑹𝑨 − 𝟏. 𝟎) × 𝒑𝑹𝑨 + 𝟏. 𝟎

For 8’ paved shoulders:

𝑪𝑴𝑭𝟐𝒓𝒖 = (𝟎. 𝟖𝟕 × 𝟏. 𝟎𝟎 − 𝟏. 𝟎) × 𝟎. 𝟐𝟕 + 𝟏. 𝟎 = 𝟎. 𝟗𝟔𝟒𝟗


𝑪𝑴𝑭𝟐𝒓𝒖 = (𝟏. 𝟎𝟎 × 𝟏. 𝟎𝟎 − 𝟏. 𝟎) × 𝟎. 𝟐𝟕 + 𝟏. 𝟎 = 𝟏. 𝟎𝟎


𝑪𝑴𝑭𝟐𝒓𝒖 = (𝟏. 𝟐𝟐𝟓 × 𝟏. 𝟎𝟎 − 𝟏. 𝟎) × 𝟎. 𝟐𝟕 + 𝟏. 𝟎 = 𝟏. 𝟎𝟔𝟎𝟖


Sample Problem 4-1

25

Existing Conditions (12’ lanes, 8’ shoulders):

𝑁𝑝𝑟𝑒𝑑𝑖𝑐𝑡𝑒𝑑 = 𝑁𝑠𝑝𝑓 × (𝐶𝑀𝐹1𝑟𝑢 × 𝐶𝑀𝐹2𝑟𝑢)

𝑁𝑝𝑟𝑒𝑑𝑖𝑐𝑡𝑒𝑑 = 4.49 × (1.0 × 0.9649) = 4.33

Proposed Design “A” (11’ lanes, 6’ shoulders):

𝑁𝑝𝑟𝑒𝑑𝑖𝑐𝑡𝑒𝑑 = 4.49 × (1.0108 × 1.00) = 4.54

Proposed Design “B” (10’ lanes, 3’ shoulders):

𝑁𝑝𝑟𝑒𝑑𝑖𝑐𝑡𝑒𝑑 = 4.49 × (1.0621 × 1.054) = 5.06

Intersection Base Conditions (4-Leg Minor STOP-controlled):

Intersection Skew Angle of 0-degrees

No left-turn or right-turn lanes (unless stop-controlled)

No lighting

CMFs will be needed for any conditions that do not meet these

intersection base conditions, so for the proposed designs the addition of

turn lanes require CMF adjustments. CMF values of 1.0 will be used for the

skew and lighting CMF as these adhere to base conditions.


Sample Problem 4-1

26

Left-turn Lane CMF:

For left-turn lanes on two approaches (total crashes):

𝑪𝑴𝑭𝟐𝒊 = 𝟎. 𝟓𝟐

For no left-turn lanes:

𝑪𝑴𝑭𝟐𝒊 = 𝟏. 𝟎𝟎

Right-turn Lane CMF:

For right-turn lanes on two approaches (total crashes):

𝑪𝑴𝑭𝟑𝒊 = 𝟎. 𝟕𝟒

For no right-turn lanes:

𝑪𝑴𝑭𝟑𝒊 = 𝟏. 𝟎𝟎


Sample Problem 4-1

27

To determine predicted crashes at intersections for each option:

Existing Conditions (12’ lanes, 8’ shoulders):

𝑁𝑎𝑑𝑗𝑢𝑠𝑡𝑒𝑑𝑝𝑟𝑒𝑑𝑖𝑐𝑡𝑒𝑑

= 𝑁𝑠𝑝𝑓 × (𝐶𝑀𝐹1𝑖 × 𝐶𝑀𝐹2𝑖 × 𝐶𝑀𝐹3𝑖 × 𝐶𝑀𝐹4𝑖)

𝑁 𝑡𝑜𝑡𝑎𝑙 𝑖𝑛𝑡𝑐𝑟𝑎𝑠ℎ𝑒𝑠 𝑎𝑑𝑗

= 12.80 × (1.0 × 1.0 × 1.0 × 1.0) = 12.80

Proposed Design “A” (add left-turn lanes, no right-turn lanes):


= 12.80 × (1.0 × 0.52 × 1.0 × 1.0) = 6.66

Proposed Design “B” (add left-turn lanes and right-turn lanes):


= 12.80 × (1.0 × 0.52 × 0.74 × 1.0) = 4.93

Combine Predicted Crashes for Segment and Intersections:

Scenario Segment

Crashes for

2009

Intersection

Crashes for

2009

Total Predicted

Crashes for

2009

Existing 4.33 12.80 17.13

A 4.54 6.66 11.20

B 5.06 4.93 9.99

Step 5 – Apply Local Calibration Factor

For site-specific comparisons, the calibration factor is the same for all

scenarios. If the goal is to simply determine which scenario would

generate the lowest number of crashes (by comparison), then the

calibration factor is not required here. If the goal is to more accurately the

actual number of crashes for each scenario, then multiply each value

obtained in Step 4 by the local calibration factor.

For the two alternative scenarios, Proposed Design “B” with the narrower

lanes and shoulders but left and right-turn lanes results in the fewest

expected crashes at this location (9.71 for the year 2009).

Acknowledgement: The original sample problem was developed by Michael

Dimaiuta, Larry Sutherland, and Karen Dixon.

Module 7: Network Screening

Case Study 7-1

28

Case Study 7-1: Network Screening – Vol. 1 (Part B) Case Study


The following case study provides sample data for ten intersections with five-years of crash data (2003-2007). A county is undertaking an effort to improve safety on their highway network and is screening ten intersections to identify sites with potential for reducing crashes depending on various criteria. The county will follow the HSM Roadway Safety Management Process beginning with Network Screening. Your first objective is to perform a network screening analysis for the 10 candidate intersections using the crash rate ranking, EPDO ranking, and expected crash frequency with EB adjustment network screening procedures.

Group Discussion Questions: What are the strengths and/or weaknesses of each analysis procedure? Do the individual procedures provide dramatically different results? Which intersections should be the target for additional analysis?


Case Study 7-1

29

Acquire data for the network screening of the selected intersections

Available Data: For performing the network screening process, you will need crash data (crash type and crash severity) as well as traffic volume

for the candidate intersections.

Table 7-1. Sample Intersections – Traffic Control and Entering Volumes

Location Area Type & Traffic Control

Major Route ADT Minor Route ADT Intersection Major Route Minor Route

1 Morris Blvd Chicago Ave Signalized 33,300 13,200

2 1st Ave Golf Rd Signalized 34,800 17,500

3 Devon Ave Main St Signalized 27,800 18,600

4 3rd St Park Ave Signalized 29,200 1,100

5 Wilson Rd Lake St Signalized 16,600 16,100

6 Kennedy Blvd Main St Signalized 33,300 13,200

7 Roosevelt Rd Lake St Signalized 20,300 17,600

8 5th St Chicago Ave Signalized 30,800 18,500

9 Cicero Ave Banks Dr Signalized 37,500 17,400

10 Dawson Ave Howard St Signalized 13,100 12,700

Table 7-2. Sample Intersections – Crash Severity (2003 – 2007)

Location Crashes by Severity

Intersection Major Route Minor Route K A B C PDO

1 Morris Blvd Chicago Ave 0 11 35 17 194

2 1st Ave Golf Rd 0 10 33 37 242

3 Devon Ave Main St 0 3 7 9 100

4 3rd St Park Ave 0 4 6 10 60

5 Wilson Rd Lake St 0 0 1 5 48

6 Kennedy Blvd Main St 0 14 30 23 248

7 Roosevelt Rd Lake St 0 0 1 3 25

8 5th St Chicago Ave 0 16 21 29 381

9 Cicero Ave Banks Dr 0 14 15 20 165

10 Dawson Ave Howard St 0 0 1 9 40


Case Study 7-1

30

Table 7-3. Sample Intersections – Crash Type (2003 – 2007)

Location Head-On and

Opposite Direction Sideswipe

Fixed Object and

Overturned

Angle and

Turning

Rear End and Same Direction Sideswipe Animal

Pedestrian and Pedal-

cyclist

Other Non-Collision

and Other Object and Parked Car

& Train Total

Intersection Major Route Minor Route

1 Morris Blvd Chicago Ave 4 2 91 129 0 18 13 257

2 1st Ave Golf Rd 2 6 154 145 9 3 3 322

3 Devon Ave Main St 0 3 45 66 0 1 4 119

4 3rd St Park Ave 0 3 37 39 0 1 0 80

5 Wilson Rd Lake St 2 4 22 21 0 3 2 54

6 Kennedy Blvd Main St 0 5 140 162 4 0 4 315

7 Roosevelt Rd Lake St 0 0 10 16 0 0 3 29

8 5th St Chicago Ave 4 1 137 301 0 3 1 447

9 Cicero Ave Banks Dr 2 3 77 125 0 1 6 214

10 Dawson Ave Howard St 0 0 38 9 0 1 2 50

Table 7-4. Sample Intersections – Light Condition

Location Light Condition Total Crashes


Day/ Daylight

Dawn/ Dusk

Lighted Night/ Dark

Unknown

1 Morris Blvd Chicago Ave 147 10 47 50 3 257

2 1st Ave Golf Rd 200 30 46 45 1 322

3 Devon Ave Main St 86 4 25 1 3 119

4 3rd St Park Ave 67 3 8 2 0 80

5 Wilson Rd Lake St 44 4 4 2 0 54

6 Kennedy Blvd Main St 229 25 34 25 2 315

7 Roosevelt Rd Lake St 26 1 0 2 0 29

8 5th St Chicago Ave 319 16 66 42 4 447

9 Cicero Ave Banks Dr 151 18 24 16 5 214

10 Dawson Ave Howard St 37 6 2 5 0 50

Table 7-5. Sample Intersections – Surface Condition


Case Study 7-1

31

Location Dry

Wet

Ice/Snow/Slush

Other/ Unknown

Total Crashes


1 Morris Blvd Chicago Ave 186 42 11 18 257

2 1st Ave Golf Rd 249 58 8 7 322

3 Devon Ave Main St 90 15 6 8 119

4 3rd St Park Ave 64 8 4 4 80

5 Wilson Rd Lake St 46 5 3 0 54

6 Kennedy Blvd Main St 260 45 6 4 315

7 Roosevelt Rd Lake St 23 4 1 1 29

8 5th St Chicago Ave 348 77 12 10 447

9 Cicero Ave Banks Dr 143 37 6 28 214

10 Dawson Ave Howard St 35 12 3 0 50

Next Step: Next, perform network screening using the (1) crash rate ranking, (2) EPDO ranking, and (3) expected crash frequency with EB

adjustment procedures.


Case Study 7-1

32

Network Screening – Method 1:

Performance Measure 1: Crash Rate Ranking

Step 1: Calculate Million Entering Vehicles (MEV): MEV = (TEV/1,000,000) x (n) x (365) Reference: Equation 4-2, p. 4-26 of HSM Where: TEV = Total entering vehicles per day, n = Number of years of crash data Step 2: Calculate Crash Rate:

Crash Rate (R ) = Nobserved i(total) / MEVi Reference: Equation 4-3, p. 4-27 of HSM

For Intersection 1:

MEV = ((33300 + 13200)/1,000,000) x 5 x 365 = 84.86

R = 257/84.86 = 3.03

Step 3: Rank Locations:

Intersection Total Crashes MEV Crash Rate (CR) Rank

1 257 84.86 3.03 4

2 322 95.45 3.37 3

3 119 84.68 1.41 7

4 80 55.30 1.45 6

5 54 59.68 0.90 9

6 315 84.86 3.71 2

7 29 69.17 0.42 10

8 447 89.97 4.97 1

9 214 100.19 2.14 5

10 50 47.09 1.06 8


Case Study 7-1

33


Performance Measure 2: EPDO - Ranking

Step 1: Calculate EPDO Weights: fy = CCy/CCPDO Reference: Equation 4-4 (p.4-30 HSM)

EPDO Weight (Injury Crash) = $82,600/$7,400 = 11.16 (Every Injury Crash is equivalent to 11.16 PDO Crash)

EPDO Weight (Fatal Crash) = $4,008,900/$7,400 = 541.74 (Every Fatal Crash is equivalent to 541.74 PDO Crash)

Severity Comprehensive Cost (2001 Dollars) (Refer to Table 4-7 on p.4-29)

Equivalent Weights

Fatal (K) $4,008,900 541.74

Injury Crashes (A/B/C) $82,600 11.16

PDO $7,400 1

Step 2: Calculate EPDO Score:

Total EPDO Score = 541.74 (Total Fatal Crashes) + 11.16 (Total Injury Crashes) + 1 (Total PDO Crashes)

For Intersection 1 - EPDO Score = (541.74 x 0) + (11.16 x 63) + (1 x 194) = 897

Step 3: Rank Sites:

Intersection EPDO Score Rank

1 897 4

2 1135 1

3 312 6

4 283 7

5 115 9

6 996 3

7 70 10

8 1118 2

9 712 5

10 152 8


Case Study 7-1

34


Performance Measure 3: Expected Crash Frequency with Empirical Bayesian (EB) Adjustment

Intersection Ranking with expected average crash frequency using EB adjustment

TOTAL crashes Fatal and Injury Crashes (KABC) PDO crashes (O)

Intersection 1 4 5 5










Summary of Network Screen Assessment: Based on the crash rate ranking, EPDO ranking, and the expected crash frequency with EB adjustment we see that Intersections 2, 6, and 8 are all ranked as the top three locations where there is the most opportunity for crash reduction. Though the ranking between first and second varies between Intersections 2 and 8, this network screen assessment can confirm that each of these three intersections merit additional diagnosis and evaluation. Acknowledgements: The original case study was developed by Darren Torbic and Ingrid Potts from MRI.

Module 9: Diagnosis and Countermeasure Selection

Case Study 9-1

35

Case Study 9-1: Diagnosis and Countermeasure Selection – Vol. 1 (Part B) Case Study


As introduced in Module #7, Case Study 7-1, one

continuous sample problem has been developed to

demonstrate the entire roadway safety management

process. Case Study 7-1 identified three candidate

intersection locations that require additional analysis

to see if there are opportunities to reduce crashes at

these locations. One of the intersections that ranked

highly by all three of the demonstrated network

screening evaluations was Intersection 2 (1st Avenue

and Golf Road). In this portion of the case study, the

agency has now elected to focus on Intersection 2,

diagnose the intersection, and then identify candidate

countermeasures for this location. In addition to a site

visit and general review of the crash history at this

location, the analyst can calculate the predicted

average number of crashes at the intersection and then

evaluate two countermeasures that have been

recommended by their staff. The two candidate

countermeasures include (1) changing the intersection

to a roundabout, and keeping the intersection and

adding a protected left-turn traffic signal phase.

An aerial photo of the intersection location is shown below:


Case Study 9-1

36

Predict crash frequency at the candidate intersection:

Available data: Information regarding intersection geometry along with necessary crash and operation data are needed to predict crash

frequency. The previous Module #7 Case Study 7-1 provided this information for the ten study intersections. Table 9-1 summarizes the specific

data associated with Intersection 2.

Table 9-1. General Information and Selected Intersection Facts (based on Worksheet 2A, p. 12-113, Vol. 2, HSM)

Site Information

Highway SH 123

Intersection Intersection 2 - 1st Ave and Golf Rd

Jurisdiction Anywhere, USA

Analysis Year 2005

Input Data

Intersection Type (3ST, 3SG, 4ST, 4SG) 4SG

ADTmajor (veh/day) 34,800

ADTminor (veh/day) 17,500

Intersection Lighting (present/not present) present

Calibration factor (Ci) 0.88

Data for unsignalized intersection only:

Number of major-road approaches with left-turn Lanes (0, 1, 2) NA


Case Study 9-1

37

Number of major-road approaches with right-turn Lanes (0, 1, 2) NA

Data for signalized intersection only:

Number of approaches with left-turn lanes (0, 1, 2, 3, 4) 4

Number of approaches with right-turn lanes (0, 1, 2, 3, 4) 3

Number of approaches with left-turn signal phasing (0, 1, 2, 3, 4) 4

Type of left-turn signal phasing for Leg #1 and #2 Protected/Permissive

Type of left-turn signal phasing for Leg #3 and #4 Permissive

Intersection red-light cameras (present/not present) Not present

Sum of all pedestrian crossing volumes (PedVol) (from Table 12-15) 240

Maximum number of lanes crossed by a pedestrian (nlanesx) 6

Number of approaches with RTOR prohibited (0, 1, 2, 3, 4) 0

Number of bus stops within 300 m (1,000 ft) of the intersection 0

Schools within 300 m (1,000 ft) of the intersection (present/not present) Present

Number of alcohol sales establishments within 300 m (1,000 ft) of intersection 6


Case Study 9-1

38

Table 9-2. Crash Modification Factors for Base Condition (based on Worksheet 2B, p. 12-114, Vol. 2, HSM)

(1) (2) (3) (4) (5) (6)

CMF for Left-

Turn Lanes

CMF for Left-Turn

Signal Phasing

CMF for Right-

Turn Lanes

CMF for Right-Turn-on-

Red CMF for Lighting

CMF for Red Light

Cameras Combined CMF

CMF 1i CMF 2i CMF 3i CMF 4i CMF 5i CMF 6i

from Table 12-

24 from Table 12-25 from Table 12-26 from Equation 12-35

from Equation

12-36

from Equation

12-37 (1)x(2)x(3)x(4)x(5)

0.66 0.98 0.88 1.00 0.91 1.00 0.52

Note: For Intersection 2 the proportion of night time crashes is assumed to be a combination of Dawn/Dusk crashes along with night/dark crashes.

If the proportion is not available, Table 12-23, p. 12-42, Vol. 2, HSM provides default values based on intersection type.


Case Study 9-1

39

Table 9-3. Multiple-Vehicle Collisions by Collision Type (based on Worksheet 2D, p. 12-114, Vol. 2, HSM)

(1) (2) (3) (4) (5) (6)

Collision Type

Crashes per year by severity level

Fatal and injury Property damage only Total

Proportion of collision

type Predicted (Nbimv)FI

Proportion of collision

type Predicted (Nbimv)PDO Predicted Nbimv

from Table 12-11 (2)x(3)FI from Table 12-11 (4)x(5)PDO (3)+(5)

Total 1.000 1.826 1.000 3.470 5.296

Rear-end collision 0.450 0.822 0.483 1.676 2.498

Head-on collision 0.049 0.089 0.030 0.104 0.194

Angle collision 0.347 0.634 0.244 0.847 1.480

Sideswipe 0.099 0.181 0.032 0.111 0.292

Other multiple-vehicle

collision 0.055 0.100 0.211 0.732 0.833

Note: The Safety Performance Function (SPF) for multiple-vehicle collisions is from HSM Equation 12-21. Coefficients for the SPF are from HSM

Table 12-10. It is assumed that the proportion of collision type distribution is based on the total universe of 4-legged urban signalized intersections

in the database.


Case Study 9-1

40

Table 9-4. Single-Vehicle Collisions by Collision Type (based on Worksheet 2F, p. 12-115, Vol. 2, HSM)

(1) (2) (3) (4) (5) (6)

Collision Type


Fatal and injury Property damage only Total

Proportion of

collision type Predicted (Nbisv)FI

Proportion of

collision type Predicted (Nbisv)PDO Predicted (Nbisv)TOTAL

from Table 12-13 (2)x(3)FI from Table 12-13 (4)x(5)PDO (3)+(5)

Total 1.000 0.068 1.000 0.221 0.289

Collision with parked vehicle 0.001 0.000 0.001 0.000 0.000

Collision with animal 0.002 0.000 0.002 0.000 0.001

Collision with fixed object 0.744 0.051 0.870 0.192 0.243

Collision with other object 0.072 0.005 0.070 0.015 0.020

Other single-vehicle collision 0.040 0.004 0.023 0.005 0.008

Single-vehicle non-collision 0.141 0.010 0.034 0.008 0.017

Note: The Safety Performance Function (SPF) for single-vehicle collisions is from HSM Equation 12-24. Coefficients for the SPF are from HSM

Table 12-12. It is assumed that the proportion of collision type distribution is based on the total universe of 4-legged urban signalized intersections

in the database.


Case Study 9-1

41

Table 9-5. Crash Modification Factors for Vehicle-Pedestrian Collisions (based on Worksheet 2H, p. 12-116, Vol. 2, HSM)

(1) (2) (3) (4)

CMF for Bus Stops CMF for Schools CMF for Alcohol Sales Establishments

Combined CMF CMF 1p CMF 2p CMF 3p

from Table 12-28 from Table 12-29 from Table 12-30 (1)x(2)x(3)

1.00 1.35 1.12 1.51


Case Study 9-1

42

Table 9-6. Vehicle-Pedestrian Collisions (based on Worksheet 2I, p. 12-116, Vol. 2, HSM)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)


Coefficients (from Table 12-14)

k

Initial Npedbase Combined CMFs Calibration Factor Predicted Npedi

a b c d e from Equation 12-29 (8)x(9)x(10)

Total -9.53 0.40 0.26 0.45 0.04 0.24 0.070 1.51 0.88 0.093

Fatal and Injury -- -- -- -- -- -- -- -- -- 0.093

Property Damage Only -- -- -- -- -- -- -- -- -- 0

Note: All vehicle-pedestrian collisions are assumed as fatal and injury crash.

Table 9-7. Vehicle-Bicycle Collisions (based on Worksheet 2J, p. 12-116, Vol. 2, HSM)

(1) (2) (3) (4) (5) (6) (7)


Predicted Nbimv Predicted Nbisv Predicted Nbi fbikei Calibration Factor Predicted Nbikei

(2) + (3) from Table 12-17 (4)x(5)x(6)

Total 5.296 0.289 5.586 0.015 0.88 0.074

Fatal and Injury -- -- -- -- -- 0.074

Property Damage Only -- -- -- -- -- 0

Note: All vehicle-bicycle collisions are assumed as fatal and injury crash.


Case Study 9-1

43

Table 9-8. Crash Summary (Base Condition) – Crash Severity Distribution (based on Worksheet 2K, p. 12-117, Vol. 2, HSM)

(1) (2) (3) (4)


Collision Type Fatal and injury Property damage only Total

MULTIPLE-VEHICLE COLLISIONS

Rear-end collision 0.822 1.676 2.498

Head-on collision 0.089 0.104 0.194

Angle collision 0.634 0.847 1.480

Sideswipe 0.181 0.111 0.292

Other multiple-vehicle collision 0.100 0.732 0.833

Subtotal 1.826 3.470 5.296

SINGLE-VEHICLE COLLISIONS

Collision with parked vehicle 0.000 0.000 0.000

Collision with animal 0.000 0.000 0.001

Collision with fix object 0.051 0.192 0.243

Collision with other object 0.005 0.015 0.020

Other single-vehicle collision 0.003 0.005 0.008

Single-vehicle non-collision 0.010 0.008 0.017

Collision with pedestrian 0.093 0.000 0.093

Collision with bicycle 0.074 0.000 0.074

Subtotal 0.235 0.221 0.456

TOTAL

Total 2.061 3.692 5.753


Case Study 9-1

44

Countermeasure Analysis and Evaluation

Identify countermeasures and review predicted average crash frequency

Table 9-9. General Information and Input data

Site Information

Highway CR 123

Intersection Intersection 2 – 1st Avenue and Golf Rd.

Jurisdiction Anywhere, USA

Analysis Year 2005

Input Data

Data Intersection 2

Intersection control Urban Signalized Intersection

Major Road AADT 34,800

Minor Road AADT 17,500

Predominate Collision Types Angle & Rear-end


Case Study 9-1

45

Crashes by Severity

Total Crashes in 5-Year Period 322

Fatal 0

Injury 80

PDO 242

Contributing Factors Increase in traffic volumes

Inadequate capacity during peak hour

Note: The current base conditions are a 4-leg signalized intersection with left-turn lanes on all approaches, right-turn lanes on 3 of

the 4 approaches, left-turn signal phasing on all 4 approaches. All candidate CMFs must adhere to this base condition.

Consider four possible countermeasures and evaluate possible HSM options (be sure they meet the intersection base conditions):

Roundabout – see page 12-48, Vol. 2, HSM Protect-only Left-turn signal – see Table 14-23, page 14-35, Vol. 3, HSM


Case Study 9-1

46

Table 9-10. Countermeasure Information

Countermeasure:

Install a Single-lane

Roundabout

(2)

Protected Left-turn

Signal

Service Life 30 Years 10 Years

Annual Traffic Growth 2.0% 2.0%

Discount Rate 4.0% 4.0%

Project Cost $1,500,000 $100,000

CMF p. 12-48, Vol. 2, HSM Table 12-43, HSM

Total Crashes 0.52 0.94

Fatal and Injury Crashes 0.51* 0.92*

Note: * represents CMF values for Fatal and Injury Crashes for the respective countermeasures based on a local traffic study and these values

are used in the sample problem for demonstration purposes only. For locations where a CMF is not available for all crash severity levels, local

assessment is one way to address this limitation.


Case Study 9-1

47

Table 9-11. Predicted Crash Frequency at Intersection #2 without Countermeasures (projected for a 30-year period)

Year in

Service Life (Y)

Calendar Year Major Road

AADT

Minor Road

AADT Npredicted (TOT) Npredicted (FI)

0 2005 34,800 17,500 5.75* 2.06*

1 2006 35,496 17,850 5.90 2.12

2 2007 36,206 18,207 6.05 2.17

3 2008 36,930 18,571 6.20 2.23

4 2009 37,669 18,943 6.36 2.29

5 2010 38,422 19,321 6.52 2.35

6 2011 39,190 19,708 6.69 2.41

7 2012 39,974 20,102 6.86 2.48

8 2013 40,774 20,504 7.03 2.54

9 2014 41,589 20,914 7.21 2.61

: : : : : :

: : : : : :

29 2034 61,799 31,077 11.94 4.43

Total 254.53 92.95

Note: * depicts the expected crash frequency number from Table 9-8 and is demonstrating calculations for Year 1.


Case Study 9-1

48

Table 9-12. Predicted Crash Frequency for Total Crashes and Fatal & Injury Crashes for the (1) Roundabout Countermeasure

Year in

Service

Life (Y)

Calendar

Year

Total Crashes Fatal and Injury Crashes

Predicted

Total

Crashes

CMF for

Total

Crashes

Predicted

Crashes with

Countermeasure

(Roundabout)

Predicted

Reduction

in Total

Crashes

Predicted

Fatal and

Injury

Crashes

CMF for

Fatal and

Injury

Crashes

Predicted Fatal

and Injury

Crashes with

Countermeasure

(Roundabout)

Predicted

Reduction

in Fatal and

Injury

Crashes

0 2005 5.753 0.52 2.991 2.761 2.061 0.51 1.051 1.010

1 2006 5.899 0.52 3.067 2.832 2.116 0.51 1.079 1.037

2 2007 6.049 0.52 3.145 2.904 2.172 0.51 1.108 1.064

3 2008 6.203 0.52 3.225 2.977 2.229 0.51 1.137 1.092

4 2009 6.361 0.52 3.308 3.053 2.289 0.51 1.167 1.121

5 2010 6.523 0.52 3.392 3.131 2.349 0.51 1.198 1.151

6 2011 6.689 0.52 3.478 3.211 2.412 0.51 1.230 1.182

7 2012 6.859 0.52 3.567 3.292 2.476 0.51 1.263 1.213

8 2013 7.034 0.52 3.657 3.376 2.542 0.51 1.296 1.246

9 2014 7.213 0.52 3.751 3.462 2.610 0.51 1.331 1.279

: : : : : : : : :

: : : : : : : : :

29 2034 11.945 0.52 6.211 5.733 4.431 0.51 2.2607 2.171

Total 132.358 122.177 47.405 45.546


Case Study 9-1

49

Example Year 2005 Calculation for Roundabout Countermeasure:

Predicted Total Crashes due to countermeasure: 5.753 x 0.52 = 2.991

Predicted Reduction in Total Crashes: 5.753 - 2.991 = 2.761

Predicted Fatal and Injury Crashes: 2.061 x 0.51 = 1.051

Predicted Reduction in Fatal and Injury Crashes: 2.061 - 1.051 = 1.010


Case Study 9-1

50

Table 9-13. Predicted Crash Frequency for Total Crashes and Fatal & Injury Crashes for the (2) Protected Left-turn Signal

Year in

Service

Life (Y)

Calendar

Year

Total Crashes Fatal and Injury Crashes

Predicted

Total

Crashes

CMF for

Total

Crashes

Predicted

Crashes with

Countermeasure

(Protected Left-

turn Signal)

Predicted

Reduction

in Total

Crashes

Predicted

Fatal and

Injury

Crashes

CMF for

Fatal and

Injury

Crashes

Predicted Fatal

and Injury

Crashes with

Countermeasure

(Protected Left-

turn Signal)

Predicted

Reduction

in Fatal and

Injury

Crashes

0 2005 5.753 0.94 5.419 0.334 2.061 0.92 1.911 0.150

1 2006 5.899 0.94 5.556 0.343 2.116 0.92 1.962 0.154

2 2007 6.049 0.94 5.697 0.352 2.172 0.92 2.013 0.159

3 2008 6.203 0.94 5.842 0.361 2.229 0.92 2.066 0.163

4 2009 6.361 0.94 5.990 0.370 2.289 0.92 2.121 0.168

5 2010 6.523 0.94 6.143 0.380 2.349 0.92 2.177 0.173

6 2011 6.689 0.94 6.299 0.390 2.412 0.92 2.234 0.178

7 2012 6.859 0.94 6.459 0.400 2.476 0.92 2.293 0.183

8 2013 7.034 0.94 6.623 0.411 2.542 0.92 2.354 0.188

9 2014 7.213 0.94 6.791 0.421 2.610 0.92 2.416 0.194

: : : : : : : : : :

: : : : : : : : : :

29 2034 11.945 0.94 11.239 0.705 4.431 0.92 4.092 0.339

Total 239.604 14.930 85.971 6.980


Case Study 9-1

51

Example Year 2005 Calculation for Protected Left-turn Signal Phase:

Predicted Total Crashes due to countermeasure: 5.753 x 0.94 = 5.419

Predicted Reduction in Total Crashes: 5.753 - 5.419 = 0.334

Predicted Fatal and Injury Crashes: 2.061 x 0.92 = 1.911

Predicted Reduction in Fatal and Injury Crashes: 2.061 - 1.911 = 0.150

Summary of Countermeasure Assessment:

For the two candidate countermeasures, the potential for a reduction in crashes is summarized in Table 9-16. At the 10-year period,

the total number of crash reductions varies for the remaining countermeasures; however, to appropriately select the most cost

effective countermeasure it is necessary to perform an economic assessment. Module 10 and Case Study 10-1 will continue this

evaluation.


Case Study 9-1

52

Table 9-16. Summary of Predicted 10-Year and 30-Year Crash Reductions Due to Candidate Countermeasures

(1)

Install a Single-lane

Roundabout

(2)

Protected Left-turn Signal

10-Year Total

Predicted Reduction in

Property Damage Only

Crashes

19.603 2.052


Fatal and Injury Crashes 11.396 1.709



30-Year Total


Property Damage Only

Crashes

76.631 7.950


Fatal and Injury Crashes 45.546 6.980



Module 10: Economic Appraisal and Prioritization

Case Study 10-1

53

Case Study 10-1: Economic Appraisal and Prioritization – Vol. 1 (Part B) Case Study


As introduced in Module #7, Case Study 7-1 and continued in Module #9, Case Study 9-1, one continuous sample problem has

been developed to demonstrate the entire roadway safety management process. Case Study 7-1 identified three candidate

intersection locations that require additional analysis to see if there are opportunities to reduce crashes at these locations. Case

Study 9-1 narrowed down the candidate intersections to one location (1st Avenue and Golf Road) and then evaluated potential

countermeasures including a roundabout, and a protected left-turn traffic signal phase. The next step is then to perform an

economic appraisal and prioritization of the candidate countermeasures in an effort to determine the most cost effective and highest

priority countermeasure options.

This sample problem demonstrates the economic appraisal and prioritization process.


Case Study 10-1

54

Economic Appraisal (HSM Chapter 7) Assessment of Countermeasures:

Available data: Information regarding intersection geometry, predicted crashes, and expected countermeasure performance have

been previously provided in Case Study 7-1 and Case Study 9-1. The next step in the safety performance analysis process is to

evaluate whether an investment in a specific countermeasure is economically strategic. Table 10-1 depicts the societal costs

estimated by crash severity.

Table 10-1. Societal Crash Costs by Severity (Source: FHWA-HRT-05-051 and included as Table 7-1, p. 7-5, Vol. 1, HSM)

Injury Severity Estimated Cost

Fatality $4,008,900

Cost of Crashes with Fatal and/or Injury $158,200

Disabling Injury (A - Injury) $216,000

Evident Injury (B - Injury) $79,000

Possible Injury (C - Injury) $44,900

PDO $7,400


Case Study 10-1

55

Convert countermeasure benefit to monetary value for the economic analysis calculations:

Table 10-2. Annual Monetary Value of Predicted Crash Reduction for Roundabout Countermeasure

Year in

Service Life (Y) Calendar Year ∆ NPred,CMF1(FI)

FI Crash

Cost AM y(FI) ∆ NPred,CMF1(PDO)

PDO Crash

Cost AM y(PDO) AM y(TOT)

0 2005 1.010 $158,200 $159,768 1.751 $7,400 $12,960 $172,728

1 2006 1.037 $158,200 $164,002 1.795 $7,400 $13,282 $177,284

2 2007 1.064 $158,200 $168,352 1.839 $7,400 $13,611 $181,963

3 2008 1.092 $158,200 $172,821 1.885 $7,400 $13,949 $186,769

4 2009 1.121 $158,200 $177,411 1.932 $7,400 $14,294 $191,706

5 2010 1.151 $158,200 $182,127 1.980 $7,400 $14,649 $196,776

6 2011 1.182 $158,200 $186,972 2.029 $7,400 $15,012 $201,984

7 2012 1.213 $158,200 $191,949 2.079 $7,400 $15,384 $207,334

8 2013 1.246 $158,200 $197,062 2.130 $7,400 $15,766 $212,828

9 2014 1.279 $158,200 $202,315 2.183 $7,400 $16,156 $218,472

: : : : : : : : :

: : : : : : : : :

29 2034 2.171 $158,200 $343,504 3.562 $7,400 $26,359 $369,863


Case Study 10-1

56


Per Case Study 9-1, Table 9-12: Predicted Reduction in Total Crashes = 2.761; Predicted Reduction in Fatal & Injury Crashes = 1.010

Per Table 10-1 (see previous page): FI Crash Costs = $158,200 and PDO Crash Costs = $7,400

Total Annual Monetary Value (AM1(TOT)) = (1.010 x $158,200) + ([2.761 – 1.010] x $7,400) = $172,728

Note: Calculated values shown in Table 10-2 have been determined with the use of a spreadsheet so predicted crash reductions (shown here to

3 decimal places) were included in the calculations to a substantially larger number of decimal places. As a result, manual calculations may vary

slightly from those determined with a spreadsheet. Ultimately, this difference in precision will not affect the results provided that all calculations

are consistently performed.


Case Study 10-1

57

Table 10-3. Annual Monetary Value of Predicted Crash Reduction for Protected Left-Turn Signal Countermeasure

Year in

Service Life (Y)

Calendar

Year ∆ NPred,CMF2(FI)

FI Crash

Cost AM y(FI) ∆ NPred,CMF2(PDO)

PDO Crash

Cost AM y(PDO) AM y(TOT)

0 2005 0.150 $158,200 $23,680 0.184 $7,400 $1,362 $25,042

1 2006 0.154 $158,200 $24,371 0.188 $7,400 $1,395 $25,766

2 2007 0.159 $158,200 $25,081 0.193 $7,400 $1,428 $26,510

3 2008 0.163 $158,200 $25,811 0.198 $7,400 $1,462 $27,273

4 2009 0.168 $158,200 $26,560 0.202 $7,400 $1,497 $28,058

5 2010 0.173 $158,200 $27,330 0.207 $7,400 $1,533 $28,864

6 2011 0.178 $158,200 $28,121 0.212 $7,400 $1,570 $29,691

7 2012 0.183 $158,200 $28,934 0.217 $7,400 $1,608 $30,542

8 2013 0.188 $158,200 $29,769 0.222 $7,400 $1,646 $31,415

9 2014 0.194 $158,200 $30,626 0.228 $7,400 $1,686 $32,312

: : : : : : : : :

: : : : : : : : :

29 2034 0.339 $158,200 $53,678 0.366 $7,400 $2,708 $56,386


Case Study 10-1

58

Calculate present value of benefits based on annual benefit for countermeasure (30 year service life)

Convert Non-Uniform Annual Benefit to Present Value:

(P/F,i,y) = (1+i)(-y) (Derived from Equation 7-2, page 7-6, Vol. 1, HSM)

Where; i = discount rate (0.04 for a 4% value as shown in Table 9-10)

y = year in the service life of the countermeasure


Case Study 10-1

59

Table 10-4. Present Monetary Value of Benefits of Predicted Crash Reduction for Roundabout Countermeasure

Year in

Service Life (Y) Calendar Year

AM y(TOT)

(calculated in Table 10-2) (P/F,i,y)

Present Monetary Value

of Benefits for Crash

Reduction

0 2005 $172,728 1.00 $172,728

1 2006 $177,284 0.96 $170,465

2 2007 $181,963 0.92 $168,235

3 2008 $186,769 0.89 $166,037

4 2009 $191,706 0.85 $163,871

5 2010 $196,776 0.82 $161,736

6 2011 $201,984 0.79 $159,631

7 2012 $207,334 0.76 $157,556

8 2013 $212,828 0.73 $155,511

9 2014 $218,472 0.70 $153,495

: : : : :

: : : : :

29 2034 $369,863 0.32 $118,597

Total: $4,316,570


Case Study 10-1

60


(P/F,i,y) = (1 + 0.04)(-1) = 0.96

Present Monetary Value of Crash Reduction Benefits = $177,284 x 0.96 = $170,465

Table 10-5. Present Monetary Value of Benefits of Predicted Crash Reduction for Protected Left-turn Signal Countermeasure

Year in

Service Life (Y) Calendar Year

AM y(TOT)

(calculated in Table 10-3) (P/F,i,y)

Present Monetary Value

of Benefits for Crash

Reduction

0 2005 $25,042 1.00 $25,042

1 2006 $25,766 0.96 $24,775

2 2007 $26,510 0.92 $24,510

3 2008 $27,273 0.89 $24,246

4 2009 $28,058 0.85 $23,984

5 2010 $28,864 0.82 $23,724

6 2011 $29,691 0.79 $23,466

7 2012 $30,542 0.76 $23,209

8 2013 $31,415 0.73 $22,955

9 2014 $32,312 0.70 $22,702

: : : : :

: : : : :

29 2034 $56,386 0.32 $18,080

Total: $642,734


Case Study 10-1

61

Table 10-6. Present Value of Countermeasure Cost

Initial Construction Second 10-yr period Third 10-yr period

Total Present

Value Cost First 10-

year's Cost

Present Value

Cost

Second 10-year's

Cost

Present Value

Cost

Third 10-

year's Cost

Present

Value

Cost

Roundabout $1,500,000 $1,500,000 --- --- --- --- $1,500,000

Protected Left-turn Signal $100,000 $100,000 $100,000 $67,556* $100,000 $45,639* $213,195

*Since the service life is 10 years for the protected left-turn signal (see Table 9-10, Case Study 9-1) an additional investment of approximately

$100,000 is assumed to occur at years 10 and 20.

Example Left-Turn Signal Calculation:

Year 10 Cost: (P/F,0.04,10) = (1.04)(-10) = 0.676 so Present Value Cost = $100,000 x 0.676 = $67,556

Year 20 Cost: (P/F,0.04,20) = (1.04)(-20) = 0.456 so Present Value Cost = $100,000 x 0.465 = $45,639

Total Present Value Cost = $100,000 + $67,556 + $45,639 = $213,195


Case Study 10-1

62

Method 1: Net Present Value (Also, referred to as net present worth)

Net Present Value (NPV) is the difference between discounted costs and discounted benefits of an individual improvement project in

a single amount.

NPV = PVB – PVC (See Equation 7-3, page 7-9, Vol. 1, HSM)

Where; PVB = Present value of project benefits

PVC = Present value of project costs

If NPV >0, then the individual project is economically justified

Example Calculation for Roundabout Countermeasure:

PVB = $4,316,570 (see Table 10-6)

PVC = $1,500,000 (see Table 10-10)

NPVRoundabout = $4,316,570 – $1,500,000 = $2,816,570


Case Study 10-1

63

Method 2: Benefit-Cost Ratio (BCR)

BCR is the ratio of present value of benefits of a project to the implementation costs of the project.

BCR = PVB/ PVC (See Equation 7- 4, p.7-9, Vol. 1, HSM)

Where; PVB = Present value of project benefits

PVC = Present value of project costs

If NPV >1.0, then the individual project is economically justified


PVB = $4,316,570 (see Table 10-6)

PVC = $1,500,000 (see Table 10-10)

BCRRoundabout = $4,316,570 /$1,500,000 = 2.88


Case Study 10-1

64

Method 3: Cost Effectiveness Analysis

Cost effective analysis of a countermeasure is expressed as the annual cost per crash reduced.

Cost Effectiveness Index = PVC/ (Np,y – No,y) (See Equation 7-5, page 7-10, Vol. 1, HSM)

Where; PVC = Present value of project costs

Np,y = Predicted crash frequency for year y

No,y = Observed crash frequency for year y


PVC = $1,500,000 (see Table 10-10)

NP – No = 122.177 (see Table 9-12)

Cost Effectiveness Index Roundabout = $1,500,000/122.177 = $12,277


Case Study 10-1

65

Table 10-7. Countermeasure Effectiveness Summary

Countermeasures Net Present Value

(NPV)

Benefit-Cost Ratio

(BCR)

Cost-Effectiveness

(Cost/Crash Reduced)

Roundabout $2,816,570 2.88 $12,277

Protected Left-turn Signal $429,539 3.01 $14,280


Case Study 10-1

66

Ranking of Countermeasures under consideration at Intersection 2

Table 10-8. Countermeasure Ranking

Project Ranking - Net Present Value (NPV)

Countermeasures Net Present Value (NPV) Ranking

Roundabout $2,816,570 1

Protected Left-turn Signal $429,539 2

Project Ranking - Benefit-Cost Ratio (BCR)

Countermeasures Benefit-Cost Ratio (BCR) Ranking

Roundabout 2.88 2

Protected Left-turn Signal 3.01 1

Project Ranking - Cost Effectiveness

Countermeasures Cost-Effectiveness (Cost/Crash Reduced) Ranking

Roundabout $12,277 1

Protected Left-turn Signal $14,280 2


Case Study 10-1

67

Summary of Economic Assessment Results

Caution must be used when evaluating effectiveness measures to rank alternative countermeasures as follows:

Net present value for the “Roundabout” countermeasure is significantly larger than for the left-turn signal, but the project costs are also substantially greater. When using net present value for ranking, it is good to also consider initial investment levels. Direct comparisons should ideally occur for countermeasures with the same initial costs. The benefit-cost ratio shows the monetary return in safety benefits for each dollar of cost invested. Therefore the protected left-turn signal is the most economically effective alternative (at $3.01 return for every $1.00 spent) followed closely by the roundabout (at $2.88 return for every $1.00 spent). The cost effectiveness measure is based on the number of crashes and does not reflect crash severity.

Project Prioritization (HSM Chapter 8) for Candidate Countermeasures at Multiple Locations

The process of project prioritization is used when comparing multiple project sites/locations for a applying a specific counter-measure after

evaluating the economic effectiveness of the selected countermeasure. All the previous steps shown for the assessment of Intersection 2 were

repeated for Intersection 1 and Intersection 10 (so that a prioritization process can be demonstrated for multiple locations). The three

intersection summary results are shown in Table 10-13.


Case Study 10-1

68

Table 10-9. Project Prioritizations

Intersection 1 Intersection 2 Intersection 10

Project Ranking - Net Present Value (NPV)

Countermeasures Net Present Value

(NPV) Ranking

Net Present Value

(NPV) Ranking

Net Present Value

(NPV) Ranking

Roundabout $2,357,841 1 $2,816,570 1 -$81,381 2

Protected Left-turn Signal $356,681 2 $429,539 2 -$30,890 1

Project Ranking - Benefit-Cost Ratio (BCR)

Countermeasures Benefit-cost Ratio (BCR) Ranking Benefit-cost Ratio

(BCR) Ranking

Benefit-cost Ratio

(BCR) Ranking

Roundabout 2.57 2 2.88 2 0.95 1

Protected Left-turn Signal 2.67 1 3.01 1 0.86 2

Project Ranking - Cost Effectiveness

Countermeasures Cost-Effectiveness

(Cost/Crash Reduced) Ranking

Cost-Effectiveness


Cost-Effectiveness


Roundabout $13,728 1 $12,277 1 $36,081 1

Protected Left-turn Signal $16,010 2 $14,280 2 $43,916 2

Module 11: Safety Effectiveness Evaluation

Case Study 11-1

69

Case Study 11-1: Safety Effectiveness Evaluation – Vol. 1 (Part B) Case Study


As introduced in Modules #7, 9, and 10, Case Study 7-1, Case Study 9-1, and Case Study 10-1 contribute to

one continuous sample problem has been developed to demonstrate the entire roadway safety management

process. Case Study 7-1 identified three candidate intersection locations that require additional analysis to

see if there are opportunities to reduce crashes at these locations. Case Study 9-1 narrowed down the

candidate intersections to one location (1st Avenue and Golf Road – Intersection 2) and then evaluated two

potential countermeasures including a roundabout, and a protected left-turn traffic signal phase. Case Study

10-1 then incorporated an economic assessment and priority evaluation (indicating that based on benefit-

cost analysis the addition of a protected left-turn signal would be effective (other ranking assessments

pointed to the more expensive roundabout option).

The next step is then to step through a project analysis for four candidate intersections located in close

proximity (Intersections 2, 15, 50, and 81). This procedure is based on the methods used in the HSM Vol. 2

(Part C) and includes weighting historic crash data with predicted number of crashes to expand the analysis

so that it no longer simply represents predicted crashes for a particular type of road and instead is

customized to the local conditions. This sample problem demonstrates this safety effectiveness evaluation.

Since many of the computations are redundant and best performed with a spreadsheet, this sample problem

will focus primarily on Intersection 2 and then project-level computations that represent all of the

intersections (please refer to the actual spreadsheet to see individual intersection calculations for

Intersections 15, 50, and 81).

Safety Effectiveness Evaluation for a Project Level (HSM Chapter 9 & HSM Vol. 2

(Part C)):

Available data: Information regarding Intersection 2 geometry, predicted crashes, and expected

countermeasure performance was previously presented in Case Studies 7-1, 9-1, and 10-1. Since a more

accurate site-specific estimate of crashes can be performed using a weighting of predicted crashes with historic

crashes and this assessment can be extended to a project level for subsequent intersections, this case study

presents this project-level application. Since calculations are similar for each intersection and can be easily

performed using a spreadsheet tool, this summary first reviews calculations for Intersection 2 and then extends

the analysis to the project level combination of data for multiple intersections in a before-after assessment. For

the purposes of this case study, it is assumed that an unknown treatment has been introduced in the year 2008

and so a before period of 2005 to 2007 will be contrasted to an after period of 2009 to 2011.


Case Study 11-1

70

Step 1. Assemble Historic Crash Data:

Table 11-1. Summary of Historic Crash Data at Intersection 2

Crash Severity Type

Before After

2005 2006 2007 3-Year

Total

2009 2010 2011 3-Year

Total

Multiple-Vehicle Collisions

Fatal (K) 0 0 0 0 0 0 0 0

Incapacitating Injury (A) 1 1 1 3 0 2 1 3

Non-incapacitating Injury (B) 5 2 0 7 3 2 0 5

Possible Injury (C) 3 3 1 7 3 3 1 7

Total Fatal plus Injury (FI) 9 6 2 17 6 7 2 15

Property Damage Only (PDO) 37 44 29 110 14 12 14 40

Total Multiple-Vehicle

Collisions

46 50 31 127 20 19 16 55

Single-Vehicle Collisions

Fatal (K) 0 0 0 0 0 0 0 0





Property Damage Only (PDO) 3 2 2 7 0 1 0 1

Total Single-Vehicle Collisions 4 2 4 10 0 2 0 2

Vehicle-Pedestrian Collisions

Fatal (K) 0 0 0 0 0 0 0 0





Vehicle-Bicycle Collisions

Fatal (K) 0 0 0 0 0 0 0 0





Total all Crash Types 52 57 40 149 21 22 17 60


Case Study 11-1

71

Table 11-2. Summary of Total Historic Crash Data at All Four Project Intersections

Collision type / Site type

Observed Total Crashes,

N observed (crashes

for 3 year period)

Observed Total Crashes,

N observed

(crashes/year)

Before After Before After

Multiple-Vehicle Collisions

Intersection 2 127 55 42.33 18.33

Intersection 15 55 44 18.33 14.67

Intersection 50 51 51 17.00 17.00

Intersection 81 39 50 13.00 16.67

Single-Vehicle Collisions

Intersection 2 10 2 3.33 0.67




Vehicle-Pedestrian Collisions





Vehicle-Bicycle Collisions





Total 302 214 100.67 71.33

Note: Refer to Mod11_EB_Example.xls Tab “EB”, columns (4) and (5) for similar intersection-specific

crash history based on severity levels.


Case Study 11-1

72

Step 2. Predict the Number of Crashes:

Using methods introduced in Vol. 2 (Part C) of the HSM as well as in Training Module 4 (Predictive

Methods), use the combination of results obtained from the SPF, the applicable CMFs, and the

Calibration factor to predict the number of crashes for the individual years of analysis. Table 11-3

demonstrates the results obtained for Intersection 2.

Table 11-3. Summary of Predicted Average Crash Frequency per Year for Intersection 2

Year Collision type / Site type Predicted average crash frequency (crashes/year)

N predicted (TOTAL) N predicted (FI) N predicted (PDO)

2005 Multiple-vehicle 5.296 1.826 3.470

Single-vehicle 0.289 0.068 0.221

Vehicle-Pedestrian 0.093 0.093 0.000

Vehicle-Bicycle 0.074 0.074 0.000






















Case Study 11-1

73

Step 3. Calculate the Expected Number of “Before” Crashes:

Table 11-4. Calculate Expected Number of Before Crashes (Total Crashes)

(1) (2) (4) (6) (7) (8)

Collision type /

Site

N predicted

(crashes

/3 years)

Observed

crashes

N observed

(crashes/ 3

years)

Over-

dispersion

Parameter

k

wiB

(weight for each

site)

Equation 9A.1-2

(1 / (1 + (6) x

(2))

Nexpected B

Equation 9A.1-1

((7) x (2) + (1 - (7) x

(4))

Before Before

Multiple-vehicle

Intersection 2 16.097 127 0.390 0.137 111.761

Intersection 15 11.812 55 0.390 0.178 47.297

Intersection 50 13.201 51 0.390 0.163 44.852

Intersection 81 13.236 39 0.390 0.162 34.819

Single-vehicle

Intersection 2 0.876 10 0.360 0.760 2.713

Intersection 15 0.738 2 0.360 0.790 0.685

Intersection 50 0.755 1 0.360 0.786 0.486

Intersection 81 0.779 0 0.360 0.781 0.280

Vehicle-

pedestrian

Intersection 2 0.284 11 0.284




Vehicle-bicyclist





COMBINED (sum

of column)

61.076 302 3.000 3.758 246.476


Case Study 11-1

74

Example Calculation for Intersection 2:

Calculate the weighting factor using Equation 9A.1-2:

Next, calculate the expected number of before-period crashes using Equation 9A.1-1:

𝑵𝒆𝒙𝒑𝒆𝒄𝒕𝒆𝒅_𝒃𝒆𝒇𝒐𝒓𝒆 = 𝒘 × 𝑁𝑝𝑟𝑒𝑑𝑖𝑐𝑡𝑒𝑑 _𝐵 + (1 −𝒘) × 𝑁𝑜𝑏𝑠𝑒𝑟𝑣𝑒𝑑 _𝐵

= (0.137 x 16.097) + [(1-0.137) x 127] = 111.761

𝑤 =1

1 + k × Npredictedall studyyears

= 1

1 + (0.137 × 16.097) = 0.137


Case Study 11-1

75

Step 4. Calculate the Expected Number of “After” Crashes:

Table 11-5. Calculate Expected Number of After Crashes (Total Crashes)

(1) (2) (3) (8) (9) (10) (11)

Collision type / Site

type

N predicted

(crashes / 3 years)

Nexpected B

Equation

9A.1-1 (7) x

(2) +

[1 – ((7) x

(4))

Adjustment

Factor ri

(Equation

9A.1-3

(3)/(2)

N expectediA

(Equation

9A.1-4)

ORi

(Equation

9A.1-5

(5)/(10) Before After

Multiple-vehicle

Intersection 2 16.097 16.734 111.761 1.040 116.184 0.473

Intersection 15 11.812 12.279 47.297 1.040 49.168 0.895

Intersection 50 13.201 13.723 44.852 1.040 46.627 1.094

Intersection 81 13.236 13.760 34.819 1.040 36.197 1.381

Single-vehicle

Intersection 2 0.876 0.901 2.713 1.029 2.791 0.717

Intersection 15 0.738 0.759 0.685 1.029 0.705 1.418

Intersection 50 0.755 0.777 0.486 1.029 0.500 2.001

Intersection 81 0.779 0.801 0.280 1.029 0.289 0.000

Vehicle-pedestrian

Intersection 2 0.284 0.300 0.284 1.057 0.300 6.663

Intersection 15 0.800 0.810 0.800 1.012 0.810 1.235

Intersection 50 0.854 0.864 0.854 1.012 0.864 1.157

Intersection 81 0.886 0.896 0.886 1.012 0.896 1.116

Vehicle-bicyclist

Intersection 2 0.224 0.233 0.224 1.039 0.233 4.296

Intersection 15 0.166 0.172 0.166 1.039 0.172 11.621

Intersection 50 0.184 0.191 0.184 1.039 0.191 10.449

Intersection 81 0.185 0.192 0.185 1.039 0.192 0.000

COMBINED (sum of

column) 61.076 63.394 246.476 16.522 256.119


Case Study 11-1

76


Calculate the adjustment factor using Equation 9A.1-3:

Next, calculate the expected number of “after” crashes using Equation 9A.1-4:

Then, calculate the Odds Ratio using Equation 9A.1-5:

𝒓𝒊 = 𝑁𝑝𝑟𝑒𝑑𝑖𝑐𝑡𝑒𝑑 𝐴𝐹𝑇𝐸𝑅𝐴

𝑁𝑝𝑟𝑒𝑑𝑖𝑐𝑡𝑒𝑑 𝐵𝐸𝐹𝑂𝑅𝐸𝐵 =

16.734

16.097= 1.040

𝑵𝒆𝒙𝒑𝒆𝒄𝒕𝒆𝒅_𝒂𝒇𝒕𝒆𝒓 = 𝑁𝑒𝑥𝑝𝑒𝑐𝑡𝑒𝑑 ,𝐵 × 𝑟𝑖 = 111.761 × 1.040 = 116.184

𝑶𝑹𝒊 =𝑁𝑜𝑏𝑠𝑒𝑟𝑣𝑒𝑑 ,𝐴

𝑁𝑒𝑥𝑝𝑒𝑐𝑡𝑒𝑑 ,𝐴 =

55

116.184 = 0.473


Case Study 11-1

77

Step 5. Calculate Site Specific Percent of Safety Effectiveness per Collision Type:

Table 11-6. Site Specific Safety Effectiveness

(1) (11) (12) (13)

Collision type / Site

ORi

(Equation 9A.1-5:

(5)/(10)

CRF: % change in

crashes

(Equation 9A.1-6:

100 x (1-(11))

CMFi

(100-(12))/100

Multiple-vehicle

Intersection 2 0.473 52.66 0.47

Intersection 15 0.895 10.51 0.89

Intersection 50 1.094 -9.38 1.09

Intersection 81 1.381 -38.13 1.38

Single-vehicle

Intersection 2 0.717 28.33 0.72

Intersection 15 1.418 -41.80 1.42

Intersection 50 2.001 -100.14 2.00

Intersection 81 0.000 100.00 0.00

Vehicle-pedestrian

Intersection 2 6.663 -566.33 6.66

Intersection 15 1.235 -23.52 1.24

Intersection 50 1.157 -15.68 1.16

Intersection 81 1.116 -11.57 1.12

Vehicle-bicyclist

Intersection 2 4.296 -329.59 4.30

Intersection 15 11.621 -1062.08 11.62

Intersection 50 10.449 -944.90 10.45

Intersection 81 0.000 100.00 0.00


Case Study 11-1

78


Calculate the crash reduction factor (CRF) using Equation 9A.1-6:

Calculate the CMF based on the CRF value calculated in the previous step:

CMF = 1 – (52.66/100) = 0.473

% 𝒔𝒂𝒇𝒆𝒕𝒚 𝒆𝒇𝒇𝒆𝒄𝒕𝒊𝒗𝒆𝒏𝒆𝒔𝒔 = 100(1 − 𝑂𝑅𝑖) = 100(1 − 0.473) = 52.66


Case Study 11-1

79

Step 6. Calculate Odds Ratio All Sites:

Table 11-7. Odds Ratio for All Sites

1) (10) (13a) (13b) (14) (15)

Collision type /

Site type

N expectediA

(Equation

9A.1-4)

CMFi

(100-

(12))/100

OR'

Equation 9A.1-

7:

total(5)/(total(10

))

VARi

(total

Nexpected A

Equation

9A.1-9

VAR(TOTA

L (10)

OR

(Equation 9A.1-8:

(11)/(1+(VAR(10)/(10)^

2)

Multiple-vehicle

Intersection 2 116.184 0.47 104.185

Intersection 15 49.168 0.89 41.997

Intersection 50 46.627 1.09 40.588

Intersection 81 36.197 1.38 31.522

Single-vehicle

Intersection 2 2.791 0.72 0.688

Intersection 15 0.705 1.42 0.152

Intersection 50 0.500 2.00 0.110

Intersection 81 0.289 0.00 0.065

Vehicle-

pedestrian

Intersection 2 0.300 6.66 0.317

Intersection 15 0.810 1.24 0.819

Intersection 50 0.864 1.16 0.875

Intersection 81 0.896 1.12 0.907

Vehicle-bicyclist

Intersection 2 0.233 4.30 0.242

Intersection 15 0.172 11.62 0.179

Intersection 50 0.191 10.45 0.199

Intersection 81 0.192 0.00 0.200

COMBINED (sum

of column)

256.119 0.836 223.046 0.833


Case Study 11-1

80

Example Calculation for Intersection 2 and then the Combined Sites (Total):

Calculate the variance for each Intersection using Equation 9A.1-9:

𝑉𝐴𝑅 ( ∑ 𝑁𝑒𝑥𝑝𝑒𝑐𝑡𝑒𝑑,𝐴𝑎𝑙𝑙 𝑠𝑖𝑡𝑒𝑠

) = ∑ [𝑟𝑖2 × 𝑁𝑒𝑥𝑝𝑒𝑐𝑡𝑒𝑑,𝐵 × (1 − 𝑤𝑖,𝐵)]

𝑎𝑙𝑙 𝑠𝑖𝑡𝑒𝑠

=

∑ [ 1.040 × 111.761 × (1 − 0.137)]

𝑎𝑙𝑙 𝑠𝑖𝑡𝑒𝑠

= 104.185

Next calculate the overall odds ratio using Equation 9A.1-8:

𝑂𝑅 =𝑂𝑅 ′

1+𝑉𝐴𝑅 𝑁𝑒𝑥𝑝𝑒𝑐𝑡𝑒𝑑 ,𝐴𝑎𝑙𝑙 𝑠𝑖𝑡𝑒𝑠

𝑉𝐴𝑅 𝑁𝑒𝑥𝑝𝑒𝑐𝑡𝑒𝑑 ,𝐴𝑎𝑙𝑙 𝑠𝑖𝑡𝑒𝑠 2

= 0.836

1+223.046

(256.119)2

= 0.833


Case Study 11-1

81

Step 7. Calculate Overall Effectiveness for All Sites:

Table 11-8. Effectiveness for All Sites

(1) (15) (16)


OR

Equation 9A.1-8:

(11)/(1+(VAR(10)/(10)^2

CRF

Equation 9A.1-10:

100*(1-(15)

COMBINED (sum of column) 0.833 16.728

Example Calculation for Overall Site Effectiveness:

Calculate the variance for each Intersection using Equation 9A.1-10:

% change in crash frequency = 100(1 − 𝑂𝑅) = 100 (1 − 0.833) = 16.728


Case Study 11-1

82

Step 8. Calculate Overall CMF for All Sites:

Table 11-9. CMF for All Sites

(1) (16) (17)


CRF

Equation 9A.1-10:

100*(1-(15)

CMF

(100-(16))/100

COMBINED (sum of column) 16.728 0.83272

CMF = 1 – (CRF/100) = 1 – (16.728/100) = 0.833

Additional analysis can be performed to evaluate standard error and confidence intervals to determine

quality of fit.

Chapter 10 Sample Problems


83

Chap 10 Sample Problem 1:


Student Notes

Rural two-lane tangent roadway segment What is the predicted average crash frequency of the roadway segment for a

particular year?

Road Features:

1.5 mile length

Tangent roadway section

AADT = 10,000 veh/day

2% grade

6 driveways per mile

10’ lanes

4’ gravel shoulder

Roadside hazard rating = 4

Assumptions:

Collision type distributions used are the default values from Table 10-4

The calibration factor is assumed to be 1.10

Step 1 – Identify data needs for the facility The following data are provided:

Existing Road (study segment length of 1.5 miles): Tangent roadway section


2% grade


10’ lanes



Step 2 – Divide Locations into Homogeneous Segments

For this study conditions are for a single homogeneous segment.



84


Predicted Segment Crashes for Base Conditions: Using Equation 10-6, the two-lane, two-way segment SPF for base conditions can be determined as follows:


Segment Base Conditions: Tangent section Level grade 5 drives per mile 12’ lanes 6’ paved shoulder RHR = 3 CMFs will be needed for any conditions that do not meet these segment base conditions. Lane Width CMF:

CMFra from table 10-8 for 10’ lane and 10,000 AADT = 1.30 pra = 0.574 - see discussion below



85

= 1.17

pra : is the proportion of total crashes constituted by related crashes. The proportion of related crashes (i.e., single vehicle run-off-road, and multiple vehicle head-on, opposite direction sideswipe, and same direction sideswipe crashes) is estimated to be 0.574 based on the default crash distribution in Table 10-4. The value pra may be updated from local data as part of the calibration process. Shoulder width and Type CMF:

Use values from Tables 10.4,10-9, and 10-10 For 4’ shoulders and AADT of 10,000, CMFwra = 1.15 Table 10-9 For 4’ gravel shoulders, CMF tra = 1.01 Table 10-10 pra = 0.574

= 1.09

Horizontal curve – tangent section CMF =1.00 (base condition) Superelevation – tangent section CMF = 1.00 Grade – Table 10-11 for a 2% grade CMF=1.00

Driveway Density -

= 1.01 Centerline Rumble Strips - no rumble strips, CMF = 1.00 (base condition) Passing Lanes - no passing lanes, CMF = 1.00 (base condition) Two-way Left-Turn Lanes - no TWLT lanes, CMF = 1.00 (base condition)



86

Roadside Design - RHR= 4. CMF calculated by equation 10-20

CMF = 1.07 Lighting – no lighting, CMF = 1.00 (base condition) Automated Speed Enforcement - no automated speed enforcement, CMF = 1.00 (base condition) CMF comb = 1.17 x 1.09 x 1.01 x 1.07 = 1.38

Step 5 - Apply Local Calibration Factor N predicted rs = Nspf rs x Cr x (CMF1 x CMF2 x … CMFn) = 4.008 x 1.10 x (1.38) = 6.084 crashes per year



Student Notes

Rural two-lane curved roadway segment What is the predicted average crash frequency of the roadway segment for a

particular year?



87

Road Features:

0.1 mile length – horizontal curve

Curved roadway section


1% grade


1200 ft horizontal curve radius

No spiral transition

11’ lanes



0.04 superelevation rate

Assumptions:


The calibration factor is assumed to be 1.10 Design speed = 60 mph

Max superelevation rate emax = 6 percent

Note: the solution here and in the spreadsheet for this problem will differ from that presented in the HSM, page 10-42. In the given problem the default distribution for SVROR,HO,SSOP, and SSsame is given as 0.78. The problem is solved here and in the spreadsheet using the default HSM crash distribution for SVROR, HO,SSOP and SSsame of 0.574.


Existing Road (study segment length of 1.5 miles): Curved roadway section


1% grade


11’ lanes



Super 0.04





88




Segment Base Conditions: Tangent section, Level grade 5 drives per mile 12’ lanes 6’ paved shoulder RHR = 3 CMFs will be needed for any conditions that do not meet these segment base conditions. Lane Width CMF:

CMFra from table 10-8 for 11’ lane and 8,000 AADT = 1.05 pra = 0.574 - see discussion below



89

= 1.03

pra : is the proportion of total crashes constituted by related crashes. The proportion of related crashes (i.e., single vehicle run-off-road, and multiple vehicle head-on, opposite direction sideswipe, and same direction sideswipe crashes) is estimated to be 0.574 based on the default crash distribution in Table 10-4. The value pra may be updated from local data as part of the calibration process. Shoulder width and Type CMF:

Use values from Tables 10.4,10-9, and 10-10 For 2’ shoulders and AADT of 8,000, CMFwra = 1.30 Table 10-9 For 2’ gravel shoulders, CMF tra = 1.01 Table 10-10 pra = 0.574

= 1.18

Horizontal curve, length, radius CMF:

CMF = 1.43 Horizontal Curves Superelevation CMF: CMF = 1.06 + 3 x (SV – 0.02) CMF = 1.06 + 3 x ((0.06-0.04) – 0.2)



90

CMF = 1.06 Grade – Table 10-11 for a 1 % grade CMF=1.00 Driveway Density - number of drives = 0 ≤ 5

Centerline Rumble Strips - no rumble strips, CMF = 1.00 (base condition) Passing Lanes - no passing lanes, CMF = 1.00 (base condition) Two-way Left-Turn Lanes - no TWLT lanes, CMF = 1.00 (base condition) Roadside Design - RHR= 5. CMF calculated by equation 10-20

CMF = 1.14 Lighting – no lighting, CMF = 1.00 (base condition) Automated Speed Enforcement - no automated speed enforcement, CMF = 1.00 (base condition) Combined CMF CMF comb = 1.03 x 1.18 x 1.43 x 1.06 x 1.14 = 2.10

Step 5 - Apply Local Calibration Factor

Note: superelevation variance (SV) = super max – actual super - example (0.06-0.04=0.02) See HSM page 10-28Formula varies according to level of SV

N predicted rs = Nspf rs x Cr x (CMF1 x CMF2 x … CMFn) = 0.214 x 1.10 x (2.10) = 0.494 crashes per year



91



Student Notes

Three leg stop-controlled intersection located on a rural two-lane roadway. What is the predicted average crash frequency of the stop-controlled for a

particular year?

Road Features:

3 legs

Minor road stop control

No right turn lanes on major road

No left-turn lanes on major road

30-degree skew angle

AADT of major road = 8,000 veh/day

AADT of minor road = 1,000 veh/day

Intersection lighting present

Assumptions:


The calibration factor is assumed to be 1.50 The proportion of crashes that occur at night are not known, so the default

proportion for nighttime crashes is assumed.


Existing Intersection: 3 legs



No left-turn lanes on major road







92

Step 2 – Divide Locations into Homogeneous Intersections For this study conditions are for a single intersection.


Predicted Segment Crashes for Base Conditions: Using Equation 10-6, the intersection SPF for base conditions can be determined as follows:


Intersection Base Conditions: Skew angle 0 degrees No intersection left turn lanes No intersection right turn lanes No lighting



93

CMFs will be needed for any conditions that do not meet these segment base conditions. Intersection Skew Angle CMF: CMF can be calculated from Equation 10-22

CMF = 1.13 Intersection Left-turn Lanes CMF: since no left-turn lanes in this problem CMF = 1.00 – base condition Intersection Right-turn Lanes CMF: since no right-turn lanes in this problem CMF = 1.00 – base condition Lighting CMF: CMF can be calculated using Equation 10-24 CMF = 1 – 0.38 x pni From table 10-15 for 3-leg stop controlled intersection pni default is: 0.26 CMF = 1 - 0.38 X 0.26 = 0.90 Combined CMF CMF comb = 1.13 x 0.90 = 1.02


N predicted rs = Nspf rs x Cr x (CMF1 x CMF2 x … CMFn)



94

= 1.867 x 1.50 x (1.02) = 2.857 crashes per year



Student Notes

Four leg signalized-controlled intersection located on a rural two-lane roadway. What is the predicted average crash frequency of the signal-controlled for a

particular year?

Road Features:

4 legs

Signalized intersection

1 right turn lane on one approach

1 left-turn lanes on each of two approaches

90-degree angle



No lighting present

Assumptions:





Signalized intersection

1 right turn lane on one approach

1 left-turn lanes on each of two approaches

90-degree angle



No lighting present



95

Step 2 – Divide Locations into Homogeneous Intersections

For this study conditions are for a single intersection.


Predicted Segment Crashes for Base Conditions: Using Equation 10-10, the intersection SPF for base conditions can be determined as follows:


Intersection Base Conditions: Skew angle 0 degrees No intersection left turn lanes No intersection right turn lanes No lighting CMFs will be needed for any conditions that do not meet these segment base conditions.



96

Intersection Skew Angle CMF: CMF for skew angle at four-leg signalized intersections is 1.00 for all cases. Intersection Left-turn Lanes CMF: From Table 10-13 for a signalized intersection with a left-turn lanes on two approaches the CMF = 0.67 Intersection Right-turn Lanes CMF: From Table 10-14 for a signalized intersection with a right-turn lane on one approach the CMF = 0.96 Lighthing CMF: Since there is no intersection lighting present CMF = 1.00 - base condition Combined CMF CMF comb = 0.67 x 0.96 = 0.64





97

Chap 10 Sample Problem 6: Student Notes


The project consists of three sites: a rural two-lane tangent segment, a rural two-lane curved segment, and a 3 leg intersection with miner leg stop-control. This project combines Sample problems 1, 2, and 3. What is the expected average crash frequency of the project for a particular year

incorporating both the predicted average crash frequencies from Sample

problems 1, 2, and 3 and the observed crash frequencies using the project-level

EB method.



Student Notes

The project consists of three sites: a rural two-lane tangent segment, a rural two-lane curved segment, and a 3 leg intersection with minor leg stop-control. This project combines Sample problems 1, 2, and 3. What is the expected average crash frequency of the project for a particular year


problems 1, 2, and 3 and the observed crash frequencies using the site-specific

EB method.

The Facts:

2 roadway segments, 1 tangent and 1 curved

1 intersection (3ST)

15 observed crashes: tangent segment 10 crashes; curved segment 2 crashes;

intersection 3 crashes

Outline of Solution:

To calculate the expected average crash frequency, site specific observed crash

frequencies are combined with the predicted average crash frequencies for the

project using the project using the site-specific EB Method (observed crashes are

assigned to specific segments or intersections).

See Spreadsheet results.



98

The Facts:

2 roadway segments, 1 tangent and 1 curved


15 observed crashes: no information to assign crashes to specific sites


Observed crash frequencies for the project as a whole are combined with

predicted average crash frequencies for the project as a whole using the project

level EB Method.




99



Rural four-lane divided roadway segment What is the predicted average crash frequency of the roadway segment for a

particular year?

Road Features:

1.5 mile length


2% grade

20-ft traversable median

12’ lanes

6’ paved shoulder

No roadway lighting

No automated enforcement

Assumptions:




Existing Road (study segment length of 1.5 miles): 1.5 mile length


2% grade

20-ft traversable median

12’ lanes

6’ paved shoulder

No roadway lighting

No automated enforcement



100





Coefficients in Table 11-5


Divided Segment Base Conditions: 12’ lanes Right shoulder width 8 feet Median width Lighting Automated speed enforcement CMFs will be needed for any conditions that do not meet these segment base conditions.



101

Lane Width CMF: CMF = 1.00 – base condition Shoulder width and Type CMF: From Table 11-17, for 6 ft paved shoulders, CMF = 1.04 Median Width CMF: From Table 11-18, for traversable median width of 20 ft, CMF = 1.02 Lighting CMF = 1.00 -base condition Automated Speed Enforcement - no automated speed enforcement, CMF = 1.00 (base condition) CMF comb = 1.04 x 1.02 = 1.06





Rural four-lane undivided roadway segment What is the predicted average crash frequency of the roadway segment for a

particular year?

Road Features:

0.1 mile length


11’ lanes




102

Sideslope of 1:6

Roadside lighting present

Automated enforcement present

Assumptions:

Collision type distributions have been adapted by local experience, SV ROR, MV

HO SSOP, SSD is 33 percent.

Proportion of night crashes not known – use default value Calibration factor is 1.10


Existing Road (study segment length of 1.5 miles): 0.1 mile length


11’ lanes


Sideslope of 1:6

Roadside lighting present

Automated enforcement present CMF=0.95







103


Undivided Segment Base Conditions: Level grade 5 drives per mile 12’ lanes 6’ paved shoulder Sideslopes 1:7 or flatter Lighting – none Automated speed enforcement - none CMFs will be needed for any conditions that do not meet these segment base conditions. Lane Width CMF: CMF can be calculated from Equation 11-13 CMF = (CMFWRA x CMFTRA) x pRA + 1.0

For 11-ft lanes and AADT of 8,000 from Table 11-11 CMF = 1.04 pra = 0.33 - see assumptions

= 1.01

Shoulder width and Type CMF: From Table 11-14 CMF can be calculated: CMF = (CMFWRA x CMFTRA) x pRA + 1.0 For 2-ft shoulders and AADT of 8,000 CMFWRA = 1.30 Table 11-12 For 2-ft gravel shoulders CMFTRA = 1.01 Table 11-13



104

pRA = 0.33 see assumptions CMF = (1.30 x 1.01 – 1.0) x 0.33 + 1.0 = 1.1 Sideslopes CMF - from Table 11-14 CMF = 1.05 Lighting – can be calculated from Equation 11-15 CMF1 – [1 – 0.72 x pinr – 0.83 x pnr] CMF = 1 – [(1 – 0.72 x 0.361 – 0.83 x 0.639) x 0.255] = 0.95 Automated Speed Enforcement CMF- CMF = 0.95 from manual Combined CMF CMF comb = 1.04 x 1.02 x 1.05 x 0.95 x 0.95 = 1.05





Three leg stop-controlled intersection located on a rural four-lane roadway. What is the predicted average crash frequency of the stop-controlled for a

particular year?

Road Features:

3 legs



1 left-turn lane on major road





105



Assumptions:







1 left-turn lane on major road





Step 2 – Divide Locations into Homogeneous Intersections

For this study conditions are for a single intersection.


Predicted Segment Crashes for Base Conditions: Using Equation 11-11, and Table 11-7 the intersection SPF for base conditions can be determined as follows:



106


Intersection Base Conditions: Skew angle 0 degrees No intersection left turn lanes, 0 except on stop-controlled approaches No intersection right turn lanes, 0 except on stop-controlled approach Lighting - none CMFs will be needed for any conditions that do not meet these segment base conditions. Intersection Skew Angle CMF: CMF can be calculated from Equation 11-18

+ 1.0

+ 1.0 = 1.33

Intersection Left-turn Lanes CMF: From Table 11-22 for a left turn lane on one non-stop-controlled approach at a 3 leg stop-controlled intersection CMF = 0.56 Intersection Right-turn Lanes CMF: since no right-turn lanes in this problem CMF = 1.00 – base condition Lighting CMF: CMF can be calculated using Equation 11-22



107

CMF = 1 – 0.38 x pni From table 11-24 for 3-leg stop controlled intersection pni default is: 0.276 CMF = 1 - 0.38 X 0.276 = 0.90 Combined CMF CMF comb = 1.33 x 0.56 x 0.90 = 0.67





The project consists of three sites: a rural four-lane divided highway segment, a rural four-lane undivided segment, and a 3 leg with minor leg stop-control. This project combines Sample problems 1, 2, and 3. What is the expected average crash frequency of the project for a particular year


problems 1, 2, and 3 and the observed crash frequencies using the site-specific

EB method?

The Facts:

2 roadway segments, 1 divided and 1 undivided


9 observed crashes: divided segment 4 crashes; undivided segment 2 crashes;

intersection 3 crashes



108


To calculate the expected average crash frequency, site specific observed crash

frequencies are combined with the predicted average crash frequencies for the

project using the project using the site-specific EB Method (observed crashes are

assigned to specific segments or intersections).


Expected average crash frequency for the project 5.7 crashes per year (rounded).



The project consists of three sites: a rural four-lane divided highway segment, a rural four-lane undivided highway segment, and a 3 leg with minor leg stop-control. This project combines Sample problems 1, 2, and 3. What is the expected average crash frequency of the project for a particular year


problems 1, 2, and 3 and the observed crash frequencies using the project-level

EB method?

The Facts:

2 roadway segments 1 divided and 1 undivided


9 observed crashes: no information to assign crashes to specific sites


Observed crash frequencies for the project as a whole are combined with

predicted average crash frequencies for the project as a whole using the project

level EB Method.


The expected average crash frequency for the project is 5.8 crashes per year.



109



An existing rural two-lane roadway is proposed for widening to a four-lane

highway facility. One portion of the project is planned as a four-lane divided

highway, while another portion is planned as a four-lane undivided highway.

There is one 3 –leg stop-controlled intersection located within the project

limits.

What is the expected average crash frequency of the proposed rural four-lane highway

facility for a particular year, and what crash reduction is expected in comparison to the

existing rural two-lane highway facility?

The Facts:

Existing rural two-lane roadway facility with two roadway segments and one

intersection equivalent to the facilities in the Chapter 10 Sample Problems 1,2, and 3.

Proposed rural four-lane highway facility with two roadway segments and one

intersection equivalent to the facilities in Sample Problems 1, 2, and 3 in this set.


Sample problem 6 applies the Project Estimation Method 1 – the expected average crash

frequency for existing conditions is compared to the predicted average crash frequency

of proposed conditions.

The expected average crash frequency for the existing rural two-lane roadway can be

represented by the results from applying the site-specific EB Method in Chapter 10

Sample Problem 5.

The predicted average crash frequency for the proposed four-lane facility can be

determined from the results of Sample Problems 1, 2, and 3 in this set.

In this case, Sample Problems 1 – 3 are considered to represent a proposed facility rather

than an existing facility; therefore, there is no observed crash frequency data, and the EB

Method is not applicable.



110

Summary of Results

Site

Expected Average

Crash

Frequency for the

Existing

Condition

(crashes/year)a

Predicted Average

Crash

Frequency for the

Proposed

Condition

(crashes/year)b

Predicted Crash

Reduction

From Project

Implementation

(crashes/year)

Segment 1 8.2 3.3 4.9

Segment 2 1.4 0.3 1.1

Intersection 1 2.9 0.8 2.1

Total 12.5 4.4 8.1

a From Sample Problems 5 in Chapter 10

b From Sample Problems 1 through 3 in Chapter 11

a Chapter 10 Sample Problem 5, Column 8, Worksheet 3A Rural Two-lane Site Total,

Worksheet 3B column 2 – Total

b Chapter 11, Column 2, Worksheet 3A – Rural Multi-lane Site Total, Worksheet 3B

column 2 – Total

Some comparisons between HSM results and worksheets differ slightly due to rounding.

Chapter 12 HSM Sample Problems – see

spreadsheets for solutions

Highway Safety Manual Training – Chapter 10 Sample Problems Data Entry Tables

Chapter 10 Data Entry Tables

111

Chapter 10 Sample Problems - Data Entry Tables

AADTMAX = 17,800 (veh/day)

Right Shld: 4 4

Right Shld: Gravel Gravel

Auto speed enforcement (present/not present) Not Present Not Present

Calibration Factor, Cr 1 1.10

Roadside hazard rating (1-7 scale) 3 4

Segment lighting (present/not present) Not Present Not Present

Passing lanes [present (1 lane) /present (2 lane) / not present)] Not Present Not Present

Two-way left-turn lane (present/not present) Not Present Not Present

Driveway density (driveways/mile) 5 6

Centerline rumble strips (present/not present) Not Present Not Present

Superelevation variance (ft/ft) < 0.01 0

Grade (%) 0 2

Radius of curvature (ft) 0 0

Spiral transition curve (present/not present) Not Present Not Present

Paved

Length of horizontal curve (mi) 0 0.0

Left Shld:Shoulder type

Lane width (ft) 12 10

6 Left Shld:Shoulder width (ft)

Length of segment, L (mi) -- 1.5

-- 10,000AADT (veh/day)

Analysis Year 2010

Input Data Base Conditions Site Conditions

Agency or Company HSM Chap 10 SP1 Roadway Section MP 0.0 to MP 1.5

Date Performed Jurisdiction Anywhere, USA

Worksheet 1A -- General Information and Input Data for Rural Two-Lane Two-Way Roadway Segments

General Information Location Information

Analyst Roadway SH 321



112


Right Shld: 2 2

Right Shld: Gravel Gravel

Roadside hazard rating (1-7 scale)

Centerline rumble strips (present/not present)

Passing lanes [present (1 lane) /present (2 lane) / not present)]

Two-way left-turn lane (present/not present)

Paved

0

0

Not Present

Driveway density (driveways/mile)

Not Present

Radius of curvature (ft)

Spiral transition curve (present/not present)

Not PresentSegment lighting (present/not present)

Auto speed enforcement (present/not present)

Calibration Factor, Cr

12

6

SH 321

MP 3.5 to MP 3.6

Anywhere, USA

2010

11

--

--

Left Shld:

Location Information

Roadway

Roadway Section

Jurisdiction

Analysis Year

Site ConditionsBase Conditions

Left Shld:

Agency or Company

Date Performed

Length of segment, L (mi)

Grade (%)

Superelevation variance (ft/ft)

AADT (veh/day)

Shoulder width (ft)

Shoulder type

Length of horizontal curve (mi)

Lane width (ft)

Worksheet 1A -- General Information and Input Data for Rural Two-Lane Two-Way Roadway Segments

General Information

Input Data

0.02

HSM Chap 10 SP2

Analyst

< 0.01

0

5

Not Present

Not Present

5

1

1

3

0.1

8,000

Not Present

1200

Not Present

Not Present

Not Present

Not Present

0.1

Not Present

1.10

0

Not Present



113



Intersection skew angle (degrees) [If 4ST, does skew differ for minor legs?] No Skew for Leg 1 (All): 30 0

Date Performed 11/21/11 Jurisdiction

Analysis Year

Worksheet 2A -- General Information and Input Data for Rural Two-Lane Two-Way Roadway Intersections


Agency or Company HSM Chap 10 SP3 Intersection Example

Analyst DRL


-- 8,000

Intersection type (3ST, 4ST, 4SG) -- 3ST

Roadway

Skew for Leg 2 (4ST only):0

-- 1,000

Number of signalized or uncontrolled approaches with a left-turn lane (0, 1, 2, 3, 4) 0 0

AADTmajor (veh/day)

AADTminor (veh/day)

Number of signalized or uncontrolled approaches with a right-turn lane (0, 1, 2, 3, 4) 0 0

Calibration Factor, Ci 1.00 1.50

Intersection lighting (present/not present) Not Present Present



114



Intersection skew angle (degrees) [If 4ST, does skew differ for minor legs?] No Skew for Leg 1 (All): 0 0


Number of signalized or uncontrolled approaches with a right-turn lane (0, 1, 2, 3, 4) 0 1

Intersection lighting (present/not present) Not Present Not Present

-- 2,000

0 Skew for Leg 2 (4ST only):

Number of signalized or uncontrolled approaches with a left-turn lane (0, 1, 2, 3, 4) 0 2

AADTminor (veh/day)

Intersection type (3ST, 4ST, 4SG) -- 4SG

-- 10,000AADTmajor (veh/day)

Analysis Year 2010


Agency or Company HSM Chap 10 SP4 Intersection Main Street at 2nd Street


Worksheet 2A -- General Information and Input Data for Rural Two-Lane Two-Way Roadway Intersections


Analyst Roadway SH 321



115

HSM Chapter 10 Sample Problem 5

(2) (3) (4) (5) (6) (7) (8)

6.106 1.960 4.146 10 0.157 0.510 8.0

0.495 0.159 0.336 2 2.360 0.461 1.3

1.000 0.0

1.000 0.0

1.000 0.0

1.000 0.0

1.000 0.0

1.000 0.0

2.847 1.181 1.665 3 0.540 0.394 2.9

1.000 0.0

1.000 0.0

1.000 0.0

1.000 0.0

1.000 0.0

1.000 0.0

1.000 0.0

9.448 3.300 6.147 15 -- -- 12.3

(3)COMB from Worksheet 3A (3)TOTAL * (2)FI / (2) TOTAL

3.300 4.3

Property Damage Only (PDO) (4)COMB from Worksheet 3A (3)TOTAL * (2)PDO / (2) TOTAL

6.147

Crash severity level N predicted N expected

8.0

Total (2)COMB from Worksheet 3A (8)COMB from Worksheet 3A

9.448 12.3

Fatal and Injury (FI)

Intersection 6

Intersection 7

Intersection 8

Worksheet 3B -- Site-Specific EB Method Summary Results

(1) (2) (3)

Segment 4

COMBINED (sum of column)

Segment 7

Segment 8

INTERSECTIONS

Intersection 1

Intersection 2

Intersection 3

Intersection 4

Intersection 5

Worksheet 3A -- Predicted and Observed Crashes by Severity and Site Type Using the Site-Specific EB Method

(1)

Site type

Predicted average crash frequency

(crashes/year)

Observed

crashes,

Nobserv ed

(crashes/year)

Overdispersion

Parameter, k

Weighted

adjustment, w

Expected

average crash

frequency,

N predicted

(TOTAL)

Segment 6

N predicted

(FI)

N predicted

(PDO)

Equation A-5

from Part C

Appendix

Equation A-4

from Part C

Appendix

Segment 5

ROADWAY SEGMENTS

Segment 1

Segment 2

Segment 3



116


(2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

6.106 1.960 0.336 -- 0.157 5.867 0.980 -- -- -- -- --

0.495 0.159 4.146 -- 2.360 0.578 1.081 -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

2.847 1.181 1.665 -- 0.540 4.376 1.240 -- -- -- -- --

-- 0.000 0.000 -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

9.448 3.300 6.147 15 -- 10.820 3.300 0.466 12.412 0.741 10.885 11.648

Property damage only (PDO) (4)COMB from Worksheet 4A (3)TOTAL * (2)PDO / (2) TOTAL

6.147 7.6

Fatal and injury (FI) (3)COMB from Worksheet 4A (3)TOTAL * (2)FI / (2) TOTAL

3.300 4.1



9.448 11.6

Intersection 5

Intersection 6

Intersection 7

Intersection 8

COMBINED

Worksheet 4B -- Project-Level EB Method Summary Results

Segment 6

Segment 7

(1) (2) (3)

INTERSECTIONS

Intersection 1

Intersection 2

Intersection 3

Intersection 4

Segment 8

Equation

A-12

Equation

A-13

Equation

A-14

ROADWAY SEGMENTS

Segment 1

Segment 2

Segment 3

Segment 4

Segment 5

w1 N1 Np/comb

N predicted

(TOTAL) N predicted (FI)

N predicted

(PDO)

Equation A-8

(6)*(2)2

Equation A-9

sqrt((6)*(2))

Equation

A-10

Equation

A-11

Worksheet 4A -- Predicted and Observed Crashes by Severity and Site Type Using the Project-Level EB Method

(1)

Site type Predicted average crash frequency

(crashes/year)

Observed

crashes,

Nobserv ed

(crashes/year)

Overdispersion

Parameter, k

Nw0 Nw1 W0 N0



117



Calibration Factor, Cr 1.00 1.10

Lighting (present/not present) Not Present Not Present

Auto speed enforcement (present/not present) Not Present Not Present

Shoulder type - right shoulder type for divided Paved Paved

Side Slopes - for undivided only 1:7 or flatter Not Applicable

Median width (ft) - for divided only 30 20

-- 10,000

Shoulder width (ft) - right shoulder width for divided [if differ for directions of travel, use average width] 8 6


AADT (veh/day)

Roadway type (divided / undivided) Undivided Divided

Date Performed



Analysis Year 2010

03/25/10 Jurisdiction Anywhere, USA

Worksheet 1A -- General Information and Input Data for Rural Multilane Roadway Segments


Agency or Company HSM Chap 11 Sample Prob 1 Roadway Section MP 0.0 to MP 1.5

Analyst HSM Roadway



118


PresentLighting (present/not present) Not Present


Auto speed enforcement (present/not present) Not Present Present

Shoulder width (ft) - right shoulder width for divided 6

1:6

Not Applicable

Gravel

2

Shoulder type - right shoulder type for divided Paved


Median width (ft) - for divided only 30

Side Slopes - for undivided only 1:7 or flatter

8,000

0.1

--

Length of segment, L (mi)

AADT (veh/day)

Undivided Undivided


Roadway type (divided / undivided)

Analysis Year 2010


--

Worksheet 1A -- General Information and Input Data for Rural Multilane Roadway Segments


Agency or Company HSM Chapter Sample Prob 2 Roadway Section MP 1.5 to MP 1.6

Analyst HSM Roadway



119





Site Conditions

Number of non-STOP-controlled approaches with right-turn lanes (0, 1, 2, 3, or 4) 0 0

Number of non-STOP-controlled approaches with left-turn lanes (0, 1, 2) 0 1

0

-- 8,000

Intersection skew angle (degrees)

AADTmajor (veh/day)

AADTminor (veh/day) -- 1,000

30

Worksheet 2A -- General Information and Input Data for Rural Multilane Highway Intersections


Analysis Year

Date Performed

Intersection type (3ST, 4ST, 4SG) -- 3ST

Agency or Company HSM Chapter 11 Sample Prob 3

Analyst HSM Roadway

Jurisdiction

Intersection Intersection at MP 1.5

2010

Anywhere, USA

Input Data Base Conditions



120


(2) (3) (4) (5) (6) (7) (8)

3.308 1.727 1.581 4 0.142 0.681 3.529

0.285 0.174 0.111 2 1.873 0.652 0.881

1.000 0.000

1.000 0.000

1.000 0.000

1.000 0.000

1.000 0.000

1.000 0.000

0.755 0.286 0.470 3 0.460 0.742 1.334

1.000 0.000

1.000 0.000

1.000 0.000

1.000 0.000

1.000 0.000

1.000 0.000

1.000 0.000

4.348 2.186 2.162 9 -- -- 5.744


(2)COMB from Worksheet 3A (8)COMB from Worksheet 3A

4.3 5.7

2.2 2.9

INTERSECTIONS

Intersection 1

Overdispersion

Parameter, k

Total

Fatal and injury (FI)

Property damage only (PDO)

Intersection 2

Intersection 3

(4)COMB from Worksheet 3A (3)TOTAL * (2)PDO / (2) TOTAL

Site type

N expected

2.2 2.9

Weighted

adjustment, w

Expected

average crash

frequency,

N predicted

(FI)

N predicted

(PDO)


(1) (2) (3)

N predicted

Intersection 6

Intersection 7

Intersection 8


Worksheet 3B -- Site-Specific EB Method Summary Results


(crashes/year)

N predicted

(TOTAL)

Worksheet 3A -- Predicted and Observed Crashes by Severity and Site Type Using the Site-Specific EB Method

(1)

Intersection 4

Intersection 5

Segment 3

Segment 4

Segment 5

Segment 6

Segment 7

Segment 8

Equation A-4

from Part C

Appendix

ROADWAY SEGMENTS

Segment 1 (Divided)

Segment 2 (Undivided)

Observed

crashes,

Nobserv ed

(crashes/year) Equation A-5

from Part C

Appendix



121


(2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

3.308 1.727 1.581 -- 0.142 1.550 0.685 -- -- -- -- --

0.285 0.174 0.111 -- 1.873 0.152 0.730 -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

0.755 0.286 0.470 -- 0.460 0.262 0.589 -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

4.348 2.186 2.162 9 -- 1.964 2.004 0.689 5.796 0.685 5.816 5.806


2.2 2.9


4.3 5.8


2.2 2.9

Total

Worksheet 4B -- Project-Level EB Method Summary Results

(1) (2) (3)

N expected

N1

Equation

A-12

Equation

A-13

ROADWAY SEGMENTS

Intersection 3

Equation

A-11

Equation A-8

(6)*(2)2

Equation A-9

sqrt((6)*(2))

Nw1 W0 N0

Equation

A-10

(1)

INTERSECTIONS

Worksheet 4A -- Predicted and Observed Crashes by Severity and Site Type Using the Project-Level EB Method

Np/comb

Equation

A-14

Segment 5

Segment 6

Segment 7

Segment 8

N predicted

(TOTAL)

Overdispersion

Parameter, k

Nw0

N predicted

(FI)

Observed

crashes,

Nobserv ed

(crashes/year)


(crashes/year)

w1


Intersection 2

Crash severity level N predicted

N predicted

(PDO)

Site type

Intersection 7

Intersection 8

Intersection 1

Intersection 5

Intersection 6

Intersection 4

Segment 1 (Divided)

Segment 2 (Undivided)

Segment 3

Segment 4



122




Minor industrial / institutional driveways (number)

--

--

1.00 1.00

10

2

15

0

--

Major commercial driveways (number) -- 0

Minor residential driveways (number)

Major industrial / institutional driveways (number)

Major residential driveways (number)

Auto speed enforcement (present / not present) Not Present Not Present

Median width (ft) - for divided only 15 Not Present

Lighting (present / not present) Not Present Present

11,000

Proportion of curb length with on-street parking -- 0.66

Type of on-street parking (none/parallel/angle) Parallel (Comm/Ind)

AADT (veh/day)

Analysis Year 2010


None

Roadway type (2U, 3T, 4U, 4D, ST) -- 3T

--

Jurisdiction Anywhere, USADate Performed


Worksheet 1A -- General Information and Input Data for Urban and Suburban Roadway Segments


Agency or Company HSM Sample Prob 1 Roadway Section MP 0.0 to MP 1.5

Analyst HSM Roadway

30

Minor commercial driveways (number) -- 10

Other driveways (number)

Speed Category

Roadside fixed object density (fixed objects / mi)

0

3

--

--

--

6Offset to roadside fixed objects (ft) [If greater than 30 or Not Present, input 30]


0



123


Worksheet 1A -- General Information and Input Data for Urban and Suburban Roadway Segments


Analyst HSM Roadway

Agency or Company HSM Sample Prob 2 Roadway Section MP 1.5 to MP 2.25


Analysis Year 2010


Roadway type (2U, 3T, 4U, 4D, ST) -- 4D


-- 23,000

0

Type of on-street parking (none/parallel/angle) None None

AADT (veh/day)

Median width (ft) - for divided only 15 40

Proportion of curb length with on-street parking --

Lighting (present / not present) Not Present Present

Auto speed enforcement (present / not present) Not Present Not Present

Major commercial driveways (number) -- 1

Minor commercial driveways (number) -- 4

0

Minor industrial / institutional driveways (number) -- 1

Major industrial / institutional driveways (number) --

Major residential driveways (number) -- 1

-- 1

Other driveways (number) -- 0

Minor residential driveways (number)

Speed Category -- Posted Speed 30 mph or Lower

Roadside fixed object density (fixed objects / mi) 0 20


Offset to roadside fixed objects (ft) [If greater than 30 or Not Present, input 30] 30 12



124



Number of major-road approaches with left-turn lanes (0,1,2) 0 1

Number of major-road approaches with right-turn lanes (0,1,2) 0 0

Worksheet 2A -- General Information and Input Data for Urban and Suburban Arterial Intersections


Analyst HSM Roadway

Agency or Company HSM Sample Prob 3 Intersection Main St at 3rd Avenue


Analysis Year 2010


Intersection type (3ST, 3SG, 4ST, 4SG) -- 3ST

-- 14,000AADT major (veh/day)

-- 4,000

Intersection lighting (present/not present) Not Present

Calibration factor, Ci

AADT minor (veh/day)

1.00 1.00

Data for unsignalized intersections only: -- --

Not Present

0 0Number of approaches with left-turn lanes (0,1,2,3,4) [for 3SG, use maximum value of 3]

0 0

-- 0Number of approaches with left-turn signal phasing [for 3SG, use maximum value of 3]

Permissive Not Applicable

Not Present Not Present

Number of bus stops within 300 m (1,000 ft) of the intersection 0 0

Type of left-turn signal phasing for Leg #3 --

0

Type of left-turn signal phasing for Leg #1

Maximum number of lanes crossed by a pedestrian (nlanesx)

Sum of all pedestrian crossing volumes (PedVol) -- Signalized intersections only

Not Applicable

Schools within 300 m (1,000 ft) of the intersection (present/not present)

Not Applicable

Type of left-turn signal phasing for Leg #2 --

Number of approaches with right-turn lanes (0,1,2,3,4) [for 3SG, use maximum value of 3]

Intersection red light cameras (present/not present)

10

--

Number of alcohol sales establishments within 300 m (1,000 ft) of the intersection 0 0

Not Present Not Present

Number of approaches with right-turn-on-red prohibited [for 3SG, use maximum value of 3] 0 0

Data for signalized intersections only: -- --

Type of left-turn signal phasing for Leg #4 (if applicable) --

Not Applicable



125



Worksheet 2A -- General Information and Input Data for Urban and Suburban Arterial Intersections


2010

Analyst HSM Roadway

Agency or Company HSM Sample Prob 4 Intersection Main St at 4th Avenue



Analysis Year

Intersection type (3ST, 3SG, 4ST, 4SG) -- 4SG

-- 15,000AADT major (veh/day)

Calibration factor, Ci 1.00 1.00

-- 9,000


AADT minor (veh/day)

Data for unsignalized intersections only: -- --

Number of major-road approaches with left-turn lanes (0,1,2) 0 0

Number of major-road approaches with right-turn lanes (0,1,2) 0 0

Data for signalized intersections only: -- --

Number of approaches with left-turn lanes (0,1,2,3,4) [for 3SG, use maximum value of 3] 0 2

Number of approaches with right-turn lanes (0,1,2,3,4) [for 3SG, use maximum value of 3] 0 2

-- Protected / Permissive

Number of approaches with left-turn signal phasing [for 3SG, use maximum value of 3] -- 2

Type of left-turn signal phasing for Leg #1 Permissive Protected / Permissive

Type of left-turn signal phasing for Leg #2

Number of approaches with right-turn-on-red prohibited [for 3SG, use maximum value of 3] 0 0

Type of left-turn signal phasing for Leg #3 -- Not Applicable

Type of left-turn signal phasing for Leg #4 (if applicable) -- Not Applicable

Intersection red light cameras (present/not present) Not Present Not Present

Sum of all pedestrian crossing volumes (PedVol) -- Signalized intersections only 1,500

Maximum number of lanes crossed by a pedestrian (nlanesx) -- 4

Number of bus stops within 300 m (1,000 ft) of the intersection 0 2

Schools within 300 m (1,000 ft) of the intersection (present/not present) Not Present Present

Number of alcohol sales establishments within 300 m (1,000 ft) of the intersection 0 6



126


(2) (3) (4) (5) (6) (7) (8)

4.954 1.192 3.763 7 0.660 0.234 6.521

2.535 0.705 1.830 6 1.320 0.230 5.203

1.000 0.000

1.000 0.000

1.179 0.336 0.842 4 1.370 0.382 2.921

0.488 0.085 0.403 3 0.860 0.705 1.230

1.000 0.000

1.000 0.000

0.731 0.178 0.554 2 1.100 0.554 1.297

0.149 0.042 0.107 1 1.390 0.828 0.296

1.000 0.000

1.000 0.000

1.267 0.406 0.862 2 0.800 0.497 1.636

2.656 0.844 1.812 6 0.390 0.491 4.358

1.000 0.000

1.000 0.000

0.234 0.072 0.162 3 1.140 0.790 0.816

0.196 0.056 0.140 0 0.360 0.934 0.183

1.000 0.000

1.000 0.000

14.391 3.916 10.475 34 -- -- 24.461


Intersection 2

Intersection 3

Intersection 4



(crashes/year)

N predicted

(TOTAL)

INTERSECTIONS

Intersection 1

Overdispersion

Parameter, k

Equation A-4

from Part C

Appendix

ROADWAY SEGMENTS

Segment 1

Segment 2

Observed

crashes,

Nobserv ed

(crashes/year) Equation A-5

from Part C

Appendix

Weighted

adjustment, w

Expected

average crash

frequency,

N predicted

(FI)

N predicted

(PDO)

Worksheet 3A -- Predicted Crashes by Severity and Site Type and Observed Crashes Using the Site-Specific EB Method for Urban and

Suburban Arterials

(1)

Intersection 4

Intersection 1

Segment 3

Segment 4

Segment 1

Segment 2

Segment 3

Segment 4

Multiple-vehicle nondriveway

Multiple-vehicle driveway-related

Single-vehicle

Segment 1

Segment 2

Segment 3

Segment 4

Multiple-vehicle

Single-vehicle

Intersection 2

Intersection 3



127


(2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

4.954 1.192 3.763 -- 0.660 16.200 1.808 -- -- -- -- --

2.535 0.705 1.830 -- 1.320 8.484 1.829 -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

1.179 0.336 0.842 -- 1.370 1.903 1.271 -- -- -- -- --

0.488 0.085 0.403 -- 0.860 0.204 0.648 -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

0.731 0.178 0.554 -- 1.100 0.589 0.897 -- -- -- -- --

0.149 0.042 0.107 -- 1.390 0.031 0.456 -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

1.267 0.406 0.862 -- 0.800 1.285 1.007 -- -- -- -- --

2.656 0.844 1.812 -- 0.390 2.752 1.018 -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

0.234 0.072 0.162 -- 1.140 0.062 0.516 -- -- -- -- --

0.196 0.056 0.140 -- 0.360 0.014 0.266 -- -- -- -- --

-- -- -- -- -- --

-- -- -- -- -- --

14.391 3.916 10.475 34 -- 31.525 9.715 0.313 27.854 0.597 22.294 25.074

Segment 4

N predicted

(PDO)

Equation

A-11

Worksheet 4A -- Predicted Crashes by Collision and Site Type and Observed Crashes Using the Project-Level EB Method for Urban and Suburban Arterials

Nexpected/comb

Equation

A-14

Segment 1

Segment 2

Segment 3

N predicted

(TOTAL)

Equation

A-13

ROADWAY SEGMENTS

Segment 1

Intersection 2

N predicted

(FI)

Predicted crashesCollision type / Site type

(1)

INTERSECTIONS

Segment 4

Intersection 3

Intersection 4

Segment 2

Multiple-vehicle driveway-related

Segment 1

Observed

crashes,

Nobserv ed

(crashes/year)

Segment 2

N1

Equation

A-12

w1

Equation A-8

(6)*(2)2

Equation A-9

sqrt((6)*(2))

Overdispersion

Parameter, k

Npredicted w1 W0 N0

Equation

A-10

Segment 3

Segment 4

Single-vehicle

Multiple-vehicle nondriveway

Npredicted w0

Segment 3

Multiple-vehicle

Single-vehicle


Intersection 2

Intersection 3

Intersection 4

Intersection 1

Intersection 1

HSM Chapter 10 Worksheets: Rural Two-Lane Two-Way Roadways

Chapter 10 Worksheets

128

HSM Chapter 10 Worksheets (Sample) Worksheet 1A: General Information and Input Data for Rural Two-Lane Two-Way Roadway Segments


Analyst Roadway

Agency or Company Roadway Section

Date Performed Jurisdiction

Analysis Year


Length of segment, L (mi) --

AADT (veh/day) --

Lane width (ft) 12

Shoulder width (ft) 6

Shoulder type Paved

Length of horizontal curve (mi) 0

Radius of curvature (ft) 0

Spiral transition curve (present/not present) Not Present

Superelevation variance (ft/ft) < 0.01

Grade (%) 0

Driveway density (driveways/mile) 5

Centerline rumble strips (present/not present) Not Present

Passing lanes (present(1 lane or 2 lane) / not present) Not Present

Two-way left-turn lane (present/not present) Not Present

Roadside hazard rating (1-7 scale) 3

Segment lighting (present/not present) Not Present

Auto speed enforcement (present/not present) Not Present

Calibration Factor, Cr 1

Worksheet 1B: Crash Modification Factors for Rural Two-Lane Two-Way Roadway Segments (1) (2) (3) (4) (5) (6)

CMF for Lane Width CMF for Shoulder Width and Type

CMF for Horizontal Curves

CMF for Super-elevation

CMF for Grades

CMF for Driveway Density

CMF 1r CMF 2r CMF 3r CMF 4r CMR 5r CMF 6r

from Equation 10-11 from Equation 10-12 from Equation 10-13 from Equations 10-14, 10-15, or 10-16

from Table 10-11

from Equation 10-17

(7) (8) (9) (10) (11) (12) (13)

CMF for Centerline Rumble Strips

CMF for Passing Lanes

CMF for Two-Way Left-Turn Lane

CMF for Roadside Design

CMF for Lighting

CMF for Automated Speed Enforcement

Combined CMF

CMF 7r CMF 8r CMF 9r CMF 10r CMF 11r CMF 12r CMF comb

from Section 10.7.1 from Section 10.7.1

from Equation 10-18 & 10-19

from Equation 10-20

from Equation

10-21

from Section 10.7.1 (1)x(2)x … x(11)x(12)



129

Worksheet 1C: Roadway Segment Crashes for Rural Two-Lane Two-Way Roadway Segments (1) (2) (3) (4) (5) (6) (7) (8)

Crash Severity Level

N spf rs Overdispersion

Parameter, k

Crash Severity

Distribution

N spf rs by Severity

Distribution

Combined CMFs


Predicted average crash

frequency, N predicted rs

(crashes/year)

from Equation

10-6

from Equation 10-7

from Table 10-3

(proportion)

(2)TOTAL x (4)

(13) from Worksheet

1B (5)x(6)x(7)

Total


Property Damage Only (PDO)

Worksheet 1D: Crashes by Severity Level and Collision Type for Rural Two-Lane Two-Way Roadway Segments

(1) (2) (3) (4) (5) (6) (7)

Collision Type

Proportion of Collision Type(TOTAL)

N predicted rs (TOTAL)

(crashes/year) Proportion of

Collision Type(FI) N predicted rs (FI)

(crashes/year) Proportion of

Collision Type(PDO)

N predicted rs (PDO)

(crashes/year)

from Table 10-4

(8)TOTAL from Worksheet 1C from Table 10-4

(8)FI from Worksheet 1C from Table 10-4

(8)PDO from Worksheet 1C

Total 1.000 1.000 1.000

(2)x(3)TOTAL (4)x(5)FI (6)x(7)PDO

SINGLE-VEHICLE

Collision with animal 0.121 0.038 0.184

Collision with bicycle 0.002 0.004 0.001

Collision with pedestrian

0.003 0.007 0.001

Overturned 0.025 0.037 0.015

Ran off road 0.521 0.545 0.505


0.021 0.007 0.029

Total single-vehicle crashes

0.693 0.638 0.735

MULTIPLE-VEHICLE

Angle collision 0.085 0.100 0.072

Head-on collision 0.016 0.034 0.003

Rear-end collision 0.142 0.164 0.122

Sideswipe collision 0.037 0.038 0.038


0.027 0.026 0.030

Total multiple-vehicle crashes

0.307 0.362 0.265



130

Worksheet 1E: Summary Results for Rural Two-Lane Two-Way Roadway Segments (1) (2) (3) (4) (5)


Crash Severity Distribution (proportion)

Predicted average crash frequency (crashes/year) Roadway segment

length (mi)

Crash rate (crashes/mi/year)

(4) from Worksheet 1C (8) from Worksheet 1C (3)/(4)

Total



Worksheet 2A: General Information and Input Data for Rural Two-Lane Two-Way Roadway Intersections


Analyst Roadway

Agency or Company Intersection

Date Performed Jurisdiction

Analysis Year


Intersection type (3ST, 4ST, 4SG) --

AADTmajor (veh/day) --

AADTminor (veh/day) --

Intersection skew angle (degrees) 0

Number of signalized or uncontrolled approaches with a left-turn lane (0, 1, 2, 3, 4) 0

Number of signalized or uncontrolled approaches with a right-turn lane (0, 1, 2, 3, 4) 0

Intersection lighting (present/not present) Not Present

Calibration Factor, Ci 1.00

Worksheet 2B: Crash Modification Factors for Rural Two-Lane Two-Way Roadway Intersections (1) (2) (3) (4) (5)

CMF for Intersection Skew Angle CMF for Left-Turn Lanes CMF for Right-Turn Lanes CMF for Lighting Combined CMF

CMF 1i CMF 2i CMF 3i CMF 4i CMF COMB

from Equations 10-22 or 10-23 from Table 10-13 from Table 10-14 from Equation 10-24 (1)*(2)*(3)*(4)

Worksheet 2C: Intersection Crashes for Rural Two-Lane Two-Way Roadway Intersections (1) (2) (3) (4) (5) (6) (7) (8)

Crash Severity Level

N spf 3ST, 4ST

or 4SG Overdispersion

Parameter, k

Crash Severity

Distribution

N spf 3ST, 4ST or

4SG by Severity

Distribution

Combined CMFs

Calibration Factor, Ci

Predicted average crash frequency, N

predicted int

from Equations 10-8, 10-9,

or 10-10 from Section

10.6.2 from Table

10-5

(2)TOTAL * (4) from (5) of Worksheet

2B

(5)*(6)*(7)

Total

Fatal and Injury (FI) -- --

Property Damage Only (PDO) -- --



131

Worksheet 2D: Crashes by Severity Level and Collision Type for Rural Two-Lane Two-Way Road (1) (2) (3) (4) (5) (6) (7)

Collision Type

Proportion of Collision Type(TOTAL)

N predicted int (TOTAL)

(crashes/year)

Proportion of Collision

Type(FI) N predicted int (FI) (crashes/year)

Proportion of Collision Type(PDO)

N predicted int (PDO) (crashes/year)

from Table 10-6

(8)TOTAL from Worksheet 2C

from Table 10-6

(8)FI from Worksheet 2C

from Table 10-6 (8)PDO from

Worksheet 2C

Total 1.000 1.000 1.000

(2)x(3)TOTAL (4)x(5)FI (6)x(7)PDO

SINGLE-VEHICLE


Collision with bicycle

Collision with pedestrian

Overturned

Ran off road


Total single-vehicle crashes

MULTIPLE-VEHICLE

Angle collision

Head-on collision

Rear-end collision

Sideswipe collision


Total multiple-vehicle crashes

Worksheet 2E: Summary Results for Rural Two-Lane Two-Way Road Intersections (1) (2) (3)

Crash severity level Crash Severity Distribution (proportion) Predicted average crash frequency (crashes / year)

(4) from Worksheet 2C (8) from Worksheet 2C

Total





132

Worksheet 3A: Predicted and Observed Crashes by Severity and Site Type Using the Site-Specific EB Method (1) (2) (3) (4) (5) (6) (7) (8)

Site type

Predicted average crash frequency (crashes/year) Observed

crashes, Nobserved (crashes/year)

Overdispersion Parameter, k

Weighted adjustment, w

Expected average crash

frequency, Nexpected

N predicted (TOTAL)

N predicted

(FI) N predicted (PDO)

Equation A-5 from Part C Appendix

Equation A-4 from Part C Appendix

ROADWAY SEGMENTS

Segment 1

Segment 2

Segment 3

Segment 4

Segment 5

Segment 6

Segment 7

Segment 8

INTERSECTIONS

Intersection 1

Intersection 2

Intersection 3

Intersection 4

Intersection 5

Intersection 6

Intersection 7

Intersection 8


Worksheet 3B: Site-Specific EB Method Summary Results (1) (2) (3)


Total





(4)COMB from Worksheet 3A (3)TOTAL * (2)PDO / (2) TOTAL



133

Worksheets 4A: Lane Site Total Worksheet 4A: Predicted and Observed Crashes by Severity and Site Type Using the Project-Level EB Method

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

Site type

Predicted average crash frequency (crashes/year) Observed crashes,

Nobserved (crashes/year)

Overdispersion Parameter, k

Nw0 Nw1 W0 N0 w1 N1 Np/comb

N predicted (total)

N

predicted (FI)

N

predicted (PDO)

Equation A-8 (6)*(2)2

Equation A-9 sqrt((6)*(2))

Equation A-10

Equation A-11

Equation A-12

Equation A-13

Equation A-14

ROADWAY SEGMENTS

Segment 1 -- -- -- -- -- --

Segment 2 -- -- -- -- -- --

Segment 3 -- -- -- -- -- --

Segment 4 -- -- -- -- -- --

Segment 5 -- -- -- -- -- --

Segment 6 -- -- -- -- -- --

Segment 7 -- -- -- -- -- --

Segment 8 -- -- -- -- -- --

INTERSECTIONS

Intersection 1 -- -- -- -- -- --

Intersection 2 -- -- -- -- -- --

Intersection 3 -- -- -- -- -- --

Intersection 4 -- -- -- -- -- --

Intersection 5 -- -- -- -- -- --

Intersection 6 -- -- -- -- -- --

Intersection 7 -- -- -- -- -- --

Intersection 8 -- -- -- -- -- --

COMBINED --

Worksheet 4B: Project-Level EB Method Summary Results (1) (2) (3)





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