An Overview of the Highway Safety Manual and Practical Applications to USVI: Part ll
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1 An Overview of the Highway Safety Manual and Practical Applications to USVI: Part ll Instructor: Benjamín Colucci Ríos, PhD, PE, JD, December 4, 2015 U.S. Virgin Islands 1
2 Good Morning! 2
3 Topics to be Covered: HSM Day 2 WORKSHOP AM: RURAL Estimate expected crashes in two-lane two-way rural roads (Chapter 10 HSM) Use of excel application developed to estimate crashes applying HSM methodology WORKSHOP PM: URBAN Estimate expected crashes for urban and sub-urban arterials. (Chapter 12 HSM) 3
4 Topics to be Covered: HSM Day 2 (cont.) Site Selection Criteria for Determining Local Calibration Factors (C r ) Crash Modification Factor (CMF) Clearinghouse FHWA The future of HSM New Changes in HSM 2010 (NCHRP 17-45) How the HSM fits within the Puerto Rico Strategic Highway Safety Plan (SHSP-PR):
5 Workshop # 1 AM Rural two way-two lane road 5
6 Situation Highway PR-114, a rural two-lane, two-way road segment located in the Municipality of Cabo Rojo that was treated with center-line rumble strips in
7 Situation (cont.) This segment is currently being investigated for alleged significant crash frequency during the past year Specifically, it consists of the following 3 segments: a 1.5 mile tangent segment followed by a 6.5 horizontal curve with an intersection angle of 60 and a 1.0 mile tangent segment after the point of tangency. 7
8 Situation (cont.) Concrete utility poles (not shown in the photograph) with a longitudinal spacing of 150 ft. were located at 3 ft. from the pavement edge when the crashes occurred in The concrete poles were removed by the Department of Transportation and Public Works due to the high incidents of single vehicle run-off the road crashes that impacted the utility poles. 8
9 Situation (cont.) The proportion of total night time crashes for unlighted roadway segments that involve a fatality or injury is 38% and the remaining 62% involve property damage only. The proportion of total crashes that occur at night for unlighted roadway segments is 37%. 9
10 Rural Two-lane, Two-way Road Segment 10
11 Pertinent Data: Design speed: 50 mph AADT: 1,800 veh/day Lane width: 11 ft. Shoulder width: 2 ft. Shoulder type: gravel Vertical Alignment: 3.0 % AASHTO Green Book superelevation rate: ft/ft Maximum (actual) superelevation rate: 0.08 ft/ft Coefficient of side friction: 0.14 ft/ft CMF for Centerline Rumble Strips in PR: 0.91 Driveways North Bound: 2 South Bound: 1 11
12 Assumptions Calibration Factor equal to 1.0. There is no spiral transition present in this horizontal alignment. There are no guardrails installed in the roadside. No left-turn lanes are provided. 12
13 Required Radius of curvature Minimum radius of curvature for the design speed Does the horizontal curve satisfy minimum AASHTO requirements? Length of horizontal curve Predicted total crash frequency for roadway segment base conditions Superelevation Variance Driveway Density Roadside Hazard Rating 13
14 Required (cont.) Crash Modification Factors (CMF s) applicable only to the horizontal curves segment 1. CMF for the effect of lane width on total crashes 2. CMF for the effect of lane width on related crashes 3. CMF for the effect of shoulder width and type on total crashes 4. CMF for related crashes based on shoulder width 5. CMF for related crashes based on shoulder type 6. CMF for the effect of horizontal alignment on total crashes 7. CMF for the effect of superelevation variance on total crashes 8. CMF for the effect of driveway density on total crashes 9. CMF for effect of roadside design 10. CMF for the effect of lighting of total crashes Combined Crash Modification Factor (CMF) Predicted Average Crash Frequency 14
15 Workshop # 1 AM Rural two way-two lane road 15
16 Solution 16
17 Solution 17
18 Workshop #2 PM Urban URBAN AND SUBURBAN ARTERIAL ROADS 18
19 Urban Arterial Roads Urban = an area typified by high densities of development or concentrations of population (population > 5,000 people) Arterial = road that provides high level of service at a great speed for uninterrupted distance, with some degree of access control. 19
20 Urban Arterial Predicted Crashes As per Highway Safety Manual Chapter 12 Example utilizing: HSM worksheets HSM Excel Spreadsheet 20
21 HSM Worksheets Found in Appendix A of the Highway Safety Manual 2010 Multiple sheets arranged in a logical order Organizes the information needed to calculate the crash frequency Provides the equation and table references for guidance Online Excel spreadsheet version available on the HSM website 21
22 How to obtain the Excel Tool: 22
23 Tools 23
24 24
25 25
26 Choose the Excel Spreadsheet that pertains to your road characteristics: Beta Versions Now, let s try some sample problems 26
27 A Two-Lane Undivided Arterial Roadway Segment 2.5 mile length of Calle Méndez Vigo, Dorado, PR 15,000 veh/day 2.0 mi of parallel on-street commercial parking on each side of street 50 driveways (30 minor commercial, 1 major commercial, 5 major residential, 10 minor residential, 4 minor industrial/institutional) Utility poles located 5 feet from the side of the road (12 poles per mile) Lighting present 30-mph posted speed Collision type distributions are the default values in HSM
28 Example of Two-Lane Undivided Urban Arterial: Calle Méndez Vigo (Dorado, PR) 28
29 Required: Crash Modification Factors (CMF s) applicable 1. CMF for the effect of on-street parking 2. CMF for the effect of roadside fixed objects 3. CMF for the effect of the median width 4. CMF for the effect of lighting 5. CMF for the effect of automated speed enforcement Combined Crash Modification Factor (CMF) Predicted Average Crash Frequency 29
30 Situation: A 2.5 mile long road segment located on an arterial in the urban City of Dorado What is the predicted crash frequency of the road segment? 30
31 First, find out what is site type from Table 12-1: 31
32 Worksheet 1A: Let s Get Started Analyst Agency or Company Date Performed Worksheet 1A -- General Information and Input Data for Urban and Suburban Roadway Segments General Information Location Information Roadway AADT MAX = 53,800 (v Type of on-street parking (none/parallel/angle) None Proportion of curb length with on-street parking -- Median width (ft) - for divided only 15 Lighting (present / not present) Not Present Auto speed enforcement (present / not present) Not Present Major commercial driveways (number) -- Minor commercial driveways (number) -- Major industrial / institutional driveways (number) -- Minor industrial / institutional driveways (number) -- Major residential driveways (number) -- Minor residential driveways (number) -- Other driveways (number) Speed Category Roadside fixed object density (fixed objects / mi) Offset to roadside fixed objects (ft) [If greater than 30 or Not Present, input 30] Calibration Factor, Cr Roadway Section Jurisdiction Analysis Year Input Data Base Conditions Site Conditions Roadway type (2U, 3T, 4U, 4D, ST) -- Length of segment, L (mi) -- AADT (veh/day)
33 Worksheet 1A: General Input for Urban & Suburban Roadway Segments Worksheet 1A -- General Information and Input Data for Urban and Suburban Roadway Segments General Information Location Information Analyst YR Roadway 2-Lane Undivided Arterial Segment Agency or Company T2 Center Roadway Section MP 0.0 to MP 1.5 Date Performed 10/17/14 AADT MAX = 32,600 (veh/day) Jurisdiction Puerto Rico Analysis Year 2014 Input Data Base Conditions Site Conditions Roadway type (2U, 3T, 4U, 4D, ST) -- 2U Length of segment, L (mi) AADT (veh/day) -- 15,000 Type of on-street parking (none/parallel/angle) None Parallel (Comm/Ind) Proportion of curb length with on-street parking Median width (ft) - for divided only 15 Not Present 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) Major industrial / institutional driveways (number) -- 0 Minor industrial / institutional driveways (number) -- 4 Major residential driveways (number) -- 5 Minor residential driveways (number) Other driveways (number) Speed Category Roadside fixed object density (fixed objects / mi) Posted Speed 30 mph or Lower 12 Offset to roadside fixed objects (ft) [If greater than 30 or Not Present, input 30] 30 5 Calibration Factor, Cr
34 Next Calculate the CMF s 34
35 Where is the CMF Information? 35
36 On Street Parking CMF (Equation 12-32) CMF 1r = 1 + p pk (f pk 1.0 )) Where: CMF 1r = crash modification factor for the effect of on-street parking on total crashes f pk = factor from Table p pk = proportion of curb length with on-street parking = (0.5 L pk / L) L pk = sum of curb length with on-street parking for both sides of the road combined (miles) L = length of roadway segment (miles) 36
37 On Street Parking CMF (Equation 12-32) CMF 1r = 1 + p pk (f pk 1.0) Where: CMF 1r = crash modification factor for the effect of on-street parking on total crashes f pk = factor from Table p pk = proportion of curb length with on-street parking = (0.5 L pk / L) L pk = sum of curb length with on-street parking for both sides of the road combined (miles) L = length of roadway segment (miles) p pk = miles + 2 miles 2.5 miles p pk = 0.8 CMF 1r = ( ) CMF 1r =
38 Roadside Fixed Objects CMF (Eqn 12-33) Where: CMF 2r = f offset D fo p fo + (1.0 p fo ) CMF 2r = crash modification factor for the effect of roadside fixed objects on total crashes f offset = fixed-object offset factor from Table D fo = fixed-object density (fixed objects/ mile) for both sides of the road combined p fo = fixed-object collisions as a proportion of total crashes from Table
39 Roadside Fixed Objects CMF (Eqn 12-33) Where: CMF 2r = f offset D fo p fo + (1.0 p fo ) CMF 2r = crash modification factor for the effect of roadside fixed objects on total crashes F offset = fixed-object offset factor from Table D fo = fixed-object density (fixed objects/ mile) for both sides of the road combined P fo = fixed-object collisions as a proportion of total crashes from Table f offset = P fo = CMF 2r = ( ) CMF 2r =
40 Median Width CMF (Table 12-22) CMF=1 is used for: Medians without traffic barriers For undivided facilities 40
41 Lighting CMF (Eqn 12-34) CMF 4r = 1.0 (p nr ( p inr 0.83 p pnr )) CMF 4r = crash modification factor for the effect of roadway segment lighting on total crashes p inr = proportion of total nighttime crashes for unlighted roadway segments that involve a fatality or injury p pnr = proportion of total nighttime crashes for unlighted roadway segments that involve property damage only P nr = proportion of total crashes for unlighted roadway segments that occur at night 41
42 Lighting CMF (Eqn 12-34) CMF 4r = 1.0 (p nr ( p inr 0.83 p pnr )) CMF 4r = crash modification factor for the effect of roadway segment lighting on total crashes p inr = proportion of total nighttime crashes for unlighted roadway segments that involve a fatality or injury p pnr = proportion of total nighttime crashes for unlighted roadway segments that involve property damage only P nr = proportion of total crashes for unlighted roadway segments that occur at night p inr =0.424 p pnr =0.576 p nr =0.316 CMF 4r = 1.0 ( ) CMF 4r =
43 Automated Speed Enforcement CMF No automated speed enforcement (base condition): CMF=1 If there is automated speed enforcement: Fatal and Injury Crashes CMF=0.83 Non-injury (PDO) CMF=
44 Combined CMFs CMF (combined) = CMF 1r CMF 2r CMF 3r CMF 4r CMF 5 CMF combined = CMF combined =
45 Worksheet 1B: CMF s Worksheet 1B -- Crash Modification Factors for Urban and Suburban Roadway Segments (1) (2) (3) (4) (5) CMF for On-Street CMF for Roadside CMF for Median Width CMF for Lighting CMF for Automated Speed Parking Fixed Objects Enforcement CMF 1r CMF 2r CMF 3r CMF 4r CMF 5r from Equation from Equation from Table from Equation from Section (6) Combined CMF CMF comb (1)*(2)*(3)*(4)*(5) 45
46 Next calculate SPFs By Collision Type Multiple-vehicle collision two or more moving motor vehicles involved in the crash in the following manners: rear-end head-on angle sideswipe other Single-vehicle collision one moving motor vehicle involved in a crash in the following manners: collision with parked vehicle, collision with animal, collision with fixed object, collision with other object, non-collision, other 46
47 Worksheet 1C: Multiple-Vehicle Non-driveway (1) Crash Severity Level Total Fatal and Injury (FI) Property Damage Only (PDO) Worksheet 1C -- Multiple-Vehicle Nondriveway Collisions by Severity Level for Urban and Suburban Roadway Segments (2) SPF Coefficients from Table 12-3 a b (3) (4) (5) Overdispersion Parameter, k Initial N brmv Proportion of Total Crashes (6) (7) (8) (9) Calibration Factor, Cr Adjusted N brmv from Table 12-3 from Equation (4) TOTAL *(5) (4) FI /((4) FI +(4) PDO ) (5) TOTAL -(5) FI Combined CMFs (6) from Worksheet 1B Predicted N brmv (6)*(7)*(8) 47
48 Table
49 Equation N brmv = exp(a + b ln AADT + ln(l)) Where: AADT=average annual daily traffic volume (veh/day) on roadway segment L= length of roadway segment (mi) a, b = regression coefficients N brm v (total)= exp ( x ln(15,000)+ln(2.5) )=6.365 N brmv (FI)=exp ( x ln(15,000)+ln(2.5) )= N brmv (PDO)=exp( x ln(15,000)+ln(2.5) )= But wait! Not finished yet 49
50 Equations and N brmv(fi) = N brmv(total) N brmv(fi) N brmv FI +N brmv(pdo) Equation N brsv(pdo) = N brsv(total) N brsv FI Equation In order to adjust the values N brmv = 6.365( )= N brmv = = *Multiply these values by the combined CMFs (1.79) and the calibration factor (1.0) 50
51 Worksheet 1C: Multiple Vehicle Non-driveway Crashes by Severity Worksheet 1C -- Multiple-Vehicle Nondriveway Collisions by Severity Level for Urban and Suburban Roadway Segments (1) (2) (3) (4) (5) (6) (7) (8) (9) Crash Severity Level SPF Coefficients Overdispersion Proportion of Total Adjusted Combined Calibration Predicted Parameter, k Initial N brmv Crashes N brmv CMFs Factor, Cr N brmv from Table 12-3 (6) from from Table 12-3 from Equation (4) TOTAL *(5) a b Worksheet 1B (6)*(7)*(8) Total Fatal and Injury (FI) (4) FI /((4) FI +(4) PDO ) Property Damage Only (PDO) (5) TOTAL -(5) FI N brmv (total) = crashes/ yr N brmv (FI) = crashes/ yr N brmv (PDO) = crashes/ yr 51
52 Worksheet 1D: Multiple Non-driveway Crashes by Type Total (1) Collision Type Rear-end collision Head-on collision Angle collision Sideswipe, same direction Sideswipe, opposite direction Other multiple-vehicle collision Worksheet 1D -- Multiple-Vehicle Nondriveway Collisions by Collision Type for Urban and Suburban Roadway Segments (2) (3) (4) (5) (6) Predicted N b rmv ( F I) Proportion of Predicted N b rmv ( PD O) (crashes/year) Collision Type (PDO) (crashes/year) Proportion of Collision Type( F I) from Table 12-4 (9)FI from Worksheet 1C from Table 12-4 (9)PDO from Worksheet 1C Predicted N brmv (TOTAL) (crashes/year) (9)TOTAL from Worksheet 1C (2)*(3) FI (4)*(5) PDO (3)+(5) 52
53 Table
54 Worksheet 1D: Multiple Non-driveway Crashes by Type (1) Collision Type Worksheet 1D -- Multiple-Vehicle Nondriveway Collisions by Collision Type for Urban and Suburban Roadway Segments (2) (3) (4) (5) (6) Proportion of Collision Predicted N b rmv ( F I) Proportion of Collision Predicted N b rmv ( PD O) Type( F I) (crashes/year) Type (PDO) (crashes/year) Predicted N brmv (TOTAL) (crashes/year) from Table 12-4 (9)FI from Worksheet (9)PD O from Worksheet from Table C 1C (9)T OT A L from Worksheet 1C Total (2)*(3) FI (4)*(5) PDO (3)+(5) Rear-end collision Head-on collision Angle collision Sideswipe, same direction Sideswipe, opposite direction Other multiple-vehicle collision
55 Worksheet 1E: Single Vehicle Crashes by Severity (1) (2) (3) (4) (5) (6) (7) (8) (9) SPF Coefficients Overdispersion Proportion of Total Adjusted Combined Calibration Predicted Parameter, k Initial N brsv Crashes N brsv CMFs Factor, Cr N brsv Crash Severity Level from Table 12-5 (6) from from Table 12-5 from Equation (4) TOTAL *(5) (6)*(7)*(8) a b Worksheet 1B Total Fatal and Injury (FI) Worksheet 1E -- Single-Vehicle Collisions by Severity Level for Urban and Suburban Roadway Segments (4) FI /((4) FI +(4) PDO ) Property Damage Only (PDO) (5) TOTAL -(5) FI 55
56 Table
57 Equation NN brsv =exp(a+b ln(aadt)+ln (L) Where: AADT=average annual daily traffic volume (veh/day) on roadway segment L= length of roadway segment (mi) a, b = regression coefficients N brsv (total)= exp ( x ln(15,000)+ln(2.5)) =2.296 N brsv (FI)=exp ( x ln(15,000)+ln(2.5)) = N brsv (PDO)=exp( x ln(15,000)+ln(2.5)) = Next 57
58 Equations and N brsv(fi) = N brsv(total) N brsv(fi) N brsv FI +N brsv(pdo) Equation N brsv(pdo) = N brsv(total) N brsv FI Equation In order to adjust the values N brsv = = N brsv = = Multiply these values by the combined CMFs (1.79) and the calibration factor (1.0) 58
59 Worksheet 1E: Single Vehicle Crashes by Severity Worksheet 1E -- Single-Vehicle Collisions by Severity Level for Urban and Suburban Roadway Segments (1) (2) (3) (4) (5) (6) (7) (8) (9) SPF Coefficients Overdispersion Proportion of Total Adjusted Combined Calibration Predicted Parameter, k Initial N brsv Crashes N brsv CMFs Factor, Cr N brsv Crash Severity Level from Table 12-5 (6) from from Table 12-5 from Equation (4) TOTAL *(5) (6)*(7)*(8) a b Worksheet 1B Total Fatal and Injury (FI) (4) FI /((4) FI +(4) PDO ) Property Damage Only (PDO) (5) TOTAL -(5) FI N brsv (total) = crashes/ yr N brsv (FI) = crashes/ yr N brsv (PDO) = crashes/ yr 59
60 Worksheet 1F: Single Vehicle Crashes by Type (1) Collision Type Total Collision with animal Collision with fixed object Collision with other object Other single-vehicle collision Worksheet 1F -- Single-Vehicle Collisions by Collision Type for Urban and Suburban Roadway Segments (2) (3) (4) (5) (6) Predicted N b rsv ( F I) Proportion of Predicted N b rsv ( PD O) (crashes/year) Collision Type (PDO) (crashes/year) Proportion of Collision Type( F I) from Table 12-6 (9)FI from Worksheet 1E from Table 12-6 (2)*(3) FI (9)PDO from Worksheet 1E Predicted N brsv (TOTAL) (crashes/year) (9)TOTAL from Worksheet 1E (4)*(5) PDO (3)+(5) 60
61 Table
62 Worksheet 1F: Single Vehicle Crashes by Type Collision Type (1) Worksheet 1F -- Single-Vehicle Collisions by Collision Type for Urban and Suburban Roadway Segments (2) (3) (4) (5) (6) Proportion of Collision Type( F I) Predicted N b rsv ( F I) (crashes/year) Proportion of Collision Type (PDO) Predicted N b rsv ( PD O) (crashes/year) Predicted N brsv (TOTAL) (crashes/year) from Table 12-6 (9)FI from Worksheet (9)PD O from Worksheet from Table E 1E (9)T OT A L from Worksheet 1E Total (2)*(3) FI (4)*(5) PDO (3)+(5) Collision with animal Collision with fixed object Collision with other object Other single-vehicle collision Column (3) N brsv (FI) = crashes/ yr Column (5) N brsv (PDO) = crashes/ yr Column (6) N brsv (total) = crashes/ yr 62
63 Worksheet 1G: Multiple Vehicle Driveway Related by Driveway Type Driveway Type Major commercial Minor commercial Major industrial/institutional Minor industrial/institutional Major residential Minor residential Other Total Worksheet 1G -- Multiple-Vehicle Driveway-Related Collisions by Driveway Type for Urban and Suburban Roadway Segments (1) (2) (3) (4) (5) (6) Crashes per driveway Coefficient for traffic Overdispersio Initial N brdwy Number of per year, N j adjustment, t n parameter, k driveways, n j Equation from Table 12-7 from Table 12-7 from Table 12-7 n j * N j * (AADT/15,000) t -- 63
64 Table
65 Worksheet 1G: Multiple Vehicle Driveway Related by Driveway Type Driveway Type Major commercial Minor commercial Major industrial/institutional Minor industrial/institutional Worksheet 1G -- Multiple-Vehicle Driveway-Related Collisions by Driveway Type for Urban and Suburban Roadway Segments (1) (2) (3) (4) (5) (6) Crashes per driveway Coefficient for traffic Overdispersion Initial N Number of driveways, brdwy per year, N j adjustment, t parameter, k n j Equation from Table 12-7 from Table 12-7 from Table 12-7 n j * N j * (AADT/15,000) t Major residential 5 Minor residential 10 Other 0 Total N taken from the given information
66 Worksheet 1G: Multiple Vehicle Driveway Related by Driveway Type Driveway Type Major commercial Minor commercial Major industrial/institutional Minor industrial/institutional Worksheet 1G -- Multiple-Vehicle Driveway-Related Collisions by Driveway Type for Urban and Suburban Roadway Segments (1) (2) (3) (4) (5) (6) Crashes per driveway Coefficient for traffic Overdispersion Initial N Number of driveways, brdwy per year, N j adjustment, t parameter, k n j Equation from Table 12-7 from Table 12-7 from Table 12-7 n j * N j * (AADT/15,000) t Major residential 5 Minor residential 10 Other 0 Total Variables N j and t taken from Table
67 Equation NN brdwy =exp (a+b x ln(aadt) + ln(l)) Where: AADT=average annual daily traffic volume (veh/day) on roadway segment L= length of roadway segment (mi) a, b = regression coefficients N brdwy (total)= exp ( x ln(15,000)+ln(2.5) =2.296 N brdwy (FI)=exp ( x ln(15,000)+ln(2.5) = N brdwy (PDO)=exp( x ln(15,000)+ln(2.5) = Next 67
68 Equations and N drwy(fi) = N brdwy(total) f dwy (12-17) N brdwy(pdo) = N brdwy(total) N brdwy(fi) (12-18) Where: F dwy = proportion of driveway-related collisions that involve fatalities or injuries In order to adjust the values N brsv = = N brsv = = Multiply these values by the combined CMFs (1.79) and the calibration factor (1.0) 68
69 Worksheet 1H: Multiple Vehicle Driveway Related Crashes by Severity Worksheet 1H -- Multiple-Vehicle Driveway-Related Collisions by Severity Level for Urban and Suburban Roadway Segments (1) (2) (3) Proportion of total Initial N brdwy crashes (f dwy ) Crash Severity Level (5) TOTAL from from Table 12-7 Worksheet 1G Total Fatal and injury (FI) Property damage only (PDO) (4) (5) (6) (7) Adjusted N brdwy (2) TOTAL * (3) Combined CMFs (6) from Worksheet 1B Calibration factor, C r Predicted N brdwy (4)*(5)*(6) 69
70 Table 12-7 (for severity proportions) 70
71 Worksheet 1H: Multiple Vehicle Driveway Related Crashes by Severity Worksheet 1H -- Multiple-Vehicle Driveway-Related Collisions by Severity Level for Urban and Suburban Roadway Segments (1) (2) (3) (4) (5) (6) (7) Crash Severity Level Proportion of total Adjusted Initial N brdwy Combined CMFs Predicted N brdwy crashes (f dwy ) N brdwy Calibration factor, C (5) TOTAL from Worksheet (6) from Worksheet r from Table 12-7 (2) TOTAL * (3) (4)*(5)*(6) 1G 1B Total Fatal and injury (FI) Property damage only (PDO)
72 Worksheet 1I: Vehicle-Pedestrian Crashes Worksheet 1I -- Vehicle-Pedestrian Collisions for Urban and Suburban Roadway Segments (1) (2) (3) (4) (5) (6) (7) (8) Predicted N brmv Crash Severity Level (9) from Worksheet 1C Total Fatal and injury (FI) -- Predicted N brsv (9) from Worksheet 1E Predicted N brdwy Predicted N br f pedr Predicted N Calibration pedr (7) from from Table (2)+(3)+(4) factor, C r (5)*(6)*(7) Worksheet 1H
73 Table
74 Worksheet 1I: Vehicle-Pedestrian Crashes Crash Severity Level Total Fatal and injury (FI) Worksheet 1I -- Vehicle-Pedestrian Collisions for Urban and Suburban Roadway Segments (1) (2) (3) (4) (5) (6) (7) (8) Predicted N brmv (9) from Worksheet 1C Predicted N brsv (9) from Worksheet 1E Predicted N brdwy Predicted N br f pedr Predicted N Calibration pedr from Table (7) from Worksheet 1H (2)+(3)+(4) factor, C r (5)*(6)*(7) Worksheet 1I -- Vehicle-Pedestrian Collisions for Urban and Suburba (1) (2) (3) (4) Predicted N brmv Predicted N brsv Predicted N brdwy Pred Crash Severity Level (9) from Worksheet 1C (9) from Worksheet 1E (7) from Worksheet 1H (2) Total Fatal and injury (FI) llisions for Urban and Suburban Roadway Segments (4) (5) (6) (7) (8) Predicted N brdwy Predicted N br f pedr Predicted N Calibration pedr from Table (7) from Worksheet 1H (2)+(3)+(4) factor, C r (5)*(6)*(7)
75 Worksheet 1J: Vehicle-Bicycle Crashes Worksheet 1J -- Vehicle-Bicycle Collisions for Urban and Suburban Roadway Segments (1) (2) (3) (4) (5) (6) (7) (8) Crash Severity Level Predicted N brmv Predicted N brsv Predicted N brdwy Predicted N br f biker Predicted N Calibration biker (9) from (9) from (7) from from Table (2)+(3)+(4) factor, C r (5)*(6)*(7) Worksheet 1C Worksheet 1E Worksheet 1H 12-9 Total Fatal and injury (FI)
76 Table
77 Worksheet 1J: Vehicle-Bicycle Crashes Worksheet 1J -- Vehicle-Bicycle Collisions for Urban and Suburban Roadway Segments (1) (2) (3) (4) (5) (6) (7) (8) Crash Severity Level Predicted N brmv Predicted N brsv Predicted N brdwy Predicted N br f biker Calibration Predicted N biker (9) from Worksheet 1C (9) from Worksheet 1E (7) from Worksheet 1H (2)+(3)+(4) from Table 12-9 factor, C r (5)*(6)*(7) Total Fatal and injury (FI)
78 Worksheet 1K: Crash Severity Distribution Collision type Rear-end collisions (from Worksheet 1D) Head-on collisions (from Worksheet 1D) Angle collisions (from Worksheet 1D) Sideswipe, same direction (from Worksheet 1D) Sideswipe, opposite direction (from Worksheet 1D) Driveway-related collisions (from Worksheet 1H) Other multiple-vehicle collision (from Worksheet 1D) Subtotal (1) Collision with animal (from Worksheet 1F) Collision with fixed object (from Worksheet 1F) Collision with other object (from Worksheet 1F) Other single-vehicle collision (from Worksheet 1F) Collision with pedestrian (from Worksheet 1I) Collision with bicycle (from Worksheet 1J) Subtotal Total Worksheet 1K -- Crash Severity Distribution for Urban and Suburban Roadway Segments (2) (3) (4) Fatal and injury (FI) Property damage only (PDO) Total (3) from Worksheet 1D and 1F; (5) from Worksheet 1D and 1F; and (6) from Worksheet 1D and 1F; (7) from Worksheet 1H; and (7) from Worksheet 1H (7) from Worksheet 1H; and (8) from Worksheet 1I and 1J (8) from Worksheet 1I and 1J MULTIPLE-VEHICLE SINGLE-VEHICLE 78
79 Worksheet 1K: Crash Severity Distribution Worksheet 1K -- Crash Severity Distribution for Urban and Suburban Roadway Segments (1) (2) (3) (4) Fatal and injury (FI) Property damage only (PDO) Total Collision type (3) from Worksheet 1D and 1F; (5) from Worksheet 1D and 1F; and (6) from Worksheet 1D and 1F; (7) from Worksheet 1H; and (7) from Worksheet 1H (7) from Worksheet 1H; and (8) from Worksheet 1I and 1J (8) from Worksheet 1I and 1J MULTIPLE-VEHICLE Rear-end collisions (from Worksheet 1D) Head-on collisions (from Worksheet 1D) Angle collisions (from Worksheet 1D) Sideswipe, same direction (from Worksheet 1D) Sideswipe, opposite direction (from Worksheet 1D) Driveway-related collisions (from Worksheet 1H) Other multiple-vehicle collision (from Worksheet 1D) Subtotal SINGLE-VEHICLE Collision with animal (from Worksheet 1F) Collision with fixed object (from Worksheet 1F) Collision with other object (from Worksheet 1F) Other single-vehicle collision (from Worksheet 1F) Collision with pedestrian (from Worksheet 1I) Collision with bicycle (from Worksheet 1J) Subtotal Total FI Crashes = PDO Crashes = Total Crashes =
80 Worksheet 1L: Summary of Results (1) Crash Severity Level Total Fatal and injury (FI) Property damage only (PDO) Worksheet 1L -- Summary Results for Urban and Suburban Roadway Segments (2) Predicted average crash frequency, N predicted rs (crashes/year) (Total) from Worksheet 1K (3) Roadway segment length, L (mi) (4) Crash rate (crashes/mi/year) (2) / (3) 80
81 Worksheet 1L: Summary of Results (1) Crash Severity Level Total Fatal and injury (FI) Property damage only (PDO) Worksheet 1L -- Summary Results for Urban and Suburban Roadway Segments (2) Predicted average crash frequency, N predicted rs (crashes/year) (Total) from Worksheet 1K (3) Roadway segment length, L (mi) (4) Crash rate (crashes/mi/year) (2) / (3)
82 Urban 4 Leg Signalized Intersection (This example using the Excel Tool) 82
83 Pertinent Data: 1 left-turn lane on each of the two major road approaches No right-turn lanes Protected left-turn signal phasing on major road (both approaches) AADT (major rd) = 20,000 veh/ day AADT (minor rd) = 8,000 veh/ day Lighting is present 83
84 Pertinent Data (cont.): 1 bus stop 400 ft from the intersection A high school is located 800 ft from the intersection Coqui Bar, Coco Bar, Fiesta Bar, and Margarita Bar located within 1,000 ft of the intersection No approaches with prohibited right-turn-on-red 4-lane undivided major road 2-lane undivided minor road Pedestrian volume = 1,200 ped/day 84
85 Assumptions: The calibration factor = 1.00 The maximum number of lanes crossed by a pedestrian is assumed to be 4 Collision type distributions are the default values from HSM
86 Required: Crash Modification Factors (CMF s) applicable only to the four-leg signalized intersections 1. CMF for the effect of left-turn lanes 2. CMF for the effect of left-turn signal phasing 3. CMF for the effect of right-turn lanes 4. CMF for the effect of right-turn-on-red 5. CMF for the effect of lighting 6. CMF for the effect of red-light cameras 7. CMF for the effect of bus stops 8. CMF for the effect of schools 9. CMF for the effect of alcohol sales establishments Combined Crash Modification Factor (CMF) Predicted Average Crash Frequency 86
87 First, find out what is the site type from Table 12-1: 87
88 Safety Performance Functions for Urban and Suburban Arterials (Table 12-2) 88
89 Worksheet 2A Urban and Suburban Arterial Intersections Worksheet 2A -- General Information and Input Data for Urban and Suburban Arterial Intersections General Information Location Information Analyst Roadway Agency or Company Intersection Date Performed Jurisdiction Analysis Year Input Data Base Conditions Site Conditions Intersection type (3ST, 3SG, 4ST, 4SG) -- AADT major (veh/day) AADT MAX = 67,700 (veh/day) -- AADT minor (veh/day) AADT MAX = 33,400 (veh/day) -- Intersection lighting (present/not present) Not Present Calibration factor, C i 1.00 Data for unsignalized intersections only: -- Number of major-road approaches with left-turn lanes (0,1,2) 0 Number of major-road approaches with right-turn lanes (0,1,2) 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 Number of approaches with right-turn lanes (0,1,2,3,4) [for 3SG, use maximum value of 3] Number of approaches with left-turn signal phasing [for 3SG, use maximum value of 3] 0 -- Type of left-turn signal phasing for Leg #1 Type of left-turn signal phasing for Leg #2 Permissive -- Type of left-turn signal phasing for Leg #3 -- Type of left-turn signal phasing for Leg #4 (if applicable) -- Number of approaches with right-turn-on-red prohibited [for 3SG, use maximum value of 3] 0 Intersection red light cameras (present/not present) Not Present Sum of all pedestrian crossing volumes (PedVol) -- Signalized intersections only Maximum number of lanes crossed by a pedestrian (n lanesx ) -- 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) Not Present Number of alcohol sales establishments within 300 m (1,000 ft) of the intersection 0 89
90 Worksheet 2B Double Check the Values! 90
91 CMF Intersection Left-Turn Lane (Table 12-24): CMF Intersection Left-Turn Lane =
92 CMF Left-Turn Phasing Signal (Table 12-25): 2 approaches, therefore must multiply 0.94 x 0.94 = 0.88 CMF Left-Turn Phasing Signal =
93 CMF of Right-Turn Lanes (Table 12-26): Are there right-turn lanes? CMF Right-Turn Lanes = 1.0 (Base Condition) 93
94 CMF for Right Turn on Red Right turn on red is not prohibited (base condition) Therefore CMF 4i = 1.00 If the movement was prohibited, use Equation
95 CMF of lighting (Table 12-27): Equation 12-36: CMF (lighting) = x P (night) P (night) : x = 0.91 CMF 5i =
96 CMF for Red Light Cameras No cameras (base condition) CMF 6i Red Light Cameras = 1.00 If there were cameras, use Equation
97 Worksheet 2C Double Check the Values! 97
98 Table
99 Worksheet 2D Double Check the Values! 99
100 Table
101 Worksheet 2E Double Check the Values! 101
102 Table
103 Worksheet 2F Double Check the Values! 103
104 Table
105 Worksheet 2G Does not apply to intersections 105
106 Worksheet 2H Double Check the Values! 106
107 Table (CMF Bus Stops) : CMF Bus Stops =
108 Table (CMF Presence of Schools) : CMF School =
109 Table (CMF Alcohol Sales): CMF Alcohol Sales =
110 Worksheet 2I Double Check the Values! 110
111 Table 12-14: 111
112 Worksheet 2J Double Check the Values! 112
113 Table
114 Worksheets 2K & 2L Crash Summaries 114
115 Worksheet 2L -- Summary Results for Urban and Suburban Arterial Intersections (1) (2) Crash severity level Predicted average crash frequency, N predicted int (crashes/year) (Total) from Worksheet 2K Total 4.1 Fatal and injury (FI) 1.6 Property damage only (PDO)
116 Empirical Bayes Method 116
117 Empirical Bayes Method: Evaluate the predicted number of crashes using the Empirical Bayes Method 117
118 Empirical Bayes Method (cont.): Used to combined observed crash frequency data for a given site with predicted crash frequency data from many similar sites to estimate its expected crash frequency. 118
119 The advantages of using EB Method for crash data analysis The Empirical Bayes method addresses two problems of safety estimation; 1. it increases the precision of estimates beyond what is possible when one is limited to the use of a two-three year history accidents, and 2. it corrects for the regression-to-mean bias. The increase in precision is important when the usual estimate is too imprecise to be useful. The elimination of the regression to mean bias is important whenever the accident history of the entity is in some way connected with the reason why its safety is estimated. Hauer, et al. Estiating Safety by the Empirical Bayes Method: A Tutorial, website: 119
120 The project Using Empirical Bayes Method What is the expected crash frequency of the project for a particular year using the site-specific EB Method? The following is the breakdown of the observed crashes per section type: 2U Segment Multiple-vehicle non-driveway = 4 Single-vehicle = 6 Multiple-vehicle driveway related = 1 4SG Segment Multiple-vehicle = 8 Single-vehicle = 2 120
121 Worksheet 3A: Predicted Crashes by Severity & Type Using EB Method (Segment) 121
122 Worksheet 3A: Predicted Crashes by Severity & Type Using EB Method (Intersection) 122
123 Column#7: Weighted Adjustment, w w = 1 1+k all study years N predicted Multiple-vehicle non-driveway (segment): w = =
124 Column#8: Expected Average Crash Frequency, N expected N expected = w N predicted + (1 w) N observed Multiple-vehicle Non-driveway Collisions (Segment): N expected = = crashes/yr 124
125 Worksheet 3B: Predicted Pedestrian & Bicycle Crashes Worksheet 1I, Column 8 Worksheet 1J, Column 8 Worksheet 2I, Column 7 Worksheet 2J, Column 7 125
126 Worksheet 3C: Site Specific EB Method Results 126
127 Calibration Factor (C r ) Formula Where: C r = C r = constant used to multiply the base SPF to correct the number of expected crashes at the applied location N observed = number of observed crashes for the selected set of sites N predicted = number of predicted crashes N observed N predicted Note: Appendix A in Part C of the HSM contains a detailed procedure to obtain the c- factor. 127
128 Site Selection Criteria to Determine the Calibration Factor (C r ) 1. Between sites minimum should be selected through random sampling 2. Sites should be long enough to be representative of a roadway section, but no shorter than 0.10 mile in length 3. Sites must exhibit at least 100 crashes per year 4. A minimum of three years of historical crash data must be used 128
129 Crash Modification Factors Clearinghouse Website 129
130 New Changes for the HSM 2010 The Enhanced Safety Prediction Methodology And Analysis Tool For Freeways And Interchanges NCHRP 17-45, May
131 PRSHSP Available: urapr.com/content/docs/ Puerto_Rico_SHSP_ _English.pdf Strategic Plan for years
132 Topics Covered: Highway Safety in the Commonwealth of Puerto Rico The planning and development process The emphasis areas Future steps in the implementation Evaluation of the Strategic Highway Safety Plan 132
133 Flowchart of the 2014 Puerto Rico SHSP Development and Implementation Process 133
134 Predictive Model for Freeway Segments (NCHRP 17-45) 1. Rural freeway with four through lanes, with six through lanes, with eight through lanes, 2. Urban freeway with four through lanes, with six through lanes, with eight through lanes, and with ten through lanes. 134
135 Predictive Model for Ramp and Collector Distributor (C-D) Road Segments RURAL Entrance ramp with one lane, Exit ramp with one lane, C-D road with one lane URBAN C-D road with one lane, C-D road with two lanes, Entrance ramp with one lane, Entrance ramp with two lanes, Exit ramp with one lane, and Exit ramp with two lanes. 135
136 Thank You for your Attention! 136
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