Proposed Guidelines for Fixed Objects in the Roadside Design Guide (2022)

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113 Current iRAP Model for Predicting Run-Off-Road Crashes This appendix presents the current RAP model for predicting injuries in ROR crashes. This model was developed by the iRAP in conjunction with its partner, the usRAP. The RAP model was developed for application throughout the world including in countries that drive on either the right or left side of the road. Therefore, the RAP documentation refers to the two sides of the road as the driver side and the passenger side. Since this research is developing a model for application in the United States, where all driving is on the right side of the road, this appendix consistently refers to the driver side as the left side of the road and the passenger side as the right side of the road. The RAP model includes procedures for estimating injuries in a wide variety of crash types, including ROR crashes. For application in this research, this appendix focuses exclusively on the estimation procedure for ROR crashes. The RAP model considers injuries to four types of road users: motor vehicle occupants (other than motorcyclists), motorcyclists, pedestrians, and bicyclists. For application in this research, this appendix focuses exclusively on injuries to motor vehicle occupants (other than motorcyclists) and motorcyclists. For some fixed-object types, the factors used in the RAP procedures for estimating injuries to motorcyclists and other motor vehicle occupants differ. However, there are no differences in the roadside fixed-object factors applicable to trees and utility poles. There were minor differences in two of the crash likelihood factors (not related directly to roadside fixed objects), but these differing factors were easily combined. Therefore, the procedures for motorcyclists and other motor vehicle occupants have been combined in this appendix. The RAP procedure estimates fatal crash frequencies and then expands that estimate with a factor to include serious injuries. Chapter 6 explains how the existing RAP procedure has been reorganized in this research to estimate total injury crashes and then to break that estimate apart by injury severity level. The RAP procedures include the capability to calibrate the models with local data. Chapter 6 shows how the existing RAP model has been calibrated with Kentucky and Washington data for tree- and utility-pole-related crashes to make the model specifically applicable to typical U.S. conditions. Chapter 7 explains how the model can be further calibrated to better represent local conditions for any specific jurisdiction. The RAP models were developed to estimate crash frequencies for roadway segments 327 ft or 0.062 mi (i.e., equivalent to 100 m) in length. Chapter 6 explains how the existing RAP model has been modified to make it applicable to roadway segments of any length. The full modified RAP model is presented in the accompanying guidelines document. A.1 General Form of Crash Prediction Model for Run-Off-Road Crashes This section presents the portion of the RAP crash prediction model that addresses ROR crashes. The general form of the crash prediction model for a specific roadway segment is as follows (iRAP, 2014):

114 𝑵𝑹𝑶𝑹 = 𝑵𝑹𝑶𝑹 𝒍𝒆𝒇𝒕 + 𝑵𝑹𝑶𝑹 𝒓𝒊𝒈𝒉𝒕 (A-48) 𝑵𝑹𝑶𝑹 𝒍𝒆𝒇𝒕 = 𝑹𝑺𝑺𝑹𝑶𝑹 𝒍𝒆𝒇𝒕 × (𝑨𝑨𝑫𝑻)𝟏.𝟎𝟑 × 𝑪𝑭𝑹𝑶𝑹 × 𝟑𝟔𝟓𝟏𝟎𝟗 (A-49) 𝑵𝑹𝑶𝑹 𝒓𝒊𝒈𝒉𝒕 = 𝑹𝑺𝑺𝑹𝑶𝑹 𝒓𝒊𝒈𝒉𝒕 × (𝑨𝑨𝑫𝑻)𝟏.𝟎𝟑 × 𝑪𝑭𝑹𝑶𝑹 × 𝟑𝟔𝟓𝟏𝟎𝟗 (A-50) where: NROR = predicted number of run off-road crashes per year on a specific roadway segment involving a fatality or serious injury to an occupant of a motor vehicle running off either side of the road within a specific roadway segment NROR-left = predicted number of run off-road crashes per year on a specific roadway segment involving a fatality or serious injury to an occupant of a motor vehicle running off the left side of the road within a specific roadway segment NROR-right = predicted number of run off-road crashes per year on a specific roadway segment involving a fatality or serious injury to an occupant of a motor vehicle running off the right side of the road within a specific roadway segment RSSROR-left = road safety score for crashes involving motor vehicles running off the left side of the road RSSROR-right = road safety score for crashes involving motor vehicles running off the right side of the road AADT = annual average daily traffic volume (veh/day) in both directions of travel combined for undivided roadway segments or roadway segments with traversable medians and in one direction of travel only for roadway segments with nontraversable medians CFROR = calibration factor for ROR crashes The calibration factor (CFROR) allows for use of local data to adjust the model to correspond to local conditions within particular jurisdictions. A.2 Road Safety Scores for Run-Off-Road Crashes The RAP procedures use a RSS as a basis for estimating the frequency of crashes of particular types. The RSS is proportional to crash frequency and considers both crash likelihood and crash severity, as well as the influence of vehicle operating speed and traffic volume. The RSS for injuries to motor vehicle occupants in run-off-road crashes on each side of the road (iRAP 2013b) is determined as: RSSROR-left = LikelihoodROR x SeverityROR-left x OSF x EFI x MT (A-51) RSSROR-right = LikelihoodROR x SeverityROR-right x OSF x EFI (A-52) where:

115 RSSROR-left = road safety score for injuries to occupants of motor vehicles running off the left side of the road RSSROR-right = road safety score for injuries to occupants of motor vehicles running off the right side of the road LikelihoodROR = crash likelihood factor for crashes involving motor vehicles running off the road SeverityROR-left = crash severity factor for crashes involving motor vehicles running off the left side of the road SeverityROR-right = crash severity factor for crashes involving motor vehicles running off the right side of the road OSF = operating speed factor EFI = external flow influence factor MT = median traversability factor A.2.1 Crash Likelihood Factor for Run-Off-Road Crashes The crash likelihood factor for crashes involving motor vehicles running off the road (iRAP 2013b) is computed as a product of risk factors as follows: LikelihoodROR = RFL1 x RFL2 x RFL3 x RFL4 x RFL5 x RFL6 x RFL7 x RFL8 (A-53) where: RFL1 = likelihood risk factor for lane width RFL2 = likelihood risk factor for roadway curvature RFL3 = likelihood risk factor for quality of curve RFL4 = likelihood risk factor for grade RFL5 = likelihood risk factor for shoulder rumble strips RFL6 = likelihood risk factor for delineation RFL7 = likelihood risk factor for road surface condition RFL8 = likelihood risk factor for pavement type/skid resistance A.2.2 Crash Severity Factor for Run-Off-Road Crashes The crash severity factors for motor vehicles running off the left and right sides of the road (iRAP 2013b) are computed as: SeverityROR-left = (RFS1-left x RFS2-left x RFS3-left) (A-54) SeverityROR-right = RFS1-right x RFS2-right x RFS3-right (A-55)

116 where: RFS1-left = crash severity risk factor for distance to the most severe roadside object on the left side of the road RFS1-right = crash severity risk factor for distance to the most severe roadside object on the right side of the road RFS2-left = crash severity risk factor for most severe roadside object type on the left side of the road RFS2-left = crash severity risk factor for most severe roadside object type on the right side of the road RFS3-left = crash severity risk factor for paved shoulder width on the left side of the road RFS3-right = crash severity risk factor for paved shoulder width on the right side of the road A.2.3 Operating Speed Factor for Run-Off-Road Crashes The operating speed factors applicable to run-off-road crashes (iRAP 2013g) are derived from the mean speed of traffic on particular road sections. The operating speed factor (OSF) values are shown in Table A-1 and are illustrated in Figure A-1. The values of the OSF have a cubic relationship to mean speed based on the power curve (Nilsson 2004).

117 Table A-1. OSF for Motor Vehicle Movements Along the Road (iRAP 2013g) Mean operating speed of motor vehicles traveling along the roadway segment of interest (mph) OSF 20 or less 0.010 25 0.019 30 0.033 35 0.053 40 0.079 45 0.113 50 0.154 55 0.205 60 0.267 65 0.339 70 0.424 75 0.521 80 0.632 85 0.758 90 or more 0.900 Figure A-1. Operating Speed Factors Representing the Relative Risk of Injury for Motor Vehicle Occupants Involved in Run-Off-Road Crashes as a Function of Mean Traffic Speed (adapted from iRAP 2013g) For applying the crash prediction models, the speed used in determining the value of OSF should be the best estimate of the mean speed of motor vehicle traffic. A.2.4 External Flow Influence Factor for Run-Off-Road Crashes The EFI factor for motor vehicle movements along the road (iRAP 2013a) represents the level of lane saturation on the road in question. The values of the factors are determined with the best available estimate of traffic volume (AADT) per lane. AADT per lane is computed as the total

118 AADT divided by the number of through lanes on the road. The EFI factor essentially represents the level of saturation in the flow on the roadway, where 19,000 to 20,000 veh/day/lane represents a fully saturated roadway. The RAP procedure uses categories for the traffic flow on the inspected road that represent ranges of AADT per lane. The applicable AADT ranges and midpoints are shown in Table A-2. The table also shows the corresponding values of the EFI factor. The factor values are plotted as a continuous function in Figure A-2. Table A-2. EFI Factors for Motor Vehicle Crashes as a Function of AADT Ranges and Midpoints (adapted from iRAP 2013a) Ranges for AADT per lane (veh/day) Midpoint of AADT per lane range (veh/day) External flow influence (EFI) factor by road type Rural two-lane undivided highway Rural four-lane undivided highway Rural divided nonfreeway less than 1,999 1,000 0.474 0.451 0.500 2,000 – 3,999 3,000 0.448 0.408 0.500 4,000 – 5,999 5,000 0.422 0.370 0.500 6,000 – 7,999 7,000 0.397 0.339 0.500 8,000 – 9,999 9,000 0.372 0.312 0.500 10,000 – 11,999 11,000 0.347 0.290 0.500 12,000 – 13,999 13,000 0.322 0.273 0.500 14,000 – 15,999 15,000 0.298 0.261 0.500 16,000 – 17,999 17,000 0.274 0.253 0.500 18,000 or more 19,000 0.250 0.250 0.500 Figure A-2. External Flow Influence Factors for Motor Vehicle Crashes as a Function of AADT (adapted from iRAP 2013a) A.2.5 Median Traversability Factor for Run-Off-Road Crashes MT represents the potential for an errant vehicle to cross any median that may be provided on a roadway and enter the opposing lanes or cross the opposing lanes to the roadside on the far side

119 of the opposing lanes (referred to in this procedure as the left roadside). The MT factor has a value of 1 for roads with traversable medians and 0 for roads with nontraversable medians (iRAP 2013a). The MT factor is used in computation of the RSS for the left side of the road, but does not affect the RSS for the right side of the road. Roadways with traversable medians include undivided roadways with only a marked centerline or with a flush median and divided highways with a relatively flat raised or depressed median with no fixed objects present that would constrain an errant vehicle from crossing the roadway. Roadways with nontraversable medians include divided highways with terrain, traffic barriers, or other fixed objects in the median that would prevent an errant vehicle from crossing the median to reach the opposing lanes or the left roadside. A.3 Crash Likelihood Risk Factors This section presents the crash likelihood risk factors used in applying Equations (A-4) and (A-5). A.3.1 Lane Width The crash likelihood risk factors (RFL1) represent the relative likelihood that motor vehicles will run off the road, as a function of lane width. The values of this factor are shown in Table A-3. As the table shows, the risk factors are generally larger for rural areas than for urban areas. Table A-3. Crash Likelihood Risk Factors for Lane Width (iRAP 2013f) Lane width Risk factor for motor vehicles of all types (RFL1) Rural area Urban area Wide (≥ 10.6 ft) 1.00 1.00 Medium (≥ 9 to 10.6 ft) 1.20 1.05 Narrow (< 9 ft) 1.50 1.10 The rationale for the risk factor values is presented in iRAP Road Attribute Risk Factors: Lane Width (2013f). These risk factors were based on the work of Turner et al. (2009). A.3.2 Curvature The likelihood that motor vehicles will run off the road is higher on horizontal curves than on tangents and increases as the radius of curvature decreases. As the likelihood that motor vehicles will run off the road increases, the crash likelihood adjustment factors for curvature (AFL2) for motor vehicle movements along the road are shown in Table A-4. The horizontal curvature categories are defined by advisory speed ranges and corresponding ranges of horizontal curve radius. If a horizontal curve is signed with an advisory speed plate, use of the category in Table A-4 corresponding to the signed advisory speed is recommended. If there is no signed advisory speed, the curvature category should be based on the horizontal curve radius.

120 Table A-4. Crash Likelihood Risk Factors for Horizontal Curvature (iRAP 2013c) Curvature Risk factor for motor vehicles other than motorcycles Risk factor for motorcycles Combined risk factor for motor vehicles of all types (RFL2) Straight or gently curving (advisory speed ≥ 60 mph or curve radius > 2600 ft)Straight or gently curving (≥ 60 mph) 1.00 1.00 1.00 Moderate curvature (advisory speed in the range from 45 to < 60 mph or curve radius in the range from 1300 to ≤ 2600 ft) 1.80 2.00 1.81 Sharp curve (advisory speed in the range from 25 to < 45 mph or curve radius in the range from 650 to ≤ 1300 ft ) 3.50 3.80 3.51 Very sharp curve (advisory speed < 25 mph or curve radius < 650 ft) 6.00 6.50 6.02 The rationale for the risk factor values in the table is presented in iRAP Road Attribute Risk Factors: Curvature (2013c). A.3.3 Quality of Curve Quality of curve represents an assessment of the ability of approaching drivers to see a horizontal curve on the roadway ahead. The quality of any specific curve considers pavement markings, chevron markers, advance signing, and sight distance to the curve. If the quality of curve is poor, motor vehicles are more likely to run off the road on the curve. The crash likelihood risk factors for quality of curve (RFL3) for motor vehicle movements along the road are shown in Table A-5. As was the case for Table A-4, the RAP procedures for run-off-road crashes include separate values of this factor for motorcycles and other motor vehicle types. These factors have been combined in Table A-5 as a weighted average based on the assumption that the traffic stream consists of 3 percent motorcycles and 97 percent other vehicle types. The values in the table show that, with rounding to two decimal places, the combined factors do not differ from the factors for motor vehicles in general. Table A-5. Crash Likelihood Risk Factors for Quality of Curve (iRAP 2013i) Quality of curve Risk factor for motor vehicles other than motorcycles Risk factor for motorcycles Combined risk factor for motor vehicles of all types (RFL3) Adequate 1.00 1.00 1.00 Poor 1.25 1.40 1.25 Not applicable 1.00 1.00 1.00 The rationale for the risk factor values is presented in iRAP Road Attribute Risk Factors: Quality of Curve (2013i). These risk factors primarily represent the potential for loss of control on horizontal curves by motor vehicles. A.3.4 Grade Motor vehicles are more likely to lose control on steep grades than on level roadway sections. The crash likelihood risk factors representing the relative likelihood that motor vehicles will run off the road as a function of grade (RFL4) are shown in Table A-6.

121 Table A-6. Crash Likelihood Risk Factors for Percent Grade (iRAP 2013e) Percent grade Risk factor for motor vehicles of all types (RFL4 ) 0% to < 7.5% 1.00 7.5% to < 10% 1.20 ≥ 10% 1.70 The rationale for the risk factor values is presented in iRAP Road Attribute Risk Factors: Grade (2013e). These risk factors represent the potential for loss of control on grades by motor vehicles. The grade factors were based on work by Harwood et al. (2000) and analysis by iRAP of an ARRB Group database and extrapolation of results by iRAP to grades over 8 percent. A.3.5 Shoulder Rumble Strips Shoulder rumble strips are placed on the edgeline or shoulder of a roadway to alert drivers that their vehicle is leaving the roadway. Thus, shoulder rumble strips reduce the likelihood that motor vehicles will run off the road. The crash likelihood risk factors for the effect of shoulder rumble strips in reducing the likelihood of motor vehicles running off the road (RFL5) are shown in Table A-7. Table A-7. Crash Likelihood Risk Factors for Shoulder Rumble Strips (iRAP 2013p) Shoulder rumble strips Risk factor for motor vehicles of all types (RFL5) Not present 1.25 Present 1.00 The rationale for the risk factor values is presented in iRAP Road Attribute Risk Factors: Shoulder Rumble Strips (2013p). These risk factors are based primarily on literature reviewed by Turner et al. (2012) and Turner et al. (2009). A.3.6 Delineation Delineation involves the placement of pavement markings and delineators to help guide drivers along the roadway. Motor vehicles are more likely to run off the road where delineation is poor than where delineation is adequate. The crash likelihood risk factors for the effect of delineation (RFL6) on the likelihood that motor vehicles will run off the road are shown in Table A-8. Table A-8. Crash Likelihood Risk Factors for Delineation (iRAP 2013d) Delineation Risk factor for motor vehicles of all types (RFL6) Adequate 1.00 Poor 1.20 The rationale for the risk factor values is presented in iRAP Road Attribute Risk Factors: Delineation (2013d). The risk factor for delineation was based primarily on work by Turner et al. (2009). A.3.7 Road Surface Condition Poor road surface condition may make it more likely that motor vehicles may run off the road. The crash likelihood risk factors representing the effect of road surface condition (RFL7) on the relative likelihood that motor vehicles will run off the road are shown in Table A-9. As was the

122 case for Tables A-4 and A-5, the RAP procedures for run-off-road crashes include separate values of this factor for motorcycles and other motor vehicle types. These factors have been combined in Table A-9 as a weighted average based on the assumption that the traffic stream consists of 3 percent motorcycles and 97 percent other vehicle types. The values in the table show that, with rounding to two decimal places, the combined factors do not differ from the factors for motor vehicles in general. Table A-9. Crash Likelihood Risk Factors for Road Surface Condition (iRAP 2013m) Road surface condition Risk factor for motor vehicles other than motorcycles Risk factor for motorcycles Combined risk factor for motor vehicles of all types (RFL7) Good 1.00 1.00 1.00 Medium 1.20 1.25 1.20 Poor 1.40 1.50 1.40 The rationale for the risk factor values is presented in iRAP Road Attribute Risk Factors: Road Condition (2013m). This result is based on an Australian study of the relationship between road surface roughness and crashes (Cairney and Bennett 2009). Medium or poor road surface conditions are likely to represent a higher risk for loss of control by motorcyclists than for loss of control by other motor vehicles. A.3.8 Pavement Type/Skid Resistance Poor pavement skid resistance increases the likelihood that drivers of motor vehicles may be unable to stop when needed to avoid striking another motor vehicle moving along the road. Poor pavement skid resistance also increases the likelihood that motor vehicles will lose control and run off the road. It is also likely that skid resistance is lower on unpaved road surfaces than on paved road surfaces. The crash likelihood risk factors for the effect of pavement type and skid resistance of the road surface (RFL8) on the likelihood that motor vehicles will run off the road are shown in Table A-10. As shown in Tables A-4, A-5, and A-9, the RAP procedures for run- off-road crashes include separate values of this factor for motorcycles and other motor vehicle types. These factors have been combined in Table A-10 as a weighted average based on the assumption that the traffic stream consists of 3 percent motorcycles and 97 percent other vehicle types. The values in the table show that the combined factors are only slightly different from the factors for motor vehicles in general. Table A-10. Crash Likelihood Risk Factors for Pavement Type/Skid Resistance (iRAP 2013q) Pavement type/skid resistance Risk factor for motor vehicle other than motorcycles Risk factor for motorcycles Combined risk factor for motor vehicles of all types (RFL8) Paved – adequate skid resistance 1.00 1.00 1.00 Paved – medium skid resistance 1.40 1.60 1.41 Paved – poor skid resistance 2.00 2.50 2.02 Unpaved – adequate skid resistance 3.00 4.00 3.03 Unpaved – poor skid resistance 5.50 7.50 5.56 The rationale for the risk factor values is presented in iRAP Road Attribute Risk Factors: Skid Resistance/Grip (2013q). These risk factors were based on a literature review by Turner et al. (2010).

123 A.4 Crash Severity Risk Factors This section presents the crash severity risk factors used in applying Equations (A-4) and (A-5). A.4.1 Most Severe Roadside Object Distance RFS1-left represents the crash severity risk factor associated with the distance from the left edge of the traveled way to the most severe roadside object that could be struck by a motor vehicle running off the left side of the roadway. A severe object is any object that could result in an injury to an occupant of a vehicle that strikes the object. The distance to object used here should be for the object on the left side of the road whose type is used to determine RS2-left in Section A.4.2. On divided highways, the distance used to determine RFS1-left is measured from the edge of the traveled way on the median or left side of the traveled way; the most severe roadside object to which the distance is measured may be in the median or may be on the roadside beyond the opposing roadway of the divided highway. On undivided highways, the distance used to determine RFS1-left is measured from the edge of the traveled way on the left side of the roadway (i.e., from what would be considered the outside or right edge of the traveled way in the opposing direction of travel to the primary direction of travel). Similarly, RFS1-right is based on the distance from the right edge of the traveled way to the most severe roadside object that could be struck by a motor vehicle running off the right side of the roadway. This risk factor is entirely analogous to RFS1-left for the left side of the road except that this attribute applies to the right side of the road. The crash severity risk factors for roadside object distance for motor vehicles running off the road are shown in Table A-11. The values of the crash severity risk factors for the left and right sides of the road are identical. Table A-11. Crash Severity Risk Factors for Distance to Roadside Objects (iRAP 2013n) Most severe roadside object distance on the left or right side of the road Risk factor for motor vehicles of all types running off the right or left side of the road (RFS1-left or RFS1-right ) 0 to <3 ft 1.00 3 to <15 ft 0.80 15 to <30 ft 0.35 More than 30 ft 0.10 The rationale for these risk factors is presented in iRAP Road Attribute Risk Factors: Roadside Severity - Distance (2013n). A.4.2 Most Severe Roadside Object Type RFS2-left represents the crash severity risk associated with the object type for the most severe roadside object on the left side of the road that could be struck by a motor vehicle running off the road. A severe object is any object that could result in an injury to an occupant of a vehicle that strikes the object. The object whose type is coded here should be the same object whose distance from the traveled way was used to determine RFS1-left. RFS2-right is based on the object type of the most severe roadside object on the right side of the road that could be struck by a motor vehicle running off the road. The object whose type is coded here should be the same object whose distance from the traveled way was used for RFS1-right.

124 The crash severity risk factors for roadside object type for motor vehicles running off the road are shown in Table A-12. The values of the crash severity risk factors for the left and right sides of the road are identical. The table shows that, for a few objects, the crash severity risk factors differ depending upon whether the vehicle running of the road is a motorcycle or another type of motor vehicle. However, the crash severity risk factors do not differ between motorcycles and other types of motor vehicles for trees, poles, or roadsides with no object present. Therefore, for application in this research, Table A-12 can be recast as shown in Table A-13. The rationale for these risk factors is presented in iRAP Road Attribute Risk Factors: Roadside Severity - Distance (2013o). Both trees and utility poles have a risk factor equal to 60, while a clear roadside with no objects present has a risk factor equal to 35. The latter value indicates that some roadside crashes, such as crashes involving vehicle overturning, are likely to occur even when no roadside objects are present. The difference between the risk factor values of 60 and 35 (i.e., a value of 25) represents the added risk from the presence of a tree or pole on the roadside. A.4.3 Paved Shoulder Width Motor vehicles are more likely to lose control, run off the road, and experience a severe crash on roads without paved shoulders than on roads with paved shoulders. As the width of a paved shoulder increases, the probability of a severe crash decreases. The crash severity risk factors for paved shoulder width for motor vehicles running off the road are shown in Table A-14. The values of the crash severity risk factors for the left and right sides of the road are identical. The rationale for the risk factor values is presented in iRAP Road Attribute Risk Factors: Paved Shoulder Width (2013h). The paved shoulder width factors were based on work by Turner et al. (2009).

125 Table A-12. Crash Severity Risk Factors for Roadside Object Types (iRAP 2013o) Most severe roadside object type on the left or right side of the road Risk factor for motor vehicles (other than motorcycles) running off the left or right side of the road (RFS2-left or RFS2-right) Risk factor for motorcycles running off the left or right side of the road (RFS2-left or RFS2-right) Traffic barrier -- metal 12 30 Traffic barrier -- concrete 15 25 Traffic barrier – motorcyclist friendly 12 20 Traffic barrier -- cable 9 30 Aggressive vertical face 55 55 Upwards slope (15o to 75o) 45 45 Upwards steep slope (> 75o) 40 40 Deep drainage ditch 55 55 Downwards slope 45 45 Cliff 90 90 Tree (≥ 4 in diameter) 60 60 Rigid (nonfrangible) sign/post/pole (≥ 4 in diameter) 60 60 Rigid (nonfrangible) structure or building 60 60 Semirigid (frangible) structure or building 30 30 Unprotected barrier end 60 60 Large boulders (≥ 8 in tall) 60 60 None (or object > 65 ft from the road) 35 35 Table A-13. Crash Severity Risk Factors for Selected Roadside Object Types for Application in the Current Research (iRAP 2013o) Most severe roadside object type on the left or right side of the road Risk factor for motor vehicles of all types running off the left or right side of the road (RFS2-left or RFS2-right) Tree (≥ 4 in diameter) 60 Utility pole (≥ 4 in diameter) 60 None (or object > 65 ft from the road) 35 Table A-14. Crash Severity Risk Factors for Paved Shoulder Width (iRAP 2013h) Paved shoulder width on the left or right side of the road Risk factor for motor vehicles of all types running off the right- or left-side road (RFS3-left or RFS3-right) ≥ 7.9 ft 0.7 3 ft to <7.9 ft 0.83 > 0 ft to <3 ft 0.95 None 1.00