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13 and reconstruction procedures had already been developed and The scope of the supplemental data collection effort for field investigators at the Primary Sampling Units (PSUs) and this study was, therefore, selected to include 2000 and 2001 the Zone Center personnel were already familiar with the NASS CDS cases. To maintain consistency among the three protocol and procedures. Thus, this approach could be easily studies, the sampling criteria remained the same as the two implemented for this study within the time and funding con- previous studies. The sampling criteria included the follow- straints. Also, this alternative would allow cases from the pre- ing parameters: vious studies to be incorporated into the database with the new cases collected under this study. Area type--rural and suburban. Urban PSUs were excluded This third alternative of retrospective supplemental field from the sample because urban roadways tend to have lower data collection and manual review and reconstruction of exist- speed limits and the roadsides are typically cluttered with ing NASS CDS cases was, therefore, selected for this study. fixed objects. More importantly, inspections at urban crash However, it should be noted that NHTSA had changed its pol- sites are generally less detailed with a higher percentage of icy, starting with the 2003 data, to keep police accident reports incomplete data due to hazardous working conditions and in the file for only one year. This in effect eliminates the loca- traffic congestion. tion information on existing NASS CDS cases. Thus, this alter- Single-vehicle, ran-off-road crashes. Only single-vehicle, native of retrospective supplemental field data collection and ran-off-road crashes were included in the sample. Single- manual review and reconstruction of existing NASS CDS cases vehicle crashes that occurred on the roadway, or involving is no longer a viable option. For the long-term data collection parked vehicles, animals, or pedestrians, were excluded since effort in the future, only the alternatives of a new data collec- the nature of the crashes is different from that of a ran-off- tion effort or a special study under the NASS CDS system road crash. Similarly, multiple-vehicle crashes were excluded could be considered. from the sample. Passenger-type vehicles. Only passenger-type vehicles, i.e., passenger cars and light trucks with a gross vehicle weight 3.4 Data Collection Protocol (GVW) of less than 4,536 kg (10,000 lbs), were included in As discussed previously, the plan for the current study was the NASS CDS sample. Heavy trucks, i.e., single-unit trucks based on a retrospective supplemental data collection approach. with higher GVW and tractor-trailers, present very differ- This retrospective approach involved collecting supplemental ent problems than passenger vehicles. Also, reconstruction field data and manual review and reconstruction of existing of crashes involving heavy trucks is much more difficult NASS CDS cases. The major components of the data collection than those involving passenger-type vehicles. protocol are summarized as follows: Speed limit of 72 km/h (45 mph). Only crashes that occurred on highways with speed limits of 72 km/h (45 mph) or higher Sampling plan were included. Low-speed roadways tend to have lower Supplemental field data collection design standards and have crash characteristics that are sig- Manual review of sampled cases nificantly different from those of high-speed highways. Thus, Reconstruction of crashes to estimate impact speed it is not desirable to mix crashes from both low-speed and high-speed highways. Brief descriptions on activities pertaining to the supple- Complete vehicle inspection, vehicle trajectory, and injury mental field data collection are presented in this section. severity data. It would not be possible to reconstruct crashes without vehicle inspection and trajectory data, and those crashes would be of little interest to the proposed study. 3.4.1 Sampling Plan Thus, only crashes with complete vehicle inspection and As discussed previously, a similar retrospective supplemen- trajectory data were included. Also, the emphasis of the tal field data collection approach was used in two previous study was on serious and fatal injury crashes, so the injury studies: NCHRP Project 17-11 and the FHWA Rollover Study. severity should, therefore, be known for the sampled cases. Supplemental field data were collected on NASS CDS cases from 1997 through 1999 in these two studies, as follows: Table 2 shows a breakdown of the 2000 and 2001 CDS cases by the first four sampling criteria. In year 2000, there NCHRP Project 17-11 were a total of 4,307 cases, 2,929 (68.0%) of which occurred 1997: 138 cases in the 16 rural and suburban PSUs, and 1,518 (51.8%) of 1998: 200 cases which occurred on highways with speed limits above 72 km/h FHWA Rollover Study (45 mph). Of these crashes, 603 (39.7%) were single-vehicle, 1999: 221 cases ran-off-road crashes. In year 2001, there were a total of

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14 Table 2. Breakdown of 2000 and 2001 NASS CDS cases by screening criteria. Total No. 16 Rural and Passenger Vehicle/ Speed Limit Year of Cases Suburban PSUs Single-Vehicle Ran- 45 mph Off-Road Crashes 2000 4307 2929 1518 603 2001 4090 2833 1500 593 Total 8397 5762 3018 1196 4,090 cases, 2,833 (49.3%) of which occurred in the 16 rural herein show both unweighted and weighted frequencies and and suburban PSUs, and 1,500 (52.9%) of which occurred on percentages. highways with speed limits above 72 km/h (45 mph). Of these Table 4 shows the distribution of the eligible cases by the crashes, 593 (39.5%) were single-vehicle, ran-off-road crashes. number of lanes. The vast majority of the cases, 998 (83.44%), Combining data from the two years, there were a total of occurred on highways with two or three lanes. Another 38 1,196 eligible cases that occurred in rural and suburban PSUs (3.18%) occurred on one-lane roadways (i.e., ramps). The on highways with speed limits above 72 km/h (45 mph), and remaining 160 cases (13.38%) occurred on highways with four involving single-vehicle, ran-off-road crashes. or more lanes. The weighted distributions are similar, 3.45% As shown in Table 3, of the 1,083 eligible cases with for one lane, 82.02% for two or three lanes, and 14.53% for known injury severity, 348 (32.13%) resulted in serious to four or more lanes. The similarity between the unweighted fatal injuries [Abbreviated Injury Scale (AIS) 3], 229 (21.14%) and weighted percentages suggests that the severity of crashes resulted in moderate injury (AIS = 2), 385 (35.55%) resulted is similar for different highway types, though slightly higher in minor injury (AIS = 1), and 121 (11.17%) incurred no for highways with two or three lanes. injury (AIS = 0). However, it should be noted that the sam- Table 5 shows the distribution of the eligible cases by vehicle pling scheme for NASS CDS is biased toward the more seri- type. Passenger cars accounted for the majority, 696 (58.19%), ous crashes. When the cases are weighted according to the of the eligible cases, followed by pickup trucks, 247 (20.65%), sampling scheme, the distribution of injury severity is very and sport utility vehicles, 198 (16.56%). The weighted distri- different: 43.64% no injury, 40.15% minor, 8.32% moderate; butions show a higher percentage for passenger cars (64.60%) and 7.90% serious to fatal injury. Thus, all analyses shown and lower percentages for the other vehicle types. This sug- Table 3. Eligible cases by maximum abbreviated injury scale. Unweighted Weighted Abbreviated Injury Scale Number Percentage Number Percentage No Injury (0) 121 11.17 280,985 43.64 Minor Injury (1) 385 35.55 258,559 40.15 Moderate Injury (2) 229 21.14 53,554 8.32 Serious Injury (3) 175 16.16 23,074 3.58 Severe Injury (4) 80 7.39 20,846 3.24 Critical Injury (5) 68 6.28 5,190 0.81 Maximum Injury (6) 25 2.31 1,712 0.27 Total 1,083 100.00 643,920 100.00 * Missing Cases = 113 unweighted (45,970 weighted)

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15 Table 4. Eligible cases by number of lanes. Unweighted Weighted Number of Lanes No. Percentage No. Percentage 1 38 3.18 23,809 3.45 2&3 998 83.44 565,855 82.02 4 160 13.38 100,227 14.53 Total 1,196 100.00 689,891 100.00 gests that a higher proportion of crashes involving passenger tribution of the sampled cases was quite similar to that of cars had lower injury severity. the eligible cases shown previously in Table 3 with a slight The final screening criteria include documentation of vehi- decrease in the percentage of crashes with no injury. The cle trajectory, complete vehicle inspection, and known injury same is true for the weighted distributions. severity data. Of the 1,196 eligible cases, only 437 (36.54%) Table 8 shows the distribution of the eligible cases by num- met all three criteria. Table 6 shows the distribution of these ber of lanes. The dominance of highways with two or three 437 cases by PSU. Note that three of the PSUs (4, 73, and 81) lanes is even more pronounced for the sampled cases with the do not have any complete cases. Two other PSUs (5 and 43) weighted percentages, increasing from the 82.02% for the eli- have only two and four complete cases, respectively. Also, three gible cases (see Table 4) to 90.36% for the sampled cases. The other PSUs (8, 9, and 75) have less than 20 complete cases. proportion of crashes on one-lane roadways also increased Since the targeted sample size was only 400 cases, it was slightly. Correspondingly, the weighted percentages of crashes decided to eliminate seven PSUs (4, 5, 8, 9, 43, 73, and 81) from on highways with four or more lanes dropped from 14.53% the sampling due to overly small number of cases, which ren- to only 5.69%. This drop in the proportion of cases occurring ders the data collection effort inefficient. The number of sam- on highways with four or more lanes is not surprising given ple cases was thus reduced from 437 to 404 cases. Distribution that only three of the sampled PSUs are in suburban areas, of the 404 sampled cases by PSU is also shown in Table 6. where multi-lane facilities are more common. In order to make sure that the sampled cases are reasonably As shown in Table 9, the distributions of the sampled cases representative of the NASS CDS cases, and thus the overall by vehicle type are similar to those of the eligible cases, shown crash population nationwide, a check was conducted on a few previously in Table 5. Passenger cars accounted for about key variables, including highest injury severity, number of 65% for both the eligible and sampled cases. The proportions lanes, and vehicle type. of sport utility vehicles and vans/minivans decreased some- As shown in Table 7, of the 404 sampled cases, 139 (34.41%) what for the sampled cases while the percentage of pickup resulted in serious to fatal injuries (AIS 3), 94 (23.27%) trucks increased. in moderate injury (AIS = 2), 142 (35.15%) in minor injury Overall, the distributions of these key variables for the (AIS = 1), and 29 (7.18%) with no injury (AIS = 0). The dis- sampled cases were reasonably similar to those of the eligible Table 5. Eligible cases by vehicle type. Unweighted Weighted Vehicle Type No. Percentage No. Percentage Passenger Car 696 58.19 445,651 64.60 Sport Utility Vehicle 198 16.56 103,434 14.99 Van/Minivan 55 4.60 26,138 3.79 Pickup Truck 247 20.65 114,668 16.62 Total 1,196 100.00 689,891 100.00

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16 Table 6. Eligible, complete, and sampled cases by primary sampling unit. Eligible Cases Complete Cases Sampled Cases Area Type PSU No. Percentage No. Percentage No. Percentage 2 59 4.93 31 7.09 31 7.67 4 35 2.93 0 0.00 0 0.00 11 145 12.12 59 13.50 59 14.60 13 130 10.87 86 19.68 86 21.29 Rural 43 100 8.36 4 0.92 0 0.00 48 114 9.53 40 9.15 40 9.90 76 109 9.11 41 9.38 41 10.15 78 85 7.11 43 9.84 43 10.64 Subtotal 777 64.97 304 69.57 300 74.26 5 16 1.34 2 0.46 0 0.00 8 28 2.34 15 3.43 0 0.00 9 64 5.35 12 2.75 0 0.00 12 94 7.86 47 10.76 47 11.63 Suburban 45 60 5.02 38 8.70 38 9.41 73 48 4.01 0 0.00 0 0.00 75 57 4.77 19 4.35 19 4.70 81 52 4.35 0 0.00 0 0.00 Subtotal 419 35.03 133 30.43 104 25.74 Total 1,196 100.00 437 100.00 404 100.00 Table 7. Sampled cases by highest injury severity. Unweighted Weighted Abbreviated Injury Scale Number Percentage Number Percentage No Injury (0) 29 7.18 88,968 41.15 Minor Injury (1) 142 35.15 87,723 40.58 Moderate Injury (2) 94 23.27 16,063 7.43 Serious Injury (3) 69 17.08 11,387 5.27 Severe Injury (4) 30 7.43 9,966 3.68 Critical Injury (5) 32 7.92 3,056 1.41 Maximum Injury (6) 8 1.98 1,024 0.47 Total 404 100.00 218,187 100.00

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17 Table 8. Sampled cases by number of lanes. Unweighted Weighted Number of Lanes No. Percentage No. Percentage 1 14 3.47 8,531 3.95 2&3 356 88.12 195,360 90.36 4 34 8.42 12,296 5.69 Total 404 100.00 216,187 100.00 Table 9. Sampled cases by vehicle type. Unweighted Weighted Vehicle Type No. Percentage No. Percentage Passenger Car 212 52.48 140,692 65.08 Sport Utility Vehicle 64 15.84 67,169 11.25 Van/Minivan 23 5.69 3,502 1.62 Pickup Truck 105 25.99 45,511 21.05 Total 404 100.00 256,874 100.00 cases, given that the sampled cases are not truly a represen- the same characteristics as the original that was damaged. tative sample of the eligible cases. Rather, it is a sample of The investigators would compare the site and struck-object convenience to make sure that the sampled cases have com- characteristics at the time of supplemental data collection to plete documentation of the vehicle trajectory, vehicle inspec- those at the time of the crash, using photographs from the tion, and information on injury severity. case files to make sure that these assumptions were accurate. Cases in which the site and/or struck-object/feature charac- teristics had been changed significantly would be deleted 3.4.2 Supplemental Field Data Collection from the sample. Data elements requiring supplemental field collection are shown in Table 10. The protocol for the supplemental field Table 10. Data elements requiring supplemental data collection effort was developed, including the field forms field data collection. and the accompanying coding and instruction manuals. The Highway type field forms were used by the PSU investigators during the - Functional class actual data collection while the manual provided definitions Highway characteristics - Number of lanes of the data elements, field data collection procedures, and - Lane width coding instructions. - Horizontal curvature - Point of departure and maximum Note that given the retrospective nature of the data col- - Vertical grade - Point of departure and maximum Roadside characteristics lection approach, there was an implicit assumption that the - Shoulder type and width data elements would not change significantly with time. This - Roadside slopes widths and rates of slopes - Median type, width, and slope is a reasonable assumption for most of the supplemental data Traffic characteristics elements, such as roadway, traffic, and roadside character- - ADT istics. As for the struck-object characteristics, there was an - Percent truck Struck-object characteristics additional assumption that any damaged objects would be - Object type replaced in kind, i.e., the replaced object or feature would have - Impact performance

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18 There were two sets of field data collection forms: Due to the large number of potential roadside objects and features, the variables are necessarily very general without spe- Supplemental Highway Data Collection Form cific details. Instead, investigators were asked to provide anno- Object Struck Data Collection Form tations or descriptions and photographs of the struck object. Since the data collection protocol was similar to that of A complete copy of the field forms and the accompanying NCHRP Project 17-11 and the FHWA Rollover Study, the Zone Center staff and PSU investigators were already famil- coding and instruction manuals are included as Appendix C iar with the data collection protocol. Thus, the data collection and will not be repeated here. experienced little problem or difficulty. The actual field data The Supplemental Highway Data Collection Form was collection was conducted by PSU investigators under the completed for each sampled case. The form contains 20 data direction of the Zone Centers: Veridian Corporation for Zone elements under four general headings: Center 1 and KLD Associates for Zone Center 2. After a qual- ity check was conducted by Zone Center personnel for accu- Case Identification: racy, the completed data were forwarded to KLD Associates, 1. Year which was a subcontractor for this study. The supplemental 2. Primary Sampling Unit field data were then combined with the regular NASS data in 3. Case Number-Stratum the manual review of the cases. General Highway Data: 4. Land Use 3.4.3 Manual Review of Sampled Cases 5. Class Trafficway 6. Access Control Additional data elements not available from the computer- 7. Average Lane Width ized data file or supplemental field data collection were gleaned 8. Roadway Alignment at Point of Departure from manual review of hard copies (in electronic form) and 9. Radius of Curve reconstruction of the sampled cases. The data elements coded 10. Roadway Profile at Point of Departure from this manual review are shown in Table 11. Part of the 11. Vertical Grade review included verification of data elements that were already Roadside Data: coded under existing NASS CDS or supplemental data collec- 12. Curb Presence tion, such as: 13. Curb Height 14. Shoulder Type Highway data--highway type, number of lanes, divided/ 15. Shoulder Width undivided, presence/absence of shoulder, and impact Slope Data: sequence 16. Roadside Cross Section at Point of Departure Roadside feature impacted--guardrail, tree, ditch, etc. 17. Number of Slopes Driver input--steering and/or braking 18. Lateral Offset to Beginning of Slope 19. Rate of Slope Table 11. Data elements requiring 20. Width of Slope reconstruction. An Object Struck Data Collection Form was completed for Encroachment conditions at point of departure - Speed each object involved in the crash. The form contains seven - Angle data elements under four general headings: Pre-impact vehicle trajectory - Vehicle path - Maximum lateral extent of encroachment Case Identification: - Total longitudinal distance 1. Year General impact data 2. Primary Sampling Unit - Post-impact trajectory Impact conditions first harmful event 3. Case Number-Stratum - Impact speed General Struck Object Data: - Impact angle - Vehicle orientation 4. Impact Number Impact conditions most harmful event 5. Object Type - Impact speed 6. Material - Impact angle - Vehicle orientation Dimensions of Struck Object--annotation Driver action Photography: - Steering vehicle path 7. Photographs Taken? - Braking

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19 The main function of the manual review was to conduct Case Identification: detailed reconstruction of the crashes to estimate parameters 1. Year such as: 2. Primary Sampling Unit 3. Case Number-Stratum Vehicle encroachment conditions--angle and orientation Current Event Identification: Vehicle trajectory after encroachment--vehicle path 4. Current Event Number Impact conditions--angle and orientation 5. Current Event Location Impact performance of struck roadside safety feature Vehicle Trajectory Data: 6. Driver Action With the exception of the reconstruction of impact speed, 7. Longitudinal Distance of Travel which was performed by the project staff, the manual review 8. Number of Trajectory Profile Points and reconstruction were conducted by Zone Center personnel 9. Lateral Offset of Trajectory Profile Points from KLD Associates. Two reconstruction coding forms were 10. Maximum Lateral Offset designed specifically for coding of these manual review and Impact Conditions--Current Event: reconstruction data elements: one for the first event or impact, 11. Location of Impact and one for subsequent events or impacts. Copies of the recon- 12. NASS CDS Data struction coding forms and the accompanying coding and 13. Impact Angle instruction manual are shown in Appendix C and will not be 14. Vehicle Heading Angle at Impact repeated here. Zone Center personnel were trained on the Separation Conditions--Current Event: manual review procedure and the coding of the data elements. 15. Location of Separation Under the reconstruction coding form for the first event, 16. Separation Angle there are 20 data elements under six general categories: 17. Vehicle Heading Angle at Separation Subsequent Event/Final Rest Case Identification: 18. Subsequent Event 1. Year 19. Location of Final Rest 2. Primary Sampling Unit 20. Vehicle Heading Angle at Final Rest 3. Case Number-Stratum Encroachment Data: The completed case, including data from the regular NASS 4. Departure Angle CDS data collection, the supplemental field data collection, 5. Vehicle Heading Angle and the manual review and reconstruction, was then sent to Vehicle Trajectory Data: the project staff for final quality control and reconstruction 6. Driver Action 7. Longitudinal Distance of Travel to estimate the impact speeds. 8. Number of Trajectory Profile Points 9. Lateral Offset of Trajectory Profile Points 3.4.4 Reconstruction of Impact Speed 10. Maximum Lateral Offset Impact Conditions--First Event: As mentioned above, the completed cases from KLD Asso- 11. Location of Impact ciates went through one final quality check by the project staff 12. NASS CDS Data to assure completeness and accuracy. The cases were then 13. Impact Angle reconstructed to estimate the impact speeds. Reconstruction 14. Vehicle Heading Angle at Impact of single-vehicle, ran-off-road crashes is greatly complicated Separation Conditions--First Event: by the wide variety of roadside objects. For example, Table 12 15. Location of Separation shows a list of first harmful events caused by objects struck 16. Separation Angle from the 1999 Fatality Analysis Reporting System (FARS) data. 17. Vehicle Heading Angle at Separation It is obvious from the list that the object struck varies widely, Subsequent Event/Final Rest from impacts with roadside hazards (e.g., trees and utility 18. Subsequent Event poles) to roadside safety devices (e.g., guardrails and crash 19. Location of Final Rest cushions) to terrain features (e.g., embankments and ditches). 20. Vehicle Heading Angle at Final Rest In order to accurately identify impact conditions associated with these accidents, it is critical to implement crash recon- Under the reconstruction coding form for subsequent struction procedures appropriate for each of the hazards listed. events, there are also 20 data elements under six general In general, reconstructions of single-vehicle, ran-off-road categories: crashes primarily involve calculating energy losses and gains

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20 Table 12. Object struck as first harmful crash investigation. For a prospective study in which data are event from 1999 FARS data. collected on crashes as they occur, the study can be designed to properly document the required data elements. However, Object Frequency Percentage Tree 2,997 26.09 in the case of a retrospective study like the current project, the Embankment 1,213 10.56 data availability and quality is limited by what was actually Guardrail 1,078 9.39 collected and could be lacking for some of the data elements. Utility Pole 1,018 8.86 Ditch 887 7.72 The availability and quality of the data elements can be divided Curb 681 5.93 into the following general categories: Culvert 592 5.15 Fence 490 4.27 Sign Support 368 3.20 Data elements that are well documented and coded in the Other Post/Support 308 2.68 NASS CDS cases, such as impact sequence, vehicle crush Concrete Barrier 275 2.39 Bridge Rail 158 1.38 profile, principal direction of force, and number of quar- Bridge Pier/Abutment 155 1.35 ter rolls. The quality of these data elements is typically high Wall 119 1.04 and no further work is needed. Luminaire Support 103 0.90 Boulder 79 0.69 Data elements that are documented and coded in the CDS Building 79 0.69 cases, but the quality of the data may be somewhat question- Shrubbery 56 0.49 able, e.g., driver action. These data elements would need Bridge Parapet 36 0.31 Equipment 26 0.23 to be checked against other available evidence, such as the Fire Hydrant 25 0.22 scaled diagram, annotated remarks, and photographic doc- Other Longitudinal Barrier 23 0.20 Snow Bank 23 0.20 umentation, to verify the accuracy of the coded data. Traffic Signal Support 22 0.19 Data elements are documented, but not coded, and the Unknown 22 0.19 quality of the data may vary greatly from case to case, e.g., Impact Attenuator 11 0.10 Other Fixed Object 506 4.41 vehicle trajectory, tire marks, impact angle, and roll distance. Other Object (not fixed) 135 1.18 These data elements would have to be gleaned from the Total 11,485 100.00 scaled diagram, annotated remarks, and photographic documentation. after leaving the roadway. Energy changes during ran-off-road Data elements that are not documented. The two areas crashes can generally be attributed to one or more of these where existing NASS CDS cases may not contain sufficient seven categories: information are elevation changes along the vehicle path and the characteristics and sustained damage of the impacted Vehicle crush roadside feature(s). These data elements would have to be Damage to roadside feature gleaned from the photographic documentation to the extent Tire braking possible or the information collected in the supplemental Tire side slip data collection effort. It should be noted, however, that the Vehicle rollover implicit assumption was that the data from the supple- Change in vehicle elevation mental data collection were the same as at the time of the Friction between vehicle and roadside feature crash, which may or may not be true. Key data elements needed to accurately estimate these Although deformation of roadside features is an important energy changes include, but are not limited to: source of energy dissipation for some crashes, many ran-off- road crashes would not involve deformable fixed objects. For Impact sequence the limited number of cases where this energy dissipation Vehicle crush profile factor is important, it may be necessary to make estimates Impact angle/principal direction of force during crash of deformation from case photographs and supplemental site Vehicle trajectory, including tire mark measurement and investigations. Change in elevation during a crash is generally description not an important source of energy change unless the vehicle Driver action, i.e., steering/braking has traversed a very deep roadside embankment. Elevation Roll distance and number of quarter roll changes along the vehicle path can be estimated by recording Changes in elevation along the vehicle path the dimensions of the various side slopes. Extent of damage to roadside feature While the general principle of identifying the energy loss parameters during the collision and summing the total to It should be noted that these data elements pertain to per- determine the change in velocity from the point of impact to ishable evidence that have to be collected at the time of the the final resting position is rather straightforward, the actual

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21 reconstruction is greatly complicated by the wide variety of 3.4.4.2 Rigid Barrier roadside features. There is not a single procedure that can be Another procedure was developed for reconstructing rigid used to reconstruct all ran-off-road crashes. Instead, differ- ent reconstruction procedures are needed to accommodate barrier impacts during a study to assess rollovers on concrete the wide variety of roadside features and types of impact. barriers (15). This study found that vehicle/barrier friction was a major source of energy dissipation during a crash. Again, There are a number of existing procedures that have been energy loss is grouped into three major categories: developed for reconstructing special types of ran-off-road, fixed-object crashes, including: Vehicle crush. The CRASH3 (27) reconstruction program was utilized to estimate vehicle crush energy based on vehi- Pole support structure (25) cle crush measurements. Rigid barrier (15) Friction. Energy loss associated with vehicle/barrier friction Semi-rigid and flexible barrier (14) was estimated as a function of the length of barrier contact. Post-impact vehicle trajectory. The CRASH3 reconstruction These roadside features accounted for about 55% of all program was also utilized, to the extent possible, for estimat- ran-off-road, fixed-object fatal crashes, as shown in Table 12. ing the energy or speed loss associated with the post-impact For the remaining 45% of crashes, the vast majority can be vehicle trajectory. Otherwise, manual calculations were used grouped into one of the following five categories: for the reconstruction. Roadside terrain The vehicle crush energy was then matched to the energy Rigid hazards associated with the lateral velocity of the impacting vehicle. Drainage structures If both energy estimates are comparable, the procedure was Buildings and walls believed to be reasonably accurate. If not, the vehicle crush Fences and shrubbery energy would be adjusted appropriately and a new estimate of the impact speed was generated. This iterative procedure has New reconstruction procedures were developed for these been found to give reasonably good estimates of impact speed five categories of roadside features. Brief discussions on recon- when used to evaluate findings from full-scale crash tests. struction procedures for the various roadside features are pre- sented in the following sections. 3.4.4.3 Semi-Rigid and Flexible Barrier 3.4.4.1 Pole Support Structures A reconstruction procedure for semi-rigid and flexible bar- riers was developed in a study of ran-off-road crashes (14). This A computerized reconstruction procedure was developed procedure utilized similar techniques for estimating vehicle for ran-off-road crashes involving pole support structure, crush and trajectory energy losses. Energy loss associated with including breakaway and nonbreakaway utility poles, lumi- the deformation of semi-rigid barriers was estimated from a naire supports, and sign supports (25). Energy loss is grouped series of computer simulations that correlated impact severity into three major categories: to maximum barrier deflection. The impact severity is calcu- lated using the following equation: Vehicle crush. The CRASH3 (27) reconstruction program M ( V sin ) 2 was utilized to estimate vehicle crush energy based on vehi- IS = 1 2 cle crush measurements. Fracture of pole. Energy associated with breaking or frac- where: ture of the pole was estimated based on empirical test data. IS = Impact Severity Post-impact vehicle trajectory. The CRASH3 reconstruction M = Vehicle mass program was also utilized, to the extent possible, for estimat- V = Vehicle velocity ing the energy or speed loss associated with the post-impact = Impact angle vehicle trajectory. Otherwise, manual calculations were per- formed for the reconstruction. The IS value has been shown to be a good indicator of the degree of loading and maximum deflection of a barrier during This procedure was utilized whenever possible for recon- an impact. Unfortunately, the maximum barrier deflection struction of crashes involving pole support structures, e.g., after a crash is seldom measured during a NASS CDS investi- utility poles; luminaire, sign, and traffic signal supports; other gation. Thus, the permanent barrier deflection was estimated post/supports; and fire hydrants. from available photographic documentation. The measured or

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22 estimated permanent barrier deflection was then related to very low (30). These simulation and test findings were used the maximum dynamic deflection, which in turn was used to to obtain gross estimates of the total speed loss associated with estimate the IS value from the impact. curb impacts. Thereafter, other reconstruction techniques The impact speed could be estimated from IS value along could be used to estimate the total energy lost during the post- with the impact angle or by traditional energy loss calcula- impact trajectory of the vehicle. tions, including vehicle crush, barrier deformation, and post- Culverts offer significantly greater challenges. Cross-drainage impact trajectory. An iterative procedure similar to that used culverts with high headwalls can act as a rigid hazard and could to reconstruct rigid barrier crashes was developed for this be reconstructed based largely on vehicle crush as described application. in the previous section. Crash tests of cross-drainage culverts The procedure from Erinle et al. (14) was refined and that have been cut to match the slope and/or grated to reduce updated for use in the current study. The revised procedure the severity of crashes have shown that these hazards provide also included techniques for reconstructing impacts with very little energy dissipation (31). This low level of energy guardrail terminals and crash cushions. dissipation would allow crashes involving these hazards to be reconstructed based on the post-impact trajectory alone. Unfortunately, reconstruction of crashes involving parallel 3.4.4.4 Roadside Terrain drainage structures were somewhat more difficult. Crash test- Impacts involving embankments and ditches could be ing has indicated that vehicles striking culverts under drive- reconstructed if detailed information is available on the ter- ways or intersecting streets are frequently subjected to violent rain and any associated gouges in the terrain along with the rollovers. Where possible, procedures for estimating energy vehicle crush. Efforts to model vehicles traversing hazardous losses during vehicle rollover formed the basis for reconstruct- roadside terrains have established reasonable measures of the ing rollover crashes associated with culvert accidents. Con- forces and energy associated with vehicle undercarriage com- ventional trajectory analyses were used whenever the vehicles ponents gouging into the terrain (28). Furthermore, for crashes remained upright after striking the culvert. involving vehicles plowing into steep embankments virtually head on, vehicle crush measurements would produce a good 3.4.4.7 Buildings and Walls estimate of the total force generated between the embankment and the vehicle. Finally, energy losses associated with rollover When buildings and walls are struck in a more or less head- accidents have been investigated through computer simulation on configuration, conventional reconstruction techniques are for a variety of passenger vehicles (29). Hence, impact speeds applicable only if the building or wall is relatively rigid. No for crashes involving roadside terrain could be estimated by procedure has been developed that can effectively estimate combining conventional trajectory analyses, such as that used the energy required to break through a building or wall. How- in the CRASH3 reconstruction program, and incorporating ever, if the structures remain intact, the building or wall was procedures for estimating the effects of terrain gouging and treated as either a rigid hazard or a rigid longitudinal barrier, vehicle rollover. depending on the nature of the impact. 3.4.4.5 Rigid Hazards 3.4.4.8 Fences and Shrubbery For rigid obstacles, such as bridge piers and parapets, boul- Most fences, including chain link and wooden privacy ders, and heavy construction equipment, there is little energy fences, provide relatively little energy dissipation when struck dissipated by the rigid hazards themselves. Thus, reconstruc- by an automobile traveling at a high rate of speed. Similarly, tions could be based almost entirely on vehicle crush energy small shrubs do not offer significant resistance to an impact- and post-impact trajectories. These procedures would be sim- ing vehicle. Therefore, crashes involving these hazards were ilar to those used by Mak and Labra (25) to reconstruct pole reconstructed using conventional procedures unless the fence crashes in which the poles remained intact. had an unusual construction or the shrubs were large enough to pose a major obstacle to a vehicle. In summary, by utilizing and refining available reconstruc- 3.4.4.6 Drainage Structures tion techniques, it was possible to produce accurate estimates Drainage structures, such as culverts and curbs, are often of the impact conditions for most ran-off-road crashes. The traversed during a ran-off-road accident without a significant reconstruction procedures discussed above should account speed reduction. Full-scale crash testing and computer sim- for almost 90% of the serious injury and fatal ran-off-road ulation have shown that speed losses during curb impacts are crashes.