Costs of Large Truck- and Bus- Involved Crashes Pacific Institute for Research and Evaluation 8201 Corporate Dr., Suite 220 Landover, Maryland 20785 Telephone: 301- 731- 9891 Fax: 301- 731- 6030 Final Report for- Federal Motor Carrier Safety Administration Federal Highway Administration 400 Seventh Street, SW Washington, DC (Project Number: DTFH61- 99- P00328) by Eduard Zaloshnja, Ph. D.; Ted Miller, Ph. D.; and Rebecca Spicer, M. P. H. Pacific Institute This study is the first major update of truck/bus crash costs in a decade Table of Contents Technical Report Documentation Page (Form DOT F 1700. 7) iii Executive Summary ........................................................ 1 Introduction.................................................................. 2 Methods....................................................................... 3 Results...................................................................... 13 References................................................................... 23 Appendix..................................................................... 26 Executive Summary This study provides comprehensive, economically sophisticated estimates of the costs of highway crashes involving large trucks and buses by severity. Based on the latest data available, the estimated cost of police- reported crashes involving trucks with a gross weight rating of more than 10, 000 pounds averaged $75,637 (in 1999 dollars). The average cost of police- reported crashes involving transit or inter- city buses was $54, 455 per crash. These costs represents the present value, computed at a 4% discount rate, of all costs over the victims' expected life span that result from a crash. They include medically related costs, emergency services costs, property damage costs, lost productivity, and the monetized value of the pain, suffering, and quality of life that the family loses because of a death or injury. Other notable findings include: The cost of crashes in which truck- tractors with two or three trailers were involved was the highest among all crashes - $117, 309 per crash. Among crashes with all configuration information available, bus- involved crashes had the lowest cost - $54,455 per crash. The costs per crash with injuries averaged $217,005 for large truck crashes and $131,214 for bus crashes. As expected, fatal crashes cost more than any other crash. The average cost of fatal crashes involving truck- tractors with two or three trailers was the highest among all fatal crashes - $3.54 million per crash. The crash costs per 1, 000 truck miles are $259 for single unit trucks, $138 for single combination trucks, and $134 for multiple combinations. The costs of large truck crashes in 1997 exceeded $24 billion. That total included $8.7 billion in productivity losses, $2. 5 billion in resource costs, and quality of life losses valued at $13. 1 billion. Bus crashes were a much smaller factor than truck crashes, costing less than $1 billion in 1997. The cost estimates exclude mental health care costs for crash victims, roadside furniture repair costs, cargo delays, earnings lost by family and friends caring for the injured, and the value of schoolwork lost. Introduction Trucks and buses with a gross weight rating of over 10,000 pounds constitute the majority of interstate commercial vehicles. They are the primary focus of Federal Motor Carrier Safety Regulations. Crashes involving such vehicles impose a variety of costs on the vehicle and its driver, other drivers either directly or indirectly involved in the crash, and society as a whole. In addition to costs such as property damage, emergency services, and travel delays, injuries and fatalities impose significant costs. This report provides unit costs of large (medium and heavy) vehicle crashes, stated in 1999 dollars. Safety analysts use crash cost data for a variety of purposes, from analyzing the effectiveness of a particular roadway enhancement to measuring the impact of seatbelt use. Crash costs are used to compare the relative efficacy of various crash countermeasures, which are expected to have a differential impact on crashes of different severity. These figures are also used to calculate and compare the cost- effectiveness of proposed safety regulations. Efficient allocation of research, enforcement, and analysis resources requires reliable data on crash costs. Miller, Viner et al. (1991) made a first attempt to estimate truck and bus crash costs. They first computed costs by threat- to- life severity measured by Maximum Abbreviated Injury Score (MAIS; AAAM, 1985). The AIS scheme is a detailed medical classification developed by physicians as a basis for rating the survival threat injuries pose. It assigns a numeric rating ranging from 0 (uninjured) to 6 (maximum, generally unsurvivable). National Highway Traffic Safety Administration (NHTSA) data sets that are AIS coded add codes for "injured, severity unknown" and "unknown if injured". MAIS is simply the maximum AIS among the multiple injuries a victim suffers. The purpose of the AIS scale is to differentiate injuries by survival threat, not the cost, functional losses, or course of recovery they involve. For example, loss of teeth is an AIS- 1 injury that can involve substantial costs and lifetime pain and suffering. Conversely, timely surgery often allows complete and rapid recovery from ruptured spleens and other AIS 3- 5 internal injuries. Nevertheless, average costs per case within a body region almost always rise with MAIS (Miller 1993). By multiplying average costs per highway crash victim by MAIS times the MAIS distribution of victims in crashes sorted by the heaviest vehicle involved, Miller, Viner et al. (1991) estimated costs by vehicle type. Those estimates implicitly assumed that the distribution of injuries by body region within an AIS severity level did not vary with vehicle type. Only property damage and crash- related travel delay costs were tailored to truck and bus crashes. Miller, Levy et al. (1998) and Miller, Spicer et al. (1999) improved on Miller, Viner et al. (1991) by computing medium/ heavy vehicle crash costs by vehicle type from 1982- 1992 data on victim MAIS and body region in medium/ heavy vehicle crashes. They also tailored the costs by victim age and sex. The present report parallels their methods. It updates their estimates and substantially increases the number of cases used to estimate the injury distribution for occupants of light passenger vehicles involved in medium/ heavy vehicle crashes. With the larger sample, it is able to more finely differentiate costs among heavy vehicle types. Notably, the present study is the first to differentiate costs of single versus multiple trailer crashes. Within the constraints of available data, it provides economically sophisticated, reliable estimates of the average costs of medium/ heavy vehicle crashes with different levels of severity. Methods Estimating crash costs requires estimates of the number of people and vehicles involved in a crash, the severity of each person's injuries, and the costs of those injuries and associated vehicle damage and travel delay. The following section describes the methodology used to estimate the incidence and severity of large truck and bus crashes. The succeeding section explains how the costs of crashes were estimated. Incidence and Severity Estimation. To estimate injury incidence and severity, we followed procedures developed by Miller and Blincoe (1994) and Miller, Galbraith et al. (1995) and also applied in Blincoe (1996), Miller, Levy et al. (1998), Miller, Lestina, and Spicer (1998), and Miller, Spicer et al. (1999). Our estimates of the average number of people and vehicles involved in a medium/ heavy vehicle crash by vehicle type, restraint use, crash severity, and police- reported injury severity come from NHTSA's Fatal Analysis Reporting System (FARS) and General Estimates System (GES). Crash databases do not accurately describe the severity of large truck and bus crashes. Accordingly, we made several adjustments to more accurately reflect the severity of crashes. These adjustments are described below. FARS is a census of U. S. fatal crashes but it does not describe injuries to survivors in these crashes. GES provides a sample of U. S. crashes by police reported severity for all crash types. GES records injury severity by crash victim on the KABCO scale (National Safety Council, 1990) from police crash reports. Police reports in almost every state use KABCO to classify crash victims as K- killed, A- disabling injury, B- evident injury, C- possible injury, or O- no apparent injury. KABCO ratings are coarse and inconsistently coded between states and over time. The codes are selected by police officers without medical training, typically without benefit of a hands- on examination. Some victims are transported from the scene before the police officer who completes the crash report even arrives. Miller, Viner et al. (1991) and Blincoe and Faigin (1992) documented the great diversity in KABCO coding across cases. O'Day (1993) more carefully quantified the great variability in use of the A- injury code between states. Viner and Conley (1994) explained the contribution to this variability of differing state definitions of A- injury. Miller, Whiting et al. (1987) found police- reported injury counts by KABCO severity systematically varied between states because of differing state crash reporting thresholds (the rules governing which crashes should be reported to the police). Miller and Blincoe (1994) found that state reporting thresholds often changed over time. Thus, police- reporting does not accurately describe injuries medically. To minimize the effects of variability in severity definitions between states, reporting thresholds, and police perception of injury severity, we turned to NHTSA data sets that included both police- reported KABCO and medical descriptions of injury in the Occupant Injury Coding system (OIC; AAAM 1990, AAAM 1985). OIC codes include AIS score and body region, plus more detailed type injury descriptors that changed from the 1985 to the 1990 edition. We used both 1988- 91 Crashworthiness Data System (CDS; NHTSA 1995) and 1982- 86 National Accident Sampling System (NASS; NHTSA 1987) data. CDS describes injuries to passenger vehicle occupants involved in tow-away crashes. The 1982- 86 NASS data provide the most recent medical description available of injuries to medium/ heavy truck and bus occupants, non- occupants, and other non- CDS crash victims. The NASS data were coded with the 1980 version of AIS, which differs slightly from the 1985 version; but NHTSA made most AIS- 85 changes well before their formal adoption. CDS data were coded in AIS- 85 through 1992, then in AIS- 90. We did not use CDS data after 1991 because AIS scores in AIS- 90 differ greatly from scores in AIS- 85, especially for brain and severe lower limb injury. Garthe et al. (1996) find that AIS scores shifted for roughly 25% of all OICs between AIS- 85 and AIS- 90. Because cost estimates by AIS- 90 severity do not exist, we did not use CDS data from 1993 onward. We pooled all other available years of data in order to get sufficient cases for analysis by truck type. We used 1988- 1997 GES data to weight the CDS and NASS data so they represent the annual estimated GES injury victim counts in medium/ heavy vehicle crashes by CDS and NASS sample strata. In applying these weights we controlled for police- reported injury severity, restraint use, and vehicle occupied (or non- occupant). Weighting the NASS data to GES restraint use levels updates the NASS injury profile to a profile reflecting contemporary belt use levels. Again, sample size considerations drove the decision to pool all available data. At the completion of the weighting process (Figure 1), we had a hybrid CDS/ NASS file with weights that summed to the estimated annual GES incidence by police- reported injury severity and other relevant factors. Trucks and buses with a gross weight rating of over 10, 000 pounds were grouped into the following categories: 1. Straight truck, no trailer; 2. Straight truck with trailer; 3. Straight truck, unknown if with trailer 4. Truck tractor with no trailer (bobtail); 5. Truck tractor with one trailer; 6. Truck tractor with two or three trailers; 7. Truck tractor with unknown number of trailers; 8. Medium/ heavy truck, unknown if with trailer; 9. All large trucks; and 10. Transit/ inter- city bus Figure 1. The merger of NASS, CDS, and GES files. In order to create reasonable sample sizes, two assumptions were made in the categorization of trucks/ buses. Trucks that were reported in the GES and FARS data as medium/ heavy trucks and had no trailing units were assumed to be straight trucks with no trailer. Trucks that were reported as unknown medium/ heavy trucks and had more than one trailing unit were assumed to be truck tractors with two or three trailers. In addition to the grouping based on the above assumptions, straight trucks with trailer and medium/ heavy trucks with one trailer were grouped together because of a discrepancy between FARS and GES estimates. A count of fatal truck crashes based on FARS revealed that medium/ heavy trucks with one trailer were involved in 131 fatal crashes between 1988 and 1997. The respective GES estimate was 742. On the other hand, FARS data suggested that straight trucks with one trailer were involved in 869 fatal crashes during the same period, as opposed to 176 estimated from GES data. Since FARS data are much more reliable than GES data - FARS represents a census of fatal crashes as opposed to GES, which is simply a modest sample - it was assumed that a good number of straight trucks with trailers were miscoded in the GES files as unknown medium/ heavy truck with one trailer. Therefore, in absence of a reliable way of separating out the misrepresented cases, unknown medium/ heavy trucks with one trailer were included in the category "straight truck with trailer." Pool 1982- 1986 NASS data on heavy vehicle incidents for non- CDS strata/ vehicles Run 1988- 1997 GES weighted counts of annual non- CDS heavy vehicle incidents By vehicle type, restraint use, etc., multiply the NASS weight on each case times the estimated multi- year incidence of cases of this type from GES divided by estimated multi- year incidence of cases of this type from NASS Pool 1982- 1986 NASS data on heavy vehicle incidents for CDS strata Run 1988- 1997 GES weighted counts of annual CDS heavy vehicle incidents By vehicle type, restraint use, etc. multiply the CDS weight on each case times the estimated multi- year incidence of cases of this type from GES divided by estimated multi- year incidence of cases of this type from NASS Pool the re-weighted data into an analysis file Cost Estimation. The second step required to estimate average crash costs is to generate estimates of crash costs by severity. This section describes the process used to develop these estimates. In order to estimate the average costs per crash by medium/ heavy vehicle type and crash severity, costs per injury by MAIS and body region were adapted from the costs in Miller (1997) and Miller, Spicer et al. (1999). These costs were merged onto the GES weighted NASS/ CDS file. The costs represent the present value, computed at a 4% discount rate, of all costs over the victim's expected life span that result from a crash. We included the following major categories of costs: * Medically related costs * Emergency services * Property damage * Lost productivity Monetized Quality- Adjusted Life Years (QALYs) The present study updated the medical cost estimates from Miller (1997) and adjusted its other cost estimates to comply with official US Department of Transportation injury cost guidance and methods (McCormick and Shane, 1993; Krusei and McFadden, 1996). Notably, to obtain the present value of costs in future years, we re- estimated medical costs of severe brain and spinal cord injuries, productivity losses, and quality of life losses with a 4% discount rate rather than the 2.5% rate used in those studies. A higher (lower) discount rate would lower (raise) future costs, especially those that occur farther into the future. Medically Related Costs include hospital, physician, rehabilitation, prescription, and related payments. Also included are coroner and burial costs for fatalities, and claims processing costs of medically- related loss compensation through insurance and the courts (omitting time spent on the loss recovery process). To update medical costs, we computed total medical costs of crashes in 1996, then used this aggregate information to adjust prior detailed cost estimates by MAIS and body region injured. The new estimate of total medical spending on crash victims used methods and data developed in a study of childhood injury costs (Miller, Romano and Spicer 2000) and in building the US Consumer Product Safety Commission's Injury Cost Model (ICM) (Lawrence et al. 1999). These methods are described briefly below, and more thoroughly in the ICM documentation (Miller, Lawrence et al. 1998). First, we estimated the incidence of injury in motor vehicle crashes on public roads. The estimated number of medically treated victim by diagnosis, age group, and sex for patients not admitted to hospital came from 1996 National Health Interview Survey (NHIS) which explicitly identifies crash victims. For hospital- admitted victims, following Miller, Romano and Spicer, we created a version of the 1996 National Hospital Discharge Survey (NHDS) with injury causes inferred for the 37% of injury victims with no cause reported in the data set. NHDS provides seven fields for coding injury diagnoses and/ or causes. The cause distribution of known cases with five or fewer diagnoses by primary diagnosis, age group, sex, and number of diagnoses (1- 2, 3- 5) was inferred probabilistically, based on the causes that were reported. For cases with six or seven diagnoses, we inferred the cause distribution using data on discharges with at least six diagnoses from six states with mandatory cause coding and either a separate cause- code field or at least ten diagnosis/ cause fields- CA, MD, MO, NY, SC, and VT. Next, we computed medical costs for each crash victim. Although the methods differed for deaths, injury survivors admitted to the hospital, and injury survivors treated elsewhere, in each case, we extracted costs of initial treatment from nationally representative or multi- state data sets. By diagnosis, we then added emergency medical, medical follow- up, rehabilitation, and long- term costs computed from national data on ancillary costs and the percentage of medical costs associated with initial treatment. Due to data unavailability, the emergency medical, follow- up, rehabilitation and long- term costs were less current than the costs for initial treatment. More specifically, for non- hospitalized victims, medical costs were estimated from: Medical care costs per visit by diagnosis from 1992- 1994 Civilian Health and Medical Program of the Uniformed Services (CHAMPUS) data, visits per case during an average of six months post- injury and emergency transport, prescription and ancillary payments per case by diagnosis group from 1987 National Medical Expenditure Survey (NMES) data, and the percentage of medical costs for non- admitted patients that are incurred more than six months after injury by diagnosis from 1979- 1988 Detailed Claims Information (DCI) data of the National Council on Compensation Insurance (Miller, Viner et al. (1991) used the same DCI data, which are unique.) For admitted patients, medical costs were estimated from Actual hospital days per patient from the NHDS file Costs per day of hospital stay by diagnosis, age group, and sex estimated from 1994 NY and 1994- 1995 MD hospital discharge data, price- adjusted to national estimates, (These two states are the only ones that regulated and tracked the detailed relationships between charges, payments, and actual costs of hospital care in recent years, a practice New York discontinued after 1994. Because health care payers negotiate widely varying, sometimes large discounts from providers, the more widely available data on hospital charges bear little relationship to actual hospital costs.) The ratio of professional fees for inpatient care to hospital payments from 1992- 1994 CHAMPUS data, The average number of hospital admissions per patient by primary injury diagnosis from 1994 MO hospital discharge data (which we used because we were able to obtain a file with linkable patient identifiers), Pre- hospital, prescription and ancillary payments per case, as well as short- term post- discharge costs, from 1987 NMES data, and the percentage of medical costs for admitted patients that are incurred more than six months after injury by diagnosis from 1979- 1988 DCI data. Medical costs for crash fatalities were computed from US Vital Statistics data on place of treatment. All fatalities were assigned the difference in present value of burial costs in 1996 versus at the end of the victim's expected life span (from Miller, Pindus et al., note x), as well as coroner or medical examiner costs from NHTSA (1983). Except for deaths at the scene, we added costs of emergency transport from 1987 NMES data. For deaths on arrival or in the emergency department, we added average charges for fatalities in the emergency department by external cause grouping from 1997 South Carolina emergency department discharge data, adjusted to US prices. Deaths in hospital were costed using the same methods as other hospital admissions but with no post- discharge costs. We assumed deaths in nursing home were preceded by hospital admissions of average cost and involved a 30- day skilled nursing facility stay at double the cost of an intermediate care facility (from Bureau of the Census 1998). Unfortunately, within the budget available, the aggregate cost estimate for nonfatal cases could not be broken down by MAIS and body region. Therefore, we adjusted published prior medical cost estimates for 1996 highway crashes (Miller, Lestina, and Spicer, 1998) to account for the difference between our total nonfatal medical cost estimate and the published one, essentially retaining the prior cost patterns by severity. The adjusting factor was 0. 924. The difference between our estimate and the previous estimate can be explained by the fact that Miller, Lestina and Spicer (1998) inflated medical cost estimates using the medical spending inflator, whereas our estimate directly reflects the medical spending levels of the managed care era. Obviously, the use of the above adjusting factor does not guarantee that the adjustment of medical cost estimates by severity is as accurate as the adjustment of the medical cost estimate as a whole. Since the new cost estimates preserve the old pattern of costs by MAIS and body region, it is worth summarizing how those costs were computed. Medical payments for paralyzing (MAIS 4 and 5) spinal cord injury came from a household and institutional survey (Berkowitz et al. 1990). Miller, Viner et al. (1991) and Miller, Pindus, and Douglass (1993) developed the remaining costs from 1979- 1988 DCI data. Payments per case were estimated by diagnosis and hospitalization status (admitted or not). Non- hospitalized costs were built from 1982- 1986 NASS data on whether treated and DCI costs per treated case. Hospitalized costs combined NASS length of initial hospital stay, DCI hospital per diem payments, readmission costs in the year after injury COSTS OF LARGE TRUCK- AND BUS- INVOLVED CRASHES 9 from MacKenzie, Shapiro, et al. (1988), and DCI data on longer- term payments. The costs were validated against average costs per injured highway crash survivor by hospitalization status from Rice et al. (1989). The costs were inflated to 1999 dollars using medical spending per capita as an inflator series. Emergency Services Costs include police, fire, ambulance, and helicopter services. Miller, Viner et al. (1991) computed emergency transport costs from the cost per transport by hospitalization status in Rice et al. (1989) and NASS data on the percentage of cases transported by treatment level, MAIS, and body region. They allocated helicopter transport proportionally across nonfatal MAIS 4 and 5 injureds and fatalities who died in the hospital. The costs per transport came from National Medical Care Utilization and Expenditure Survey data (Rice et al, 1989) and published helicopter medical transport statistics, and are averages for all injury victims who were transported. From a survey of 6 providers, Miller, Viner et al. (1991) estimated 65% of trauma transports were for motor vehicle crashes. Fire and police costs were computed from assumed response patterns by crash severity and vehicle involvement, constrained by data on total responses. For fatal, injury, and PDO crashes, time spent per police cruiser responding came from ten jurisdictions with automated police time- tracking systems. A single officer was assumed to have responded to a PDO crash and one officer per injury to other crashes. Time spent per fire truck responding came from nine large fire departments. It was assumed that the fire personnel would respond to: * 90 percent of fatal and severe injury crashes and 95 percent of critical injury crashes. * 35 percent of serious injury crashes and 15 percent of moderate injury crashes. * 40 percent of heavy truck crashes involving minor injury and 1 percent of other minor injury crashes. * 25 percent of police- reported heavy truck crashes involving only property damage. Property Damage is the cost to repair or replace damaged vehicles, cargo, and other property including the costs of damage compensation. Property damage costs were inflated, using the Consumer Price Index - All Items, from Miller, Viner et al. (1991) for medium/ heavy vehicles and from Blincoe (1996) for light vehicles. The original medium/ heavy vehicle property damage estimates came from Bureau of Motor Carrier Safety (BMCS) 50- B and 50- T crash reports and represent vehicles in interstate commerce. The BMCS reports were completed by vehicle owners. BMCS did not audit owner estimates of crash damages for accuracy. Lost Productivity includes wages, fringe benefits, and household work lost by the injured, as well as the costs of processing productivity loss compensation claims. It also includes productivity loss by those stuck in crash- related traffic jams and by co- workers and supervisors investigating crashes, recruiting and training replacements for disabled workers, and repairing damaged company vehicles. Excluded are earnings lost by family and friends caring for the injured and the value of schoolwork lost. The productivity loss resulting from traffic delay is given separately and as part of total productivity lost. Miller (1997) updated the lifetime earnings and household production loss models in Miller, Viner et al. (1991) with 1990- 1991 data. Loss models estimate likely lifetime productivity based on demographic characteristics, earnings profiles, and life tables. The productivity loss attached to each NASS/ CDS victim was age and sex specific. For cost calculations by crash type, tailoring costs for each case by age and sex represents a major improvement over Miller, Viner et al. (1991). Employer productivity losses largely were recomputed using the assumptions in Miller and Galbraith (1995), namely: * A quarter of the time wasted by deaths, disabling injuries, and injuries outside of work is supervisory time. * A fatal injury costs 4 months of productivity (wages plus fringe benefits). Recruitment, retraining, and lost special skills are the major cost factors. A disabling injury serious enough to qualify for Worker's Compensation or require hospital admission costs one month of productivity for other employees. On average, such injuries involve 41 days of work loss. * Other injuries outside of work cause 3 days of lost productivity if they involve work loss and 1.5 days otherwise. * Other injuries on the job that cause work loss cost 2 days of supervisory time and 4 days of non- supervisory time. * Work- related crashes without lost- work injuries cost 2 days of supervisory time and one day of non- supervisory time. This assumption is consistent with PHH FleetAmerica's unpublished data from their subscribers. * Other on- duty injuries without work loss cost one supervisory day and one non- supervisory day. Following Miller, Spicer et al. (1999), however, supervisor and co- worker staff time lost to a permanently disabling injury was assumed to equal the losses for a fatality. These assumptions yield employer costs that average $13, 379 for a fatality, $2,162 for a lost- workday injury, and $405 for an injury without work loss. By comparison, in a Washington state study of construction injury costs, Hinze (1991) finds employer costs of $1, 273 for a lost- workday or restricted- activity injury and $462 for an injury without workdays lost. Leigh et al. (1995) estimate employer costs at $8, 108 for a fatality, $6, 757 for a partial permanent disability, $676 for a less serious lost- workday injury, and $135 for an injury without work loss . Miller (1997) developed the insurance administrative and legal expense models used in the cost computations. It introduced a $100,000 average policy limit on liability claims and a $500, 000 limit on average court awards for catastrophic injuries. Legal costs were reestimated with unit litigation costs from Kakalik and Pace (1986) and probabilities of lawsuit from Hensler et al. (1991), as well as the updated medical care and productivity loss estimates used to estimate attorney fees, which average 31 percent of losses recovered (Hensler et al., 1991). Travel delay was computed similarly to Miller, Viner et al. (1991), but with three refinements. First, the prior work differentiated delay by crash severity in proportion to police time at the crash scene. We modified the prior analysis by assuming that the larger number of emergency vehicles involved in injury and fatal crashes creates twice as much delay per minute on the scene as a crash involving property damage only (PDO). That assumption, which reduced delay costs for PDO crashes, resulted in an hours- of- delay ratio of 40: 130: 385 for the delays due to PDO, injury, and fatal crashes. Second, we increased the hours of delay per urban interstate crash in proportion to the major increase documented by Lan and Hu (2000) in Minneapolis- St Paul. Their study found an average of 5057 hours of delay per heavy truck crash in Minneapolis- St Paul (and 2405 hours per crash without heavy vehicles involved). The study collected data on 289 heavy truck crashes (and 3, 762 other crashes). Third, the previous analysis arbitrarily assumed no travel delay on some classes of roadways and arbitrarily stepped down the delay estimates for other classes. Instead, we started from the hours of delay per crash on urban interstates (the most complete and data- driven estimates available). Delay for other roadway classes by rural- urban location was computed in proportion to traffic density (vehicle- miles per lane mile) for each roadway class relative to urban interstate. Traffic density was computed from Federal statistical data (FHWA 1998). We used the costs per hour of delay from the prior analysis (60 % of the wage rate for non- commercial drivers and 100 % for commercial drivers) since they fell in the range prescribed by current guidance from the Office of the Secretary (U. S. DOT, 1997). Table 1 details the delay estimates per heavy vehicle crash by roadway class and location. Costs inflated to 1999 dollars using the wage index. Table 1. Hours of Delay per Heavy Vehicle Crash by Roadway Class, Location, and Severity Road Class/ Location PDO Injury Fatal URBAN Interstate 2260 7344 21749 Other Freeway 1766 5737 16990 Major Arterial 949 3082 9127 Minor Arterial 594 1929 5711 Collector 31 102 301 Local Street 9 28 83 RURAL Interstate 814 2646 7835 Major Arterial 416 1350 3999 Minor Arterial 255 829 2454 Major Collector 10 34 100 Minor Collector 4 14 42 Local Street 1 4 12 Note: Delay on local streets includes vehicles unable to exit from driveways as planned and therefore not in operation. Each hour of delay is valued at $13. 86 in urban areas and $16.49 in rural areas. The cost differential is due to the differences in vehicle occupancy. Monetized Quality- Adjusted Life Years (QALYs) values the pain, suffering, and quality of life that the family looses because of a death or injury. For fatalities, the monetized value of QALY loss ($ 2.7 million) comes from the Office of the Secretary of Transportation's (OST) guidance (Krusei and McFadden, 1996). It is computed from the amount people routinely spend (in dollars or time) to reduce their risk of death and injury. The value derives from almost 50 studies of explicit or implicit family expenditures on auto safety features, pedestrian safety, and smoke detectors, and of extra wages paid to workers who take risky jobs. The OST value given is for the average highway crash fatality. We used it to compute the present value of QALY loss per fatality by victim age and sex, then applied those values to the age and sex distribution of people killed in medium/ heavy vehicle crashes in 1997 from FARS. For nonfatal injuries, as in the OST's guidance (Krusei and McFadden, 1996), the costs are developed from estimated quality- adjusted life years (QALYs) lost. A QALY is a health outcome measure that assigns a value of 1 to a year of perfect health and 0 to death. Prior studies (Miller 1993; and Miller, Pindus et al., 1995) assessed QALY losses along seven dimensions: cognitive, mobility, bending/ grasping/ lifting, sensory, cosmetic, pain, and ability to work. With survey data describing how people value losses within and between dimensions, they computed average QALY loss for crash victims by MAIS and body region. To compute the percentage of lifetime QALYs lost over the victim's lifetime, one averages the fraction of perfect health lost (the QALY loss) during each year that a victim is recovering from a health problem or living with a residual disability (with some adjustments to get a present value estimate). To monetize the loss, we multiplied the percentage loss by the loss per fatality when someone of the victim's age and sex was killed. To avoid double- counting, we subtracted lost productivity from estimated quality of life lost. The resulting cost estimates were inflated to 1999 dollars using the Employment Cost Index (Economic Report of the President, 2000). Finally, costs per injury were multiplied by the average number of injuries by severity per crash to produce cost estimates per crash, by truck type and crash severity. Results Table 2 summarizes estimated victims per highway crash, by truck/ bus type and police- reported injury severity. For example, the table indicates that crashes in which trucks with no trailers are involved, an average of 1. 993 people had no injury, 0. 198 had possible injury, and so on. An average of 2.430 are involved in these types of crashes. Some caution is warranted in interpreting these numbers because police- reported injury severity is often inaccurate. Many victims who the police code as not injured are actually injured; conversely, the majority of injuries reported by police as disabling do not result in hospital admission (Miller et al. 1991). These shortcomings are one of the reasons why Miller, Lestina, and Spicer (1998) developed their injury costs based on the body region injured, MAIS threat- to- life severity, and level of medical treatment. Another problem with police- reported counts of people in crashes, which is evident in Table 2, is the undercount of uninjured people involved in transit/ intercity bus crashes. Specifically, Table 2 suggests that no more than 3 people were involved in an average transit/ intercity bus crash. This obviously incorrect number results from the widespread police practice of not recording uninjured bus passengers involved in a crash. Table 3 presents estimated victims per highway crash, by truck/ bus type, crash severity, and police- reported injury severity. As mentioned earlier, estimates for fatal crashes came from FARS. Truck- tractors with two or three trailers involved in a fatal crash caused more deaths than any other truck configuration - an average of 1. 118 people had fatal injuries in a typical crash. The unweighted and weighted GES counts of people involved in truck/ bus crashes by vehicle type and police- reported severity are presented in Tables 4 through 7. The number of people killed in fatal truck/ bus crashes is presented in Table 8. The GES tables reveal adequate cell sizes (a minimum of 10 and preferably 30 cases per cell) except when trailer information is unknown. Given the cell sizes, when information about trailers is unknown, it is advisable to use the average cost per large truck crash rather than a configuration- specific cost. Table 9 presents the average estimated costs per victim injured by vehicle type and injury severity. These costs vary modestly with vehicle type. Their estimation was an intermediate step toward estimating costs per crash. Table 10 provides detailed cost per crash estimates for different truck/ bus configurations and crash severity. Tables 11 presents the estimated costs per crash for all crashes and Table 12 presents the estimated costs per crash for injury crashes only. The $117,309 average cost per crash for vehicles with two or three trailers far exceeds the $84,587 for a tractor- trailer crash. Bus crashes and crashes where trailer presence was unknown have the lowest average costs. Crashes involving bobtails have higher average costs than straight truck crashes. The reason for the finding is unclear. These vehicles could have stability problems. Alternatively, since their engines are far more powerful than their trailer- less weight demands, they may be driven aggressively. Also, since bobtail drivers are not generating revenue and are often not paid, they may face financial incentives to speed. We also conducted a sensitivity analysis, using the travel delay costs from Miller, Viner et al. (1991) instead of the new estimates. The resulting crash costs are presented in the appendix. On a percentage basis costs for low- severity crashes are much more sensitive to this change than costs for severe crashes. Table 13 shows the total cost of police- reported heavy vehicle crashes captured in 1997 GES data. The costs of large truck crashes in 1997 exceeded $24 billion. That total included $8.7 billion in productivity losses, $2. 5 billion in resource costs, and quality of life losses valued at $13. 1 billion. The largest share of this total was the $13.2 billion in costs of single- trailer combination trucks. Bobtail crashes cost about one thirty- seventh this much, meaning that bobtails would be over- (or under-) represented in crashes if they comprise less (or more) than about 2.7% of combination truck traffic. Similarly, combination trucks with multiple trailers accounted for about 7. 6% of combination truck crash costs. Single straight trucks accounted for $8.2 billion dollars of the truck crash costs, about one third. Bus crashes were a much smaller factor than truck crashes, costing less than $1 billion in 1997. Computed with 1997 Vehicle Inventory and Use Survey (VIUS) data on truck mileage (Bureau of the Census, 1999), the crash costs per 1, 000 truck miles are $259 for single unit trucks, $138 for single combination trucks, and $134 for multiple combinations. Truck/ Bus Type No injury Possible injury Non incapacitating Incapacitating Fatal injury Unknown severity Unknown if injured Straight truck, no trailer 1.993 0. 198 0.108 0. 059 0.008 0. 005 0.059 Straight truck with trailer 2.004 0. 138 0.096 0. 054 0.010 0. 002 0.095 Straight truck, unknown if with trailer 1.547 0. 018 0.041 0. 017 0.765 Bobtail 1.966 0. 163 0.110 0. 060 0.010 0. 003 0.054 Truck- tractor, 1 trailer 1.836 0. 156 0.099 0. 067 0.015 0. 003 0.073 Truck- tractor, 2 or 3 trailers 1.656 0. 180 0.121 0. 058 0.027 0. 002 0.079 Truck- tractor, with unknown # of trailers 1.936 0. 058 0.012 0. 043 0.012 0. 233 Medium/ heavy truck, unknown if with trailer 1.611 0. 161 0.058 0. 041 0.002 0. 003 0.307 All large trucks 1.903 0. 171 0.102 0. 062 0.012 0. 004 0.072 Bus, transit/ intercity 2.253 0. 380 0.101 0. 049 0.003 0. 023 0.120 TABLE 2. The Average Number of People Involved in a Truck/ Bus Crash by Truck/ Bus Type and Police- Reported Injury Severity (1988- 1997) Source: GES COSTS OF LARGE TRUCK- AND BUS- INVOLVED CRASHES 16 Truck/ Bus Type No injury Posibble injury Unknown severity Unknown if injured Straight truck, no trailer 1.529 1.309 0.002 0.025 Straight truck with trailer 1.558 1.208 - 0. 059 Straight truck, unknown if with trailer 1.153 1.005 - 0. 382 Bobtail 1.483 1.218 - 0. 033 Truck- tractor, 1 trailer 1.371 1.242 0.002 0.045 Truck- tractor, 2 or 3 trailers 1.400 1.225 - 0. 071 Truck- tractor, with unknown # of trailers 0.720 1.053 - 0. 132 Medium/ heavy truck, unknown if with trailer 1.123 1.476 - 0. 236 All large trucks 1.445 1.270 0.002 0.039 Bus, transit/ intercity 1.683 1.765 0.005 0.081 Posibble injury Non incapacitating Unknown severity Unknown if injured Straight truck, no trailer 0.275 1.194 0.002 0.033 Straight truck with trailer 0.144 1.137 0.002 0.061 Straight truck, unknown if with trailer 0.122 1.213 0.000 0.478 Bobtail 0.266 1.302 - 0. 029 Truck- tractor, 1 trailer 0.198 1.143 0.003 0.034 Truck- tractor, 2 or 3 trailers 0.255 1.176 0.001 0.011 Truck- tractor, with unknown # of trailers 0.411 1.074 - 0. 208 Medium/ heavy truck, unknown if with trailer 0.164 1.237 - 0. 101 All large trucks 0.230 1.172 0.002 0.035 Bus, transit/ intercity 0.779 1.345 0.048 0.132 Posibble injury Non incapacitating Incapacitating Unknown severity Unknown if injured Straight truck, no trailer 0.211 0.245 1.220 0.010 0.021 Straight truck with trailer 0.199 0.047 1.184 - 0. 010 Straight truck, unknown if with trailer 0.225 0.225 1.003 - 0. 484 Bobtail 0.184 0.236 1.157 - 0. 021 Truck- tractor, 1 trailer 0.148 0.136 1.170 0.005 0.022 Truck- tractor, 2 or 3 trailers 0.200 0.167 1.107 - 0. 100 Truck- tractor, with unknown # of trailers - - 1.021 - Medium/ heavy truck, unknown if with trailer 0.316 0.350 1.927 - 0. 020 All large trucks 0.175 0.179 1.190 0.006 0.022 Bus, transit/ intercity 0.938 0.260 1.361 0.071 0.036 No injury Posibble injury Non incapacitating Incapacitating Fatal Unknown severity Unknown if injured Straight truck, no trailer 0.828 0.236 0.28491 0.353 1.108 0.007 0.006 Straight truck with trailer 0.936 0.231 0.30631 0.317 1.081 0.026 0.002 Straight truck, unknown if with trailer 0.955 0.273 0.36364 0.227 1.000 - Bobtail 0.782 0.241 0.2455 0. 326 1.112 0.008 0.008 Truck- tractor, 1 trailer 0.866 0.221 0.28035 0.337 1.109 0.007 0.009 Truck- tractor, 2 or 3 trailers 0.855 0.237 0.3043 0. 295 1.118 0.007 0.007 Truck- tractor, with unknown # of trailers 0.961 0.353 0.17647 0.348 1.054 0.015 0.059 Medium/ heavy truck, unknown if with trailer 0.884 0.390 0.14938 0.357 1.058 0.017 0.050 All large trucks 0.856 0.227 0.279 0.337 1.108 0.078 0.087 Bus, transit/ intercity 0.872 1.175 0.795 0.477 1.110 0.106 0.013 Unknown severity Unknown if injured Unknown if injured Straight truck, no trailer 1.265 0.099 1.075 Straight truck with trailer 1.061 0.049 1.081 Straight truck, unknown if with trailer - - 3.686 Bobtail 1.030 - 1. 033 Truck- tractor, 1 trailer 1.137 0.042 1.028 Truck- tractor, 2 or 3 trailers 1.000 - 1. 013 Truck- tractor, with unknown # of trailers - - 1.003 Medium/ heavy truck, unknown if with trailer 2.780 0.593 1.082 All large trucks 1.198 0.069 1.051 Bus, transit/ intercity 3.216 0.063 1.158 Maximum severity in crash: Possible injury TABLE 3. The Average Number of People Involved in a Truck/ Bus Crash by Truck/ Bus Type, Crash Severity, and Police- Reported Injury Severity (1988- 1997) Maximum severity in crash: Non incapacitating 2.310 2.277 2.003 2.238 2.123 2.202 Maximum severity in crash: No injury No injury 1.154 1.209 1.895 2.323 1.956 2.543 1.320 1.320 1.110 1.262 1.272 1.180 1.145 1.853 No injury 1.115 Maximum severity in crash: : Incapacitating 0.354 1.005 1.819 1.770 0.290 1.085 1.016 1.076 1.417 No injury Maximum severity in crash: Fatal Maximum severity in crash: Unknown severity Maximum severity in crash: Unknown if injured No injury 1.334 3.390 0.966 1.149 1.716 Source: GES and FARS 0.875 0.052 3.370 1.241 1.710 1.137 1.139 0.105 1.202 1.220 1.326 1.129 1.209 COSTS OF LARGE TRUCK- AND BUS- INVOLVED CRASHES 17 Truck/ Bus Type No injury Posibble injury Non incapacitating Incapacitating Fatal injury Unknown severity Unknown if injured Straight truck, no trailer 21, 139 2,139 1, 278 602 43 47 546 Straight truck with trailer 2, 373 177 104 84 7 3 83 Straight truck, unknown if with trailer 21 1 2 0 0 0 12 Bobtail 2,545 190 157 76 12 4 73 Truck- tractor, 1 trailer 37, 288 2,488 1, 705 841 111 57 1,478 Truck- tractor, 2 or 3 trailers 1,267 97 51 27 3 1 31 Truck- tractor, with unknown # of trailers 118 4 3 4 1 0 30 Medium/ heavy truck, unknown if with trailer 483 47 8 10 1 0 127 All large trucks 65, 234 5,143 3, 308 1,644 178 112 2, 380 Bus, transit/ intercity 2,535 1, 175 242 141 3 126 157 Truck/ Bus Type No injury Posibble injury Non incapacitating Incapacitating Fatal injury Unknown severity Unknown if injured Straight truck, no trailer 14, 964 5,807 3, 535 2,076 295 162 483 Straight truck with trailer 1, 686 603 370 212 31 6 68 Straight truck, unknown if with trailer 21 4 8 3 0 0 4 Bobtail 2, 058 696 477 249 32 7 63 Truck- tractor, 1 trailer 27, 914 10, 810 6,536 3, 892 686 198 1,089 Truck- tractor, 2 or 3 trailers 939 384 244 128 29 2 45 Truck- tractor, with unknown # of trailers 140 27 14 7 1 0 5 Medium/ heavy truck, unknown if with trailer 453 169 99 40 4 7 18 All large trucks 48, 175 18, 500 11, 283 6,607 1, 078 382 1, 775 Bus, transit/ intercity 1,796 522 414 207 19 14 89 TABLE 4. The Unweighted Count of Truck Occupants Involved in Crashes by Truck/ Bus Type and Police- Reported Injury Severity (1988- 1997) Source: GES TABLE 5. The Unweighted Count of Non Truck Occupants Involved in Truck/ Bus Crashes by Truck/ Bus Type and Police- Reported Injury Severity (1988- 1997) Source: GES COSTS OF LARGE TRUCK- AND BUS- INVOLVED CRASHES 18 Truck/ Bus Type No injury Posibble injury Non incapacitating Incapacitating Fatal injury Unknown severity Unknown if injured Straight truck, no trailer 1,403,201 67,258 40,221 19,223 1,764 2,007 46,936 Straight truck with trailer 134,164 3,307 2,912 2,265 99 18 8,865 Straight truck, unknown if with trailer 1,352 6 16 0 0 0 364 Bobtail 204,519 6,637 5,558 2,531 471 53 7,233 Truck- tractor, 1 trailer 1,657,786 56,991 45,830 25,364 3,003 1,753 86,786 Truck- tractor, 2 or 3 trailers 43,308 2,394 1,065 440 155 89 2,327 Truck- tractor, with unknown # of trailers 11,299 309 16 255 93 0 1, 970 Medium/ heavy truck, unknown if with trailer 34,399 1,786 150 989 55 0 14,120 All large trucks 3,490,028 138,688 95,768 51,067 5,640 3,921 168,600 Bus, transit/ intercity 299,571 58,285 9,692 4,050 298 4,740 13,588 Truck/ Bus Type No injury Posibble injury Non incapacitating Incapacitating Fatal injury Unknown severity Unknown if injured Straight truck, no trailer 1,153,704 186,354 98,000 56,327 8,086 4,968 29,100 Straight truck with trailer 113,112 13,713 8,878 4,425 1,182 176 2,823 Straight truck, unknown if with trailer 1,308 24 54 30 0 0 952 Bobtail 182,888 25,525 16,023 9,374 1,541 564 3,495 Truck- tractor, 1 trailer 1,458,873 207,263 121,684 88,107 22,428 4,136 36,862 Truck- tractor, 2 or 3 trailers 34,826 6,119 4,635 2,317 1,118 11 1,412 Truck- tractor, with unknown # of trailers 12,101 393 133 260 46 0 843 Medium/ heavy truck, unknown if with trailer 42,615 5,928 2,609 990 31 140 552 All large trucks 2,999,427 445,319 252,017 161,830 34,432 9,994 76,039 Bus, transit/ intercity 244,674 33,599 14,783 7,793 526 882 15,387 TABLE 6. The Weighted Count of Truck Occupants Involved in Crashes by Truck/ Bus Type and Police- Reported Injury Severity (1988- 1997) Source: GES TABLE 7. The Weighted Count of Non Truck Occupants Involved in Truck/ Bus Crashes by Truck/ Bus Type and Police- Reported Injury Severity (1988- 1997) Source: GES COSTS OF LARGE TRUCK- AND BUS- INVOLVED CRASHES 19 Truck/ Bus Type Number of fatal crashes Truck occupants killed in crashes Non- truck occupants killed in crashes Total number of people killed in crashes Straight truck, no trailer 7427 1105 7122 8227 Straight truck with trailer 1000 141 940 1081 Straight truck, unknown if with trailer 22 4 18 22 Bobtail 2664 455 2507 2962 Truck- tractor, 1 trailer 28756 4181 27706 31887 Truck- tractor, 2 or 3 trailers 1745 286 1665 1951 Truck- tractor, with unknown # of trailers 204 22 193 215 Medium/ heavy truck, unknown if with trailer 241 28 227 255 All large trucks 42059 6221 40378 46599 Bus, transit/ intercity 1348 80 1416 1496 TABLE 8. The Number of People Killed in Truck/ Bus Crashes by Truck/ Bus Type (1988- 1997) Source: FARS COSTS OF LARGE TRUCK- AND BUS- INVOLVED CRASHES 21 TRUKTYPE Maximum severity in crash Medical cost Emergency services Property damage Lost productivity from delays Total lost productivity Monetized QALYs Total No injury 160 74 2,911 7,280 7,890 571 11,605 Possible injury 1,648 189 5,255 22,911 26,801 8, 122 42,015 Non incapacitating 5, 276 338 6,808 23,945 37,890 36,904 87,216 Incapacitating 44,643 611 9,051 26,780 85,031 302,291 441,625 Fatal injury 35,371 1, 772 18,087 43,292 907,658 2, 352, 174 3,315, 062 Unknown severity 2,540 213 5,457 21,670 27,009 12,982 48,202 Unknown if injured 1, 673 133 3,541 3,584 8,027 9,271 22,645 No injury 206 73 2,855 7,177 7,854 863 11,851 Possible injury 3,717 263 6,167 21,587 30,022 19,601 59,769 Non incapacitating 6, 433 333 6,641 21,517 38,065 50,336 101,808 Incapacitating 19,593 548 8,858 25,318 63,482 179,748 272,229 Fatal injury 25,677 1, 731 17,933 42,974 908,354 2, 261, 505 3,215, 199 Unknown severity 15,375 348 7,892 25,324 51,966 113,546 189,126 Unknown if injured 1, 203 114 3,398 3,589 6,241 6,955 17,911 No injury 146 60 2,441 6,313 6,842 626 10,115 Possible injury 2,109 154 3,891 11,006 15,663 11,120 32,937 Non incapacitating 6, 654 364 7,589 22,588 40,643 55,252 110,501 Incapacitating 14,282 387 6,071 16,039 50,901 138,716 210,358 Fatal injury 24,118 1, 542 16,236 39,510 656,642 1, 709, 226 2,407, 764 Unknown if injured 3, 741 278 6,980 330 8,380 23,999 43,378 No injury 155 72 2,817 7,053 7,640 549 11,233 Possible injury 1,509 176 4,930 21,493 25,123 7, 376 39,113 Non incapacitating 5, 604 364 7,362 25,807 41,183 40,039 94,552 Incapacitating 45,630 577 8,543 25,183 85,637 319,826 460,214 Fatal injury 36,033 1, 761 17,849 42,411 961,899 2, 420, 455 3,437, 995 Unknown severity 1,825 162 4,150 17,255 20,802 9, 335 36,274 Unknown if injured 1, 540 127 3,513 3,846 7,891 8,728 21,799 No injury 191 68 2,660 6,691 7,319 788 11,025 Possible injury 3,810 262 6,010 21,500 30,368 20,489 60,939 Non incapacitating 6, 761 341 6,683 22,044 39,059 51,444 104,287 Incapacitating 19,360 525 7,992 23,343 60,848 176,511 265,237 Fatal injury 26,308 1, 761 18,057 42,962 956,183 2, 365, 564 3,367, 873 Unknown severity 7,444 184 3,879 18,453 32,449 54,492 98,448 Unknown if injured 1, 186 118 3,557 4,180 6,905 6,929 18,693 No injury 183 62 2,399 5,973 6,562 735 9,940 Possible injury 3,796 262 6,040 21,315 30,212 20,066 60,377 Non incapacitating 7, 083 362 7,163 23,747 41,352 54,166 110,125 Incapacitating 18,472 525 8,129 23,521 61,094 171,808 260,026 Fatal injury 25,751 1, 764 18,091 43,130 1, 034, 892 2,462, 275 3,542, 774 Unknown severity 504 44 1,447 13,966 14,997 2, 491 19,483 Unknown if injured 1, 108 107 3,199 3,558 6,135 6,414 16,962 No injury 209 74 2,908 7,324 7,971 817 11,979 Possible injury 3,172 203 4,479 16,030 23,902 17,583 49,339 Non incapacitating 7, 421 382 7,681 24,513 41,072 51,591 108,146 Incapacitating 15,383 403 6,795 18,954 52,043 131,674 206,299 Fatal injury 24,588 1, 689 17,640 42,482 941,168 2, 260, 946 3,246, 030 Unknown if injured 1, 123 106 3,275 3,812 6,224 6,933 17,660 No injury 142 59 2,381 6,166 6,652 574 9,807 Possible injury 4,506 303 6,805 23,912 33,852 24,865 70,330 Non incapacitating 6, 541 351 7,070 23,059 39,477 48,953 102,392 Incapacitating 31,317 853 12,130 36,905 101,557 313,119 458,976 Fatal injury 25,946 1, 703 17,704 42,633 911,627 2, 291, 273 3,248, 252 Unknown severity 9,424 345 9,695 49,008 70,826 68,285 158,574 Unknown if injured 1, 197 111 3,399 3,787 6,446 7,402 18,556 No injury 182 70 2,764 6,939 7,565 718 11,299 Possible injury 3,051 237 5,778 22,114 29,228 16,124 54,419 Non incapacitating 6, 285 344 6,813 23,000 39,084 46,694 99,220 Incapacitating 28,685 560 8,454 24,791 70,269 224,204 332,172 Fatal injury 28,429 1, 757 17,975 42,987 969,247 2, 401, 793 3,419, 202 Unknown severity 5,357 199 4,669 20,156 30,392 36,814 77,431 Unknown if injured 1, 326 121 3,525 3,913 7,114 7,630 19,716 No injury 36 60 2,800 8,017 8,267 91 11,253 Possible injury 4,547 345 8,404 29,743 40,075 26,131 79,502 Non incapacitating 10,039 528 10,790 35,827 63,233 91,357 175,947 Incapacitating 17,331 672 12,467 40,771 77,856 161,980 270,305 Fatal injury 29,936 2, 075 24,574 66,573 952,161 2, 342, 427 3,351, 173 Unknown severity 4,303 555 13,442 49,799 61,946 19,499 99,745 Unknown if injured 1, 216 121 3,982 5,391 7,969 7,170 20,458 All large trucks Bus, transit/ intercity Medium/ heavy truck, unknown if with trailer Bobtail TABLE 10. Costs per Crash by Truck/ Bus Type and Crash Severity (in 1999 dollars) Truck- tractor, 1 trailer Truck- tractor, 2 or 3 trailers Truck- tractor, with unknown # of trailers Straight truck, no trailer Straight truck with trailer Straight truck, unknown if with trailer COSTS OF LARGE TRUCK- AND BUS- INVOLVED CRASHES 22 Truck/ bus type Medical costs Emergency services Property damage Lost productivity from delays Total lost productivity Monetized QALYs Total Straight truck, no trailer 3,139 150 3,959 11,583 22,444 34,973 64,667 Straight truck with trailer 2,217 152 3,933 10,577 24,012 38,889 69,203 Straight truck, unknown if with trailer 1,448 117 3,535 5,921 9,340 10,741 25,181 Bobtail 3,341 148 3,843 11,103 25,163 42,200 74,695 Truck- tractor, 1 trailer 2,525 160 3,868 10,657 28,466 49,568 84,588 Truck- tractor, 2 or 3 trailers 2,754 178 3,947 10,910 37,993 72,437 117, 309 Truck- tractor, with unknown # of trailers 1,527 121 3,414 7,959 19,906 30,784 55,751 Medium/ heavy truck, unknown if with trailer 1,819 128 3,515 8,763 13,786 16,699 35,948 All large trucks 2,769 156 3,913 10,993 25,760 43,039 75,637 Bus, transit/ intercity 2,270 174 4,844 14,837 22,900 24,267 54,455 Truck/ bus type Medical costs Emergency services Property damage Lost productivity from delays Total lost productivity Monetized QALYs Total Straight truck, no trailer 9,746 315 6,212 21,150 54,735 111, 394 182, 404 Straight truck with trailer 6,816 332 6,383 18,377 61,050 126, 080 200, 662 Straight truck, unknown if with trailer 4,977 272 6,503 4,859 16,144 38,191 66,087 Bobtail 11,111 334 6,321 20,993 67,922 143, 876 229, 565 Truck- tractor, 1 trailer 7,626 360 6,502 19,332 74,716 156, 268 245, 472 Truck- tractor, 2 or 3 trailers 7,797 405 6,980 20,600 99,679 213, 148 328, 008 Truck- tractor, with unknown # of trailers 4,133 213 4,408 9,218 43,510 90,072 142, 337 Medium/ heavy truck, unknown if with trailer 4,105 222 5,045 12,316 23,511 38,699 71,581 All large trucks 8,448 343 6,409 19,908 65,739 136, 066 217, 005 Bus, transit/ intercity 6,241 378 8,481 26,952 48,896 67,218 131, 214 TABLE 11. Costs per Crash by Truck/ Bus Type (in 1999 dollars) TABLE 12. Costs per Injury Crash by Truck/ Bus Type (in 1999 dollars) Truck/ bus type Medical costs Emergency services Property damage Lost productivity from delays Total lost productivity Monetized QALYs Total Straight truck, no trailer 410,925, 609 21, 925, 212 605,615, 580 1,754, 633,438 3, 023, 590, 965 4,097, 371,035 8, 159, 428, 402 Straight truck with trailer 48, 903, 125 2,912, 334 70, 427,328 195, 646, 027 468,812, 579 815,743, 198 1,406, 798,564 Straight truck, unknown if with trailer ------ Bobtail 19, 668, 249 1,367, 907 40, 435,116 125, 570, 523 164,578, 498 126,436, 920 352,486, 690 Truck- tractor, 1 trailer 436,023, 967 29, 575, 165 763,765, 923 2,077, 019,020 4, 665, 005, 936 7,271, 946,362 13, 166,317,352 Truck- tractor, 2 or 3 trailers 19, 805, 517 1,301, 041 25, 671,809 66, 897,451 365, 454, 447 779,751, 440 1,191, 984,254 Truck- tractor, with unknown # of trailers 1,644, 565 150, 998 4,657, 117 6, 599, 714 10, 173, 215 10, 308, 955 26, 934, 849 Medium/ heavy truck, unknown if with trailer 3,665, 223 314, 045 9,387, 909 24, 692,838 33, 706,475 25, 075,241 72, 148,893 All large trucks 940,636, 254 57, 546, 702 1,519, 960,782 4, 251, 059, 012 8,731, 322,115 13, 126,633,151 24, 376,099,004 Bus, transit/ intercity 36, 167, 501 3,228, 524 93, 226,729 283, 158, 870 432,821, 334 412,292, 371 977,736, 458 TABLE 13. 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COSTS OF LARGE TRUCK- AND BUS- INVOLVED CRASHES 26 Appendix COSTS OF LARGE TRUCK- AND BUS- INVOLVED CRASHES 28 TRUKTYPE Maximum severity in crash Medical cost Emergency services Property damage Lost productivity from delays Total lost productivity Monetized QALYs Total No injury 160 74 2,911 304 914 571 4,630 Possible injury 1,648 189 5,255 440 4,329 8,122 19,543 Non incapacitating 5, 276 338 6,808 477 14,422 36,904 63,748 Incapacitating 44,643 611 9,051 531 58,781 302,291 415,376 Fatal injury 35,371 1, 772 18,087 935 865,302 2, 352, 174 3,272, 706 Unknown severity 2,540 213 5,457 433 5,772 12,982 26,964 Unknown if injured 1, 673 133 3,541 319 4,763 9,271 19,381 No injury 206 73 2,855 299 977 863 4,974 Possible injury 3,717 263 6,167 651 27,292 19,601 57,040 Non incapacitating 6, 433 333 6,641 469 8,904 50,336 72,647 Incapacitating 19,593 548 8,858 459 17,007 179,748 225,754 Fatal injury 25,677 1, 731 17,933 939 866,319 2, 261, 505 3,173, 165 Unknown severity 15,375 348 7,892 651 27,292 113,546 164,453 Unknown if injured 1, 203 114 3,398 315 2,967 6,955 14,637 No injury 146 60 2,441 261 790 626 4,062 Possible injury 2,109 154 3,891 320 4,977 11,120 22,251 Non incapacitating 6, 654 364 7,589 545 18,600 55,252 88,458 Incapacitating 14,282 387 6,071 361 35,223 138,716 194,680 Fatal injury 24,118 1, 542 16,236 862 617,994 1, 709, 226 2,369, 116 Unknown if injured 3, 741 278 6,980 582 8,631 23,999 43,629 No injury 155 72 2,817 295 882 549 4,475 Possible injury 1,509 176 4,930 417 4,046 7,376 18,037 Non incapacitating 5, 604 364 7,362 520 15,896 40,039 69,265 Incapacitating 45,630 577 8,543 502 60,956 319,826 435,533 Fatal injury 36,033 1, 761 17,849 919 920,407 2, 420, 455 3,396, 504 Unknown severity 1,825 162 4,150 325 3,872 9,335 19,343 Unknown if injured 1, 540 127 3,513 322 4,367 8,728 18,275 No injury 191 68 2,660 279 907 788 4,613 Possible injury 3,810 262 6,010 450 9,317 20,489 39,888 Non incapacitating 6, 761 341 6,683 455 17,470 51,444 82,699 Incapacitating 19,360 525 7,992 473 37,977 176,511 242,366 Fatal injury 26,308 1, 761 18,057 938 914,159 2, 365, 564 3,325, 849 Unknown severity 7,444 184 3,879 310 14,306 54,492 80,305 Unknown if injured 1, 186 118 3,557 332 3,057 6,929 14,846 No injury 183 62 2,399 250 839 735 4,217 Possible injury 3,796 262 6,040 454 9,351 20,066 39,515 Non incapacitating 7, 083 362 7,163 491 18,096 54,166 86,870 Incapacitating 18,472 525 8,129 486 38,059 171,808 236,991 Fatal injury 25,751 1, 764 18,091 940 992,703 2, 462, 275 3,500, 585 Unknown severity 504 44 1,447 143 1,174 2,491 5,660 Unknown if injured 1, 108 107 3,199 297 2,874 6,414 13,702 No injury 209 74 2,908 305 953 817 4,961 Possible injury 3,172 203 4,479 324 8,195 17,583 33,632 Non incapacitating 7, 421 382 7,681 534 17,093 51,591 84,167 Incapacitating 15,383 403 6,795 462 33,551 131,674 187,807 Fatal injury 24,588 1, 689 17,640 933 899,618 2, 260, 946 3,204, 481 Unknown if injured 1, 123 106 3,275 309 2,722 6,933 14,158 No injury 142 59 2,381 254 741 574 3,896 Possible injury 4,506 303 6,805 494 10,433 24,865 46,911 Non incapacitating 6, 541 351 7,070 487 16,905 48,953 79,820 Incapacitating 31,317 853 12,130 643 65,294 313,119 422,713 Fatal injury 25,946 1, 703 17,704 929 869,923 2, 291, 273 3,206, 548 Unknown severity 9,424 345 9,695 922 22,739 68,285 110,487 Unknown if injured 1, 197 111 3,399 320 2,979 7,402 15,088 No injury 182 70 2,764 290 915 718 4,649 Possible injury 3,051 237 5,778 449 7,564 16,124 32,755 Non incapacitating 6, 285 344 6,813 469 16,553 46,694 76,689 Incapacitating 28,685 560 8,454 499 45,978 224,204 307,881 Fatal injury 28,429 1, 757 17,975 934 927,194 2, 401, 793 3,377, 148 Unknown severity 5,357 199 4,669 374 10,610 36,814 57,648 Unknown if injured 1, 326 121 3,525 326 3,527 7,630 16,129 No injury 36 60 2,800 319 570 91 3,556 Possible injury 4,547 345 8,404 612 10,944 26,131 50,371 Non incapacitating 10,039 528 10,790 732 28,138 91,357 140,852 Incapacitating 17,331 672 12,467 779 37,863 161,980 230,312 Fatal injury 29,936 2, 075 24,574 1, 320 886,908 2, 342, 427 3,285, 920 Unknown severity 4,303 555 13,442 932 13,079 19,499 50,878 Unknown if injured 1, 216 121 3,982 391 2,969 7,170 15,457 Medium/ heavy truck, unknown if with trailer All large trucks Bus, transit/ intercity Note: Travel delay costs form Miller, Viner, et al. Bobtail Truck- tractor, 1 trailer Truck- tractor, 2 or 3 trailers Truck- tractor, with unknown # of trailers TABLE 10- A. Costs per Crash by Truck/ Bus Type and Crash Severity (in 1999 dollars) Straight truck, no trailer Straight truck with trailer Straight truck, unknown if with trailer COSTS OF LARGE TRUCK- AND BUS- INVOLVED CRASHES 29 Truck/ bus type Medical costs Emergency services Property damage Lost productivity from delays Total lost productivity Monetized QALYs Total Straight truck, no trailer 3,139 150 3,959 352 11,213 34,973 53,435 Straight truck with trailer 2,217 152 3,933 348 13,783 38,889 58,974 Straight truck, unknown if with trailer 1,448 117 3,535 333 3,753 10,741 19,594 Bobtail 3,341 148 3,843 342 14,402 42,200 63,934 Truck- tractor, 1 trailer 2,525 160 3,868 333 18,143 49,568 74,265 Truck- tractor, 2 or 3 trailers 2,754 178 3,947 326 27,409 72,437 106, 725 Truck- tractor, with unknown # of trailers 1,527 121 3,414 321 12,267 30,784 48,112 Medium/ heavy truck, unknown if with trailer 1,819 128 3,515 315 5,339 16,699 27,501 All large trucks 2,769 156 3,913 341 15,108 43,039 64,985 Bus, transit/ intercity 2,270 174 4,844 426 8,489 24,267 40,045 Truck/ bus type Medical costs Emergency services Property damage Lost productivity from delays Total lost productivity Monetized QALYs Total Straight truck, no trailer 9,746 315 6,212 454 34,039 111, 394 161, 707 Straight truck with trailer 6,816 332 6,383 459 43,132 126, 080 182, 744 Straight truck, unknown if with trailer 4,977 272 6,503 530 11,815 38,191 61,757 Bobtail 11,111 334 6,321 456 47,385 143, 876 209, 028 Truck- tractor, 1 trailer 7,626 360 6,502 450 55,834 156, 268 226, 591 Truck- tractor, 2 or 3 trailers 7,797 405 6,980 474 79,553 213, 148 307, 883 Truck- tractor, with unknown # of trailers 4,133 213 4,408 351 34,642 90,072 133, 469 Medium/ heavy truck, unknown if with trailer 4,105 222 5,045 396 11,591 38,699 59,662 All large trucks 8,448 343 6,409 453 46,284 136, 066 197, 550 Bus, transit/ intercity 6,241 378 8,481 615 22,559 67,218 104, 877 TABLE 11- A. Costs per Crash by Truck/ Bus Type (in 1999 dollars) TABLE 12- A. Costs per Injury Crash by Truck/ Bus Type Note: Travel delay costs form Miller, Viner, et al. Note: Travel delay costs form Miller, Viner, et al. COSTS OF LARGE TRUCK- AND BUS- INVOLVED CRASHES 30 Truck/ bus type Medical costs Emergency services Property damage Lost productivity from delays Total lost productivity Monetized QALYs Total Straight truck, no trailer 410,925, 609 21, 925, 212 605,615, 580 45, 106, 581 1,438, 963,528 4, 097, 371, 035 6,574, 800,964 Straight truck with trailer 48, 903, 125 2,912, 334 70, 427,328 4, 295, 535 170,077, 016 815,743, 198 1,108, 063,001 Straight truck, unknown if with trailer ------ Bobtail 19, 668, 249 1,367, 907 40, 435,116 6, 736, 052 283,773, 001 126,436, 920 471,681, 193 Truck- tractor, 1 trailer 436,023, 967 29, 575, 165 763,765, 923 56, 485, 046 3,079, 087,566 7, 271, 946, 362 11, 580, 398,982 Truck- tractor, 2 or 3 trailers 19, 805, 517 1,301, 041 25, 671,809 1, 536, 699 129,297, 584 779,751, 440 955,827, 391 Truck- tractor, with unknown # of trailers 1,644, 565 150, 998 4,657, 117 387, 664 14, 825, 473 10, 308, 955 31, 587, 108 Medium/ heavy truck, unknown if with trailer 3,665, 223 314, 045 9,387, 909 1, 503, 533 25, 512, 841 25, 075, 241 63, 955, 259 All large trucks 940,636, 254 57, 546, 702 1,519, 960,782 116, 297, 253 5,150, 951,716 13, 126,633,151 20, 795,728,605 Bus, transit/ intercity 36, 167, 501 3,228, 524 93, 226,729 10, 290,559 205, 041, 915 412,292, 371 749,957, 039 TABLE 13- A. Total Crash Costs by Truck/ Bus Type: 1997 (in 1999 dollars) Note: Travel delay costs form Miller, Viner, et al.