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Vehicle Data Sources for the Accident Reconstructionist
Published in Donald E. Struble, John D. Struble, Automotive Accident Reconstruction, 2020
Donald E. Struble, John D. Struble
The Vehicle Identification Number, or VIN, is a unique number assigned to each vehicle for registration and identification purposes. VINs have been used since 1954, but different manufacturers used different formats. In the mid-1960s, model year began to be included with a production serial number, and in the early 1970s the number of digits was standardized at 10. In 1981, the National Highway Traffic Administration (NHTSA) standardized the format and required that all over-the-road vehicles sold in the United States have a 17-character VIN. Any letter had to be uppercase, but the VIN could not include the letters I, O, or Q, to avoid confusion with the numbers 1 and 0. A one-character code for model year was included, which allowed for a 30-year cycle.
The association between data collected in IIHS side crash tests and real-world driver death risk
Published in Traffic Injury Prevention, 2022
Eric R. Teoh, Raul A. Arbelaez
Counts of fatally injured drivers for each of the study vehicles were extracted from the Fatality Analysis Reporting System (FARS) for crashes occurring during 2000–2016. FARS is a census of fatal crashes occurring in the United States. The make/series/model year of each vehicle was determined by decoding the Vehicle Identification Number (VIN) in FARS using proprietary software developed by the Highway Loss Data Institute (HLDI), and the vehicle type, curb weight, and side airbag fitment were determined by merging with vehicle information databases maintained by HLDI. Data were limited to vehicles where the initial impact was on the driver side, crash test information was known, and vehicles with standard head- and chest-protecting side airbags. Driver age and sex, and initial impact point (driver side includes codes 8, 9, 10, 61, 62, 63) also were extracted from FARS. The final sample (56% male, 26% ages 15-29, 42% ages 30–64, 16% SUV/pickup, average curbweight 3,272 lbs or 1,484 kg) included 2,778 driver deaths (FARS injury severity = 4) in rated vehicles.
Crash rates of convertible cars
Published in Traffic Injury Prevention, 2021
Exposure measures were registered vehicle years (RVY; the sum of annual registration counts over multiple years), based on data obtained from IHS Markit (https://ihsmarkit.com/products/auto-market-statistics-vio-vin.html), and vehicle miles traveled (VMT). Odometer readings/dates at the Vehicle Identification Number level were obtained from CARFAX, a unit of IHS Markit, and transformed to average daily VMT at the level of make/series/model year by HLDI. In particular, the average daily VMT for a vehicle (make/series/model year) was derived when multiple odometer readings/dates existed during that year; odometer readings were subtracted and divided by the number of days the 2 dates spanned. Estimates of total VMT each calendar year were obtained by multiplying that year’s daily VMT estimates by number of days in that year and by the number of registered vehicles in that year. Estimates across multiple years were then obtained by summing each year’s estimates. HLDI validated this method by comparing aggregate VMT with figures published by the Federal Highway Administration and the results tracked closely. Therefore, VMT accounts for both convertible/nonconvertible differences in the number of vehicles on the road and how much they are driven. Restricting to vehicles at least 1 year old allowed for a full year of exposure to be reflected in counts of registered vehicles and for vehicles to have sufficient time on the road to compute estimates of VMT.
Vehicle safety characteristics in vulnerable driver populations
Published in Traffic Injury Prevention, 2020
Kristina B. Metzger, Emma Sartin, Robert D. Foss, Nina Joyce, Allison E. Curry
The unique NJ-SHO warehouse links data from multiple statewide data sources and includes the full history of driver licensing and police-reported crashes of every NJ driver from 2004 through 2017 (n ≈ 11 million; see Curry et al. 2019 for details). Ninety-six percent of crash-involved NJ drivers matched with a unique licensing record. Vehicle data available in the crash database include make, model, model year, and full Vehicle Identification Number (VIN). Driver-level variables included age and sex. License status at the time of the crash was obtained from licensing data. Using ArcGIS, we geocoded the residential address of each crash-involved driver (from the crash report [primary source] or licensing data [secondary source]) to their census tract; we were able to identify the census tract of 97% of crash-involved drivers. We then obtained the median household income for each NJ census tract from the 2009–2013 American Community Survey 5-year estimates.