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From page 20...
... 20 3.1 Introduction This chapter presents a study conducted for this project to identify the types of vehicles that are more likely to roll over on slopes through an analysis of existing crash databases. The presentation includes (1)
From page 21...
... Crash Data Analysis 21 The lack of roadside geometry data does not prohibit the crash data analysis from identifying vehicle types more likely to roll over for the following reason. Although individual vehicles may experience different sideslope ratios when they encroach on the roadside, the distribution of sideslope ratios experienced collectively by a particular type of passenger vehicle (e.g., 4-door sedans)
From page 22...
... 22 Guidelines for Traversability of Roadside Slopes FARS and GES data definitions and coding, simplify crash data entry and analysis, and reduce costs and errors. The crashes investigated in CDS have been collected and published annually since 1979.
From page 23...
... Crash Data Analysis 23 resulting sample can be very different from the overall population from which it is drawn and about which we wish to make inferences. Statistically, it is a biased sample by design, in which crashes are selected with unequal probabilities.
From page 24...
... 24 Guidelines for Traversability of Roadside Slopes uses the same 1,195 PSUs as GES. But it sampled only 24 of the PSUs in the first stage, from which a number of police jurisdictions are surveyed in the second stage.
From page 25...
... Crash Data Analysis 25 Two databases were developed from the CDS data: NCHRP Report 665 (30) and NCHRP Project 17-43 (ongoing)
From page 26...
... 26 Guidelines for Traversability of Roadside Slopes vehicles, pickup trucks, vans, and medium/heavy trucks (2)
From page 27...
... Crash Data Analysis 27 of rollover crashes needed to maintain a good statistical quality in assessing the rollover risk made the analysis at the vehicle model level infeasible. Grouping vehicles based on vehicle characteristics, such as wheelbase, track width, CG height, and curb weight, required manual extractions of vehicle data from other data sources, such as Expert AutoStats (31)
From page 28...
... 28 Guidelines for Traversability of Roadside Slopes the slope-related rollover crashes were identified from the database will be given in Section 3.5. Vehicle body types that have the greatest number of sampled cases are: • 4-Door sedan: 1,104 cases • Compact utility vehicle: 1,092 cases • Standard pickup truck: 593 cases • Compact pickup truck: 405 cases • 2-Door sedan: 293 cases On average, each sampled vehicle represents about 76 crashes in the target crash population of interest.
From page 29...
... Crash Data Analysis 29 3.4.1 Composition Ratio Vehicle CR is derived by dividing the proportion of a specific type of vehicles in passenger vehicles involved in slope-related rollover crashes by the proportion of the same type of vehicles in passenger vehicles involved in all slope-related crashes, which include both rollover and non-rollover crashes. It can be expressed in an equation as CR (for Type Vehicles)
From page 30...
... 30 Guidelines for Traversability of Roadside Slopes Let's take RR (compact utility and non-compact utility vehicles) equal to 2.4 as an example.
From page 31...
... Crash Data Analysis 31 more roadside encroachments and thus more crashes involving roadside slopes. This is a reasonable assumption in that roadside conditions, such as slopes and fixed objects, do not discriminate against any vehicle type.
From page 32...
... 32 Guidelines for Traversability of Roadside Slopes Body Type Slope-Related Slope-Related CR Rollovers (%) Crashes (%)
From page 33...
... Crash Data Analysis 33 0.60 0.56 2.13 2.39 1.22 1.31 1.14 1.49 0.0 0.5 1.0 1.5 2.0 2.5 C o m p o si ti o n R at io 2Dr S ed an 4Dr S ed an Co m pa ct U til ity La rg e U til ity Mi ni va n La rg e V an Co m pa ct P ick up St an da rd P ick up Vehicle Body Type (Data Source: FARS, 2004-2010; Posted Speed Limit: 45-75 mph) Figure 3.2.
From page 34...
... 34 Guidelines for Traversability of Roadside Slopes vehicles and large utility vehicles are again overrepresented, and passenger cars, both 2-door and 4-door sedans, are underrepresented, which are generally consistent with the results from FARS data. Recall that large vans were included for comparison purposes only because of their sample size and thus statistical limitation.
From page 35...
... Crash Data Analysis 35 compact utility vehicles, large utility vehicles, and standard pickup trucks. This is consistent with the results based on CR values, as presented above.
From page 36...
... 36 Guidelines for Traversability of Roadside Slopes Table 3.7 and Figure 3.5 show the RR of slope-related rollovers for one particular vehicle type to that of the rest of the vehicle types and the associated confidence interval from GES data. As seen from the figure, the statistical uncertainty associated with the estimate is much greater than that obtained from the FARS data for a particular vehicle type.
From page 37...
... Crash Data Analysis 37 3.6 Conclusion Based on the observed frequency of slope-related rollover crashes from the 2004 to 2010 FARS data, five top ranked vehicle models for each body type are presented in Table 3.8. For each of the five ranked models, the model-year (2001 or newer)
From page 38...
... 38 Guidelines for Traversability of Roadside Slopes Since 2001, NHTSA has provided estimates of rollover risk annually for some popular passenger vehicle models. Estimates are available to the public on NHTSA's website as part of its 5-star safety ratings consumer information program.
From page 39...
... Crash Data Analysis 39 Vehicle Body Type Vehicle Make Vehicle Model Model Years (2004+) Risk of Rollover 2-Wheel Drive 4-Wheel Drive 2-door sedan, hardtop, coupe Chevrolet Cavalier 2004-05 11.30% -- -- -- 2-door sedan, hardtop, coupe Ford Mustang 2005-10 8.70% -- -- -- 2-door sedan, hardtop, coupe Chevrolet Monte Carlo 2006-07 10.30% -- -- -- 2-door sedan, hardtop, coupe Pontiac Grand AM 2004-05 10.90% -- -- -- 2-door sedan, hardtop, coupe Honda (Non-Acura)

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