Are SUVs “Supremely Unsafe Vehicles”?: Analysis of Rollovers and Injuries with Sport Utility Vehicles

2003 ◽  
Vol 1840 (1) ◽  
pp. 167-177 ◽  
Author(s):  
Asad J. Khattak ◽  
Marta Rocha
Keyword(s):  
Injury Severity ◽  
Negative Binomial ◽  
Crash Analysis ◽  
Abbreviated Injury Scale ◽  
Rollover Risk ◽  
Light Trucks ◽  
Stratified Sample ◽  
Single Vehicle ◽  
Driver Injuries ◽  
Binomial Models

With increasing speed limits and more light trucks penetrating the market, concern over their rollover risk is growing. In particular, the general public and automobile manufacturers would like to know if the increasingly popular sport utility vehicles (SUVs) are indeed safer than other vehicle platforms. The influences of various vehicle platforms on rollovers and driver injuries were investigated. Specifically, ( a) the rollover intensities of SUVs vis-à-vis those of other vehicle types in single-vehicle crashes and ( b) the severity of the resulting driver injury were explored. Data from a good-quality federally maintained database were used for crash analysis. The database contains a relatively clean stratified sample of police-reported tow-away crashes nationwide, and it contains detailed information about vehicle rollovers. Rollover intensity, captured by the number of quarter turns, was investigated by using weighted negative binomial models; injury severity, measured on the abbreviated injury scale, was examined by using weighted ordered logit models. New insights emerged about the factors that increase rollover intensity and injury severity. As expected, SUVs are more likely to roll over and therefore injure their occupant drivers more severely. However, SUVs also protect their drivers during collisions because of their greater crashworthiness. In fact, the SUV crashworthiness effect exceeds the rollover effect, on average. The implications of these findings are discussed.

Injury Effects of Rollovers and Events Sequence in Single-Vehicle Crashes

2000 ◽  
Vol 1717 (1) ◽  
pp. 46-54 ◽  
Author(s):  
Kimberly A. Krull ◽  
Asad J. Khattak ◽  
Forrest M. Council
Keyword(s):  
Injury Severity ◽  
Seat Belt ◽  
Policy Implications ◽  
Vehicle Crashes ◽  
Passenger Cars ◽  
Logistic Regression Models ◽  
Crash Testing ◽  
Restraint Use ◽  
Single Vehicle ◽  
Driver Injuries

The effect that rollovers and tripping-event sequence surrounding rollover crashes have on the severity of driver injury was explored. Three-year crash and inventory data from Michigan ( N = 35,447) and Illinois ( N = 24, 296) were analyzed to explore the effect of rollover, while controlling for roadway, vehicle, and driver factors. The results show that 9 percent of single-vehicle crashes are either fatal or cause incapacitating driver injuries (K + A injuries). Significantly more fatalities and incapacitating injuries occur in rollover crashes. Logistic regression models of fatal and incapacitating injuries (K + A) versus other injuries and noninjuries (B + C + 0) were estimated separately and together for the two states. The results show that the effects of independent variables are largely consistent across the two states. Driver-injury severity increases with rollovers; failure to use a seat belt; passenger cars (as opposed to pickup trucks); alcohol use; daylight; rural roads (as opposed to urban); posted speed limit; and dry pavement (as opposed to slick pavement). Restricting the injury models to rollover crashes only, it was determined that hitting point objects or longitudinal objects before rolling over resulted in a more severe injury than rolling over first. The policy implications of the findings for restraint use, crash-testing, and roadside design and hardware are discussed.

Examining Driver Injury Severity in Single-Vehicle Road Departure Crashes Involving Large Trucks

2021 ◽  
pp. 036119812110101
Author(s):  
Mehdi Hosseinpour ◽  
Kirolos Haleem
Keyword(s):  
Rural Areas ◽  
Injury Severity ◽  
Factors Affecting ◽  
Crash Data ◽  
Natural Logarithm ◽  
Concrete Barriers ◽  
Local Roads ◽  
Single Vehicle ◽  
Safety Countermeasures ◽  
Injury Severities

Road departure (RD) crashes are among the most severe crashes that can result in fatal or serious injuries, especially when involving large trucks. Most previous studies neglected to incorporate both roadside and median hazards into large-truck RD crash severity analysis. The objective of this study was to identify the significant factors affecting driver injury severity in single-vehicle RD crashes involving large trucks. A random-parameters ordered probit (RPOP) model was developed using extensive crash data collected on roadways in the state of Kentucky between 2015 and 2019. The RPOP model results showed that the effect of local roadways, the natural logarithm of annual average daily traffic (AADT), the presence of median concrete barriers, cable barrier-involved collisions, and dry surfaces were found to be random across the crash observations. The results also showed that older drivers, ejected drivers, and drivers trapped in their truck were more likely to sustain severe single-vehicle RD crashes. Other variables increasing the probability of driver injury severity have included rural areas, dry road surfaces, higher speed limits, single-unit truck types, principal arterials, overturning-consequences, truck fire occurrence, segments with median concrete barriers, and roadside fixed object strikes. On the other hand, wearing seatbelt, local roads and minor collectors, higher AADT, and hitting median cable barriers were associated with lower injury severities. Potential safety countermeasures from the study findings include installing median cable barriers and flattening steep roadside embankments along those roadway stretches with high history of RD large-truck-related crashes.

scholarly journals Factors Contributing to the Relationship between Driving Mileage and Crash Frequency of Older Drivers

2019 ◽  
Vol 11 (23) ◽  
pp. 6643 ◽  
Author(s):  
Lee ◽  
Guldmann ◽  
Choi
Keyword(s):  
Negative Binomial ◽  
Age Groups ◽  
Urban Environments ◽  
Vehicle Miles Traveled ◽  
Crash Frequency ◽  
Rural Environments ◽  
Lower Likelihood ◽  
Conditional Autoregressive ◽  
The Relationship ◽  
Binomial Models

As a characteristic of senior drivers aged 65 +, the low-mileage bias has been reported in previous studies. While it is thought to be a well-known phenomenon caused by aging, the characteristics of urban environments create more opportunities for crashes. This calls for investigating the low-mileage bias and scrutinizing whether it has the same impact on other age groups, such as young and middle-aged drivers. We use a crash database from the Ohio Department of Public Safety from 2006 to 2011 and adopt a macro approach using Negative Binomial models and Conditional Autoregressive (CAR) models to deal with a spatial autocorrelation issue. Aside from the low-mileage bias issue, we examine the association between the number of crashes and the built environment and socio-economic and demographic factors. We confirm that the number of crashes is associated with vehicle miles traveled, which suggests that more accumulated driving miles result in a lower likelihood of being involved in a crash. This implies that drivers in the low mileage group are involved in crashes more often, regardless of the driver’s age. The results also confirm that more complex urban environments have a higher number of crashes than rural environments.

Zapatista and counter-Zapatista protests

2012 ◽  
Vol 49 (3) ◽  
pp. 459-472 ◽  
Author(s):  
María Inclán
Keyword(s):  
Negative Binomial ◽  
Empirical Test ◽  
Party Competition ◽  
Public Works ◽  
Social Programs ◽  
Reciprocal Effect ◽  
Systematic Analysis ◽  
Binomial Models ◽  
Different Levels ◽  
Protest Activity

This study represents the first systematic analysis of the interactions between pro-Zapatista and counter-Zapatista protestors in Chiapas, Mexico, and the first empirical test of movement–countermovement theories in a transitional democracy. Three claims are tested: (1) movement protests trigger countermovement protest activity; (2) different political parties at different levels of government trigger movement–countermovement protest activity; and (3) victories won by one side of a conflict, viewed as procedural concessions, trigger further pro- and countermovement protest activity. These hypotheses are tested using negative binomial models and data on Zapatista-related protest activity between 1994 and 2003. The results show that: (1) movement and countermovement protests have a positive, reciprocal effect on both groups' future protest activity; (2) movement and countermovement protesting groups use the dominant political party as a target of protest. The characteristics of the electoral cycle and rise of multi-party competition at all levels of government do not have a consistent effect on protest activity; (3) granting procedural concessions to pro-movement actors generates more protest activity among both groups. However, granting procedural concessions via social programs and public works to the population irrespective of its sympathy to either side of the movement–countermovement conflict decreases movement protests and increases countermovement protests.

scholarly journals An Application Comparison of Two Negative Binomial Models on Rainfall Count Data

2021 ◽  
Vol 1818 (1) ◽  
pp. 012100
Author(s):  
L. H. Hashim ◽  
N. K. Dreeb ◽  
K. H. Hashim ◽  
Mushtak A. K. Shiker
Keyword(s):  
Count Data ◽  
Negative Binomial ◽  
Negative Binomial Models ◽  
Binomial Models

scholarly journals Criminal Justice Debt During the Prisoner Reintegration Process: Who Has It and How Much?

2018 ◽  
Vol 46 (1) ◽  
pp. 154-172 ◽  
Author(s):  
Nathan W. Link
Keyword(s):  
Criminal Justice ◽  
Negative Binomial ◽  
Policy Implications ◽  
Community Supervision ◽  
Individual Level ◽  
Prisoner Reintegration ◽  
Negative Binomial Models ◽  
The Individual ◽  
Binomial Models ◽  
Transition Home

Much recent, national attention has centered on financial sanctions and associated debt burdens related to criminal justice. Scholars and practitioners alike have argued that financial debt among the incarcerated, in particular, exacerbates a transition home already defined by difficulties. This article takes a step back and assesses who is at risk of these adverse consequences in reentry by examining the extent of debt burdens that resulted from financial sanctions, its sources, and the individual-level factors that are associated with owing criminal justice debt. Relying on the Returning Home data ( N = 740), results from descriptive analyses, logistic regression, and negative binomial models show that a large proportion of respondents owed debts and that debt was strongly linked with being mandated to community supervision. In addition, debt amount was predicted by employment, income, and race. Policy implications in the realm of financial sanctioning by courts and correctional agencies are discussed.

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