Injury severities of truck drivers in single- and multi-vehicle accidents on rural highways

Chen, Feng; Chen, Suren

doi:10.1016/j.aap.2011.03.026

Cited by 333 publications

(267 citation statements)

References 33 publications

(53 reference statements)

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“…Lower daily average traffic volume leads, in general, to higher severity injuries. This finding is consistent with a number of previous studies that have shown that crash severity is higher on low-traffic volume roads, and significantly decreases with increasing volumes, presumably due to better safety design on highways with high traffic volumes (see Das et al, 2009, Christoforou et al, 2010, and Chen and Chen, 2011. Lower traffic volume could be related with higher speeds that more often lead to severe crashes.…”

Section: Environmental Factorssupporting

confidence: 82%

“…The flexibility of our GORP framework allows such doubleedged reductions at the extremes to be captured. However, if a crash involves only women drivers, there is a reduced probability of no injuries and a higher probability of IF injuries (see Yamamoto et al, 2008, Xie et al, 2009, Chen and Chen, 2011, and Liu and Donmez, 2011 for a similar result). Given that the drivers of vehicles are the ones who typically sustain the most severe injury, a plausible reason for this effect is that women are more vulnerable to injuries due to their generally smaller physical frames.…”

Section: Characteristics Of Drivers Involved In the Crashmentioning

confidence: 88%

“…In particular, when present, these unobserved heterogeneity effects can have very real implications for the accurate assessment of the effects of variables and for the design of countermeasures to reduce injury severity. This realization has resulted in many more studies in the past five years or so that consider unobserved heterogeneity effects, including in SOR structures (see Srinivasan, 2002, Eluru and Bhat, 2007, and Christoforou et al, 2010, in UR structures (see Milton et al, 2008, Anastasopoulos and Mannering, 2011, Chen and Chen, 2011, and Moore et al, 2011, and in GOR structures (see Eluru et al, 2008). 2 The GOR structure discussed here is quite different from other generalizations of the ordered structure used in Quddus et al (2010) and Wang et al (2011).…”

Section: Unobserved Heterogeneity In the Effects Of Variablesmentioning

confidence: 98%

“…A crash involving multiple vehicles increases the probability of the most severe IF injury category, presumably because of multiple injury exposure instances (see Donnell, 2010 andChen, 2011). The effect of the number of passengers is best captured using both continuous and dummy variable representations.…”

Section: Crash Characteristicsmentioning

confidence: 99%

“…7 A similar approach has been adopted in many earlier studies to circumvent the statistical issues that arise from having a very low number of crashes in one or more categories; see, for example, Savolainen and Mannering (2007), Eluru et al (2008), Milton et al (2008) and Chen and Chen (2011).…”

mentioning

confidence: 99%

See 4 more Smart Citations

A spatial generalized ordered response model to examine highway crash injury severity

Castro

Paleti

Bhat

2013

Accident Analysis & Prevention

106

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This paper proposes a flexible econometric structure for injury severity analysis at the level of individual crashes that recognizes the ordinal nature of injury severity categories, allows unobserved heterogeneity in the effects of contributing factors, as well as accommodates spatial dependencies in the injury severity levels experienced in crashes that occur close to one another in space. The modeling framework is applied to analyze the injury severity sustained in crashes occurring on highway road segments in Austin, Texas. The sample is drawn from the Texas Department of Transportation (TxDOT) crash incident files from 2009 and includes a variety of crash characteristics, highway design attributes, driver and vehicle characteristics, and environmental factors. The results from our analysis underscore the value of our proposed model for data fit purposes as well as to accurately estimate variable effects. The most important determinants of injury severity on highways, according to our results, are (1) whether any vehicle occupant is ejected, (2) whether collision type is head-on, (3) whether any vehicle involved in the crash overturned, (4) whether any vehicle occupant is unrestrained by a seat-belt, and (5) whether a commercial truck is involved.

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Section: Environmental Factorssupporting

confidence: 82%

Section: Characteristics Of Drivers Involved In the Crashmentioning

confidence: 88%

Section: Unobserved Heterogeneity In the Effects Of Variablesmentioning

confidence: 98%

Section: Crash Characteristicsmentioning

confidence: 99%

mentioning

confidence: 99%

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A spatial generalized ordered response model to examine highway crash injury severity

Castro

Paleti

Bhat

2013

Accident Analysis & Prevention

106

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Occupational fatalities among driver/sales workers and truck drivers in the United States, 2003–2008

Chen

Amandus

2014

American J Industrial Med

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Background This study provides a national profile of occupational fatalities among truck drivers and driver-sales workers. Methods Data from the 2003–2008 Census of Fatal Occupational Injuries were used. Cases were extracted specifically for occupational subcategories included in the Driver/Sales Workers and Truck Drivers occupational category: Driver/Sales Workers, Heavy and Tractor-Trailer Truck Drivers, and Light Truck or Delivery Services Drivers. Results In 2003–2008, the group Driver/Sales Workers and Truck Drivers had 5,568 occupational fatalities, representing 17% of all occupational fatalities in the United States. The majority of these fatalities were in the subgroup Heavy and Tractor-Trailer Truck Drivers (85%) and due to transportation incidents (80%). Older and male drivers had higher fatality rates than their counterparts. Conclusions Findings suggest a need for targeted interventions to reduce highway fatalities among heavy truck drivers. Better employment data are needed to separate the three occupational subcategories by worker characteristic and employment history for use in research and prevention efforts.

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Differences in single heavy vehicle crashes at intersections and midblocks

Balakrishnan

Moridpour

Tay

2016

J of Advced Transportation

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The objective of this research is to identify the factors differentiating between single heavy vehicle collisions at intersections and midblocks by using a binary logit model. Our results show that single vehicle crashes involving heavy vehicle at intersections are more likely to occur on main roads and highways, whereas crashes at midblocks are more likely to occur on divided two-way roads, roads with special facilities or features (e.g. bridge) and roads with a higher percentage of heavy vehicle traffic. Intersection crashes are also more likely to involve vehicles that are turning left or right, resulting in angle crashes and vehicle overturn, whereas midblock crashes are more likely to involve vehicles on higher posted speed roads.Note: Distribution (%) of collisions reported for categorical variables. Mean and (standard deviation) reported for continuous variables. HEAVY VEHICLE CRASHES

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Injury severities of truck drivers in single- and multi-vehicle accidents on rural highways

Cited by 333 publications

References 33 publications

A spatial generalized ordered response model to examine highway crash injury severity

A spatial generalized ordered response model to examine highway crash injury severity

Occupational fatalities among driver/sales workers and truck drivers in the United States, 2003–2008

Differences in single heavy vehicle crashes at intersections and midblocks

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