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.

Analysis of Single-Vehicle Crash Injury Severities in Urban River-Crossing Road Tunnels

2015 ◽  
Vol 743 ◽  
pp. 526-532 ◽  
Author(s):  
C.M. Jiang ◽  
J.J. Lu ◽  
L.J. Lu
Keyword(s):  
Heavy Vehicles ◽  
Probit Regression ◽  
Factors Affecting ◽  
Explanatory Variables ◽  
Urban Road ◽  
Road Tunnels ◽  
Negative Effect ◽  
Single Vehicle ◽  
Injury Severities ◽  
One Year

Based on the originally unprocessed data from the Official Platform of“110”Alarming Receiving Center (OP110ARC) of Shanghai Public Security Bureau (SPSB), 529 single-vehicle crashes reported during one year and a half which happened at the thirteen urban road tunnels going across the Huangpu River are used in this study. To investigate the factors affecting the crash influence severity levels, ordered probit regression is established. Several categories of factors are considered as explanatory variables in the models. The study finds that the entrance of the tunnels is the site where severe injury crashes trend to occur. Rainy and snowy days impose vehicles and motorists driving via the tunnel sections in danger. Tunnels with a low speed limit (40 km/h in this study) may be not as safe as we thought before. Two-wheel vehicles without sufficient physical protection for its drivers and heavy vehicles also show a negative effect on the operation safety of single-vehicle at these studied tunnels. Alcohol involved drivers are more likely to suffer from a severe crashes and gets badly hurt.

scholarly journals Risk Factors Affecting Driver Severity of Single- Vehicle Run Off Road Crash for Thailand Highway

2020 ◽  
Vol 24 (5) ◽  
pp. 207-216
Author(s):  
Chamroeun Se ◽  
Thanapong Champahom ◽  
Sajjakaj Jomnonkwao ◽  
Vatanavongs Ratanavaraha
Keyword(s):  
Risk Factors ◽  
Injury Severity ◽  
Information Management System ◽  
Logit Analysis ◽  
Factors Affecting ◽  
Roadside Safety ◽  
Fatal Crash ◽  
Run Off ◽  
Single Vehicle ◽  
Safety Features

Single-Vehicle Run Off Road (ROR) crash has been the leading crash type in terms of frequency and severity in Thailand. In this study, multinomial logit analysis was applied to identify the risk factors potentially influencing driver injury severity of single-vehicle ROR crash using accident records between 2011 and 2017 which were extracted from Highway Accident Information Management System (HAIMS) database. The analysis results show that the age of driver older than 55 years old, male driver, driver under influence of alcohol, drowsiness, ROR to left/right on straight roadway increase the probability of fatal crash, while other factors are found to mitigate severity such as the age of driver between 26-35 years old, using seatbelt, ROR and hit fixed object on straight and curve segment of roadway, mounted traffic island, intersection-related and accident in April. This study recommends the need to improve road safety campaign, law enforcement, and roadside safety features that potentially reduce level of severity of driver involving in single-vehicle ROR crash.

Passengers and Other Factors Affecting the Safety of Young and Older Drivers

2005 ◽  
Vol 1937 (1) ◽  
pp. 7-13 ◽  
Author(s):  
Patrycja Padlo ◽  
Lisa Aultman-Hall ◽  
Nikiforos Stamatiadis
Keyword(s):  
Older Drivers ◽  
Vehicle Crashes ◽  
Or Education ◽  
Factors Affecting ◽  
Young Driver ◽  
Young Drivers ◽  
Graduated Driver Licensing ◽  
Specific Objective ◽  
Local Roads ◽  
Single Vehicle

The specific objective of this study was to assess the relative propensity of young (16 to 20 years old) or older (65 years and older) drivers in Connecticut to be at fault in a traffic crash when they ( a) travel at night, ( b) travel on different classes of roadway (freeway versus state route versus local road), and ( c) travel with different numbers of passengers. For young drivers, the age of the passengers was also considered. The quasi-induced exposure technique was used with police-reported crashes between 1997 and 2001. The results show that young driver risk increases at night, on freeways (and for single-vehicle crashes on local roads), as well as with increased numbers of passengers. For older drivers the risk also increases at night and on freeways (and for single-vehicle crashes on local roads); however, older drivers are less likely to cause crashes when traveling with passengers. These results suggest that the new graduated driver licensing restrictions in place in Connecticut will reduce crashes and that there is the potential to improve young driver safety further by extending these restrictions. Furthermore, similar regulations or education programs aimed at older drivers might improve crash experience for these individuals, especially those older than 75.

Modeling severity of single vehicle run-off-road crashes in rural areas: model comparison and selection

2016 ◽  
Vol 43 (6) ◽  
pp. 493-503 ◽  
Author(s):  
Linfeng Gong ◽  
Wei Fan ◽  
E. Matthew Washing
Keyword(s):  
Rural Areas ◽  
Model Comparison ◽  
Statistical Tests ◽  
Mixed Logit ◽  
Discrete Choice Models ◽  
Model Structure ◽  
Crash Data ◽  
Run Off ◽  
Single Vehicle ◽  
Selection Framework

Run-off-road (ROR) crashes account for a large proportion of fatalities and serious injuries to vehicle occupants, especially in rural areas. While performing crash severity analysis using discrete choice models (DCMs), researchers may be confused by the following questions: first, should an ordered or unordered model structure be used and secondly, which modeling level is more appropriate, basic or advanced? A model selection framework is developed considering the following factors: (1) model structure — ordered or unordered; (2) intrinsic deficiency of each model; (3) computational burdens; (4) complexity of parameter interpretation; and (5) model fitness. Historical ROR crash data were utilized to illustrate how to choose an appropriate DCM based on the proposed framework. Using statistical tests and comparison of evaluation and validation measurements, both the mixed logit model and the partial proportional odds model yield a reasonable performance. All factors that significantly affect the severity level of a single-vehicle ROR crash were identified as well.

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