Injury severity analysis of truck-involved crashes under different weather conditions

Numerous driver, vehicle, roadway, and environmental factors contribute to crash-injury severity. In addition to main effects, interactions between factors are very likely to be significant. The large number of potentially important factors, combined with the complex nature of crash etiology and injury outcome, present significant challenges to the safety analyst, who must select from a large number of factors and specify a comprehensive but feasible set of main factors and interactions for testing in statistical models. In addition, some factors contain a relatively large number of categories (e.g., weather conditions), and the selection of cut-off points for categorization of continuous factors may not be readily obvious (e.g., driver age). It is also important that statistical tests underlying these analyses accurately address the frequent problem of data sparseness. The development and testing of a variable-selection procedure to address each of these problems is the stated objective. Bus-involved crash data for Freeway 1 in Taiwan from 1985 through 1993 were used to screen a set of 39 possible influential factors, along with interactions. The final log-linear model shows that late-night or early-morning driving increases the risk for bus drivers of being severely injured, particularly when the drivers caused the accident or when the drivers were involved in rear-end accidents. Bus accidents involving large trucks or tractor-trailers also increase the risk. An assessment of the importance of considering interactions in crash models is presented as a conclusion.

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Investigating the Temporal Instability in Injury Severity Outcomes of Clear and Adverse Weather Crashes on Rural Mountainous Highways

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/03611981211057052 ◽

2021 ◽

pp. 036119812110570

Author(s):

Irfan U. Ahmed ◽

Mohamed M. Ahmed

Keyword(s):

Monte Carlo ◽

Injury Severity ◽

Statistical Significance ◽

Weather Conditions ◽

Warning Signs ◽

Parameter Estimates ◽

Connected Vehicle ◽

Temporal Instability ◽

Short Period ◽

Adverse Weather

Analysis of driver injury severity based on weather conditions on rural highways is limited in the literature. Such analyses provide insights useful to policymakers in optimizing the allocation of limited resources based on weather conditions. Furthermore, if there is a possibility of factors exhibiting temporal instability, then an aggregate analysis can lead to erroneous allocation of funds. In this study, separate models for clear and adverse weather conditions were developed for each of the years from 2015 to 2019 using crash data from a rural mountainous highway corridor. A random-intercept Bayesian logistic approach was used to analyze the dichotomous injury severity response and capture the between-crash variance. An efficient Markov chain Monte Carlo sampling technique known as the No-U-Turn Hamiltonian Monte Carlo was employed to sample the posterior distributions of parameter estimates. Likelihood ratio tests provided statistical significance of the temporal instability and also the differences in driver injury severities resulting from clear and adverse weather crashes. While most of the variables demonstrated temporal instability, some factors exhibited temporal stability over a short period of time and only during clear weather conditions. Findings from the separate models suggest that there are major differences in both the combination and magnitude of the significant contributing factors. Implementation of confirmatory warning signs, variable message signs, connected vehicle technology, strict enforcements during different times and locations, and driver awareness programs have been recommended as suitable countermeasures. The findings and recommendations could potentially help in guiding the respective agencies in formulating injury severity mitigation policies and strategies.

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INFLUENCE OF EXTERNAL RISK FACTORS ON ALPINE SKIING INJURIES IN RECREATIONAL SKIERS

sportlogia ◽

10.5550/sgia.211701.en.kkap ◽

2021 ◽

Vol 17 (1) ◽

pp. 58-71

Author(s):

Dinko Kolarić ◽

◽

Ana Kolarić ◽

Drago Ambroš ◽

Siniša Popek ◽

...

Keyword(s):

Risk Factors ◽

Injury Severity ◽

Weather Conditions ◽

Control Group ◽

Chi Square ◽

Vision Condition ◽

Severity Of Injury ◽

Skiing Injuries ◽

Potential Risk Factors ◽

External Risk

The main goal of this study was to identify potential external risk factors for injury in recreational skiers through a survey questionnaire. Subjects were divided into injured skiers and a control group who never had an injury. Injured skiers (N=212) answered questions that helped define potential risk factors. The control group (N=206) completed the same questionnaire but without questions about injury. Common questions were used to determine the possibility of injury using Chi-Square test, and additional questions were used to determine the influence on injury severity using Fisher’s test. An analysis of external factors showed that formal ski school was not statistically related to the possibility and severity of injury, but significantly increased knowledge of skiing. Skiing with another person did not decrease the possibility of injury but did increase the severity of injury. Visibility, field of vision, condition of the slope, temperature, and weather conditions are not statistically related to injury severity, but when combined, they could be an important factor in the possibility of injury.

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The Impact of Aggressive Driving Behavior on Driver-Injury Severity at Highway-Rail Grade Crossings Accidents

Journal of Advanced Transportation ◽

10.1155/2018/9841498 ◽

2018 ◽

Vol 2018 ◽

pp. 1-10 ◽

Cited By ~ 64

Author(s):

Changxi Ma ◽

Wei Hao ◽

Wang Xiang ◽

Wei Yan

Keyword(s):

Open Space ◽

Injury Severity ◽

Mixed Logit ◽

Weather Conditions ◽

Driving Behavior ◽

Aggressive Driving ◽

Driving Behaviors ◽

Grade Crossings ◽

High Level ◽

The Impact

The effect of aggressive driving behavior on driver’s injury severity is analyzed by considering a comprehensive set of variables at highway-rail grade crossings in the US. In doing so, we are able to use a mixed logit modelling approach; the study explores the determinants of driver-injury severity with and without aggressive driving behaviors at highway-rail grade crossings. Significant differences exist between drivers’ injury severity with and without aggressive driving behaviors at highway-rail grade crossings. The level of injury for younger male drivers increases a lot if they are with aggressive driving behavior. In addition, driving during peak-hour is found to be a statistically significant predictor of high level injury severity with aggressive driving behavior. Moreover, environmental factors are also found to be statistically significant. The increased level of injury severity accidents happened for drivers with aggressive driving behavior in the morning peak (6-9 am), and the probability of fatality increases in both snow and fog condition. Driving in open space area is also found to be a significant factor of high level injury severity with aggressive driving behaviors. Bad weather conditions are found to increase the probability of drivers’ high level injury severity for drivers with aggressive driving behaviors.

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Tulsa Oklahoma Oktoberfest Tent Collapse Report

Emergency Medicine International ◽

10.1155/2012/729795 ◽

2012 ◽

Vol 2012 ◽

pp. 1-9 ◽

Cited By ~ 1

Author(s):

Kelly E. Deal ◽

Carolyn K. Synovitz ◽

Jeffrey M. Goodloe ◽

Brandi King ◽

Charles E. Stewart

Keyword(s):

Injury Severity ◽

Spinal Injury ◽

Fire Department ◽

Weather Conditions ◽

Mass Casualty Incident ◽

Mass Casualty ◽

Severe Weather ◽

Emergency Department Care ◽

Incident Command ◽

Severity Scores

Background. On October 17, 2007, a severe weather event collapsed two large tents and several smaller tents causing 23 injuries requiring evacuation to emergency departments in Tulsa, OK.Methods. This paper is a retrospective analysis of the regional health system’s response to this event. Data from the Tulsa Fire Department, The Emergency Medical Services Authority (EMSA), receiving hospitals and coordinating services were reviewed and analyzed. EMS patient care reports were reviewed and analyzed using triage designators assigned in the field, injury severity scores, and critical mortality.Results. EMT's and paramedics from Tulsa Fire Department and EMSA provided care at the scene under unified incident command. Of the 23 patients transported by EMS, four were hospitalized, one with critical spinal injury and one with critical head injury. One patient is still in ongoing rehabilitation.Discussion. Analysis of the 2007 Tulsa Oktoberfest mass casualty incident revealed rapid police/fire/EMS response despite challenges of operations at dark under severe weather conditions and the need to treat a significant number of injured victims. There were no fatalities. Of the patients transported by EMS, a minority sustained critical injuries, with most sustaining injuries amenable to discharge after emergency department care.

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Investigating the Risk Factors Associated with the Severity of the Pedestrians Injured on Spanish Crosstown Roads

Sustainability ◽

10.3390/su11195194 ◽

2019 ◽

Vol 11 (19) ◽

pp. 5194 ◽

Cited By ~ 4

Author(s):

Natalia Casado-Sanz ◽

Begoña Guirao ◽

Antonio Lara Galera ◽

Maria Attard

Keyword(s):

Risk Factors ◽

Injury Severity ◽

Motor Vehicle ◽

Weather Conditions ◽

Crash Data ◽

Factors Associated ◽

The Road ◽

Pedestrian Injury ◽

On The Road ◽

Pedestrian Crashes

According to the Spanish General Traffic Accident Directorate, in 2017 a total of 351 pedestrians were killed, and 14,322 pedestrians were injured in motor vehicle crashes in Spain. However, very few studies have been conducted in order to analyse the main factors that contribute to pedestrian injury severity. This study analyses the accidents that involve a single vehicle and a single pedestrian on Spanish crosstown roads from 2006 to 2016 (1535 crashes). The factors that explain these accidents include infractions committed by the pedestrian and the driver, crash profiles, and infrastructure characteristics. As a preliminary tool for the segmentation of 1535 pedestrian crashes, a k-means cluster analysis was applied. In addition, multinomial logit (MNL) models were used for analysing crash data, where possible outcomes were fatalities and severe and minor injured pedestrians. According to the results of these models, the risk factors associated with pedestrian injury severity are as follows: visibility restricted by weather conditions or glare, infractions committed by the pedestrian (such as not using crossings, crossing unlawfully, or walking on the road), infractions committed by the driver (such as distracted driving and not respecting a light or a crossing), and finally, speed infractions committed by drivers (such as inadequate speed). This study proposes the specific safety countermeasures that in turn will improve overall road safety in this particular type of road.

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Developing a Traffic Management Framework for Coastal Expressway Bridges under Adverse Weather Conditions: Case Study of Rain Day in Shenzhen, China

Discrete Dynamics in Nature and Society ◽

10.1155/2015/218672 ◽

2015 ◽

Vol 2015 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

Chenming Jiang ◽

Jian John Lu ◽

Yuming Jiang ◽

Xiaonan Cai ◽

Anning Ni

Keyword(s):

Traffic Management ◽

Injury Severity ◽

Control Strategies ◽

Geographical Location ◽

Surface Friction ◽

Weather Conditions ◽

Negative Influence ◽

Management Framework ◽

Adverse Weather ◽

Alternate Routes

Adverse weather can reduce visibility and road surface friction, lower vehicle maneuverability, and increase crash frequency and injury severity. The impacts of adverse weather and its interactions with drivers and roadway on the operation and management of expressway or expressway bridges have drawn the researchers’ and managers’ attention to develop traffic management frameworks to mitigate the negative influence. Considering the peculiar geographical location and meteorological conditions, the Guangshen Coast Expressway-Shenzhen Segment (GSCE-SS) was selected as a case in this study to illustrate the proposed traffic management framework on rain days. Conditions categorized by rainfall intensity and traffic flow were the main precondition to make the management decisions. CORSIM simulator was used to develop the alternate routes choice schemes, providing reference for other systems in the proposed traffic management framework. Maps of (a) entrance ramp control (ERC) strategies; (b) mainline control strategies; (c) alternate routes choice; (d) information release schemes, under scenarios of different volume and rainstorm warning grades (BLUE to RED), were drawn to present a reference or demonstration for managers of long-span expressway bridges not only in China, but even in the world.

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Analyzing Severity of Vehicle Crashes at Highway-Rail Grade Crossings: Multinomial Logit Modeling

Journal of the Transportation Research Forum ◽

10.5399/osu/jtrf.54.2.4282 ◽

2015 ◽

Cited By ~ 4

Author(s):

Wei (David) Fan ◽

Martin R. Kane ◽

Elias Haile

Keyword(s):

Logit Model ◽

High Speed ◽

Injury Severity ◽

Weather Conditions ◽

Multinomial Logit Model ◽

The United States ◽

Multinomial Logit ◽

Vehicle Crashes ◽

Grade Crossings ◽

The Impact

The purpose of this paper is to develop a nominal response multinomial logit model (MNLM) to identify factors that are important in making an injury severity difference and to explore the impact of such explanatory variables on three different severity levels of vehicle-related crashes at highway-rail grade crossings (HRGCs) in the United States. Vehicle-rail and pedestrian-rail crash data on USDOT highway-rail crossing inventory and public crossing sites from 2005 to 2012 are used in this study. A multinomial logit model is developed using SAS PROC LOGISTICS procedure and marginal effects are also calculated. The MNLM results indicate that when rail equipment with high speed struck a vehicle, the chance of a fatality resulting increased. The study also reveals that vehicle pick-up trucks, concrete, and rubber surfaces were more likely to be involved in more severe crashes. On the other hand, truck-trailer vehicles in snow and foggy weather conditions, development area types (residential, commercial, industrial, and institutional), and higher daily traffic volumes were more likely to be involved in less severe crashes. Educating and equipping drivers with good driving habits and short-term law enforcement actions, can potentially minimize the chance of severe vehicle crashes at HRGCs.

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