Investigation of factors contributing to injury severity in single vehicle motorcycle crashes in India

2021 ◽  
pp. 1-12
Author(s):  
Sathish Kumar Sivasankaran ◽  
Harikrishna Rangam ◽  
Venkatesh Balasubramanian
Keyword(s):  
Injury Severity ◽  
Single Vehicle ◽  
Motorcycle Crashes

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.

Modeling Safety Effects of Horizontal Curve Design on Injury Severity of Single-Motorcycle Crashes with Mixed-Effects Logistic Model

2017 ◽  
Vol 2637 (1) ◽  
pp. 38-46 ◽  
Author(s):  
Chunfu Xin ◽  
Zhenyu Wang ◽  
Chanyoung Lee ◽  
Pei-Sung Lin
Keyword(s):  
Logistic Model ◽  
Injury Severity ◽  
Unobserved Heterogeneity ◽  
Mixed Effects ◽  
Severe Injury ◽  
Horizontal Curve ◽  
Random Parameters ◽  
Horizontal Curves ◽  
Curve Design ◽  
Motorcycle Crashes

Horizontal curves have been of great interest to transportation researchers because of expected safety hazards for motorcyclists. The impacts of horizontal curve design on motorcycle crash injuries are not well documented in previous studies. The current study aimed to investigate and to quantify the effects of horizontal curve design and associated factors on the injury severity of single-motorcycle crashes with consideration of the issue of unobserved heterogeneity. A mixed-effects logistic model was developed on the basis of 2,168 single-motorcycle crashes, which were collected on 8,597 horizontal curves in Florida for a period of 11 years (2005 to 2015). Four normally distributed random parameters (moderate curves, reverse curves, older riders, and male riders) were identified. The modeling results showed that sharp curves (radius <1,500 ft) compared with flat curves (radius ≥4,000 ft) tended to increase significantly the probability of severe injury (fatal or incapacitating injury) by 7.7%. In total, 63.8% of single-motorcycle crashes occurring on reverse curves are more likely to result in severe injury, and the remaining 26.2% are less likely to result in severe injury. Motorcyclist safety compensation behaviors (psychologically feeling safe, and then riding aggressively, or vice versa) may result in counterintuitive effects (e.g., vegetation and paved medians, full-access-controlled roads, and pavement conditions) or random parameters (e.g., moderate curve and reverse curve). Other significant factors include lighting conditions (darkness and darkness with lights), weekends, speed or speeding, collision type, alcohol or drug impairment, rider age, and helmet use.

scholarly journals Motorcycle crashes and upper extremity trauma

SICOT-J ◽  
2021 ◽  
Vol 7 ◽  
pp. 8
Author(s):  
Erin Cravez ◽  
Kelsey A. Rankin ◽  
Nathaniel Ondeck ◽  
Lee Yaari ◽  
Michael Leslie ◽  
...  
Keyword(s):  
Upper Extremity ◽  
Injury Severity ◽  
Cohort Analysis ◽  
Cost Of Care ◽  
Hospital Length Of Stay ◽  
Rank Test ◽  
Severe Injuries ◽  
Increased Risk ◽  
Extremity Injuries ◽  
Motorcycle Crashes

Objectives: Upper extremity injuries following motorcycle crashes (MCC) incur increased healthcare costs and rehabilitation needs. We aim to characterize the epidemiology of MCC upper extremity injuries and identify factors that influence the severity of and cost of care for upper extremity injuries. Methods: We performed a retrospective cohort analysis of 571 patients with upper extremity injuries after MCC at a level 1 trauma center from 2002 to 2013. We collected data pertaining to demographics, helmet use, toxicology, bony injury, Injury Severity Score (ISS), Glasgow Coma Scale (GCS), hospital length of stay (LOS), and cost. Continuous variables were compared using t-test or Wilcoxon rank test, depending on data distribution, and dichotomous variables were compared using Pearson’s chi-squared or Fisher’s exact tests. Regression models were used to evaluate the effect of intoxication or helmets on injury location, severity, cost of care, and LOS. Results: The incidence of MCC upper extremity injury was 47.5%, with hand and forearm fractures the most common injuries (25.5% and 24.7% of total injuries). Intoxicated patients were more likely to have a high cost of care (p = 0.012), extended LOS (p = 0.038), plastic surgery involvement in their care (p = 0.038), but fewer upper extremity bony injuries (p = 0.019). Non-helmeted patients sustained less upper extremity bony injuries (p < 0.001) and upper extremity soft tissue injuries (p = 0.001), yet more severe injuries (ISS ≥ 30, p = 0.006 and GCS < 9, p < 0.01) than helmeted patients. Conclusion: Upper extremity injuries are common in motorcyclists. Despite vital protection for the brain and maxillofacial injury, helmeted MCC patients have an increased incidence of upper extremity injuries compared to non-helmeted patients, but overall have less severe injuries. Intoxicated patients have fewer upper extremity bony injuries, but the higher cost of care, and extended LOS. Therefore, even with the increased risk of injury helmets may expose to the upper extremity, helmets reduced overall morbidity and mortality. In addition to mandatory helmet laws, we advocate for further development of safety equipment focusing specifically on the prevention of upper extremity injuries.

scholarly journals Motor Scooters and Mopeds

2008 ◽  
Vol 2074 (1) ◽  
pp. 69-76 ◽  
Author(s):  
Narelle Haworth ◽  
Angela Nielson
Keyword(s):  
Medical Treatment ◽  
The State ◽  
Crash Severity ◽  
Loss Of Control ◽  
Vehicle Crashes ◽  
Low Speed ◽  
Registration Data ◽  
Single Vehicle ◽  
Crash Types ◽  
Motorcycle Crashes

Little is known about the crash involvement of scooters and mopeds and whether they are safer than other motorcycles. Difficulties in defining motor scooters and mopeds and identifying them in crash and other databases have hindered research. This paper reviews recent research and analyzes the nature and extent of moped and motorcycle crashes in the State of Queensland, Australia. Analyses of merged crash and registration data found that the number of moped crashes increased from 25 in 2001 to 97 in 2005. Most crashes resulted in hospitalization (43%) or medical treatment (38%) and occurred between 6 a.m. and 6 p.m. on weekdays in low-speed areas. Overall, 50.8% of crashes occurred at intersections and 32.3% were single-vehicle crashes. The most common crash types were collisions between vehicles traveling in the same direction (24.8%), loss of control on a straight road (23.1%), and collisions between the moped and another vehicle on an adjacent approach to an intersection (18.2%). The ratio of motorcycle to moped crashes was about 19:1, but moped crashes increased at a greater rate during 2001–2005 (260% versus 71%). The distributions of crash severity were similar. Moped crashes more often involved loss of control on a straight road (23.1% versus 12.7%), while motorcycle crashes more often involved loss of control on a curve (13.6% versus 5.0%). Moped riders in crashes were much more likely than motorcycle riders to be female (37.9% versus 7.2%) and younger and hold an interstate (10.8% versus 1.3%) or overseas (7.8% versus 0.7%) license. The interpretation of these data and their implications for licensing and other countermeasures are discussed.

Perils of Rib Fractures

2008 ◽  
Vol 74 (4) ◽  
pp. 310-314 ◽  
Author(s):  
Om P. Sharma ◽  
Michael F. Oswanski ◽  
Shashank Jolly ◽  
Sherry K. Lauer ◽  
Rhonda Dressel ◽  
...  
Keyword(s):  
Elderly Patients ◽  
Blunt Chest Trauma ◽  
Chest Trauma ◽  
Injury Severity ◽  
Motor Vehicle ◽  
Rib Fractures ◽  
Trauma Patients ◽  
Close Observation ◽  
Motorcycle Crashes ◽  
Level 1 Trauma Center

Rib fractures (RF) are noted in 4 to 12 per cent of trauma admissions. To define RF risks at a Level 1 trauma center, investigators conducted a 10-year (1995–2004) retrospective analysis of all trauma patients. Blunt chest trauma was seen in 13 per cent (1,475/11,533) of patients and RF in 808 patients (55% blunt chest trauma, 7% blunt trauma). RF were observed in 26 per cent of children (<18 years), 56 per cent of adults (18–64 years), and 65 per cent of elderly patients (≥65 years). RF were caused by motorcycle crashes (16%, 57/347), motor vehicle crashes (12%, 411/3493), pedestrian-auto collisions (8%, 31/404), and falls (5%, 227/5018). Mortality was 12 per cent (97/808; children 17%, 8/46; adults 9%, 46/522; elderly 18%, 43/240) and was linearly associated with a higher number of RF (5% 1–2 RF, 15% 3–5 RF, 34% ≥6 RF). Elderly patients had the highest mortality in each RF category. Patients with an injury severity score ≥15 had 20 per cent mortality versus 2.7 per cent with ISS <15 ( P < 0.0001). Increasing age and number of RF were inversely related to the percentage of patients discharged home. ISS, age, number of RF, and injury mechanism determine patients’ course and outcome. Patients with associated injuries, extremes of age, and ≥3 RF should be admitted for close observation.

Analysis of Severity of Young Driver Crashes: Sequential Binary Logistic Regression Modeling

2002 ◽  
Vol 1784 (1) ◽  
pp. 108-114 ◽  
Author(s):  
Sunanda Dissanayake ◽  
John Lu
Keyword(s):  
Logistic Regression ◽  
Injury Severity ◽  
Selection Process ◽  
Model Development ◽  
Weather Condition ◽  
Binary Logistic Regression ◽  
The United States ◽  
Crash Severity ◽  
Young Drivers ◽  
Single Vehicle

Young drivers have the highest fatality involvement rates of any driver age group within the United States driving population. They also experience a higher percentage of single-vehicle crashes compared with others. When looking at the methods of improving this alarming death rate of young drivers, it is important to identify the determinants of higher crash and injury severity. With that intention, the study developed, using the Florida Traffic Crash Database, a set of sequential binary logistic regression models to predict the crash severity outcome of single-vehicle fixed-object crashes involving young drivers. Models were organized from the lowest severity level to the highest and vice versa to examine the reliability of the selection process, but it was found that there was no considerable impact based on this selection. The developed models were validated and the accuracy was tested by using crash data that were not utilized in the model development, and the results were found to be satisfactory. Factors influential in making a crash severity difference to young drivers were then identified through the models. Factors such as influence of alcohol or drugs, ejection in the crash, point of impact, rural crash locations, existence of curve or grade at the crash location, and speed of the vehicle significantly increased the probability of having a more severe crash. Restraint device usage and being a male clearly reduced the tendency of high severity, and some other variables, such as weather condition, residence location, and physical condition, were not important at all.

Analysis of driver injury severity in single-vehicle crashes on rural and urban roadways

2016 ◽  
Vol 94 ◽  
pp. 35-45 ◽  
Author(s):  
Qiong Wu ◽  
Guohui Zhang ◽  
Xiaoyu Zhu ◽  
Xiaoyue Cathy Liu ◽  
Rafiqul Tarefder
Keyword(s):  
Injury Severity ◽  
Vehicle Crashes ◽  
Rural And Urban ◽  
Single Vehicle
Sign in / Sign up

Export Citation Format

Share Document