Characteristics of animal-related motor vehicle crashes in select National Park Service units—United States, 1990–2013

Cherry, Cara C.; Dietz, Stephanie; Sauber-Schatz, Erin K.; Russell, Samuel P.; Proctor, Jennifer L.; Buttke, Danielle

doi:10.1080/15389588.2018.1508835

Cited by 12 publications

(6 citation statements)

References 4 publications

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“…Installation of road side barriers in high risk zones could also prevent drivers from veering into oncoming traffic or trees at the roadside while avoiding a kangaroo. While installation of under or overpasses to allow animals to cross roads can reduce risk in some settings [ 45 ], this is not feasible for Australia’s extensive rural road network [ 44 ]. Moreover, those roadside barriers would need to account for the capacity of kangaroos to jump 2–3 metres in height.…”

Section: Discussionmentioning

confidence: 99%

Classification of road traffic injury collision characteristics using text mining analysis: Implications for road injury prevention

2021

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Road traffic injuries are a leading cause of morbidity and mortality globally. Understanding circumstances leading to road traffic injury is crucial to improve road safety, and implement countermeasures to reduce the incidence and severity of road trauma. We aimed to characterise crash characteristics of road traffic collisions in Victoria, Australia, and to examine the relationship between crash characteristics and fault attribution. Data were extracted from the Victorian State Trauma Registry for motor vehicle drivers, motorcyclists, pedal cyclists and pedestrians with a no-fault compensation claim, aged > = 16 years and injured 2010–2016. People with intentional injury, serious head injury, no compensation claim/missing injury event description or who died < = 12-months post-injury were excluded, resulting in a sample of 2,486. Text mining of the injury event using QDA Miner and Wordstat was used to classify crash circumstances for each road user group. Crashes in which no other was at fault included circumstances involving lost control or avoiding a hazard, mechanical failure or medical conditions. Collisions in which another was predominantly at fault occurred at intersections with another vehicle entering from an adjacent direction, and head-on collisions. Crashes with higher prevalence of unknown fault included multi-vehicle collisions, pedal cyclists injured in rear-end collisions, and pedestrians hit while crossing the road or navigating slow traffic areas. We discuss several methods to promote road safety and to reduce the incidence and severity of road traffic injuries. Our recommendations take into consideration the incidence and impact of road trauma for different types of road users, and include engineering and infrastructure controls through to interventions targeting or accommodating human behaviour.

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Section: Discussionmentioning

confidence: 99%

Classification of road traffic injury collision characteristics using text mining analysis: Implications for road injury prevention

2021

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“…The authors suggest improved coordination between the laws relating to AVCs and human safety along with better management practices for abandoned domesticated animals. Cherry et al aimed to describe conditions and circumstances involving AVCs using U.S. National Park Service (NPS) law enforcement motor vehicle crash (MVC) data to guide traffic and wildlife management for the prevention of AVCs in select NPS units ( 20 ). Northeast and intermountain NPS regions had the largest percentage of the total AVC burden.…”

Section: Literature Reviewmentioning

confidence: 99%

Applying Data Mining Methods to Explore Animal-Vehicle Crashes

Rahman

Das

Codjoe

et al. 2023

Transportation Research Record: Journal of the Transportation R

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Animal-vehicle crashes (AVCs) are a significant issue in Louisiana that requires attention. Data on AVCs that occurred from 2015 to 2020 were obtained from the Louisiana Department of Transportation and Development (DOTD), including 14,349 crashes with major injury (KA), minor injury (BC), and no injury (O) severity groups. Aiming to find the collective association of attributes from AVC data, which are categorical in nature, this study utilized two data mining methods: multiple correspondence analysis (MCA) and association rule mining (ARM). Five hierarchical clusters that were generated from the BC and O AVC datasets were particularly significant. Among several other findings, MCA revealed that BC and O AVCs are more concentrated on parish roads during the spring season, while O AVCs in the fall and winter tend to occur on highways with speed limits of 50 mph or higher. ARM revealed that moderate-speed parish roads are frequently associated with KA and BC AVCs, particularly in residential areas and during the spring season, and they often involve young drivers. The findings of this study can be particularly beneficial by considering the spatiotemporal factors associated with animal concentration and movement to develop targeted interventions and mitigation strategies.

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“…Trend analysis is also applied to a study by Cherry et al (2019), which focuses on the settings and parameters that influence the number of AVC in the National Park Service (NPC) in the United States for data between 1990 to 2013, using the statistical method -Pearson's chi-square. The work successfully points out that the seasonality pattern is the main condition that affects the number of AVC in NPC.…”

Section: Trend and Characteristic Study Of Avcmentioning

confidence: 99%

Review of Current Animal-Vehicle Collision (AVC) Studies

Said

Mohd²,

Faye³

et al. 2021

JSAEM

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Animal-Vehicle Collision (AVC) is one of the widest and foremost research segments in the road safety research area. This paper aims to give a critical review of highlighted points and characteristics of different types of research that is within the AVC research segment. There are distinctively four categories of AVC research namely: trend and characteristic of AVC study, AVC spatial modeling study, human-animal behavioral study, and AVC mitigation study. Specific traits of each category are explored and related reported data are presented. In conclusion, each category of AVC research required further analysis especially on gathering comprehensive field data and records.

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Characteristics of animal-related motor vehicle crashes in select National Park Service units—United States, 1990–2013

Cited by 12 publications

References 4 publications

Classification of road traffic injury collision characteristics using text mining analysis: Implications for road injury prevention

Classification of road traffic injury collision characteristics using text mining analysis: Implications for road injury prevention

Applying Data Mining Methods to Explore Animal-Vehicle Crashes

Review of Current Animal-Vehicle Collision (AVC) Studies

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