All-terrain vehicles (ATVs) have become well recognized as associated with injuries. This recognition has resulted in attempts at education and regulation to reduce the number and severity of injuries and number of deaths. The Marshfield Clinic and St. Joseph's Hospital surveyed all-terrain vehicle accidents in the Emergency Department in 1985 and again in 1988 and followed these patients for at least 1 year after the injury. Between the two dates, extensive educational and legislative activity had taken place. The actual number of all-terrain vehicle accidents had increased. The characteristics of victims who were involved in all-terrain vehicle accidents did not change. The actual number of accidents associated with three-wheeled ATVs did not appreciably decrease but the number of accidents associated with four-wheeled ATVs did increase. To date, it is not clear that legislative and educational activities are effective in reducing the number of ATV accidents or in changing the pattern of the accidents.
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Sensors (Basel)
December 2024
Institute of Automotive Engineering, Jiangsu University, Zhenjiang 212013, China.
To address the shortcomings of light detection and ranging (LiDAR) sensors in extracting road surface elevation information in front of a vehicle, a scheme for digital terrain construction based on the fusion of an Inertial Measurement Unit (IMU) and LiDAR perception is proposed. First, two sets of sensor coordinate systems were configured, and the parameters of LiDAR and IMU were calibrated. Then, a terrain construction system based on the fusion perception of IMU and LiDAR was established, and improvements were made to the state estimation and mapping architecture.
View Article and Find Full Text PDFSci Rep
December 2024
New Technology Research Institute, BYD Auto Industry Co., Ltd., Shenzhen, 518118, China.
Effective road terrain recognition is crucial for enhancing the driving safety, passability, and comfort of autonomous vehicles. This study addresses the challenges of accurately identifying diverse road surfaces using deep learning in complex environments. We introduce a novel end-to-end Tire Noise Recognition Residual Network (TNResNet) integrated with a time-frequency attention module, designed to capture and leverage time-frequency information from tire noise signals for road terrain classification.
View Article and Find Full Text PDFInj Prev
December 2024
Direction de la sécurité dans le loisir et le sport, Ministère de l'Éducation du Québec, Trois-Rivières, Québec, Canada.
Background: Unintentional injury deaths in sport and recreation represent a significant public health concern. This study analysed coronial recommendations related to such deaths, focusing on case specifics and recurring themes from January 2006 to December 2019.
Methods: This mixed-methods study used data from the Bureau du coroner du Québec.
J Pediatr Orthop B
December 2024
Department of Orthopaedic Surgery, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA.
All-terrain vehicle (ATV) accidents frequently cause orthopedic injuries. Previous studies have reported the frequency of fractures in ATV injuries. No studies have provided detailed assessments of fracture patterns, types of operative intervention, or risks for multiple surgeries.
View Article and Find Full Text PDFAccid Anal Prev
December 2024
Traffic Engineering and Safety, CSIR-Central Road Research Institute, India.
Driving is a multifaceted activity involving a complex interplay of cognitive, perceptual, and motor skills, demanding continuous attention on the road. In recent years, the increased integration of automation and digitalization technologies in vehicles has improved drivers' convenience and safety. However, the spare attentional capacity available during automation and the prevalence of various infotainment systems in vehicles enable drivers to perform some secondary tasks not related to driving, which may divert their attention away from the road, increasing the chances of accidents.
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