We estimated how much the Federal government and state/local government pay for different kinds of crashes in the United States. Government costs include reductions in an array of public services (emergency, incident management, vocational rehabilitation, coroner court processing of liability litigation), medical payments, social safety net assistance to the injured and their families, and taxes foregone because victims miss work. Government also pays when its employees crash while working and covers fringe benefits for crash-involved employees and their benefit-eligible dependents in non-work hours. We estimated government shares of crash costs by component. We applied those estimates to existing US Department of Transportation estimates of crash costs to society and employers. Government pays an estimated $35 billion annually because of crashes, an estimated 12.6% of the economic cost of crashes (Federal 7.1%, State/local 5.5%). Government bears a higher percentage of the monetary costs of injury crashes than fatal crashes or crashes involving property damage only. Government is increasingly recovering the medical cost of crashes from auto insurers. Nevertheless, medical costs and income and sales tax losses account for 75% of government's crash costs. For State/local government to break even on a 100%-State funded investment in road safety, the intervention would need to have an unrealistically high benefit-cost ratio of 34. Government invests in medical treatment of illness to save lives and improve quality of life. Curing a child's leukemia, for example, is not less costly than leaving that leukemia untreated. Safety should not be held to a different standard.
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Risk Anal
December 2024
University of Liverpool Management School, University of Liverpool, Liverpool, UK.
Advances in artificial intelligence (AI) are reshaping mobility through autonomous vehicles (AVs), which may introduce risks such as technical malfunctions, cybersecurity threats, and ethical dilemmas in decision-making. Despite these complexities, the influence of consumers' risk preferences on AV acceptance remains poorly understood. This study explores how individuals' risk preferences affect their choices among private AVs (PAVs), shared AVs (SAVs), and private conventional vehicles (PCVs).
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December 2024
School of Vehicle and Mobility, Tsinghua University, Beijing, China.
Multifarious applications of unmanned aerial vehicles (UAVs) are thriving in extensive fields and facilitating our lives. However, the potential third-party risks (TPRs) on the ground are neglected by developers and companies, which limits large-scale commercialization. Risk assessment is an efficacious method for mitigating TPRs before undertaking flight tasks.
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December 2024
Injury Division, The George Institute for Global Health, Faculty of Medicine and Health, UNSW.
Objective: Incorrect use of child restraints is a long-standing issue, limiting the protection offered by child restraints in the event of a crash. Child restraint fitting services are a measure to reduce incorrect use but have limited reach and availability to underserved populations. Virtual child restraint fitting services have the potential to increase the reach and availability, but as with any digital intervention, need to be acceptable to users to be effective.
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December 2024
Department of Orthopaedic Surgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Objectives: Electric biking (e-biking) is a rapidly growing recreation, sport, and mode of transportation that often presents to emergency departments (EDs) with high-impact head injuries. This study aimed to evaluate the epidemiology of e-bike-related concussions and closed-head injuries (CHI) to inform more effective injury prevention strategies.
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Accid Anal Prev
February 2025
School of Civil & Environment Engineering, Queensland University of Technology, 2 George Street, Brisbane, 4000 QLD, Australia. Electronic address:
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