Predicting motorcycle crash injury severity using weather data and alternative Bayesian multivariate crash frequency models

2017/09/06 by Wen Cheng, Gurdiljot Singh Gill, Taha Sakrani +2 · 11 citations
Engineering · Medicine · Agricultural and Biological Sciences · #Traffic and Road Safety #Injury Epidemiology and Prevention #Agriculture and Farm Safety

paper · doi:10.1016/j.aap.2017.08.032

Cited by

• Safety Analysis of Motorcycle Crashes in Seoul Metropolitan Area, South Korea: An Application of Nonlinear Optimal Scaling Methods. [europepmc]
• Predicting and Interpreting Spatial Accidents through MDLSTM. [europepmc]
• A Comprehensive Review on the Behaviour of Motorcyclists: Motivations, Issues, Challenges, Substantial Analysis and Recommendations. [europepmc]
• Association of Air Pollution and Weather Factors with Traffic Injury Severity: A Study in Taiwan. [europepmc]
• Environmental Factors Associated with Severe Motorcycle Crash Injury in University Neighborhoods: A Multicenter Study in Taiwan. [europepmc]
• Assessment of Two-Vehicle and Multi-Vehicle Freeway Rear-End Crashes in China: Accommodating Spatiotemporal Shifts. [europepmc]
• Analyzing the Prevalence of and Factors Associated with Road Traffic Crashes (RTCs) among Motorcyclists in Bangladesh. [europepmc]
• The effects of weather factors on road traffic casualties: Analysis on provincial panel data of China from 2006 to 2021. [europepmc]
• Factors influencing injury severity in three-wheeled motorized rickshaw and motorcycle collisions. [europepmc]
• Investigating factors influencing injury severity in crashes involving vulnerable road users in Pakistan. [europepmc]
• Motorized Two-Wheeled Vehicles Contribute Disproportionately to the Increase in Pandemic-Period Road Traffic Fatalities in New York State. [europepmc]