of transportation is continuing to grow in popularity, particularly in large cities in the United States and Europe. With this upsurge in popularity, it is important to create a safe environment for all road users. Improvements in the cycling infrastructure (especially the installation of protected bike lanes) reduce hazards not only to cyclists but to pedestrians as well.
  The number of road fatalities have been falling throughout the European Union (EU) over the past 20 years and most Member States have achieved an overall reduction. Research has mainly focused on protecting car occupants, with car occupant fatalities reducing significantly. However, recently there has been a plateauing in fatalities amongst 'Vulnerable Road Users' (VRUs), and in 2016 accidents involving VRUs accounted for nearly half of all EU road deaths.
 
  The SaferWheels study collected in-depth data on 500 accidents involving Powered Two-Wheelers (PTWs) and bicycles across six European countries. A standard in-depth accident investigation methodology was used by each team.  https://www.selleckchem.com/products/bardoxolone.html  The Driver Reliability and Error Analysis Method (DREAM) was used to systematically classify accident causation factors.
 
  The most common causal factors related to errors in observation by the PTW/bicycle rider or the driver of the other vehicle, typically called 'looked but failed to see' accidents. Common scenarios involved the other analyzed by researchers on a case-study basis to gain detailed insights on such accidents. Preliminary analysis suggests that 'looked but failed to see' remains a common cause, and in many cases the actions of the other vehicle were the critical factor, though PTW rider speed or inexperience played a role in some cases. Practical Applications The collected data can be analyzed to better understand the characteristics and causes of accidents involving PTWs and bicycles in the EU. The results can be used to develop policies aimed at reducing road deaths and injuries to VRUs.
  The extremely low accident rate for U.S air carriers relative to that of general aviation (∼1 and ∼60/million flight hours respectively) partly reflects advanced airman certification, more demanding recurrency training and stringent operational regulations. However, whether such skillset/training/regulations translate into improved safety for airline pilots operating in the general aviation environment is unknown and the aim of this study.
 
  Accidents (1998-2017) involving airline pilots and instrument-rated private pilots (PPL-IFR) operating non-revenue light aircraft were identified from the NTSB accident database. An online survey informed general aviation flight exposure for both pilot cohorts. Statistics used proportion testing and Mann-Whitney U tests.
 
  In degraded visibility, 0 and 40% (χ
  p = 0.043) of fatal accidents involving airline and PPL-IFR airmen were due to in-flight loss-of-control, respectively. For landing accidents, airline pilots were under-represented for mishaps related to airspeed usual attitude recovery and managing approach speeds. Airline pilots should seek additional instructional time regarding landing tail-wheel aircraft and become familiar with 14CFR 91 rules covering minimum altitudes.
 These findings inform safety deficiencies for (a) airline pilots, landing/ground operations in tail-wheel aircraft and lack of 14CFR 91 familiarization regulations regarding minimum operating altitudes and (b) PPL-IFR airmen in-flight loss-of-control and poor landing speed management. Practical Applications For PPL-IFR airmen, training/recurrency should focus on unusual attitude recovery and managing approach speeds. Airline pilots should seek additional instructional time regarding landing tail-wheel aircraft and become familiar with 14CFR 91 rules covering minimum altitudes.
  This study evaluates prevalence and trends in distracted driving in Canada based on multiple indicators collected from the Road Safety Monitor (RSM) and Canada's National Fatality Database maintained by the Traffic Injury Research Foundation (TIRF).
 
  Data from the RSM on self-reported distracted driving behaviors were analyzed using multivariate techniques including logistic regression analysis in various years spanning from 2004 to 2019. Data from TIRF's National Fatality Database from 2000 to 2016 were also analyzed using piecewise regression analysis to evaluate trends and prevalence of driver distraction.
 
  Significantly more Canadians reported talking on their phone hands-free or handheld phone while driving in 2019 compared to 2010. There was a 102% increase in the percentage that reported texting while driving in 2019 (9.7%) compared to 2010 (4.8%). For every 10-year increase in age, drivers were 44% less likely to text, 38% less likely to use a handheld phone, and 28% less likely to use a hands-frerms of distracted driving (i.e., texting while driving) is indeed dangerous, there is a minority who are unaware of, or resistant to, this fact. Practical Applications Enforcement activities and education initiatives to combat distracted driving ought to be tailored to the target audience based on the patterns uncovered.
  Bicyclists are more vulnerable compared to other road users. Therefore, it is critical to investigate the contributing factors to bicyclist injury severity to help provide better biking environment and improve biking safety. According to the data provided by National Highway Traffic Safety Administration (NHTSA), a total of 8,028 bicyclists were killed in bicycle-vehicle crashes from 2007 to 2017. The number of fatal bicyclists had increased rapidly by approximately 11.70% during the past 10 years (NHTSA, 2019).
 
  This paper conducts a latent class clustering analysis based on the police reported bicycle-vehicle crash data collected from 2007 to 2014 in North Carolina to identify the heterogeneity inherent in the crash data. First, the most appropriate number of clusters is determined in which each cluster has been characterized by the distribution of the featured variables. Then, partial proportional odds models are developed for each cluster to further analyze the impacts on bicyclist injury severity for specific crash patterns.