Exploring Implicit Relationships between Pavement Surface Friction and Vehicle Crash Severity Using Interpretable Extreme Gradient Boosting Method

Pavement friction has been identified as crucial in traffic safety. Since the Highway Safety Manual prediction algorithm is often based on crash frequency, the crash severity distribution might be assumed unchanged before and after the countermeasure. However, pavement surface treatments can improve the friction to different levels, by which crash severity outcomes may vary greatly. To explore the implicit effects of pavement friction on vehicle crash severity, this paper first validates the extreme gradient boosting model performance and then the Shapley additive explanations interaction values are employed to interpret individual features and the nonlinear interactions among predictors. Under various scenarios, the XGBoost output probability is utilized to convert into dynamic crash severity distributions. Results also indicate that friction becomes more significant when the friction number is less than 38, and immediate corrective actions are needed when the friction number is below 20.

Critical Analysis of Prototype Autonomous Vehicle Crash Rates: Six Scientific Studies from 2015–2018

Will Automated Vehicles be Safer than Conventional Vehicles? One of the critically important questions that has emerged about advanced technologies in transportation is how to test the actual effects of these advanced systems on safety, particularly how to evaluate the safety of highly automated driving systems. Richard Young's Critical Analysis of Prototype Autonomous Vehicle Crash Rates does a deep dive into these questions by reviewing and then critically analyzing the first six scientific studies of AV crash rates.

Trends in Cannabis Involvement and Risk of Alcohol Involvement in Motor Vehicle Crash Fatalities in the United States, 2000‒2018

Objectives. To assess cannabis and alcohol involvement among motor vehicle crash (MVC) fatalities in the United States. Methods. In this repeated cross-sectional analysis, we used data from the Fatality Analysis Reporting System from 2000 to 2018. Fatalities were cannabis-involved if an involved driver tested positive for a cannabinoid and alcohol-involved based on the highest blood alcohol concentration (BAC) of an involved driver. Multinomial mixed-effects logistic regression models assessed cannabis as a risk factor for alcohol by BAC level. Results. While trends in fatalities involving alcohol have remained stable, the percentage of fatalities involving cannabis and cannabis and alcohol increased from 9.0% in 2000 to 21.5% in 2018, and 4.8% in 2000 to 10.3% in 2018, respectively. In adjusted analyses, fatalities involving cannabis had 1.56 (95% confidence interval [CI] = 1.48, 1.65), 1.62 (95% CI = 1.52, 1.72), and 1.46 (95% CI = 1.42, 1.50) times the odds of involving BACs of 0.01% to 0.049%, 0.05% to 0.079%, and 0.08% or higher, respectively. Conclusions. The percentage of fatalities involving cannabis and coinvolving cannabis and alcohol doubled from 2000 to 2018, and cannabis was associated with alcohol coinvolvement. Further research is warranted to understand cannabis- and alcohol-involved MVC fatalities. (Am J Public Health. Published online ahead of print October 28, 2021:e1–e10. https://doi.org/10.2105/AJPH.2021.306466 )