Investigating occupant injury severity of truck-involved crashes based on vehicle types on a mountainous freeway: A hierarchical Bayesian random intercept approach

BACKGROUND: Spatial disorientation, poor situational awareness, and aerodynamic stalls are often causal/contributory to general aviation accidents. To mitigate against the occurrence of these mishaps Cirrus Aircraft has, since 2002, introduced advanced avionics into their piston airplanes (Cirrus SR20/22). These airplanes are also certificated to more rigorous crashworthiness tests than legacy aircraft approved prior to these standards being codified. Herein, using for comparison two legacy aircraft fleets manufactured prior to 2002, we determined whether a reduced mishap rate for all accidents or relating to the aforementioned causes/contributing factors and/or diminished injury severity for survivable accidents were evident for Cirrus SR20/22 airplanes.METHODS: Accidents (2008–2017) involving Cirrus SR20/22 airplanes (manufactured 2002 or later) and Beechcraft 35/36 (Bonanza) and Mooney 20 models (both manufactured no later than 2001) (14CFR Part 91 rules) were identified (N = 136, 259, 164, respectively) from the NTSB database. Statistical analyses used Poisson distribution/contingency tables/ t- and Mann-Whitney tests.RESULTS: For each year within the 2013–2017 timespan the Cirrus SR20/22 all-accident rate was diminished 39–75% relative to both legacy fleets. Temporally, the fraction of fatal Cirrus SR20/22 accidents, initially higher, declined 50% achieving a lower, or comparable, proportion to the two legacy airframes. Fatal accident rates involving spatial disorientation/situational awareness/aerodynamic stalls were > 80% lower for Cirrus SR20/22 airplanes. For survivable mishaps, Cirrus SR20/22 aircraft showed a lower proportion (0.13 compared with 0.20–0.35) of fatal/serious injuries.CONCLUSION: Toward improving legacy aircraft safety, owners should be encouraged to upgrade their avionics for mitigating against the occurrence of such human-factor-related mishaps and install airbags to minimize injury severity.Boyd DD, Howell C. Accident rates, causes, and occupant injury involving high-performance general aviation aircraft. Aerosp Med Hum Perform. 2020; 91(5):387–393.

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Use of Real-Time Traffic and Signal Timing Data in Modeling Occupant Injury Severity at Signalized Intersections

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/03611981211047836 ◽

2021 ◽

pp. 036119812110478

Author(s):

Emmanuel Kidando ◽

Angela E. Kitali ◽

Boniphace Kutela ◽

Alican Karaer ◽

Mahyar Ghorbanzadeh ◽

...

Keyword(s):

Real Time ◽

Logistic Model ◽

Injury Severity ◽

Random Effect ◽

Signal Timing ◽

Data Set ◽

Lighting Condition ◽

Real Time Traffic ◽

Timing Data ◽

Occupant Injury

This study explored the use of real-time traffic events and signal timing data to determine the factors influencing the injury severity of vehicle occupants at intersections. The analysis was based on 3 years (2017–2019) of crash and high-resolution traffic data. The best fit regression was first identified by comparing the conventional regression model and logistic models with random effect. The logistic model with a heavy-tailed distribution random effect best fitted the data set, and it was used in the variable assessment. The model results revealed that about 13.6% of the unobserved heterogeneity comes from site-specific variations, which underlines the need to use the logistic model with a random effect. Among the real-time traffic events and signal-based variables, approach delay and platoon ratio significantly influenced the injury severity of vehicle occupants at 90% Bayesian credible interval. Additionally, the manner of a collision, occupant seat position, number of vehicles involved in a crash, gender, age, lighting condition, and day of the week significantly affected the vehicle occupant injury. The study findings are anticipated to provide valuable insights to transportation agencies for developing countermeasures to mitigate the crash severity risk proactively.

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