Machine learning methods to analyze injury severity of drivers from different age and gender groups
Access to non-biased and accurate models capable of predicting driver injury severity of
collision events is vital for determining what safety measures should be implemented at …
collision events is vital for determining what safety measures should be implemented at …
Classification tree modeling to identify severe and moderate vehicular injuries in young and middle-aged adults
OBJECTIVES: Motor vehicle crashes are a leading cause of mortality and morbidity
worldwide. Even though trauma centers provide the gold standard of care for motor vehicle …
worldwide. Even though trauma centers provide the gold standard of care for motor vehicle …
Crash severity analysis of rear-end crashes in California using statistical and machine learning classification methods
Investigating drivers' injury level and detecting contributing factors that aggravate the
damage level imposed on drivers and vehicles is a critical subject in the field of crash …
damage level imposed on drivers and vehicles is a critical subject in the field of crash …
Prediction and factor identification for crash severity: comparison of discrete choice and tree-based models
Crash severity is one of the most widely studied topics in traffic safety area. Scholars have
studied crash severity through various types of models. Using the publicly available 2017 …
studied crash severity through various types of models. Using the publicly available 2017 …
[HTML][HTML] Factor identification and prediction for teen driver crash severity using machine learning: A case study
Crashes among young and inexperienced drives are a major safety problem in the United
States, especially in an area with large rural road networks, such as West Texas. Rural …
States, especially in an area with large rural road networks, such as West Texas. Rural …
Comparison of four statistical and machine learning methods for crash severity prediction
A Iranitalab, A Khattak - Accident Analysis & Prevention, 2017 - Elsevier
Crash severity prediction models enable different agencies to predict the severity of a
reported crash with unknown severity or the severity of crashes that may be expected to …
reported crash with unknown severity or the severity of crashes that may be expected to …
Considering demographics of other involved drivers in predicting the highest driver injury severity in multi-vehicle crashes on rural two-lane roads in California
The injury severity of a driver in a crash is significantly related to the driver's age and gender
and vehicle characteristics. Previous studies have used only information about the most …
and vehicle characteristics. Previous studies have used only information about the most …
Comparing prediction performance for crash injury severity among various machine learning and statistical methods
Crash injury severity prediction is a promising research target in traffic safety. Traditionally,
various statistical methods were used for modeling crash injury severities. In recent years …
various statistical methods were used for modeling crash injury severities. In recent years …
[HTML][HTML] Predicting road crash severity using classifier models and crash hotspots
The rapid increase in traffic volume on urban roads, over time, has altered the global traffic
scenario. Additionally, it has increased the number of road crashes, some of which are …
scenario. Additionally, it has increased the number of road crashes, some of which are …
Using latent class analysis and mixed logit model to explore risk factors on driver injury severity in single-vehicle crashes
The single-vehicle crash has been recognized as a critical crash type due to its high fatality
rate. In this study, a two-year crash dataset including all single-vehicle crashes in New …
rate. In this study, a two-year crash dataset including all single-vehicle crashes in New …