A literature review of machine learning algorithms for crash injury severity prediction
Introduction: Road traffic crashes represent a major public health concern, so it is of
significant importance to understand the factors associated with the increase of injury …
significant importance to understand the factors associated with the increase of injury …
Severity analysis for large truck rollover crashes using a random parameter ordered logit model
Large truck rollover crashes present significant financial, industrial, and social impacts. This
paper presents an effort to investigate the contributing factors to large truck rollover crashes …
paper presents an effort to investigate the contributing factors to large truck rollover crashes …
A review of naturalistic driving study surrogates and surrogate indicator viability within the context of different road geometries
Advancements in data collection and processing methods have produced large databases
containing high quality vehicular data. Despite this, conventional vehicle-vehicle collisions …
containing high quality vehicular data. Despite this, conventional vehicle-vehicle collisions …
What can we learn from autonomous vehicle collision data on crash severity? A cost-sensitive CART approach
Autonomous vehicles (AVs) are emerging in the automobile industry with potential benefits
to reduce traffic congestion, improve mobility and accessibility, as well as safety. According …
to reduce traffic congestion, improve mobility and accessibility, as well as safety. According …
Crash severity analysis of vulnerable road users using machine learning
Road crash fatality is a universal problem of the transportation system. A massive death toll
caused annually due to road crash incidents, and among them, vulnerable road users (VRU) …
caused annually due to road crash incidents, and among them, vulnerable road users (VRU) …
Analysis of injury severity in rear-end crashes on an expressway involving different types of vehicles using random-parameters logit models with heterogeneity in …
To examine the difference in contributing factors of rear-end crashes of different injury
severity involving different types of vehicles, this paper proposed random-parameters …
severity involving different types of vehicles, this paper proposed random-parameters …
Predicting and analyzing road traffic injury severity using boosting-based ensemble learning models with SHAPley Additive exPlanations
Road traffic accidents are one of the world's most serious problems, as they result in
numerous fatalities and injuries, as well as economic losses each year. Assessing the …
numerous fatalities and injuries, as well as economic losses each year. Assessing the …
Discovering injury severity risk factors in automobile crashes: a hybrid explainable AI framework for decision support
Millions of car crashes occur annually in the US, leaving tens of thousands of deaths and
many more severe injuries. Thus, understanding the most impactful contributors to severe …
many more severe injuries. Thus, understanding the most impactful contributors to severe …
Hybrid feature selection-based machine learning Classification system for the prediction of injury severity in single and multiple-vehicle accidents
To undertake a reliable analysis of injury severity in road traffic accidents, a complete
understanding of important attributes is essential. As a result of the shift from traditional …
understanding of important attributes is essential. As a result of the shift from traditional …
Enhancing work zone crash severity analysis: The role of synthetic minority oversampling technique in balancing minority categories
Road work zones are becoming increasingly common due to the aging infrastructure and
the need for capacity enhancement. They present significant safety risks due to narrow …
the need for capacity enhancement. They present significant safety risks due to narrow …