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[HTML][HTML] Advances, challenges, and future research needs in machine learning-based crash prediction models: A systematic review
Accurately modelling crashes, and predicting crash occurrence and associated severities
are a prerequisite for devising countermeasures and develo** effective road safety …
are a prerequisite for devising countermeasures and develo** effective road safety …
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 …
Injury severity prediction of traffic crashes with ensemble machine learning techniques: A comparative study
A better understanding of injury severity risk factors is fundamental to improving crash
prediction and effective implementation of appropriate mitigation strategies. Traditional …
prediction and effective implementation of appropriate mitigation strategies. Traditional …
Short-term traffic flow prediction method for urban road sections based on space–time analysis and GRU
G Dai, C Ma, X Xu - IEEE Access, 2019 - ieeexplore.ieee.org
Accurate short-term traffic forecasts help people choose transportation and travel time.
Through the query data, many models for traffic flow prediction have neglected the temporal …
Through the query data, many models for traffic flow prediction have neglected the temporal …
Statistical and machine-learning methods for clearance time prediction of road incidents: A methodology review
Accurate clearance time prediction for road incident would be helpful to evaluate the
incident impacting range and provide route guiding strategy according to the predicted …
incident impacting range and provide route guiding strategy according to the predicted …
[HTML][HTML] Handling imbalanced data in road crash severity prediction by machine learning algorithms
Crash severity is undoubtedly a fundamental aspect of a crash event. Although machine
learning algorithms for predicting crash severity have recently gained interest by the …
learning algorithms for predicting crash severity have recently gained interest by the …
Investigating factors affecting severity of large truck-involved crashes: Comparison of the SVM and random parameter logit model
Introduction: Reducing the severity of crashes is a top priority for safety researchers due to
its impact on saving human lives. Because of safety concerns posed by large trucks and the …
its impact on saving human lives. Because of safety concerns posed by large trucks and the …
Comparative study of machine learning classifiers for modelling road traffic accidents
Road traffic accidents (RTAs) are a major cause of injuries and fatalities worldwide. In recent
years, there has been a growing global interest in analysing RTAs, specifically concerned …
years, there has been a growing global interest in analysing RTAs, specifically concerned …
A hybrid approach of random forest and random parameters logit model of injury severity modeling of vulnerable road users involved crashes
Vulnerable road users (VRUs) involved crashes are a major road safety concern due to the
high likelihood of fatal and severe injury. The use of data-driven methods and heterogeneity …
high likelihood of fatal and severe injury. The use of data-driven methods and heterogeneity …