[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 developing effective road safety …
are a prerequisite for devising countermeasures and developing effective road safety …
Transparent deep machine learning framework for predicting traffic crash severity
Abstract Analysis of crash injury severity is a promising research target in highway safety
studies. A better understanding of crash severity risk factors is vital for the proactive …
studies. A better understanding of crash severity risk factors is vital for the proactive …
Classification of truck-involved crash severity: Dealing with missing, imbalanced, and high dimensional safety data
While the cost of road traffic fatalities in the US surpasses $240 billion a year, the availability
of high-resolution datasets allows meticulous investigation of the contributing factors to …
of high-resolution datasets allows meticulous investigation of the contributing factors to …
[HTML][HTML] Developing new hybrid grey wolf optimization-based artificial neural network for predicting road crash severity
With more cars on the road and an increasing travel rate, one of the main issues in
transportation engineering is how to make roads safe. The evaluation of the level of road …
transportation engineering is how to make roads safe. The evaluation of the level of road …
A data-driven, kinematic feature-based, near real-time algorithm for injury severity prediction of vehicle occupants
Q Wang, S Gan, W Chen, Q Li, B Nie - Accident Analysis & Prevention, 2021 - Elsevier
Accurate real-time prediction of occupant injury severity in unavoidable collision scenarios is
a prerequisite for enhancing road traffic safety with the development of highly automated …
a prerequisite for enhancing road traffic safety with the development of highly automated …
Machine Learning Insights on Driving Behaviour Dynamics among Germany, Belgium, and UK Drivers
The i-DREAMS project has a core objective: to establish a comprehensive framework that
defines, develops, and validates a context-aware 'Safety Tolerance Zone'(STZ). This zone is …
defines, develops, and validates a context-aware 'Safety Tolerance Zone'(STZ). This zone is …
Forecasting road traffic accident using deep artificial neural network approach in case of Oromia Special Zone
Millions of people are dying, and billions of properties are damaged by road traffic accidents
each year worldwide. In the case of our country Ethiopia, the effect of traffic accidents is even …
each year worldwide. In the case of our country Ethiopia, the effect of traffic accidents is even …
Recent Advances in Traffic Accident Analysis and Prediction: A Comprehensive Review of Machine Learning Techniques
Traffic accidents pose a severe global public health issue, leading to 1.19 million fatalities
annually, with the greatest impact on individuals aged 5 to 29 years old. This paper …
annually, with the greatest impact on individuals aged 5 to 29 years old. This paper …
Boosting Ensemble Learning for Freeway Crash Classification under Varying Traffic Conditions: A Hyperparameter Optimization Approach
Freeway crashes represent a significant and persistent threat to road safety, resulting in both
loss of life and extensive property damage. Effectively addressing this critical issue requires …
loss of life and extensive property damage. Effectively addressing this critical issue requires …
Risk levels classification of near-crashes in Naturalistic driving data
HAH Naji, Q Xue, N Lyu, X Duan, T Li - Sustainability, 2022 - mdpi.com
Identifying dangerous events from driving behavior data has become a vital challenge in
intelligent transportation systems. In this study, we compared machine and deep learning …
intelligent transportation systems. In this study, we compared machine and deep learning …