Real-time framework to predict crash likelihood and cluster crash severity
This study proposes a three-stage framework for real-time crash likelihood and severity
prediction. Firstly, a real-time crash likelihood prediction model was developed. Secondly, a …
prediction. Firstly, a real-time crash likelihood prediction model was developed. Secondly, a …
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 …
Real-time crash likelihood prediction using temporal attention–based deep learning and trajectory fusion
P Li, M Abdel-Aty - Journal of transportation engineering, Part A …, 2022 - ascelibrary.org
A crucial component of the proactive traffic safety management system is the real-time crash
likelihood prediction model, which takes real-time traffic data as input and predicts the crash …
likelihood prediction model, which takes real-time traffic data as input and predicts the crash …
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 …
[HTML][HTML] Fatal Crash Occurrence Prediction and Pattern Evaluation by Applying Machine Learning Techniques
Background Highway safety remains a significant issue, with road crashes being a leading
cause of fatalities and injuries. While several studies have been conducted on crash …
cause of fatalities and injuries. While several studies have been conducted on crash …
Utilizing structural equation modeling and segmentation analysis in real-time crash risk assessment on freeways
The study aimed to utilize Structural Equation Modeling (SEM) and K-means clustering for
predicting real-time crash risks on freeways. The SEM was used to transform a number of …
predicting real-time crash risks on freeways. The SEM was used to transform a number of …
How to determine an optimal threshold to classify real-time crash-prone traffic conditions?
One of the proactive approaches in reducing traffic crashes is to identify hazardous traffic
conditions that may lead to a traffic crash, known as real-time crash prediction. Threshold …
conditions that may lead to a traffic crash, known as real-time crash prediction. Threshold …
A hybrid machine learning model for predicting real-time secondary crash likelihood
P Li, M Abdel-Aty - Accident Analysis & Prevention, 2022 - Elsevier
Secondary crashes usually occur within the spatio-temporal impact ranges of primary
crashes, which could cause traffic disturbance and increase traffic safety problems …
crashes, which could cause traffic disturbance and increase traffic safety problems …
Crash severity prediction using two-layer ensemble machine learning model for proactive emergency management
Many unfortunate victims in road traffic crashes do not receive ideal treatment because their
injury severity is not understood at an early stage. Swift crash severity prediction enables …
injury severity is not understood at an early stage. Swift crash severity prediction enables …
[HTML][HTML] Crash prediction for freeway work zones in real time: A comparison between Convolutional Neural Network and Binary Logistic Regression model
J Wang, H Song, T Fu, M Behan, L Jie, Y He… - International journal of …, 2022 - Elsevier
Safety of drivers in freeway work zones has been a problem. Real-time crash prediction
helps prevent crashes before they happen. This paper looks at real-time crash prediction in …
helps prevent crashes before they happen. This paper looks at real-time crash prediction in …