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 …
Data-driven approaches for road safety: A comprehensive systematic literature review
Road crashes cost over a million lives each year. Consequently, researchers and transport
engineers continue their efforts to improve road safety and minimize road crashes. With the …
engineers continue their efforts to improve road safety and minimize road crashes. With the …
Graph neural networks for intelligent transportation systems: A survey
Graph neural networks (GNNs) have been extensively used in a wide variety of domains in
recent years. Owing to their power in analyzing graph-structured data, they have become …
recent years. Owing to their power in analyzing graph-structured data, they have become …
A comparison of statistical learning methods for deriving determining factors of accident occurrence from an imbalanced high resolution dataset
One of the main aims of accident data analysis is to derive the determining factors
associated with road traffic accident occurrence. While current studies mainly use variants of …
associated with road traffic accident occurrence. While current studies mainly use variants of …
Graph deep learning model for network-based predictive hotspot mapping of sparse spatio-temporal events
The predictive hotspot mapping of sparse spatio-temporal events (eg, crime and traffic
accidents) aims to forecast areas or locations with higher average risk of event occurrence …
accidents) aims to forecast areas or locations with higher average risk of event occurrence …
Inferring high-resolution traffic accident risk maps based on satellite imagery and GPS trajectories
Traffic accidents cost about 3% of the world's GDP and are the leading cause of death in
children and young adults. Accident risk maps are useful tools to monitor and mitigate …
children and young adults. Accident risk maps are useful tools to monitor and mitigate …
[HTML][HTML] IoT-based emergency vehicle services in intelligent transportation system
Emergency Management System (EMS) is an important component of Intelligent
transportation systems, and its primary objective is to send Emergency Vehicles (EVs) to the …
transportation systems, and its primary objective is to send Emergency Vehicles (EVs) to the …
Overfitting prevention in accident prediction models: Bayesian regularization of artificial neural networks
N Fiorentini, D Pellegrini… - Transportation research …, 2023 - journals.sagepub.com
In the present paper, we implemented the Bayesian regularization (BR) backpropagation
algorithm for calibrating an artificial neural network (ANN) as an accident prediction model …
algorithm for calibrating an artificial neural network (ANN) as an accident prediction model …
Development of an accident prediction model for Italian freeways
F La Torre, M Meocci, L Domenichini, V Branzi… - Accident Analysis & …, 2019 - Elsevier
The roadway safety management process plays an important role in the national efforts for
improving road safety along the Italian freeway network. In 2016, 8.3% of the overall Italian …
improving road safety along the Italian freeway network. In 2016, 8.3% of the overall Italian …
Vehicle detection and accident prediction in sand/dust storms
A Singh, DP Kumar, K Shivaprasad… - 2021 International …, 2021 - ieeexplore.ieee.org
In this era of a smart and modern world that is designed by progressing technology,
automated vehicles would become a precious part of it. The first thing that strikes in our …
automated vehicles would become a precious part of it. The first thing that strikes in our …