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 …
Road traffic accidents: An overview of data sources, analysis techniques and contributing factors
Road traffic accidents are one among the world's leading causes of injuries and fatalities
and hence represent an important field of research towards the use of traffic accident …
and hence represent an important field of research towards the use of traffic accident …
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 …
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 …
Machine learning approaches to traffic accident analysis and hotspot prediction
Traffic accidents are one of the most important concerns of the world, since they result in
numerous casualties, injuries, and fatalities each year, as well as significant economic …
numerous casualties, injuries, and fatalities each year, as well as significant economic …
Different ways… same message? Road safety-targeted communication strategies in Spain over 62 years (1960–2021)
Among the most generalised preventive measures against traffic crashes, advertisements
and broadcast campaigns in the media have stood out over the last six decades. The core …
and broadcast campaigns in the media have stood out over the last six decades. The core …
SARIMA modelling approach for forecasting of traffic accidents
N Deretić, D Stanimirović, MA Awadh, N Vujanović… - Sustainability, 2022 - mdpi.com
To achieve greater sustainability of the traffic system, the trend of traffic accidents in road
traffic was analysed. Injuries from traffic accidents are among the leading factors in the …
traffic was analysed. Injuries from traffic accidents are among the leading factors in the …
[HTML][HTML] A review on neural network techniques for the prediction of road traffic accident severity
The occurrence rate of death and injury due to road traffic accidents is rising increasingly
globally day by day. For several decades, the focus of research has been on getting a …
globally day by day. For several decades, the focus of research has been on getting a …
Deep learning ensemble model for the prediction of traffic accidents using social media data
Traffic accidents are a major concern worldwide, since they have a significant impact on
people's safety, health, and well-being, and thus, they constitute an important field of …
people's safety, health, and well-being, and thus, they constitute an important field of …
[HTML][HTML] Research on the big data of traditional taxi and online car-hailing: A systematic review
T Lyu, PS Wang, Y Gao, Y Wang - Journal of Traffic and Transportation …, 2021 - Elsevier
The purpose of this paper is to provide a summary of a quick overview of the latest
developments and unprecedented opportunities for scholars who want to set foot in the field …
developments and unprecedented opportunities for scholars who want to set foot in the field …