Learning spatial patterns and temporal dependencies for traffic accident severity prediction: A deep learning approach
Traffic accidents have a substantial impact on human life and property, resulting in millions
of injuries every year. To ensure road safety and enhance the research in this direction, it is …
of injuries every year. To ensure road safety and enhance the research in this direction, it is …
DTIN: Dual Transformer-based Imputation Nets for multivariate time series emitter missing data
Z Sun, H Li, W Wang, J Liu, X Liu - Knowledge-Based Systems, 2024 - Elsevier
As a kind of multivariate time series (MTS) data, emitter signals often exhibit missing or
corrupt values, posing serious challenges to emitter data research such as specific emitter …
corrupt values, posing serious challenges to emitter data research such as specific emitter …
A novel generative adversarial network for improving crash severity modeling with imbalanced data
Traffic crash data is often greatly imbalanced with the majority of non-fatal crashes and only
a small number of fatal crashes. Such data imbalance issue poses a challenge for crash …
a small number of fatal crashes. Such data imbalance issue poses a challenge for crash …
Comparison of cluster-based sampling approaches for imbalanced data of crashes involving large trucks
SAS Tahfim, Y Chen - Information, 2024 - mdpi.com
Severe and fatal crashes involving large trucks result in significant social and economic
losses for human society. Unfortunately, the notably low proportion of severe and fatal injury …
losses for human society. Unfortunately, the notably low proportion of severe and fatal injury …
A Generative Deep Learning Approach for Crash Severity Modeling with Imbalanced Data
Crash data is often greatly imbalanced, with the majority of crashes being non-fatal crashes,
and only a small number being fatal crashes due to their rarity. Such data imbalance issue …
and only a small number being fatal crashes due to their rarity. Such data imbalance issue …
Analysis of factors influencing the degree of accidental injury of bicycle riders considering data heterogeneity and imbalance
X Dong, D Zhang, C Wang, T Zhang - PLoS one, 2024 - journals.plos.org
Bicycle safety has emerged as a pressing concern within the vulnerable transportation
community. Numerous studies have been conducted to identify the significant factors that …
community. Numerous studies have been conducted to identify the significant factors that …
Comparative Study for Optimized Deep Learning-Based Road Accidents Severity Prediction Models
H Hijazi, K Sattar, HM Al-Ahmadi, S El-Ferik - Arabian Journal for Science …, 2024 - Springer
Road traffic accidents remain a major cause of fatalities and injuries worldwide. Effective
classification of accident type and severity is crucial for prompt post-accident protocols and …
classification of accident type and severity is crucial for prompt post-accident protocols and …
Road Crash Injury Severity Prediction Using a Graph Neural Network Framework
Crash severity prediction is a challenging research area, where the objective is to accurately
assess the extent of severity of an injury resulting from road traffic accidents. The main aim of …
assess the extent of severity of an injury resulting from road traffic accidents. The main aim of …
Predicting Pedestrian Involvement in Fatal Crashes Using a TabNet Deep Learning Model
To make road transportation systems safe for pedestrians, understanding the contributing
features in vehicle-pedestrian fatal crashes is critical. With a better prediction model, it is …
features in vehicle-pedestrian fatal crashes is critical. With a better prediction model, it is …
[HTML][HTML] Prediction of the Road Accidents Severity Level: Case of Saint-Petersburg and Leningrad Oblast.
A Skhvediani, M Rodionova, N Savchenko… - International Journal …, 2023 - ijtech.eng.ui.ac.id
This article examines the factors influencing the severity of road accidents in St. Petersburg
and Leningrad oblast for 2015–2023. The study is carried out on the analysis of 69190 road …
and Leningrad oblast for 2015–2023. The study is carried out on the analysis of 69190 road …