Toward safer highways, application of XGBoost and SHAP for real-time accident detection and feature analysis
Detecting traffic accidents as rapidly as possible is essential for traffic safety. In this study, we
use eXtreme Gradient Boosting (XGBoost)—a Machine Learning (ML) technique—to detect …
use eXtreme Gradient Boosting (XGBoost)—a Machine Learning (ML) technique—to detect …
Highway 4.0: Digitalization of highways for vulnerable road safety development with intelligent IoT sensors and machine learning
Abstract According to United Nations (UN) 2030 agenda, the transportation system needs to
be enhanced for the establishment of access to safe, affordable, accessible, and sustainable …
be enhanced for the establishment of access to safe, affordable, accessible, and sustainable …
Critical review on data-driven approaches for learning from accidents: comparative analysis and future research
Y Niu, Y Fan, X Ju - Safety science, 2024 - Elsevier
Data-driven intelligent technologies are promoting a disruptive digital transformation of
human society. Industrial accident prevention is also amid this change. Although many …
human society. Industrial accident prevention is also amid this change. Although many …
Minimizing cost overrun in rail projects through 5D-BIM: A systematic literature review
Mega projects delivering rail infrastructure are constantly seeking cost-effective and efficient
technologies to sustain the growing population. Building information modeling (BIM) and …
technologies to sustain the growing population. Building information modeling (BIM) and …
[HTML][HTML] Injury severity analysis of highway-rail grade crossing crashes in non-divided two-way traffic scenarios: A random parameters logit model
Highway-rail grade crossing (HRGC) crashes in non-divided two-way traffic scenarios have
caused numerous fatalities and injuries over the years. Although crucial to the safety of …
caused numerous fatalities and injuries over the years. Although crucial to the safety of …
Detecting lane change maneuvers using SHRP2 naturalistic driving data: A comparative study machine learning techniques
Lane change has been recognized as a challenging driving maneuver and a significant
component of traffic safety research. Developing a real-time continuous lane change …
component of traffic safety research. Developing a real-time continuous lane change …
Identifying incident causal factors to improve aviation transportation safety: Proposing a deep learning approach
Aviation is a complicated transportation system, and safety is of paramount importance
because aircraft failure often involves casualties. Prevention is clearly the best strategy for …
because aircraft failure often involves casualties. Prevention is clearly the best strategy for …
Dense traffic detection at highway-railroad grade crossings
In the United States, highway-railroad grade crossings are easily congested, which not only
causes significant traffic delays to travelers but also brings potential threats to the first …
causes significant traffic delays to travelers but also brings potential threats to the first …
A novel deep learning approach to predict crash severity in adverse weather on rural mountainous freeway
The main focus of this study was to develop a robust prediction model based on deep
learning capable of providing timely predictions of injury and fatal crashes in adverse …
learning capable of providing timely predictions of injury and fatal crashes in adverse …
A comprehensive study of macro factors related to traffic fatality rates by XGBoost-based model and GIS techniques
F Jiang, J Ma - Accident Analysis & Prevention, 2021 - Elsevier
With the fast development of economics, road safety is becoming a serious problem.
Exploring macro factors is effective to improve road safety. However, the existing studies …
Exploring macro factors is effective to improve road safety. However, the existing studies …