What can we learn from autonomous vehicle collision data on crash severity? A cost-sensitive CART approach
Autonomous vehicles (AVs) are emerging in the automobile industry with potential benefits
to reduce traffic congestion, improve mobility and accessibility, as well as safety. According …
to reduce traffic congestion, improve mobility and accessibility, as well as safety. According …
Crash injury severity prediction considering data imbalance: A Wasserstein generative adversarial network with gradient penalty approach
Y Li, Z Yang, L Xing, C Yuan, F Liu, D Wu… - Accident Analysis & …, 2023 - Elsevier
For each road crash event, it is necessary to predict its injury severity. However, predicting
crash injury severity with the imbalanced data frequently results in ineffective classifier. Due …
crash injury severity with the imbalanced data frequently results in ineffective classifier. Due …
Analysis of traffic accident causes based on data augmentation and ensemble learning with high-dimensional small-sample data
L Zhu, Z Zhang, D Song, B Chen - Expert Systems with Applications, 2024 - Elsevier
The causes analysis of road traffic accidents is often modelled based on high-dimensional
small-sample data; however, such models often have low predictive accuracy and poor …
small-sample data; however, such models often have low predictive accuracy and poor …
Exploring the effects of stationary camera spots on inferences drawn from real-time crash severity models
This study combined crash reports, land use, real-time traffic, and weather data to form an
integrated database to analyze the severity of crashes taking place on rural highways. As …
integrated database to analyze the severity of crashes taking place on rural highways. As …
Cross-city crash severity analysis with cost-sensitive transfer learning algorithm
Due to the difficulties of data collection in some cities and the relatively small portion of more
severe crashes, this paper proposes a cost-sensitive transfer learning framework for more …
severe crashes, this paper proposes a cost-sensitive transfer learning framework for more …
Machine learning-based injury severity prediction of level 1 trauma center enrolled patients associated with car-to-car crashes in Korea
Injury prediction models enables to improve trauma outcomes for motor vehicle occupants in
accurate decision-making and early transport to appropriate trauma centers. This study aims …
accurate decision-making and early transport to appropriate trauma centers. This study aims …
Identifying factors associated with roadside work zone collisions using machine learning techniques
Identifying factors that are associated with the probability of roadside work zone collisions
enables decision makers to better assess and control the risk of scheduling a particular …
enables decision makers to better assess and control the risk of scheduling a particular …
Multi-Objective Particle Swarm Optimization Based Preprocessing of Multi-Class Extremely Imbalanced Datasets
Today's datasets are usually very large with many features and making analysis on such
datasets is really a tedious task. Especially when performing classification, selecting …
datasets is really a tedious task. Especially when performing classification, selecting …
A deep spatiotemporal approach in maritime accident prediction: A case study of the territorial sea of South Korea
Predicting the risk of maritime accidents is crucial for improving traffic surveillance and
marine safety. The availability of data sources and development of machine learning and …
marine safety. The availability of data sources and development of machine learning and …
[HTML][HTML] Predicting child occupant crash injury severity in the United Arab Emirates using machine learning models for imbalanced dataset
Road traffic crashes have increased over the years leading to greater injury severity among
children who are mostly vehicle occupants in high-income countries. This adversely affects …
children who are mostly vehicle occupants in high-income countries. This adversely affects …