Recent advances in traffic accident analysis and prediction: a comprehensive review of machine learning techniques

N Behboudi, S Moosavi, R Ramnath - arxiv preprint arxiv:2406.13968, 2024 - arxiv.org
Traffic accidents pose a severe global public health issue, leading to 1.19 million fatalities
annually, with the greatest impact on individuals aged 5 to 29 years old. This paper …

Analyzing the transition from two-vehicle collisions to chain reaction crashes: A hybrid approach using random parameters logit model, interpretable machine learning …

SA Samerei, K Aghabayk - Accident Analysis & Prevention, 2024 - Elsevier
Chain reaction crashes (CRC) begin with a two-vehicle collision and rapidly intensify as
more vehicles get directly involved. CRCs result in more extensive damage compared to two …

Real-time accident anticipation for autonomous driving through monocular depth-enhanced 3D modeling

H Liao, Y Li, Z Li, Z Bian, J Lee, Z Cui, G Zhang… - Accident Analysis & …, 2024 - Elsevier
The primary goal of traffic accident anticipation is to foresee potential accidents in real time
using dashcam videos, a task that is pivotal for enhancing the safety and reliability of …

[HTML][HTML] Machine learning for predictions of road traffic accidents and spatial network analysis for safe routing on accident and congestion-prone road networks

Y Berhanu, D Schröder, BT Wodajo, E Alemayehu - Results in Engineering, 2024 - Elsevier
Road traffic accidents (RTAs) and the resulting traffic congestion are global concerns mainly
in metropolitan environments. The need for road safety is directly correlated with the rapidly …

Enhancing work zone crash severity analysis: The role of synthetic minority oversampling technique in balancing minority categories

M Adeel, AJ Khattak, S Mishra, D Thapa - Accident Analysis & Prevention, 2024 - Elsevier
Road work zones are becoming increasingly common due to the aging infrastructure and
the need for capacity enhancement. They present significant safety risks due to narrow …

Investigating older driver crashes on high-speed roadway segments: a hybrid approach with extreme gradient boosting and random parameter model

A Hossain, X Sun, S Das, M Jafari… - … A: Transport Science, 2024 - Taylor & Francis
Older drivers are often more susceptible to crashes due to age-related physical and
cognitive limitations, particularly in complex driving environments. Considering the limited …

Analyzing urban traffic crash patterns through spatio-temporal data: A city-level study using a sparse non-negative matrix factorization model with spatial constraints …

J **, P Liu, H Huang, Y Dong - Applied Geography, 2024 - Elsevier
Urban traffic crashes represent a significant challenge affecting public safety and urban
mobility worldwide. This study introduces a novel application of Sparse Non-negative Matrix …

A hybrid Machine learning and statistical modeling approach for analyzing the crash severity of mobility scooter users considering temporal instability

M Sadeghi, K Aghabayk, M Quddus - Accident Analysis & Prevention, 2024 - Elsevier
One of the main objectives in improving the quality of life for individuals with disabilities,
especially those experiencing mobility issues such as the elderly, is to enhance their day-to …

[HTML][HTML] Machine learning assisted crystal structure prediction made simple

CN Li, HP Liang, BQ Zhao, SH Wei… - Journal of Materials …, 2024 - oaepublish.com
Crystal structure prediction (CSP) plays a crucial role in condensed matter physics and
materials science, with its importance evident not only in theoretical research but also in the …

LSTM Transformer Real-Time Crash Risk Evaluation Using Traffic Flow and Risky Driving Behavior Data

L Han, M Abdel-Aty, R Yu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Crash risk evaluation studies mainly established the relationship between the macro traffic
status and crashes. However, the impact of risky driving behavior, a significant factor in …