[HTML][HTML] A review on neural network techniques for the prediction of road traffic accident severity

ME Shaik, MM Islam, QS Hossain - Asian Transport Studies, 2021 - Elsevier
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 …

[HTML][HTML] A study on road accident prediction and contributing factors using explainable machine learning models: Analysis and performance

S Ahmed, MA Hossain, SK Ray, MMI Bhuiyan… - Transportation research …, 2023 - Elsevier
Road accidents are increasing worldwide and are causing millions of deaths each year.
They impose significant financial and economic expenses on society. Existing research has …

Intelligent transportation and control systems using data mining and machine learning techniques: A comprehensive study

NO Alsrehin, AF Klaib, A Magableh - IEEE Access, 2019 - ieeexplore.ieee.org
Traffic congestion is becoming the issues of the entire globe. This study aims to explore and
review the data mining and machine learning technologies adopted in research and industry …

[HTML][HTML] Machine learning for road traffic accident improvement and environmental resource management in the transportation sector

M Megnidio-Tchoukouegno, JA Adedeji - Sustainability, 2023 - mdpi.com
Despite the measures put in place in different countries, road traffic fatalities are still
considered one of the leading causes of death worldwide. Thus, the reduction of traffic …

[PDF][PDF] Driving pattern profiling and classification using deep learning

M Malik, R Nandal, S Dalal, V Jalglan… - Intelligent Automation & …, 2021 - academia.edu
The last several decades have witnessed an exponential growth in the means of transport
globally, shrinking geographical distances and connecting the world. The automotive …

Relationship between road traffic features and accidents: An application of two-stage decision-making approach for transportation engineers

SAR Shah, N Ahmad, Y Shen, MA Kamal… - Journal of Safety …, 2019 - Elsevier
Introduction: An efficient decision-making process is one of the major necessities of road
safety performance analysis for human safety and budget allocation procedure. Method …

Sdcae: Stack denoising convolutional autoencoder model for accident risk prediction via traffic big data

C Chen, X Fan, C Zheng, L Xiao… - … on advanced cloud …, 2018 - ieeexplore.ieee.org
Traffic accident is considered as one of main causes for traffic congestion in cities. There are
many causal factors that may give rise to traffic accidents, eg driver characteristics, road …

[HTML][HTML] Safety evaluation of centerline rumble strips on rural two-lane undivided highways: Application of intervention time series analysis

A Hossain, X Sun, A Rahman, S Khanal - IATSS research, 2023 - Elsevier
Centerline rumble strips are low-cost effective countermeasures installed on the center of
the highway segments to reduce crashes, especially roadway departure crashes. For safety …

Predicting road traffic accidents using artificial neural network models

B García de Soto, A Bumbacher… - Infrastructure Asset …, 2018 - icevirtuallibrary.com
As of 2015, Switzerland's road network was among the safest when compared to other
European countries. Nonetheless, the endeavour to further decrease the number of traffic …

[HTML][HTML] Road infrastructure analysis with reference to traffic stream characteristics and accidents: An application of benchmarking based safety analysis and …

SAR Shah, N Ahmad - Applied Sciences, 2019 - mdpi.com
Road infrastructure sustainability is directly associated with the safety of human beings. As a
transportation engineer and policymaker, it is necessary to optimize the funding mechanism …