[HTML][HTML] A new pedestrian crossing level of service (PCLOS) method for promoting safe pedestrian crossing in urban areas

T Ahmed, M Moeinaddini, M Almoshaogeh… - International journal of …, 2021 - mdpi.com
Crosswalks are critical locations in the urban transport network that need to be designed
carefully as pedestrians are directly exposed to vehicular traffic. Although various methods …

A comparative performance of machine learning algorithm to predict electric vehicles energy consumption: A path towards sustainability

I Ullah, K Liu, T Yamamoto… - Energy & …, 2022 - journals.sagepub.com
The rapid growth of transportation sector and related emissions are attracting the attention of
policymakers to ensure environmental sustainability. Therefore, the deriving factors of …

Injury severity prediction of traffic crashes with ensemble machine learning techniques: A comparative study

A Jamal, M Zahid, M Tauhidur Rahman… - … journal of injury …, 2021 - Taylor & Francis
A better understanding of injury severity risk factors is fundamental to improving crash
prediction and effective implementation of appropriate mitigation strategies. Traditional …

Grey wolf optimizer-based machine learning algorithm to predict electric vehicle charging duration time

I Ullah, K Liu, T Yamamoto, M Shafiullah… - Transportation …, 2023 - Taylor & Francis
Precise charging time prediction can effectively mitigate the inconvenience to drivers
induced by inevitable charging behavior throughout trips. Although the effectiveness of the …

Transparent deep machine learning framework for predicting traffic crash severity

K Sattar, F Chikh Oughali, K Assi, N Ratrout… - Neural Computing and …, 2023 - Springer
Abstract Analysis of crash injury severity is a promising research target in highway safety
studies. A better understanding of crash severity risk factors is vital for the proactive …

A comparative study of machine learning classifiers for injury severity prediction of crashes involving three-wheeled motorized rickshaw

M Ijaz, M Zahid, A Jamal - Accident Analysis & Prevention, 2021 - Elsevier
Motorcycles and motorcyclists have a variety of attributes that have been found to be a
potential contributor to the high liability of vulnerable road users (VRUs). Vulnerable Road …

Prioritizing rear-end crash explanatory factors for injury severity level using deep learning and global sensitivity analysis

M Owais, A Alshehri, J Gyani, MH Aljarbou… - Expert Systems with …, 2024 - Elsevier
Traffic accidents are usually unique events with unpredictable geographical and temporal
dimensions; thus, accident injury severity level (INJ-SL) analysis presents formidable …

Variance-based global sensitivity analysis for rear-end crash investigation using deep learning

GS Moussa, M Owais, E Dabbour - Accident Analysis & Prevention, 2022 - Elsevier
Traffic accidents are rare events with inconsistent spatial and temporal dimensions; thus,
accident injury severity (INJ-S) analysis faces a significant challenge in its classification and …

[HTML][HTML] A fuzzy-logic approach based on driver decision-making behavior modeling and simulation

AIM Almadi, RE Al Mamlook, Y Almarhabi, I Ullah… - Sustainability, 2022 - mdpi.com
The present study proposes a decision-making model based on different models of driver
behavior, aiming to ensure integration between road safety and crash reduction based on …

[HTML][HTML] Modeling retroreflectivity degradation of traffic signs using artificial neural networks

A Jamal, I Reza, M Shafiullah - IATSS Research, 2022 - Elsevier
Traffic signs are vital for communicating guidance, rules, warning, and other highway
agency information for safe and efficient navigation through transportation networks. Signs …