A new pedestrian crossing level of service (PCLOS) method for promoting safe pedestrian crossing in urban areas
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 …
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
The rapid growth of transportation sector and related emissions are attracting the attention of
policymakers to ensure environmental sustainability. Therefore, the deriving factors 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 better understanding of injury severity risk factors is fundamental to improving crash
prediction and effective implementation of appropriate mitigation strategies. Traditional …
prediction and effective implementation of appropriate mitigation strategies. Traditional …
Grey wolf optimizer-based machine learning algorithm to predict electric vehicle charging duration time
Precise charging time prediction can effectively mitigate the inconvenience to drivers
induced by inevitable charging behavior throughout trips. Although the effectiveness of the …
induced by inevitable charging behavior throughout trips. Although the effectiveness of the …
Transparent deep machine learning framework for predicting traffic crash severity
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 …
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
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 …
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
Traffic accidents are usually unique events with unpredictable geographical and temporal
dimensions; thus, accident injury severity level (INJ-SL) analysis presents formidable …
dimensions; thus, accident injury severity level (INJ-SL) analysis presents formidable …
Variance-based global sensitivity analysis for rear-end crash investigation using deep learning
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 …
accident injury severity (INJ-S) analysis faces a significant challenge in its classification and …
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 …
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
Traffic signs are vital for communicating guidance, rules, warning, and other highway
agency information for safe and efficient navigation through transportation networks. Signs …
agency information for safe and efficient navigation through transportation networks. Signs …