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Now showing items 21-30 of 36
ANN-Based traffic volume prediction models in response to COVID-19 imposed measures
(
Elsevier
, 2022 , Article)
Many countries around the globe have imposed several response measures to suppress the rapid spread of the COVID-19 pandemic since the beginning of 2020. These measures have impacted routine daily activities, along with ...
Data-Driven Optimization for Dynamic Shortest Path Problem Considering Traffic Safety
(
IEEE
, 2022 , Article)
Traffic congestion is an inescapable problem that frustrates drivers in megacities. Although there is hardly a way to eliminate the congestion, it is possible to mitigate the impact through predictive methods. This paper ...
Are Professional Drivers more Aggressive than General Drivers? A Case Study from Doha, Qatar
(
Elsevier B.V.
, 2022 , Conference Paper)
Previous studies have revealed that aggressive and reckless driving can largely affect the occurrence and severity of road crashes. There could be intentional aggressive and unsafe acts, which could significantly affect ...
Impact of COVID-19 Pandemic on Qatar Electricity Demand and Load Forecasting: Preparedness of Distribution Networks for Emerging Situations
(
MDPI
, 2022 , Article)
The COVID-19 pandemic has brought several global challenges, one of which is meeting the electricity demand. Millions of people are confined to their homes, in each of which a reliable electricity supply is needed, to ...
Planning and Optimizing Electric-Vehicle Charging Infrastructure Through System Dynamics
(
IEEE
, 2022 , Article)
One of the key solutions to address the issue of energy efficiency and sustainable mobility is to integrate plug-in electric vehicle (EV) infrastructure and photovoltaic (PV) systems. The research proposes a comprehensive ...
Road Crossing at Unmarked Mid-Block Locations: Exploring Pedestrians’ Perception and Behavior
(
Springer
, 2022 , Article)
Violations, risky behaviors and perceptions may largely contribute to crashes involving pedestrians, particularly at unmarked mid-block locations. The likelihood and severity of crashes at mid-block locations are higher ...
Application of Unsupervised Machine Learning Classification for the Analysis of Driver Behavior in Work Zones in the State of Qatar
(
Elsevier
, 2022 , Article)
Work zone areas are commonly known as crash-prone areas. Thus, they usually receive high priority by road operators as drivers and workers have higher chances of being involved in road crashes. The paper aims to investigate ...
Safer pedestrian crossing facilities on low-speed roads: Comparison of innovative treatments
(
Elsevier
, 2022 , Article)
Despite the international efforts to improve pedestrian safety in different regions of the world, pedestrian fatalities still account for around one-third of annual road traffic deaths. Residential areas are commonly ...
Improved driver behaviour at bus stops on local roads: Comparison of different treatments
(
Elsevier
, 2022 , Article)
Every day, millions of students use school bus as a mean of transportation to and from schools. Nevertheless, most of the school bus related crashes occur at or near bus stops. The overtaking of stopped school buses during ...
Urban resilience and livability performance of European smart cities: A novel machine learning approach
(
Elsevier
, 2022 , Article)
Smart cities are centres of economic opulence and hope for standardized living. Understanding the shades of urban resilience and livability in smart city models is of paramount importance. This study presents a novel ...