In recent years, traffic congestion prediction has led to a growing research area, especially
of machine learning of artificial intelligence (AI). With the introduction of big data by …

Events are occurrences in specific locations, time, and semantics that nontrivially impact
either our society or the nature, such as earthquakes, civil unrest, system failures …

Detecting, predicting, and alleviating traffic congestion are targeted at improving the level of
service of the transportation network. With increasing access to larger datasets of higher …

Electrified vehicles are considered a promising technology for energy savings and emission
reductions. Both powertrain design (configuration design and component sizing) and energy …

Traffic congestion has been widely perceived as an inevitable byproduct in the process of
global urbanization, leading to significant negative economic and environmental impacts …

Recent studies on traffic congestion prediction have paved a promising path towards the
reduction of potential economic and environmental loss. However, at the city-wide scale …

Traffic congestion is a contemporary urban issue plaguing transportation planners, land
developers, policy-makers, and citizens. While many studies have investigated the impact of …

This paper introduces DataFITS (Data Fusion on Intelligent Transportation System), an open-
source framework that collects and fuses traffic-related data from various sources, creating a …

Forecasting citywide traffic congestion on large road networks has long been a nontrivial
research problem due to the challenge of modeling complex evolution patterns of …

The expansion of the Internet of Things has resulted in new creative solutions, such as smart
cities, that have made our lives more productive, convenient, and intelligent. The core of …