Recently, development in intelligent transportation systems (ITS) requires the input of
various kinds of data in real-time and from multiple sources, which imposes additional …

Traffic emissions are a complex and variable cocktail of toxic chemicals. They are the major
source of atmospheric pollution in the parts of cities where people live, commute and work …

Traffic prediction is a core problem in the intelligent transportation system and has broad
applications in the transportation management and planning, and the main challenge of this …

Traffic forecasting is a challenging problem in the transportation research field as the
complexity and non-stationary changing of the traffic data, thus the key to the issue is how to …

Recently, Graph Convolution Network (GCN) and Temporal Convolution Network (TCN) are
introduced into traffic prediction and achieve state-of-the-art performance due to their good …

Even though a variety of human mobility models have been recently developed, models that
can capture real-time human mobility of urban populations in a sustainable and economical …

Accurate and explainable short-term traffic forecasting is pivotal for making trustworthy
decisions in advanced traffic control and guidance systems. Recently, deep learning …

Previous studies have shown that the max pressure control is a throughput-optimal policy
that can stabilize the store-and-forward traffic network when the demand is within the …

The rapid advancement of information and communication technology has brought a
revolution in the domain of public transport (PT) planning alongside other areas of transport …

Floating car data (FCD), characterized by wide spatiotemporal coverage, low collection cost,
and immunity to adverse weather conditions, are one of the key approaches for intelligent …