Review of data fusion methods for real-time and multi-sensor traffic flow analysis
SA Kashinath, SA Mostafa, A Mustapha… - IEEE …, 2021 - ieeexplore.ieee.org
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 …
various kinds of data in real-time and from multiple sources, which imposes additional …
Emerging big data sources for public transport planning: A systematic review on current state of art and future research directions
KE Zannat, CF Choudhury - Journal of the Indian Institute of Science, 2019 - Springer
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 …
revolution in the domain of public transport (PT) planning alongside other areas of transport …
Optimized graph convolution recurrent neural network for traffic prediction
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 …
applications in the transportation management and planning, and the main challenge of this …
Dynamic graph convolution network for traffic forecasting based on latent network of Laplace matrix estimation
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 …
complexity and non-stationary changing of the traffic data, thus the key to the issue is how to …
Modeling real-time human mobility based on mobile phone and transportation data fusion
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 …
can capture real-time human mobility of urban populations in a sustainable and economical …
[HTML][HTML] Multistep traffic forecasting by dynamic graph convolution: Interpretations of real-time spatial correlations
Accurate and explainable short-term traffic forecasting is pivotal for making trustworthy
decisions in advanced traffic control and guidance systems. Recently, deep learning …
decisions in advanced traffic control and guidance systems. Recently, deep learning …
Dual dynamic spatial-temporal graph convolution network for traffic prediction
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 …
introduced into traffic prediction and achieve state-of-the-art performance due to their good …
Learning the max pressure control for urban traffic networks considering the phase switching loss
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 …
that can stabilize the store-and-forward traffic network when the demand is within the …
Review of modelling air pollution from traffic at street-level-The state of the science
H Forehead, N Huynh - Environmental Pollution, 2018 - Elsevier
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 …
source of atmospheric pollution in the parts of cities where people live, commute and work …
Revealing the day-to-day regularity of urban congestion patterns with 3D speed maps
In this paper, we investigate the day-to-day regularity of urban congestion patterns. We first
partition link speed data every 10 min into 3D clusters that propose a parsimonious sketch of …
partition link speed data every 10 min into 3D clusters that propose a parsimonious sketch of …