Urban traffic signal control with connected and automated vehicles: A survey
Inefficient traffic control is pervasive in modern urban areas, which would exaggerate traffic
congestion as well as deteriorate mobility, fuel economy and safety. In this paper, we …
congestion as well as deteriorate mobility, fuel economy and safety. In this paper, we …
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 …
Traffic flow prediction based on combination of support vector machine and data denoising schemes
Traffic flow prediction with high accuracy is definitely considered as one of most important
parts in the Intelligent Transportation Systems. As interfering by some external factors, the …
parts in the Intelligent Transportation Systems. As interfering by some external factors, the …
[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 …
Physics-informed neural networks for integrated traffic state and queue profile estimation: A differentiable programming approach on layered computational graphs
This paper presents an integrated framework for physics-informed joint traffic state and
queue profile estimation (JSQE) on freeway corridors, utilizing heterogeneous data sources …
queue profile estimation (JSQE) on freeway corridors, utilizing heterogeneous data sources …
Domain adaptation from daytime to nighttime: A situation-sensitive vehicle detection and traffic flow parameter estimation framework
Vehicle detection in traffic surveillance images is an important approach to obtain vehicle
data and rich traffic flow parameters. Recently, deep learning based methods have been …
data and rich traffic flow parameters. Recently, deep learning based methods have been …
Real-time traffic state estimation in urban corridors from heterogeneous data
In recent years, rapid advances in information technology have led to various data collection
systems which are enriching the sources of empirical data for use in transport systems …
systems which are enriching the sources of empirical data for use in transport systems …
[HTML][HTML] 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 …
Short-term traffic flow prediction: An integrated method of econometrics and hybrid deep learning
This study proposes a short-term traffic flow prediction framework. The vector autoregression
(VAR) model based on econometric theory and the CNN-LSTM hybrid neural network model …
(VAR) model based on econometric theory and the CNN-LSTM hybrid neural network model …
Assessment of antenna characteristic effects on pedestrian and cyclists travel-time estimation based on Bluetooth and WiFi MAC addresses
Monitoring pedestrian and cyclists movement is an important area of research in transport,
crowd safety, urban design and human behaviour assessment areas. Media Access Control …
crowd safety, urban design and human behaviour assessment areas. Media Access Control …