Urban big data fusion based on deep learning: An overview
Urban big data fusion creates huge values for urban computing in solving urban problems.
In recent years, various models and algorithms based on deep learning have been …
In recent years, various models and algorithms based on deep learning have been …
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 …
Deep learning-based urban big data fusion in smart cities: Towards traffic monitoring and flow-preserving fusion
Objective In the last few years, several techniques and models are used for retrieving
significant information from urban big data of smart cities. This research work aims at …
significant information from urban big data of smart cities. This research work aims at …
[HTML][HTML] Traffic state estimation of urban road networks by multi-source data fusion: Review and new insights
Accurate traffic state (ie, flow, speed, density, etc.) on an urban road network is important
information for urban traffic control and management strategies. However, due to the …
information for urban traffic control and management strategies. However, due to the …
Travel time prediction: Based on gated recurrent unit method and data fusion
Travel time prediction is the basis for the implementation of advanced traveler information
systems and advanced transport management systems in intelligent transportation systems …
systems and advanced transport management systems in intelligent transportation systems …
[HTML][HTML] Dynamic adaptive vehicle re-routing strategy for traffic congestion mitigation of grid network
C Wang, T Atkison, H Park - International Journal of Transportation Science …, 2023 - Elsevier
This paper proposes a possible methodology for detecting and mitigating traffic congestion.
This method is carried out using a custom-designed traffic scenario model. The model is fully …
This method is carried out using a custom-designed traffic scenario model. The model is fully …
A survey of methods and technologies for congestion estimation based on multisource data fusion
Traffic congestion occurs when traffic demand is greater than the available network capacity.
It is characterized by lower vehicle speeds, increased travel times, arrival unreliability, and …
It is characterized by lower vehicle speeds, increased travel times, arrival unreliability, and …
[HTML][HTML] Decision support for improved construction traffic management and planning
Densifying cities continuously call for new construction, renovation and demolition projects,
each generating vast amounts of heavy goods vehicle (HGV) transports. However, how …
each generating vast amounts of heavy goods vehicle (HGV) transports. However, how …
Deep learning-based marine big data fusion for ocean environment monitoring: Towards shape optimization and salient objects detection
Objective During the last few years, underwater object detection and marine resource
utilization have gained significant attention from researchers and become active research …
utilization have gained significant attention from researchers and become active research …
Symbolic aggregate approximation based data fusion model for dangerous driving behavior detection
Detecting dangerous driving behavior is of great significance for reducing the occurrence of
traffic accidents, and very challenging as it is affected by multiple factors. However, the …
traffic accidents, and very challenging as it is affected by multiple factors. However, the …