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Traffic Flow Prediction With Big Data: A Deep Learning Approach
TLDR
A novel deep-learning-based traffic flow prediction method is proposed, which considers the spatial and temporal correlations inherently and is applied for the first time that a deep architecture model is applied using autoencoders as building blocks to represent traffic flow features for prediction. Expand
A deep learning based approach for traffic data imputation
TLDR
This paper proposes an approach based on deep learning to impute the missing traffic data and shows that the proposed approach can keep a stable error under different traffic data missing rate. Expand
A Kind of Novel ITS Based on Space-Air-Ground Big-Data
  • Gang Xiong, F. Zhu, +5 authors Teng Teng
  • Computer Science, Engineering
  • IEEE Intelligent Transportation Systems Magazine
  • 18 January 2016
Based on the big-data collected from Space-Air-Ground, i.e. Space means satellite, Air means helicopter, the key technologies of novel ITS (Intelligent Transportation System) are investigated,Expand
Managing Emergency Traffic Evacuation With a Partially Random Destination Allocation Strategy: A Computational-Experiment-Based Optimization Approach
TLDR
A partially random destination allocation strategy for evacuation management is proposed using a metamodel-based simulation optimization method to design the strategy, leading to reduced network clearance times. Expand
Traffic signal coordination for emergency vehicles
TLDR
This paper proposes an emergency vehicle signal coordination (EVSC) approach, which is intended to provide “green wave” for EVs and indicates that the proposed approach can reduce EV travel time by 26.9% without too much negative impact on the normal traffic streams. Expand
Continuous Travel Time Prediction for Transit Signal Priority Based on a Deep Network
TLDR
A deep learning based approach for continuous travel time prediction problem and it is revealed that, except for obvious factors like speed, travel distance and traffic density, the signal time when the prediction is made is also an important factor affecting travel time. Expand
Novel ITS based on Space-Air-Ground collected big-data
Based on the big-data collected from Space-Air-Ground, novel ITS (Intelligent Transportation System) is researched, including key technologies such as sensor data acquisition, dynamic dataExpand
A heuristic implementation of emergency traffic evacuation in urban areas
With the acceleration of China's urbanization, more and more unexpected disasters in big cities make a severe challenge to city emergency traffic management. Under this background, we present aExpand
A kind of adaptive dynamic transit signal priority control method
Transit signal priority (TSP) is the most effective method to improve the operational efficiency of public transports. This paper presents an adaptive dynamic TSP control method of public traffic, byExpand
Semi-actuated arterial coordination for traffic control: A practical method
Arterial coordination is a common method in urban traffic control. Traditional arterial coordination methods are usually off-line control methods based on mixed-integer linear program. These methodsExpand
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