Urban Traffic Flow Prediction System Using a Multifactor Pattern Recognition Model
Urban Traffic Flow Prediction System Using a Multifactor Pattern Recognition Model
- New search for: Oh, Se-do
- New search for: Kim, Young-jin
- New search for: Hong, Ji-sun
- New search for: Oh, Se-do
- New search for: Kim, Young-jin
- New search for: Hong, Ji-sun
Current urban traffic congestion costs are increasing on account of the population growth of cities and increasing numbers of vehicles. Many cities are adopting intelligent transportation systems (ITSs) to improve traffic efficiency. ITSs can be used for monitoring traffic congestion using detectors, such as calculating an estimated time of arrival or suggesting a detour route. In this paper, we propose an urban traffic flow prediction system using a multifactor pattern recognition model, which combines Gaussian mixture model clustering with an artificial neural network. This system forecasts traffic flow by combining road geographical factors and environmental factors with traffic flow properties from ITS detectors. Experimental results demonstrate that the proposed model produces more reliable predictions compared with existing methods.
Document information
Urban Traffic Flow Prediction System Using a Multifactor Pattern Recognition Model
IEEE Transactions on Intelligent Transportation Systems ; 16 , 5 ; 2744-2755
2015-10-01
1560105 byte
Article (Journal)
Electronic Resource
English
Similar titles
Urban Traffic Flow Prediction System Using a Multifactor Pattern Recognition Model
| Online Contents | 2015
PREDICTION SYSTEM AND METHOD OF URBAN TRAFFIC FLOW USING MULTIFACTOR PATTERN RECOGNITION MODEL
| European Patent Office | 2016
Multifactor feature extraction for human movement recognition
| British Library Online Contents | 2011