Incidents Prediction in Road Junctions Using Artificial Neural Networks

The implementation of an incident detection system (IDS) is an indispensable operation in the analysis of the road traffics. However the IDS may, in no case, represent an alternative to the classical monitoring system controlled by the human eye. The aim of this work is to increase detection and pre...

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Bibliographic Details
Published in:IOP conference series. Materials Science and Engineering 2018-05, Vol.353 (1), p.12017
Main Authors: Hajji, Tarik, Alami Hassani, Aicha, Ouazzani Jamil, Mohammed
Format: Article
Language:English
Subjects:
ANN
Artificial intelligence
Artificial neural networks
Cameras
Comparative studies
Computer architecture
Images and videos processing
Incidents prediction
Learning theory
Neural networks
Supervisors
Trajectory analysis
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Summary:The implementation of an incident detection system (IDS) is an indispensable operation in the analysis of the road traffics. However the IDS may, in no case, represent an alternative to the classical monitoring system controlled by the human eye. The aim of this work is to increase detection and prediction probability of incidents in camera-monitored areas. Knowing that, these areas are monitored by multiple cameras and few supervisors. Our solution is to use Artificial Neural Networks (ANN) to analyze moving objects trajectories on captured images. We first propose a modelling of the trajectories and their characteristics, after we develop a learning database for valid and invalid trajectories, and then we carry out a comparative study to find the artificial neural network architecture that maximizes the rate of valid and invalid trajectories recognition.
ISSN:1757-8981
1757-899X
DOI:10.1088/1757-899X/353/1/012017