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Development of automated traffic control systems using artificial intelligence

Annotation

Almost all major cities suffer from significant traffic congestion. To achieve improved detection performance and multi-vehicle recognition in a complex urban environment, a detection algorithm based on histogram oriented gradients (HOG) features is applied. This algorithm takes full advantage of HOG for vehicles, i.e. we can talk about the good descriptive ability of the HOG function. With ever-increasing demand for urban mobility and modern developments in logistics, the number of vehicles has been steadily increasing over the past few decades.

In our proposed method, the system is designed to control the time of a traffic light depending on the traffic density on the corresponding road. It acts as a multi-class classification that recognizes traffic. The system detects a traffic event in real time.

Keywords

capacity
multiclass classification
automated traffic control system
planning algorithm
traffic intensity.

References:

1. Elanskaya M.V., Lyubichev D.M., Dormidontova T.V. Automated traffic control system // Eurasian Union of Scientists (ESU). - 2019. - No. 4. - Р. 22-25.

2. Litvinenko N.A. Review of modern technical means of traffic organization in the Russian Federation // European science. - 2017. - No. 1. - Р. 13-14.

3. Porubov D.M., Beresnev P.O., Tyugin D.Yu. The system of automated control of the movement of vehicles based on the recognition of the road scene and its objects // Izvestiya MSTU "MAMI". - 2018. - No. 1. - Р. 52-63.

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