Application of Object Tracking for Intelligent Transport Systems

Ayobami Godwin Oki, Brendan Ubochi


Effective road network operations require maximizing the available capacity especially in congested urban road networks. One of the ways of improving traffic flow and optimizing road network capacity, especially in peak periods, is by utilizing reversible lanes. This involves utilizing real-time road traffic information to reduce congestion. This study applies the video processing techniques of object detection and object tracking to feed traffic data into a database (PostgreSQL). The data is pre-processed and analyzed and the information is used to assign directions to vehicles through an indicator. The prototype design uses a three-lane model and assigns the middle lane for traffic in either direction depending on the acquired traffic information.

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