Intelligent Cooperative System for Traffic Monitoring in Smart Cities

Abstract

Smart cities introduce the strategies of solving the problems faced by the current cities; such as traffic jams, resource management, and climate change. Traffic flow monitoring is considered as one of the major challenges to be solved. Cooperative systems introduced a suitable solution for sharing information between the road elements, which provides a helpful tool for monitoring the traffic. However, most of the solutions are based on the sensors or cameras mounted in fixed locations, which have a limited range of vision and produce blind areas. In order to deal with the problem, this paper presents a cooperative system based on using Unmanned Aerial Vehicles (UAVs); to monitor the traffic flow. This system proposed a lightweight semantic neural network; that takes the RGB images as input and generates a segmented image of the vehicles and its 2D real-world positions. This data then is sent to each vehicle; to have full information about its surroundings. The proposed method has been validated with several experiments of different scenarios and situations, and the obtained results show its robustness and efficiency of the system, illustrating its functionality in traffic monitoring purposes.