On the results of the project and analysis session, which took place at South Ural State University in December, a Memorandum on creating a system of managing a Smart City project was signed. The “Smart Public Transport” project group proposed the system of monitoring and optimization of city traffic, as well as controlling the level of hazardous emissions from vehicles.
Candidate of Sciences (Engineering), Associate Professor of the Department of Automobile Transport of the SUSU Institute of Engineering and Technology Vladimir Shepelev told us about the Artificial Intelligence Monitoring System project, developed at SUSU and presented during the project and analysis session. The main task of the project is to develop and implement the evaluation system of the using of traffic infrastructure, predicting traffic jams and total toxic emissions from vehicles. The use of deep learning neural networks makes it possible to collect, interpret and aggregate data by traffic intensity and classification in a real-time mode.
“One of the innovative solutions of our project is the use of artificial intelligence in diagnosis and analysis of traffic infrastructure. The system helps to evaluate the efficiency of municipal roads usage, to identify reserves and prevent wrong solutions related to their broadening, to justify the traffic management facilities costs.”
An intelligent system of traffic flows and traffic infrastructure monitoring helps to solve a number of complex tasks of collection, interpreting and aggregation of traffic data, identification of underused resources in traffic infrastructure, which will help to reduce capital and operating costs. The system helps to evaluate the efficiency of traffic management solutions in a real-time mode (changes in cycles of traffic lights, and marking location changes, etc.), to forecast total toxic gas emissions from vehicles in terms of atmospheric and climate conditions. This program will also warn of exceeding the maximum permissible concentration on the nodes (crossroads) of road traffic, which will help to prevent a negative scenario (increasing the throughput capacity of the node, restricting traffic for trucks).
“The use of intelligent monitoring will help to increase city traffic throughput capacity significantly, create more comfortable conditions, and increase the population mobility, the speed of movement for both individual and public transport, and to create more comfortable living conditions by reducing noise from vehicles and hazardous emissions.”
According to Vladimir Shepelev, the technology with the use of smart neural networks does not require large expenditures on server equipment and video cameras. To monitor major crossroads, you will need one outdoor video surveillance camera. The software developed at SUSU provides the solution of complex tasks on increasing the efficiency of stable city traffic and infrastructure management. In addition, in order to save money and quickly implement the AIMS system, deployed systems of street surveillance cameras owned by various state and municipal departments can be involved.
SUSU academic staff, postgraduates and students from the Department of Automobile Transport, Department of Applied Mathematics and Programming, Department of Applied Mathematics, Department of Computer Science, and Department of Architecture are working on the “Smart Public Transport” project.