IMPROVEMENT OF THE URBAN TRANSPORTATION SYSTEM BY THE INTRODUCTION OF ADAPTIVE TRAFFIC CONTROL SYSTEMS

The article is devoted to the prospects of improving the quality of traffi c in the junction of the urban street and road network through the introduction of intelligent transport systems, especially automatic traffi c control systems (ATCS). The paper analyzes the problems of implementing intelligent transport systems in urban conditions, taking into account the current regulatory framework. The classifi cation of local automated traffi c control systems according to the adaptability of traffi c light regulation to the changing parameters of traffi c fl ows is given. For the decision of a problem of practicability of introduction of ACSDS, the technique including construction of imitation models for more exact forecasting of eff ect of introduction of local ACSDS on the considered site of an urban street-road network is off ered. The application of the methodology is demonstrated on the example of the intersection of Engels Avenue and Suzdal Avenue in St. Petersburg. Two variants of the organization of control of phases of traffi c light objects are analyzed: static and adapted according to the time of day. The infl uence of ADCS implementation on average speed of vehicles and characteristics of traffi c jams in the junction in question was estimated based on simulation modeling in PTV Vissim. In accordance with the analysis, the prospects of introducing adaptive local ACSDS in the considered transport junction are described

Circuitry and Proof of Concept for an Adaptive Traffic Control System

This paper illustrates the circuitry and proof of concept of a novel density based traffic mitigating system for the vehicles. The intention of this paper is to make an adaptive signalling system, which can be optimally used in real-time. This project is accomplished with the help of NVIDIA Jetson Nano and utilizes python for image processing as open source in order to measure the size of the traffic on the road.