Abstract
A mathematical model to quantify the efficiency of traffic flow on the road network was developed. The authors have developed a comprehensive criterion considering key performance indicators: the traffic flow performance, traffic safety, environmental safety.Study of the efficiency criterion is based on the analysis of the traffic flow dynamics. The problem of structural and parametric identification of the mathematical model is complex. The solution to this problem is based on the theory of traffic flow, regression analysis, simulation and dynamic programming.
Highlights
Modern research shows that the intensive development of motor transport (MT) is supposed to be both positive and negative nowadays
These problems are especially prevalent in large cities, where traffic jams, road traffic accidents (RTF) and smog have become commonplace
The evaluation criterion of the traffic control efficiency, including the TF performance, the traffic safety level, environmental risk assessment should be the basic principles of traffic control (TC) of the city road network (MAC)
Summary
Modern research shows that the intensive development of motor transport (MT) is supposed to be both positive and negative nowadays. Besides MT is the basic source of adverse environmental impact. These problems are especially prevalent in large cities, where traffic jams, road traffic accidents (RTF) and smog have become commonplace. Correct road traffic organization, transport safety and environmental risks management are a priority to improve the life quality of population at any modern city. The evaluation criterion of the traffic control efficiency, including the TF performance, the traffic safety level (traffic safety), environmental risk assessment should be the basic principles of traffic control (TC) of the city road network (MAC). The evaluation criterion can be formed on the basis of dynamic characteristics of the TP study. Study of the TF dynamics, evaluation criteria development, structure and parameters of the model TS identification is of high priority. The final results will allow to efficiently solve the problems of the functioning processes of the TF optimization
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