In this research the main attention is paid to establishing dynamics of changes in the driver’s reaction time in a traffic jam that affects traffic safety.With the help of the regression model, graphs of driver’s reaction time are constructed taking into account different age groups and types of the nervous system depending on the initial level of fatigue at the entrance to traffic jam and duration of traffic jam.Analysis of these graphs allowed us to establish trends in the driver’s reaction time in traffic jams, which indicate an increase in the driver’s reaction time with an increase in the time spent in the traffic jam. However, at the beginning of the traffic jam, depending on the initial fatigue level, different combinations of the reaction time change occur at the entrance to the traffic jam: at low values, the reaction time increases, and at high values it decreases. It was also found that the traffic jam has a different effect on the reaction time of drivers depending on their temperament. For the reaction time of the driver-phlegmatic traffic jam does not have a significant impact.
The article describes the method of estimating the parameters of transport flows using the two-fluid mathematical model of Herman-Prigogine and developed and based on the proposed method of estimating the parameters of the system on the basis of passive processing of navigation data on the movement of vehicles. The efficiency of the proposed algorithms, mathematical models for estimating the parameters of road traffic flow and system as a whole was confirmed during its testing using a set of tracks on the main highways of Commonwealth of Independent States.
The paper presents survey results from shopping behavior transformation in developed and developing countries due to the COVID-19 pandemic outbreak in spring 2020. The survey includes the polling process that covered 515 and 117 young adults, respectively, for two economies and factor analysis to determine the latent intentions of purchase behavior. Shopping patterns were studied for food, medicine, goods of first priority, electronics, clothing, and shoes. According to factor analysis results, we determined nine factors that reveal some similarities in shopping behavior as pro-safe purchases and belt-tightening patterns for both economies. Along with that, we revealed that people from developed countries perceived the greater danger and fear due to the COVID-19 crisis than young adults from developing economy. Based on polling results, the post–COVID-19 shopping channel choice behavior was evaluated for developed and developing economies.
This study focuses on establishing the dynamics of changes in the level of fatigue of an average driver in a traffic jam, which affects road safety. Linear and nonlinear models of the effect of traffic jam on the level of fatigue of an average driver have been developed, which allow assessing their condition depending on the driver’s age and the duration of the jam. Using a nonlinear regression model, the graphs of changes in the level of fatigue of an average driver of 25 and 65 years are plotted. The analysis of these graphs allowed us to establish the patterns of influence of road parameters on the functional state of the driver. The level of fatigue of the driver, which is determined by the change in his functional state, increases during his stay in the traffic jam. Therefore, the duration of the jam and the initial level of fatigue when entering the jam influence most the final level of fatigue of the driver. The driver’s age affects the level of fatigue to a lesser extent, but still significantly.
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