## 2 Statement of the Problem and Analysis of Publications  
### Review of Factors Affecting the Free Flow Speed  
Since FFS is a parameter of many mathematical models of traffic flow, a large number of publications have been devoted to studies of this parameter since the middle of the last century.  
It is known that the speed of a single car on a road section is a random value that is chosen directly by the driver and is realized as a result of a psychophysiological process, which is based on the reflection of goal setting, motivation, awareness, and perception of the totality of road conditions and circumstances environment. The driver constantly strives to choose the most appropriate speed mode based on the criteria of minimizing travel time and ensuring comfortable and safe driving conditions. At the same time, the driver's choice of speed is also influenced by his qualification, psychophysiological state, the purpose of the trip, and other factors [5; 6; 7; 8; 9]. Experience shows that the driver drives the car at maximum speed only in exceptional cases and for a short time, as it is associated with excessive mental stress. Studies conducted in the same road conditions on the same type of car showed that the average speed of the car in different highly qualified drivers can vary within \(\pm 10\%\) of the average value. In inexperienced drivers, this difference is greater [7].  
As observations show, the actual range of instantaneous FFS on horizontal sections of main streets and roads is from 50 to 120 km/h, regardless of the established speed limits [6; 10].  
It should be noted that most of the papers analyzing the effect of road conditions on FFS consider suburban highways. Among the road factors that influence a driver's choice of speed on urban roads in different regions of the world, the researchers noted the following: Speed Limits, Land-use type (commercial, residential, industrial); Road Geometry; Surface Type and Quality; Weather Conditions; Roadside Environment (the presence of buildings, trees, or other barriers); Access Points (like driveways or intersections); Lane Configuration (the number of lanes, their arrangement); and roadside frictional (parking, pedestrian and bicycle activity, etc.) [11; 12; 13; 14; 15]. It is noted in [11; 12] that gradients, curvilinear sections, and road irregularities lead to a decrease in FFS. In urban environments, FFS is further affected by speed limits, the presence of pedestrian traffic, parking, and other factors [14; 15]. Studies [1; 16] show that factors such as road class and area type have a stronger effect on the FFS of passenger cars, for which the average values for different streets range from 58 to 80 km/h. The average FFS values for urban highways turned out to be on average 22-25 km/h higher than those for local traffic streets [1; 8; 12; 17].  
Since one-way traffic is very common in cities in different regions of the world, traffic conditions on such streets are often the object of modeling [18; 19; 20]. Therefore, studying the differences in FFS for one-way traffic conditions can improve the accuracy of traffic flow description. In addition, the use of models of traffic characteristics and parameters once obtained for some conditions, such as in cities in developed countries, may not work well when modeling traffic in other regions of the planet [21]. Therefore, expanding the geographic scope of the study of traffic parameters, particularly FFS, is also relevant.  
For the one-way traffic, although in some works there are the results of FFS analysis for city streets with one-way traffic, we have not come across any work where the influence of this factor would be studied separately from others. Our work, it seems to us, can fill this gap.