# Exploring the Relationship Between Mixed Non-Motorized Traffic Flow Width and Other Parameters
## 3 Data Extraction  
The traffic flow data collected for this study included the speed, flow rate, density, and traffic flow width of bicycles, and the counts of bicycles crossing the lane and entering motor vehicle lanes. The variable \"the counts of bicycles crossing the lane and entering motor vehicle lanes\" refers to situations where non-motorized vehicles temporarily leave their designated lanes to overtake slower-moving vehicles or respond to special circumstances. Typically, these vehicles return to non-motorized lanes after completing overtaking maneuvers (though some faster electric bicycles may persistently occupy motor vehicle lanes, a behavior that visibly reflects their speed relative to the width of non-motorized traffic flow). Specifically, while we recorded the furthest and closest lateral positions of bicycles to the curb within 30 s intervals, we also noted instances when bicycles crossed into the adjacent motor vehicle lane. By quantifying this variable, we can not only determine when non-motorized traffic flow reaches its maximum width, but also analyze how lane-crossing behavior correlates with traffic speed, density, and flow under varying conditions. This analysis provides theoretical reference for improving the management of cycling behaviors. In order to obtain bicycle speeds, this research employed the simulation coil method, which extracts relevant data from roadside video recordings. Specifically, the simulation coil method involves placing two white adhesive tapes on the ground perpendicular to the travel direction at each survey section, serving as the survey reference lines. The distance between these two reference lines was set at 10 m, and the survey area was confined to the space within these reference lines, as depicted in Figure 1. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Number** & **Road Name** & **Road Width (m)** & **Land Use Type** \\ \hline LS & Laoshan South Road & 1.5 & Residential \\ PG & Pingguoyuan South Road & 2.0 & Residential and School \\ YH & Yinhe Avenue & 2.5 & Commercial \\ YZ & Yangzhuang Avenue & 3.0 & Residential \\ YQ1 & Yuquan Road & 3.4 & Commercial and Office \\ YQ2 & Yuquan Road & 4.2 & Commercial and Office \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Road section information. 1. Speed of bicycle  
In this work, the potplayer software (version 1.7) was used to play the video frame-by-frame to extract bicycle speed. The rate of movement of the frames at which the front wheel of a bicycle reached the first white tape was recorded as \(f_{1}\), and the rate at which it reached the second white tape was recorded as \(f_{2}\). Accordingly, the speed of the bicycle can be calculated using Equation (1). \[v=\frac{s}{(f_{2}-f_{1})/f}\times 3.6 \tag{1}\]  
where \(s\) is the distance traveled by the bicycle through the test segment, which is 10 m, and \(f\) is the frame rate of the video. 2. Bicycle traffic flow rate  
The bicycle flow rate is obtained by dividing the number of standard bicycles passing through a certain section by the width of the lane within a unit time interval. There are studies which indicate that different sampling time intervals have a significant impact on the results. If the statistical interval is too short, the volatility of traffic flow will increase, resulting in poor stability of traffic flow. However, if the statistical interval is too long, the density level will be \"averaged\" out, masking changes in vehicle concentration states, which is not conducive to studying the characteristics of traffic flow under different congestion conditions [18]. Therefore, combining the findings reported in the literature with the actual situation, this article sets the sampling time interval to 30 s. Considering that \(n_{1}\) mechanical bicycles and \(n_{2}\) electric bicycles passed during this period, the bicycle flow rate can be calculated using Equation (2). \[q=\frac{n_{1}+n_{2}\times BE}{5\times w} \tag{2}\]  
where \(BE\) is the conversion coefficient for electric bicycles [19] and \(w\) is the width of the lane (m).