# Exploring the Relationship Between Mixed Non-Motorized Traffic Flow Width and Other Parameters
## 3 Data Extraction
3. Bicycle traffic flow density  
Due to the lack of strict lane division for bicycles, surface density is used to represent the bicycle traffic flow density, which is defined as the number of bicycles per unit area at a certain moment, with a sampling time interval of 30 s. Within each sampling interval, the number of mechanical and electric bicycles is recorded every 5 s. The average of six such  
Figure 1: Schematic diagram of simulation coil method. records is taken as the density for that period, which is represented by \(k\) and expressed as in Equation (3). \[k=\frac{n}{10\times w} \tag{3}\]  
where \(n\) is the number of bicycles within the observation range at a certain moment, and \(w\) is the width of the lane (m). 4. Width of bicycle lane  
In order to satisfy the sampling requirements for calculating the speed, flow, and density of bicycle traffic, this article adopted a sampling time interval of 30 s. Furthermore, the original bicycle lane was segmented into lanes with a width interval of 1 m using previously calibrated reference objects on the sections of the bicycle lane. Taking a 3.3 m wide bicycle lane as an example, the lane was divided into three 1 m wide bicycle lanes (denoted as L1, L2, and L3) and one 0.3 m wide L-boundary lane (denoted as LB) starting from the curb. If the width of the lane can be divided evenly into integer lanes, an L-boundary lane need not be created. This approach was applied to other roads also, as shown in Figure 2. Additionally, the scenario where bicycles cross into other lanes is denoted as CL (crossing the lane). Then, the distribution of the positions of the bicycle flow within each sampling interval was observed and measured. The average width of the bicycle flow in a sampling interval is calculated using Equation (4). \[w_{\text{t}}=\frac{\sum_{i=1}^{m}L_{\text{ik}}}{n} \tag{4}\]  
where \(w_{t}\) is the average width of the bicycle flow in the \(t\)-th time interval, \(L_{\text{ik}}\) is the width of the \(k\)-th subdivided lane occupied by the \(i\)-th bicycle, and \(n\) is the total number of bicycles passing through in that time interval. This study defines the width of bicycle flow as the average width of the bicycle traffic flow passing through a certain distance within a unit of time. It is measured from the curb to the position of the outermost bicycle in the observation section. This study first categorizes common mixed bicycle flow widths based on whether they exceed the width of the designated bicycle lane. Specifically, the common mixed bicycle flow is classified into four states based on the positions of the bicycles on the road: unsaturated state, saturated state, supersaturated state, and random riding state, as shown in Figure 3.  
Figure 2: Lane division diagram. The unsaturated state refers to the ideal condition where the width of the mixed bicycle flow on a road segment during peak hours is less than the width of the bicycle lane, and few instances of bicycles crossing the lane and entering the motor vehicle lane are observed. The saturated state occurs when the width of mixed bicycle flow on a road segment during peak hours is less than or slightly greater than the width of the bicycle lane, with a small number of bicycles entering the motor vehicle lane. The supersaturated state is characterized by frequent occurrences of bicycles crossing the lane and entering the motor vehicle lane during peak hours, indicating that the width of the mixed bicycle flow exceeds the width of the bicycle lane. The random riding state describes a situation where the position of bicycle riding exhibits no fixed pattern during peak hours, but is determined solely by the rider's own habits, which may negatively impact traffic safety and efficiency. Through video analysis, it can be observed that when the bicycle traffic flow during peak hours exhibits a saturated or unsaturated state, this indicates that the width design of the bicycle lane in this road segment meets the actual travel demand of the bicycle traffic flow.