A simulation software effectiveness evaluation method based on pedestrian flow bottleneck experiment

Abstract

The present invention discloses a method for evaluating the effectiveness of simulation software based on pedestrian flow bottleneck experiments, comprising the following steps: S1, dividing the pedestrian flow bottleneck experiment into a width-limited bottleneck experiment and a flow-limited bottleneck experiment; S2, collecting the layout parameters, number of participants, experiment duration, and basic information of pedestrians of the pedestrian flow bottleneck experiment; S3, analyzing the mechanism of pedestrian flow bottleneck action using the collected pedestrian flow data according to different pedestrian flow bottleneck types; S4, establishing a pedestrian flow bottleneck model using different simulation software based on the pedestrian flow bottleneck layout parameters and pedestrian flow data; and changing the configuration of the pedestrian flow bottleneck while ensuring the simulation effect; S5, outputting and analyzing the pedestrian flow data using different simulation software. By determining reasonable simulation effect evaluation indicators and comparing and analyzing the simulation effects of different pedestrian flow simulation software for the same type of bottleneck experiment, the present invention can lay a foundation for research on pedestrian flow bottleneck simulation.

Description

Technical Field

[0001] The present invention relates to a pedestrian flow bottleneck experiment, and in particular to a simulation software effect evaluation method based on the pedestrian flow bottleneck experiment. Background Art

[0002] The continuous growth of urban populations indicates the prosperity and development of urban economies, but it also creates a huge demand for pedestrian transportation. In the rapid process of urbanization, problems such as traffic congestion, environmental pollution, and energy shortages have emerged one after another. Walking, as the most primitive and basic mode of transportation, is extremely flexible and has become an indispensable and extremely important component for connecting different modes of transportation and completing the "last mile" of travel. Pedestrian research involves multiple fields such as mathematics, statistical physics, systems science, transportation engineering, computer science, and even sociology and psychology, and has therefore attracted the attention of a large number of scholars at home and abroad. As the demand for pedestrian transportation continues to grow, the importance of studying pedestrian flow bottlenecks has become increasingly prominent.

[0003] Pedestrian flow simulation software is more convenient and efficient for solving real-life pedestrian traffic problems. Currently, commonly used pedestrian flow software includes VISSIM, AnyLogic, SUMO, Pedestrian Dynamics, STEPS, Legion, and SimWalk. The three most common pedestrian simulation software, VISSIM, AnyLogic, and SUMO, are applicable to different scenarios. VISSIM is often used to study the interaction between pedestrian and vehicle flows and pedestrian evacuation. AnyLogic is more suitable for pedestrian simulation in scenarios such as rail transit station facility layout, while SUMO focuses on the interaction between pedestrian and vehicle flows.

[0004] However, current research on pedestrian simulation software focuses more on case simulation research and improved model verification, and rarely uses different pedestrian software to compare the simulation effects of the same scene. Therefore, there is a lack of research on the selection of comparative indicators for the simulation effects of pedestrian flow software, making it difficult to determine the most reliable simulation software. Summary of the Invention

[0005] Purpose of the invention: The purpose of the present invention is to provide a simulation software effect evaluation method based on pedestrian flow bottleneck experiments by selecting reasonable evaluation indicators to evaluate the simulation effect.

[0006] Technical solution: The simulation software effect evaluation method of the present invention comprises the following steps:

[0007] S1, divides the pedestrian flow bottleneck experiment into the limited width bottleneck experiment and the limited flow bottleneck experiment according to the bottleneck type;

[0008] S2: Collect the layout parameters of the pedestrian bottleneck experiment, the number of participants, the duration of the experiment, and basic information about pedestrians. Use drone video and pedestrian data collection software to extract pedestrian flow data, and process the pedestrian flow data based on different pedestrian flow bottlenecks. For bottlenecks with limited flow, calculate the average speed and standard deviation of pedestrians at different locations. For bottlenecks with limited width, divide the circular channel into equal areas, and calculate the pedestrian flow at the area boundary and the pedestrian density within the area.

[0009] S3, according to different pedestrian flow bottleneck types, using the collected pedestrian flow data to analyze the pedestrian flow bottleneck mechanism;

[0010] S4, based on the pedestrian bottleneck layout parameters and pedestrian flow data, use different simulation software to establish a pedestrian bottleneck model; change the configuration of the pedestrian bottleneck while ensuring the simulation effect;

[0011] S5, after the pedestrian flow bottleneck simulation is completed, the pedestrian flow data is output and analyzed using different simulation software;

[0012] S6, for different pedestrian bottleneck experiments, select different evaluation indicators for comparison; by comparing the results of multiple evaluation indicators, comprehensively evaluate the simulation effects of different software.

[0013] Furthermore, in step S2, the basic information of pedestrians in the experimental configuration parameters includes pedestrian height, pedestrian width, and pedestrian walking speed.

[0014] Furthermore, in step S2, the pedestrian flow data is collected by first using a drone to shoot a pedestrian flow experiment video, and then using three-dimensional tracking software to extract the pedestrian flow data.

[0015] Furthermore, in step S3, for the bottleneck of traffic flow, pedestrian trajectory diagrams are drawn using real-time coordinates of pedestrians and the changing trend of pedestrian speed statistics is analyzed;

[0016] For bottlenecks with restricted width, pedestrian flow and pedestrian density are used to draw the spatial-temporal map of pedestrian flow and the spatial-temporal map of pedestrian density as well as the comparison map of average pedestrian flow.

[0017] Furthermore, in step S4, it is ensured that changing the configuration of the pedestrian flow bottleneck will not have a qualitative impact on the simulation results.

[0018] Furthermore, in step S5, when the pedestrian flow data is output using the simulation software, the output real-time positions and real-time speeds of pedestrians need to be processed accordingly to obtain other pedestrian flow data.

[0019] Furthermore, in step S6, the evaluation indicators are selected as follows: the comparison indicator for the flow bottleneck experiment is the pedestrian speed statistics, and the comparison indicator for the width bottleneck experiment is the pedestrian flow statistics and density statistics; wherein the pedestrian speed statistics are the average speed and speed standard deviation of pedestrians at different locations, and the pedestrian flow statistics are the average pedestrian flow, pedestrian flow, and density standard deviation counted within a set time interval; then, a comparison chart is drawn for different effect evaluation indicators.

[0020] Compared with the prior art, the present invention has the following significant effects:

[0021] 1. Based on different pedestrian flow bottleneck types, the real-time pedestrian coordinate data and pedestrian speed data obtained by the pedestrian data extraction software are converted into pedestrian speed statistics, pedestrian density, and pedestrian flow statistics. This allows for pedestrian flow bottleneck experiment and simulation results to facilitate the next step of simulation effect evaluation.

[0022] 2. Use pedestrian flow simulation software to simulate pedestrian flow bottleneck experimental conditions, and select reasonable evaluation indicators to evaluate the simulation effect, so as to determine the most reliable simulation software. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a flow chart of the present invention;

[0024] Figure 2 This is a layout diagram of the limited width bottleneck experiment of the present invention;

[0025] FIG3( a ) is a density space-time diagram in a width-limited bottleneck according to the present invention, where the bottleneck width is 1.5 meters;

[0026] FIG3( b ) is a density space-time diagram in a width-limited bottleneck of the present invention, where the bottleneck width is 1 meter;

[0027] FIG3( c ) is a density space-time diagram in a width-limited bottleneck of the present invention, where the bottleneck width is 0.5 m;

[0028] FIG4( a ) is a time-space diagram of the flow rate in the limited-width bottleneck experiment of the present invention, where the bottleneck width is 1.5 meters;

[0029] Figure 4(b) is a flow time-space diagram in the limited width bottleneck experiment of the present invention, where the bottleneck width is 1 meter.

[0030] Figure 4(c) is a flow time-space diagram in the limited width bottleneck experiment of the present invention, where the bottleneck width is 0.5 meters.

[0031] Figure 5 This is a comparison chart of average flow rates in the limited width bottleneck experiment of the present invention, with a preset density of 3 people / square meter;

[0032] FIG6( a ) is a density space-time diagram of the present invention when performing a width-limited bottleneck simulation using VISSIM, where the bottleneck width is 1.5 meters;

[0033] FIG6( b ) is a density space-time diagram of the present invention when using VISSIM to perform a width-limited bottleneck simulation, where the bottleneck width is 1 meter;

[0034] FIG6( c ) is a density space-time diagram of the present invention when using VISSIM to perform a width-limited bottleneck simulation, where the bottleneck width is 0.5 meters;

[0035] FIG7( a ) is a flow space-time diagram of the present invention when using VISSIM to perform a width-limited bottleneck simulation, where the bottleneck width is 1.5 meters;

[0036] FIG7( b ) is a flow space-time diagram of the present invention when using VISSIM to perform a width-limited bottleneck simulation, where the bottleneck width is 1 meter;

[0037] FIG7( c ) is a flow space-time diagram of the present invention when using VISSIM to perform a width-limited bottleneck simulation, where the bottleneck width is 0.5 meters;

[0038] Figure 8(a) shows the density space-time diagram of the present invention when AnyLogic is used to simulate a bottleneck with a width of 1.5 meters.

[0039] Figure 8(b) shows the density space-time diagram of the present invention when AnyLogic is used to simulate a bottleneck with a width of 1 meter.

[0040] Figure 8(c) shows the density space-time diagram of the present invention when AnyLogic is used to simulate a bottleneck with a width of 0.5 meters.

[0041] Figure 9(a) shows the flow rate spatiotemporal diagram of the present invention when AnyLogic is used to simulate a bottleneck with a width of 1.5 meters.

[0042] Figure 9(b) shows the flow space-time diagram of the present invention when AnyLogic is used to simulate a bottleneck with a width of 1 meter.

[0043] Figure 9(c) shows the flow space-time diagram of the present invention when AnyLogic is used to simulate a bottleneck with a width of 0.5 meters.

[0044] FIG10( a ) is a comparison diagram of the average pedestrian flow in a bottleneck with a limited width according to the present invention, where the bottleneck width is 1.5 meters;

[0045] Figure 10(b) is a comparison chart of the average pedestrian flow in the bottleneck with limited width of the present invention, where the bottleneck width is 1 meter.

[0046] Figure 10(c) is a comparison chart of the average pedestrian flow in the bottleneck with limited width of the present invention, where the bottleneck width is 0.5 meters.

[0047] FIG11( a ) is a comparison diagram of the standard deviation of pedestrian flow in a bottleneck with a limited width according to the present invention, where the bottleneck width is 1.5 meters;

[0048] FIG11( b ) is a comparison diagram of the pedestrian flow standard deviation of the limited-width bottleneck of the present invention, where the bottleneck width is 1 meter;

[0049] FIG11( c ) is a comparison diagram of the pedestrian flow standard deviation of the limited-width bottleneck of the present invention, where the bottleneck width is 0.5 meters;

[0050] FIG12( a ) is a comparison diagram of the standard deviation of pedestrian density in a bottleneck with a limited width according to the present invention, where the bottleneck width is 1.5 meters;

[0051] FIG12( b ) is a comparison diagram of the standard deviation of pedestrian density in a bottleneck with a limited width according to the present invention, where the bottleneck width is 1 meter;

[0052] FIG12( c ) is a comparison diagram of the standard deviation of pedestrian density in a bottleneck with a limited width according to the present invention, where the bottleneck width is 0.5 m; DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0054] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0055] like Figure 1 As shown, the simulation software effect evaluation method of the present invention includes the following steps:

[0056] Step S1: Determine the pedestrian flow bottleneck experiment type

[0057] The pedestrian flow experiment of the present invention is a bottleneck experiment with limited width, such as Figure 2 shown.

[0058] Step S2: Collect pedestrian flow bottleneck experiment configuration parameters and pedestrian flow data

[0059] Collect the layout parameters of the pedestrian flow bottleneck experiment, the number of participants, the duration of the experiment, and basic information of pedestrians;

[0060] First, the configuration parameters of the pedestrian flow bottleneck experiment were collected, including a loop width of 1.5 meters, an inner radius of 4 meters, an outer radius of 5.5 meters, 137 people participating in the experiment (global density of 3 people / square meter), and bottleneck widths of 0.5 meters, 1 meter, and 1.5 meters (no bottleneck). The basic information of pedestrians was collected, including pedestrian height of 1.6 meters to 1.75 meters, width of 0.45 meters to 0.55 meters, and pedestrian walking speed of 0.8 meters / second to 1.4 meters / second.

[0061] Secondly, a drone was used to film the pedestrian flow bottleneck experiment process. After the experiment, the pedestrian flow data in the experimental video was extracted using PeTrack software, including pedestrian real-time coordinates, pedestrian real-time speed, pedestrian flow, pedestrian density, etc.; because the software cannot directly output pedestrian density and flow data, the collected pedestrian real-time coordinates need to be processed accordingly. For the limited width bottleneck experiment, the experimental loop was divided into 8 evenly spaced areas using 4 symmetrical straight lines X1, X2...X8, such as Figure 2 As shown in the figure, X8 is the bottleneck location, and only by dividing the area equally from this point can effective pedestrian flow and density data be obtained. Next, a coordinate system is established with the center of the ring road as the origin and the line containing X8 as the X-axis to determine the coordinate value range of each area. Based on this, the number of pedestrians in different areas within each time interval is counted, which is converted into pedestrian density in different areas. Finally, by calculating the coordinate value range of different sections, the number of pedestrians passing through each time interval can be counted, and then divided by the section width to calculate the pedestrian flow passing through the section at different times.

[0062] Step S3: Analyze pedestrian flow bottleneck experiment results

[0063] The mechanism of pedestrian flow bottlenecks is analyzed according to the type of pedestrian flow bottlenecks. For bottlenecks with limited flow, in order to intuitively show the relationship between pedestrian speed and the bottleneck with limited flow, the real-time coordinates of pedestrians can be used to draw pedestrian trajectory maps and analyze the changing trends of pedestrian speed statistics. For bottlenecks with limited width, in order to analyze the impact of bottlenecks on pedestrian flow and pedestrian density, pedestrian flow and pedestrian density can be used to draw pedestrian flow space-time maps, pedestrian density space-time maps, and pedestrian average flow comparison maps.

[0064] like Figure 3(a) 、 3(b) 3(c), in the present invention, when the global density is 3 people / m2, no typical density wave appears on the image regardless of whether there is a bottleneck. Figure 4(a) 、 4(b)4(c), in the present invention, when the global density is 3 people / square meter, the system flow is high and pedestrians do not enter a state of walking and stopping. Figure 5 In the present invention, when the density is constant, the average pedestrian flow rate will decrease as the bottleneck width decreases. This is because the bottleneck will limit the number of pedestrians passing through the bottleneck. The smaller the bottleneck width, the fewer pedestrians can pass through.

[0065] Step S4: Use different simulation software to establish a pedestrian flow bottleneck simulation model

[0066] The different simulation software are commonly used pedestrian simulation software, such as VISSIM, AnyLogic, Pedestrian Dynamics, JuPedSim and NOMAD based on the social force model, Legion and STEPS based on the cellular automaton model, and SUMO with the built-in pedestrian micro-motion model as the stripe model.

[0067] Based on the pedestrian bottleneck layout parameters and pedestrian flow data, different simulation software were used to establish the pedestrian bottleneck model. Due to software version limitations, the configuration of the pedestrian bottleneck can be reasonably changed while ensuring the simulation effect.

[0068] In this study, the commonly used pedestrian flow simulation software, VISSIM and AnyLogic, were used to compare simulation results. First, a simulation model of a pedestrian flow bottleneck with a restricted width, identical to the experimental model, was established, with the same pedestrian parameters as in the experiment. The total number of pedestrians in the road network was limited to 30, and the loop length was proportionally compressed. Finally, the simulation environment was set to an outer radius of 1.8 meters, an inner radius of 0.3 meters, and a constant channel width of 1.5 meters.

[0069] Step S5: Analyze the pedestrian flow simulation results of the simulation software

[0070] VISSIM simulation software can directly measure pedestrian density at different times and intervals using surface measurements. However, VISSIM does not have a direct pedestrian flow measurement function. Therefore, we first use surface measurements to calculate the number of pedestrians entering each surface within a certain time interval (since pedestrians walk counterclockwise, the number of pedestrians entering is the number of pedestrians passing through the corresponding section). This is then divided by the length of each section, 1.5 meters, to obtain the pedestrian flow.

[0071] like Figure 6(a) 、 6(b)6(c). In the present invention, when a bottleneck exists, a small density wave appears between areas 1 and 6, and the smaller the bottleneck width, the more pronounced it is, similar to the experiment. However, unlike the experiment, the density in areas 7 and 8 is significantly lower than in other areas in the simulation. This is due to certain defects in the VISSIM pedestrian flow model. Pedestrians form a single-file queue at the outermost edge of the loop and may remain stationary for long periods of time, resulting in significantly lower density in these two areas.

[0072] like Figure 7(a) 、 7(b) 7(c) In the present invention, pedestrian flow approaches zero in certain spatial and temporal ranges, and more pedestrians stop when the bottleneck width is smaller. This is inconsistent with the experimental results. In other words, the average pedestrian flow and speed in the VISSIM simulation are lower.

[0073] AnyLogic provides the PedFlowStatistics module for counting pedestrian flow and density. Simply call the corresponding function to output pedestrian flow data.

[0074] like Figure 8(a) 、 8(b) 8(c) In the present invention, the simulation results show typical density waves. Even at low density and with no bottlenecks, the wave propagation is visible, which is inconsistent with the experimental results. Due to AnyLogic's inherent settings, pedestrians move quickly and aggressively when there is space, which is in stark contrast to their pauses during congestion.

[0075] like Figure 9(a) 、 9(b) 9(c),In the present invention, in the AnyLogic simulation results, the fluctuation of flow is very small, so that only a single color can be seen in most images, which is inconsistent with the actual situation.

[0076] Step 6: Select simulation effect evaluation indicators to evaluate the simulation effects of different simulation software

[0077] Different evaluation metrics should be selected for comparison in different pedestrian bottleneck experiments. By comparing the results of multiple evaluation metrics, the simulation performance of different software programs can be comprehensively evaluated. For the limited-width bottleneck experiment, the comparison metrics are pedestrian flow statistics and density statistics. Pedestrian speed statistics are the average speed and standard deviation of pedestrian speed at different locations, while pedestrian flow statistics are the average pedestrian flow, standard deviation of pedestrian flow, and density calculated at 15-second intervals. Next, a comparison chart is drawn for each performance evaluation metric. Finally, the simulation software with the best simulation performance is comprehensively evaluated.

[0078] To address the bottleneck of limited width, the present invention counted the average pedestrian flow at different cross-sections in simulation and experiment at 15-second intervals. Since it is impossible to directly compare different flow or density spatiotemporal graphs, the standard deviation of pedestrian flow and density over time was compared.

[0079] like Figure 10(a) 、 10(b) , 10(c) and Figure 11(a) 、 11(b) ,11(c), regardless of the bottleneck width, the average flow and flow standard deviation of the experiment are significantly larger than the simulation results of AnyLogic and VISSIM. In other words, the pedestrian flow models used by VISSIM and AnyLogic have certain defects and cannot fully reflect the movement characteristics of pedestrians in reality.

[0080] like Figure 12(a) 、 12(b) ,12(c),When there is a bottleneck, the simulation results of VISSIM and AnyLogic are close to the ,experimental results.

[0081] In summary, VISSIM, AnyLogic, and SUMO each have their own strengths and weaknesses when simulating pedestrian bottlenecks. While no single software can perfectly reproduce all experimental results, AnyLogic, with its configuration of a 4-meter inner radius and a 5.5-meter outer radius, performs slightly better overall in the simulation of limited-width bottlenecks.

[0082] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0083] It should be noted that the terms "first, second, and third" used in the embodiments of the present application are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It is understood that the terms "first, second, and third" may interchangeably represent a specific order or precedence, where permitted. It should be understood that the terms "first, second, and third" may interchangeably represent objects, where appropriate, such that the embodiments of the present application described herein may be implemented in an order other than that illustrated or described herein.

[0084] The terms "including," "having," and any variations thereof in the embodiments of the present application are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or device comprising a series of steps or modules is not limited to the listed steps or modules, but may optionally include steps or modules not listed, or may optionally include other steps or modules inherent to the process, method, product, or device.

[0085] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A simulation software effect evaluation method based on pedestrian flow bottleneck experiment, characterized in that: The following steps are involved: S1, divides the pedestrian flow bottleneck experiment into the limited width bottleneck experiment and the limited flow bottleneck experiment according to the bottleneck type; S2: Collect the layout parameters of the pedestrian bottleneck experiment, the number of participants, the duration of the experiment, and basic information about pedestrians. Use drone video and pedestrian data collection software to extract pedestrian flow data, and process the pedestrian flow data based on different pedestrian flow bottlenecks. For bottlenecks with limited flow, calculate the average speed and standard deviation of pedestrians at different locations. For bottlenecks with limited width, divide the circular channel into equal areas, and calculate the pedestrian flow at the area boundary and the pedestrian density within the area. S3, according to different pedestrian flow bottleneck types, using the collected pedestrian flow data to analyze the pedestrian flow bottleneck mechanism; S4, based on the pedestrian bottleneck layout parameters and pedestrian flow data, a pedestrian bottleneck model is established using different simulation software; Under the premise of ensuring the simulation effect, change the configuration of pedestrian flow bottleneck; S5, after the pedestrian flow bottleneck simulation is completed, the pedestrian flow data is output and analyzed using different simulation software; S6, for different pedestrian bottleneck experiments, selects different evaluation indicators for comparison; through the comparison results of multiple evaluation indicators, comprehensively evaluates the simulation effects of different software; The evaluation indicators are as follows: the comparison indicator for the flow bottleneck experiment is the pedestrian speed statistics, and the comparison indicators for the width bottleneck experiment are the pedestrian flow statistics and density statistics; among them, the pedestrian speed statistics are the average speed and speed standard deviation of pedestrians at different locations, and the pedestrian flow statistics are the average pedestrian flow, pedestrian flow, and density standard deviation calculated within a set time interval; Then, draw a comparison chart for different effect evaluation indicators.

2. The simulation software effect evaluation method based on pedestrian flow bottleneck experiment according to claim 1 is characterized in that: In step S2, the basic information of the pedestrian in the experimental configuration parameters includes the pedestrian's height, pedestrian's width, and pedestrian's walking speed.

3. The simulation software effect evaluation method based on pedestrian flow bottleneck experiment according to claim 1 is characterized in that: In step S2, the method for collecting pedestrian flow data is to first use a drone to shoot a pedestrian flow experiment video, and then use three-dimensional tracking software to extract the pedestrian flow data.

4. The simulation software effect evaluation method based on pedestrian flow bottleneck experiment according to claim 1 is characterized in that: In step S3, for limiting the flow bottleneck, the pedestrian trajectory map is drawn using the pedestrian's real-time coordinates and the changing trend of the pedestrian speed statistics is analyzed; For bottlenecks with restricted width, pedestrian flow and pedestrian density are used to draw the spatial-temporal map of pedestrian flow and the spatial-temporal map of pedestrian density as well as the comparison map of average pedestrian flow.

5. The simulation software effect evaluation method based on pedestrian flow bottleneck experiment according to claim 1 is characterized in that: In step S4, it is ensured that changing the configuration of the pedestrian flow bottleneck will not have a qualitative impact on the simulation results.

6. The simulation software effect evaluation method based on pedestrian flow bottleneck experiment according to claim 1 is characterized in that: In step S5, when the pedestrian flow data is outputted using the simulation software, the outputted real-time positions and real-time speeds of pedestrians need to be processed accordingly to obtain other pedestrian flow data.

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