A heuristic micro-evacuation modeling method and simulation system based on pedestrian vision

Abstract

The present invention discloses a heuristic micro-evacuation modeling method based on pedestrian vision and a simulation system. The method is to construct a perception area, define pedestrian perception objects as all visible objects in the perception area, and update the pedestrian position based on speed direction decision, speed size decision and collision elimination mechanism. At the same time, a simulation system for implementing a heuristic micro-evacuation modeling method based on pedestrian vision is constructed. The modeling method disclosed in the present invention makes the pedestrian's perception of the environment and the decision-making process more in line with reality; comprehensively considering the current speed size and the maximum speed size, determining the pedestrian's speed size in the next time step, is more in line with the fact that pedestrians in reality do not tend to significantly change their own speed size.

Description

Technical Field

[0001] The present invention belongs to the technical field of pedestrian evacuation, and in particular relates to a pedestrian vision-based heuristic microscopic evacuation modeling method and a simulation system. Background Art

[0002] With the rapid development of social economy, the urban population is increasing. At the same time, with the increase in the frequency of pedestrian travel and the increase in various gathering activities, large-scale crowds often gather in public places such as railway stations, subway stations, and stadiums, which brings challenges to urban safety management. Therefore, in order to ensure that the crowd can be evacuated safely when an emergency occurs, it is crucial to study the movement characteristics and behavior laws of pedestrians and formulate corresponding evacuation strategies. Pedestrian flow modeling is an important way to achieve these goals.

[0003] The existing microscopic models for studying pedestrian flow mainly include: rule-based models, represented by the cellular automaton model (CAM); force-based models, represented by the social force model (SFM); and velocity-based models, represented by the collision-free velocity model (CVM). However, the models based on CAM may have some defects due to excessive dispersion in space and time, such as difficulty in selecting the size of the grid and time step, different distances between diagonal movement and horizontal and vertical movement, and limited speed range and maximum density; the models based on SFM may have unrealistic vibration and retreat phenomena, and the model does not consider the maximum force that pedestrians may bear. In addition, the behavioral mechanism of pedestrian evacuation consists of three parts: perception, decision-making, and action. Due to the limitations of basic rules, the models based on CAM and SFM cannot reproduce the behavioral mechanism of pedestrian evacuation, and thus cannot reflect the autonomy and heterogeneity of pedestrians in the evacuation process, which is precisely the advantage of the model based on CVM.

[0004] In the existing CVM-based models, according to the way the pedestrian's speed direction is determined, the related models are mainly divided into two categories: one is to select an optimal direction as the pedestrian's moving direction from a discrete or continuous speed direction set according to certain rules; the other is to express the relationship between pedestrians and environmental perception objects in the form of force, and the final resultant force direction is the pedestrian's moving direction. However, in the process of pedestrians perceiving the surrounding environment, these models simply define the perception object as all pedestrians within a certain range, while in fact pedestrians perceive environmental information based on vision, that is, the pedestrian's perception object should be all visible objects; in addition, the factors considered by the existing models in the pedestrian's decision-making process are related to the current state of the perception object, while in fact pedestrians have a certain degree of predictability of the environment when making decisions; finally, these models usually use density-speed function or forward distance-speed function to determine the pedestrian's speed, while in fact pedestrians do not tend to change their speed direction or speed significantly during movement.

[0005] In summary, the existing models cannot reproduce the perception behavior of pedestrians during movement well, and the factors considered when determining the speed of pedestrians are too single. Summary of the invention

[0006] In order to address the deficiencies in the prior art, the present invention provides a heuristic micro-evacuation modeling method and simulation system based on pedestrian vision, which can better reproduce the process of perception, decision-making and action during pedestrian movement, making pedestrian movement more reasonable and efficient.

[0007] The technical solution adopted by the present invention is as follows:

[0008] A heuristic microscopic evacuation modeling method based on pedestrian vision includes the following steps:

[0009] Step 1: construct a perception area, wherein the perception area is composed of a plurality of sub-areas;

[0010] Step 2: acquiring perception information in the perception area, wherein the perception information is composed of all visible objects in the perception area, and the visible objects include visible pedestrians and visible obstacles;

[0011] Step 3: Calculate the speed direction of pedestrian i at time step t The direction cost is selected, and the speed direction with the smallest direction cost is selected as the speed direction e of the next time step i (t+1), complete the speed direction decision of pedestrian i at time step t;

[0012] Step 4: Based on the current speed V of pedestrian i i (t) and the maximum velocity V at the next time step imax (t+1), determine the velocity V of the next time step i (t+1), complete the speed decision of pedestrian i at time step t;

[0013] Step 5: determine the collision elimination mechanism adopted by pedestrian i after the collision at time step t;

[0014] Step 6: Based on the speed direction decision, speed magnitude decision and collision elimination mechanism, update the position of pedestrian i at time step t+1.

[0015] Furthermore, the method for calculating the directional cost of each speed direction of pedestrian i at time t is:

[0016] S1.1, based on the intrinsic The maximum distance V that can be moved in a direction i 0 Δt and Distance in the direction where no collision occurs Determine pedestrian i in Direction The distance that can be moved in the next time step Δt

[0017] S1.2, calculate separately The distance cost, inertia cost and psychological cost of the direction are expressed as:

[0018]

[0019] Among them, R i is the radius of the sensing area, e i 0 (t) represents the expected moving direction of pedestrian i at time step t, A is the distance value, e i (t) is the speed direction of pedestrian i at the current time step, e j (t) is the speed direction of pedestrian j at the current time step, d ij (t+t p ) represents the position of pedestrian i and the predicted time t after visible pedestrian j p The distance between the rear positions, r ij represents the sum of the radii of pedestrian i and pedestrian j, r i is the radius of pedestrian i; d iw (t) represents the distance between pedestrian i and obstacle w; and Respectively expressed in e i k (t) Pedestrians and obstacles that may collide with pedestrian i in the direction;

[0020] S1.3, based on distance cost, inertia cost and psychological cost, Direction cost of direction It is expressed as:

[0021]

[0022] Among them, κ 1、 κ 2、 κ3 are the weights of the distance cost, inertia cost and psychological cost respectively; N dis 、N ine 、N phy They represent the normalized constants of the corresponding distance cost, inertia cost and psychological cost respectively.

[0023] Furthermore, in S1.1 Distance in the direction where no collision occurs The calculation steps are as follows:

[0024] ① Calculate the visible pedestrian set P i (t) The pedestrian passes the predicted time t p The position after is expressed as:

[0025] x j (t+t p )=x j (t)+e j (t)·V j (t)·t p

[0026] Among them, x j (t) represents the position of pedestrian j at time step t, e j (t) and V j (t) represent the direction and magnitude of the speed of pedestrian j at time step t, t p Indicates the prediction time;

[0027] ②Calculate in Pedestrians who may collide with pedestrian i in the direction and obstacles It is expressed as:

[0028]

[0029]

[0030] Among them, e i (t) is the speed direction of pedestrian i at the current time step, e ij (t+t p ) represents the unit vector pointing from pedestrian i to the predicted position of pedestrian j; cos<e i (t),e ij (t+t p )> indicates the speed direction of pedestrian i and eij (t+t p ) between the cosine value; d ij (t+t p ) represents the position of pedestrian i and the predicted time t after visible pedestrian j p The distance between the rear positions; is the k-th perception direction of pedestrian i and e ij (t+t p ), r ij represents the sum of the radii of pedestrians i and j; d iw (t) represents the distance between pedestrian i and obstacle w, e iw (t) is the normal direction of the obstacle;

[0031] ③Calculation The predicted time t of the person in the middle p The distance between the rear position and the position of pedestrian i is e i k (t) The projection value in the direction, The distance between the obstacle position and the pedestrian i position is e i k The projection value in the (t) direction and the perception area are the radius R i The minimum value between i k (t) Distance in the direction where no collision occurs

[0032] Further, in step 4, the maximum velocity V of the next time step is calculated i max Steps for (t+1):

[0033] The distance that pedestrian i should travel without collision in the direction of the speed in the next time step is the pedestrian’s forward distance h. If the forward distance h is less than the minimum forward distance h, min , then V i max (t+1)=0;

[0034] If h is greater than h min And (hh min ) / T is less than V i 0 , then V i max (t+1)=(hh min ) / T;

[0035] If h is greater than h min And (hh min ) / T is greater than V i 0 , then V imax (t+1)=V i 0 .

[0036] Furthermore, the speed of the pedestrian in the next time step is V i (t+1) is the pedestrian’s current speed V i (t) and the maximum velocity V at the next time step i max The interpolation between (t+1) is calculated as follows:

[0037]

[0038] Where τ is the time interval.

[0039] Furthermore, the collision elimination mechanism is as follows: if e i (t)·e j (t)<0, at time step t+1, pedestrian i will remain stationary and pedestrian j will update its position; if e i (t)·e j (t)≥0, at time step t+1, pedestrians i and j both update their positions, but pedestrian j reduces its size by half to simulate sideways movement.

[0040] Furthermore, in step 6, the pedestrian position is updated, expressed as: i (t+1)=x i (t)+e i (t+1)·V i (t+1)·Δt,

[0041] Furthermore, the perception area of ​​pedestrian i at time step t is radius R i The 180° fan-shaped area is composed of n sub-areas with the same central angle.

[0042] Furthermore, visible pedestrians and visible obstacles are defined as follows: assuming that a number of rays are emitted from the position of pedestrian i, other pedestrians or obstacles intersecting with the rays in the sensing area are visible pedestrians and visible obstacles.

[0043] A pedestrian vision-based heuristic micro-evacuation simulation system, used to implement the above-mentioned pedestrian vision-based heuristic micro-evacuation modeling method, the system includes a perception module, a decision module and an execution module;

[0044] The perception module is used for pedestrians to perceive the surrounding environment information; based on the constructed pedestrian perception area, the position and speed of all visible pedestrians and obstacles are obtained;

[0045] The decision module is composed of a speed direction decision module and a speed magnitude decision module. Based on the perception information provided by the perception module, the speed direction decision module considers various factors that affect the speed direction of the pedestrian and determines the speed direction of the next time step. The speed magnitude decision module comprehensively considers the current speed magnitude and the maximum speed magnitude and determines the speed magnitude of the next time step.

[0046] Execution module: Based on the speed and direction of the decision module, the execution module updates the position of pedestrians and eliminates collisions between pedestrians during movement.

[0047] Beneficial effects of the present invention:

[0048] (1) The present invention defines pedestrian perception objects as all visible objects in the perception area, eliminating the drawback that the perception objects in the traditional model are all objects in the perception area, making the pedestrian's perception of the environment in the model more realistic.

[0049] (2) The present invention takes into account the predictability of the environment in the pedestrian decision-making process, and abandons the drawback that the factors considered in the traditional model in the pedestrian decision-making process are related to the current state of the perceived object, making the pedestrian decision-making process in the model more realistic.

[0050] (3) The present invention comprehensively considers the current speed and the maximum speed to determine the speed of the pedestrian in the next time step, thereby eliminating the drawback of the traditional model that determines the speed based only on the density-speed function or the forward distance-speed function, making it more consistent with the fact that pedestrians in reality do not tend to significantly change their own speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 Schematic diagram of the pedestrian i perception area described in the present invention.

[0052] Figure 2 Schematic diagram of pedestrian i perception information according to the present invention.

[0053] Figure 3 Schematic diagram of the collision distance of pedestrian i according to the present invention.

[0054] Figure 4 Schematic diagram of the pedestrian i collision handling mechanism of the present invention. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0056] In this embodiment, pedestrians are homogeneous, that is, the parameter values ​​of all pedestrians are the same.

[0057] Under the above conditions, a heuristic micro-evacuation modeling method based on pedestrian vision specifically includes the following steps:

[0058] Step 1: Construction of perception area. Figure 1 As shown, the perception area of ​​pedestrian i at time step t is radius R i The 180° fan-shaped area is composed of n sub-areas with the same central angle. The center direction of the sensing area is the speed direction e of pedestrian i at the current time step. i (t). Where R i =10m, n=15, the sub-area set is

[0059] Step 2: Acquisition of perception information. The perception information of pedestrian i at time step t is composed of all visible objects in the perception area. Visible objects include visible pedestrians and visible obstacles. Visible pedestrians and visible obstacles are defined as: there is a ray emitted from the position of pedestrian i that intersects with other pedestrians or obstacles in the perception area. The visible pedestrian set is composed of all visible pedestrians in the entire perception area of ​​pedestrian i at time step t, which is expressed as Among them, p i k (t) represents the visible pedestrians in the kth sub-area of ​​pedestrian i at time t. The obstacle set is composed of all obstacles in the entire perception area of ​​pedestrian i at time step t, which is expressed as Among them, i k (t) represents the visible obstacles of pedestrian i in the kth sub-area at time step t. Figure 2 (a) is the top view of the perceived information of pedestrian i. Figure 2 (b) is the perspective of pedestrian i itself, where p1 and p2 are the visible pedestrians of pedestrian i.

[0060] Step 3: Pedestrian speed direction decision. The speed direction of pedestrian i at time step t is Composition Collection Calculate the directional cost of each speed direction in the set respectively, and select the speed direction with the smallest directional cost as the speed direction e of the next time step i (t+1), the specific steps are as follows:

[0061] S1, calculate the speed direction set E of pedestrian i at time t i The directional cost of each speed direction in (t). The speed direction set E i (t) in any direction Direction cost is the distance cost in that direction Inertia Cost and psychological costs Composition, so the direction cost The calculation steps are as follows:

[0062] S1.1, calculate the pedestrian i in any direction The distance that can be moved in the next time step Δt If pedestrian i is within the next time step The maximum distance V that can be moved in a direction i 0 ·Δt is less than Distance in the direction where no collision occurs but Pick:

[0063]

[0064] On the contrary, if pedestrian i is within the next time step The maximum distance V that can be moved in a direction i 0 ·Δt is greater than or equal to Distance in the direction where no collision occurs but Pick:

[0065]

[0066] Among them, V i 0 is the free speed of pedestrian i, and its value is V i 0 =1.55m / s; Δt is the time step, and its value is Δt=0.04s.

[0067] More specifically, in S1.1 above Distance in the direction where no collision occurs The calculation steps are as follows:

[0068] ① Calculate the visible pedestrian set P i (t) The pedestrian passes the predicted time t p The position after x j (t+t p ), the process is as follows:

[0069] For P i Any pedestrian j in (t) will pass through the predicted time t p The position after can be expressed as:

[0070] x j (t+t p )=x j (t)+e j (t)·V j(t)·t p

[0071] Among them, x j (t) represents the position of pedestrian j at time step t, e j (t) and V j (t) represent the speed direction and speed magnitude of pedestrian j at time step t, respectively, and the prediction time t p = 0.5s, such as Figure 3 As shown in (a), p1 and p2 are the current states of pedestrians visible to pedestrian i, and p′1 and p′2 are the states of pedestrians visible to pedestrian i after t p Status after time.

[0072] ②Calculate in Pedestrians who may collide with pedestrian i in the direction and obstacles The process is as follows:

[0073] In e i k The visible pedestrians that may collide with pedestrian i in the direction (t) satisfy the following conditions: the position of the visible pedestrian after the prediction time is still within the perception area of ​​pedestrian i, and the predicted position of the visible pedestrian is within the range of e i k (t) The distance of the straight line in the direction is less than the sum of the radii of the two pedestrians;

[0074] In e i k The obstacles that may collide with pedestrian i in the direction (t) satisfy the following conditions: the visible obstacle position is from e to i k (t) The distance of the straight line in the direction is less than the pedestrian radius;

[0075] Based on the above conditions, in e i k (t) Pedestrians who may collide with pedestrian i in the direction and obstacles The calculation formula is as follows:

[0076]

[0077] Among them, e i (t) is the speed direction of pedestrian i at the current time step, e ij (t+t p ) represents the unit vector pointing from pedestrian i to the predicted position of pedestrian j; cos<e i (t),e ij (t+t p )> indicates the speed direction of pedestrian i and e ij (t+t p) between the cosine value; d ij (t+t p ) represents the position of pedestrian i and the predicted time t after visible pedestrian j p The distance between the rear positions; is the k-th perception direction of pedestrian i and e ij (t+t p ), r ij represents the sum of the radii of pedestrian i and pedestrian j, which can be expressed as r ij =r i +r j , the pedestrian radius is 0.2m; d iw (t) represents the distance between pedestrian i and obstacle w, which can be expressed as d iw (t)=||x i (t)-x w (t)||,e iw (t) is the normal direction of the obstacle.

[0078] ③Calculation The predicted time t of the person in the middle p The distance between the rear position and the position of pedestrian i is e i k (t) The projection value in the direction, The distance between the obstacle position and the pedestrian i position is e i k The projection value in the (t) direction and the perception area are the radius R i The minimum value between i k (t) Distance in the direction where no collision occurs Therefore It can be expressed as:

[0079]

[0080] The distance in all directions that pedestrian i can avoid collision like Figure 3 As shown in (b).

[0081] S1.2, calculate separately Distance cost, inertia cost and psychological cost of direction:

[0082]

[0083] Among them, e i 0 (t) represents the expected moving direction of pedestrian i at time step t, and A is the distance value, which can be 3 (unit: meter). i (t) is the velocity direction of pedestrian i at the current time step.

[0084] S1.3, Direction cost of direction The distance cost, inertia cost and psychological cost in this direction are normalized and multiplied by the sum of the corresponding weights, expressed as:

[0085]

[0086] Among them, κ1, κ2, and κ3 are the weights of the distance cost, inertia cost, and psychological cost, respectively, κ1 = 0.375, κ2 = 0.125, and κ3 = 0.5; N dis 、N ine 、N phy Respectively represent the corresponding cost normalization constants, and their values ​​are

[0087] S2, select the direction with the smallest direction cost as the pedestrian speed direction for the next time step:

[0088]

[0089] Step 4: Pedestrian i’s speed decision at time step t. Comprehensively consider the current speed V of pedestrian i i (t) and the maximum velocity V at the next time step i max (t+1), determine the velocity V of the next time step i (t+1). The calculation steps are as follows:

[0090] S4.1, calculate the maximum velocity V of the next time step i max (t+1).

[0091] The distance that pedestrian i should travel without collision in the direction of the speed in the next time step is the pedestrian's forward distance h. Based on the relationship between the forward distance and the pedestrian's speed, the maximum speed V of pedestrian i is determined. i max (t+1). If the forward distance h is less than the minimum forward distance h min , then V i max (t+1)=0;

[0092] If h is greater than h min And (hh min ) / T is less than V i 0 , then V i max (t+1)=(hh min ) / T;

[0093] If h is greater than h min And (hh min ) / T is greater than V i 0 , then V i max (t+1)=V i 0 , where h = 0.3m, T = 0.6.

[0094] Therefore, the maximum velocity of the next time step can be summarized as:

[0095]

[0096] S4.2, the speed of the pedestrian at the next time step V i (t+1) is the pedestrian’s current speed V i (t) and the maximum velocity V at the next time step i max The interpolation between (t+1) is calculated as follows:

[0097]

[0098] Wherein, τ is the time interval, which can be taken as τ=0.5s.

[0099] Step 5: Collision processing of pedestrian i at time step t.

[0100] The condition for a collision between pedestrian i and pedestrian j is: the distance d between the two pedestrians at time step t ij (t) <r ij .

[0101] When a collision occurs, a collision elimination mechanism is used to eliminate the collision, such as Figure 4 As shown, the collision elimination mechanism is as follows: if e i (t)·e j (t)<0, at time step t+1, pedestrian i will remain stationary, and pedestrian j will update its position, such as Figure 4 As shown in (a); on the contrary, at time step t+1, pedestrians i and j both update their positions, but pedestrian j reduces its size by half to simulate sideways movement, as shown in Figure 4 As shown in (b). i (t) is the speed direction of pedestrian i at the current time step, e j (t) is the speed direction of pedestrian j at the current time step. Step 6: Pedestrian i updates its position at time step t+1. Based on the speed direction decision, speed magnitude decision and collision processing results, the updated pedestrian position is calculated: x i (t+1)=x i (t)+e i (t+1)·V i(t+1)·Δt.

[0102] A heuristic microscopic evacuation simulation system based on pedestrian vision includes a perception module, a decision module and an execution module.

[0103] The perception module is used for pedestrians to perceive the surrounding environment information; based on the constructed pedestrian perception area, the position and speed of all visible pedestrians and obstacles are obtained.

[0104] The decision module consists of a speed direction decision module and a speed magnitude decision module. Based on the perception information provided by the perception module, the speed direction decision module considers various factors that affect the speed direction of pedestrians and determines the speed direction of the next time step. The speed magnitude decision module comprehensively considers the current speed magnitude and the maximum speed magnitude and determines the speed magnitude of the next time step.

[0105] Execution module: Based on the speed and direction of the decision module, the execution module updates the position of pedestrians and eliminates collisions between pedestrians during movement.

[0106] The above embodiments are only used to illustrate the design ideas and features of the present invention, and their purpose is to enable those skilled in the art to understand the content of the present invention and implement it accordingly. The protection scope of the present invention is not limited to the above embodiments. Therefore, any equivalent changes or modifications made based on the principles and design ideas disclosed by the present invention are within the protection scope of the present invention.

Claims

1. A heuristic microscopic evacuation modeling method based on pedestrian vision, characterized in that: Includes steps: Step 1: construct a perception area, wherein the perception area is composed of a plurality of sub-areas; Step 2: acquiring perception information in the perception area, wherein the perception information is composed of all visible objects in the perception area, and the visible objects include visible pedestrians and visible obstacles; Step 3: Calculate the speed direction of pedestrian i at time step t The direction cost is selected, and the speed direction with the smallest direction cost is selected as the speed direction e of the next time step i (t+1), complete the speed direction decision of pedestrian i at time step t; Step 4: Based on the current speed V of pedestrian i i (t) and the maximum velocity V at the next time step i max (t+1), determine the velocity V of the next time step i (t+1), complete the speed decision of pedestrian i at time step t; Step 5: determine the collision elimination mechanism adopted by pedestrian i after the collision at time step t; Step 6: Based on the speed direction decision, speed magnitude decision and collision elimination mechanism, the position of pedestrian i at time step t+1 is updated, and the directional cost of each speed direction of pedestrian i at time t is calculated: S1.1, based on the intrinsic The maximum distance V that can be moved in a direction i 0 Δt and Distance in the direction where no collision occurs Determine pedestrian i in Direction The distance that can be moved in the next time step Δt Among them, V i 0 is the free speed of pedestrian i; S1.2, calculate separately The distance cost, inertia cost and psychological cost of the direction are expressed as: Among them, R i is the radius of the sensing area, e i 0 (t) represents the expected moving direction of pedestrian i at time step t, A is the distance value, e i (t) is the speed direction of pedestrian i at the current time step, e j (t) is the speed direction of pedestrian j at the current time step, d ij (t+t p ) represents the position of pedestrian i and the predicted time t of visible pedestrian j p The distance between the rear positions, r ij represents the sum of the radii of pedestrian i and pedestrian j, r i is the radius of pedestrian i; d iw (t) represents the distance between pedestrian i and obstacle w; and Respectively expressed in e i k (t) Pedestrians and obstacles that may collide with pedestrian i in the direction; S1.3, based on distance cost, inertia cost and psychological cost, Direction cost of direction It is expressed as: Among them, κ 1、 κ 2、 κ3 are the weights of the distance cost, inertia cost and psychological cost respectively; N dis 、N ine 、N phy They represent the normalized constants of the corresponding distance cost, inertia cost and psychological cost respectively.

2. The heuristic microscopic evacuation modeling method based on pedestrian vision according to claim 1 is characterized in that: S1.1 Distance in the direction where no collision occurs The calculation steps are as follows: ① Calculate the visible pedestrian set P i (t) The pedestrian passes the predicted time t p The position after is expressed as: x j (t+t p )=x j (t)+e j (t)·V j (t)·t p Among them, x j (t) represents the position of pedestrian j at time step t, e j (t) and V j (t) represent the direction and magnitude of the speed of pedestrian j at time step t, t p Indicates the prediction time; ②Calculate Pedestrians who may collide with pedestrian i in the direction and obstacles It is expressed as: Among them, e i (t) is the speed direction of pedestrian i at the current time step, e ij (t+t p ) represents the unit vector pointing from pedestrian i to the predicted position of pedestrian j; cos<e i (t),e ij (t+t p )> indicates the direction of pedestrian i’s speed and e ij (t+t p ) between the cosine value; d ij (t+t p ) represents the position of pedestrian i and the predicted time t of visible pedestrian j p The distance between the rear positions; is the k-th perception direction of pedestrian i and e ij (t+t p ), r ij represents the sum of the radii of pedestrians i and j; d iw (t) represents the distance between pedestrian i and obstacle w, e iw (t) is the normal direction of the obstacle; ③Calculation The predicted time t of the person in the middle p The distance between the rear position and the position of pedestrian i is e i k (t) The projection value in the direction, The distance between the obstacle position and the pedestrian i position is e i k The projection value in the (t) direction and the perception area are the radius R i The minimum value between i k (t) Distance in the direction where no collision occurs 3. The heuristic microscopic evacuation modeling method based on pedestrian vision according to claim 1 is characterized in that: In step 4, calculate the maximum velocity V of the next time step i max Steps for (t+1): The distance that pedestrian i should travel without collision in the direction of the speed in the next time step is the pedestrian's forward distance h. If the forward distance h is less than the minimum forward distance h, min , then V i max (t+1)=0; If h is greater than h min And (hh min ) / T is less than V i 0 , then V i max (t+1)=(hh min ) / T; If h is greater than h min And (hh min ) / T is greater than V i 0 , then V i max (t+1)=V i 0 .

4. The heuristic microscopic evacuation modeling method based on pedestrian vision according to claim 3 is characterized in that: The speed of the pedestrian at the next time step V i (t+1) is the pedestrian’s current speed V i (t) and the maximum velocity V at the next time step i max The interpolation between (t+1) is calculated as follows: Where τ is the time interval.

5. The heuristic microscopic evacuation modeling method based on pedestrian vision according to claim 1 is characterized in that: The specific collision elimination mechanism is: if e i (t)·e j (t)<0, at time step t+1, pedestrian i will remain stationary and pedestrian j will update its position; if e i (t)·e j (t)≥0, at time step t+1, pedestrians i and j both update their positions, but pedestrian j reduces its size by half to simulate sideways movement.

6. The heuristic microscopic evacuation modeling method based on pedestrian vision according to claim 1 is characterized in that: In step 6, the pedestrian position is updated, expressed as: i (t+1)=x i (t)+e i (t+1)·V i (t+1)·Δt, where V i (t+1) is the speed of the pedestrian in the next time step, e i (t+1) is the velocity direction of the next time step, Δt is the next time step, x i (t) is the position of pedestrian i at time step t.

7. The heuristic microscopic evacuation modeling method based on pedestrian vision according to claim 1 is characterized in that: The perception area of ​​pedestrian i at time step t is radius R i The 180° sector area is composed of n sub-areas with the same central angle.

8. The heuristic microscopic evacuation modeling method based on pedestrian vision according to claim 1 is characterized in that: Visible pedestrians and visible obstacles are defined as follows: Assuming that several rays are emitted from the position of pedestrian i, other pedestrians or obstacles intersecting with the rays in the sensing area are visible pedestrians and visible obstacles.

9. A heuristic microscopic evacuation simulation system based on pedestrian vision, characterized in that: For implementing the heuristic microscopic evacuation modeling method based on pedestrian vision as described in claim 1 above, the system includes a perception module, a decision module and an execution module; The perception module is used for pedestrians to perceive the surrounding environment information; based on the constructed pedestrian perception area, the position and speed of all visible pedestrians and obstacles are obtained; The decision module is composed of a speed direction decision module and a speed magnitude decision module. Based on the perception information provided by the perception module, the speed direction decision module considers various factors that affect the speed direction of the pedestrian and determines the speed direction of the next time step. The speed magnitude decision module comprehensively considers the current speed magnitude and the maximum speed magnitude and determines the speed magnitude of the next time step. Execution module: Based on the speed and direction of the decision module, the execution module updates the position of pedestrians and eliminates collisions between pedestrians during movement.

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