CN117993225A

CN117993225A - Method and device for simulating crossing behavior of narrow area

Info

Publication number: CN117993225A
Application number: CN202410396600.8A
Authority: CN
Inventors: 彭靖萱; 魏中华; 佟雪莹; 王世豪; 李永行; 陈艳艳; 王少帆; 李昀轩
Original assignee: Beijing University of Technology
Current assignee: Beijing University of Technology
Priority date: 2024-04-03
Filing date: 2024-04-03
Publication date: 2024-05-07
Anticipated expiration: 2044-04-03
Also published as: CN117993225B

Abstract

The present disclosure relates to a method and apparatus for simulating crossing behavior of a stenotic region. The simulation method of the crossing behavior of the narrow area comprises the following steps: constructing a target model of a target pedestrian in a narrow area, and determining motion related information of the target pedestrian; the width of the narrow area is smaller than the shoulder width of the target pedestrian and larger than the chest thickness of the target pedestrian; based on the target model, the width of the narrow area and the motion related information, determining a lateral constraint condition of the crossing behavior of the target pedestrian in the narrow area; constructing a torsion social force model based on the sideways behavior; under the constraint of the lateral constraint condition, the crossing behavior of the target pedestrian in the narrow area is simulated by utilizing the torsion social force model, and the target behavior track of the target pedestrian is obtained. The method and the device can simulate the crossing behavior of the target pedestrian in the narrow area based on the sideways behavior of the pedestrian, and improve the reality of the simulation.

Description

Method and device for simulating crossing behavior of narrow area

Technical Field

The disclosure relates to the field of computer technology, and in particular relates to a simulation method and device for crossing behavior of a narrow area.

Background

As an important component of transportation travel, pedestrian comfort and safety have been the focus of research. Over the past few decades, scholars have conducted extensive research on pedestrian dynamics and have proposed a variety of microscopic simulation models to simulate pedestrian behavior.

In the related art, when the micro simulation models simulate the crossing behavior of the narrow area, the pedestrian can choose to change the moving direction, stop moving or detour when touching the wall of the narrow area or other pedestrians, and therefore, the micro simulation models ignore that the pedestrian keeps a distance from the wall of the narrow area through lateral behaviors, namely rotation behaviors, so as to avoid collision.

Disclosure of Invention

In view of the above, the embodiments of the present disclosure provide a method and an apparatus for simulating a traversing behavior of a narrow area, so as to solve the problems in the related art.

In a first aspect of an embodiment of the present disclosure, a method for simulating a traversing behavior of a narrow area is provided, including:

Constructing a target model of a target pedestrian in a narrow area, and determining motion related information of the target pedestrian; wherein the width of the narrow area is smaller than the shoulder width of the target pedestrian and larger than the chest thickness of the target pedestrian;

Determining a lateral constraint condition of the crossing behavior of the target pedestrian in the narrow area based on the target model, the width of the narrow area and the motion related information;

Constructing a torsion social force model based on the sideways behavior;

And under the constraint of the lateral constraint condition, simulating the crossing behavior of the target pedestrian in the narrow area by using the torsion social force model to obtain a target behavior track of the target pedestrian.

In a second aspect of the embodiments of the present disclosure, there is provided an apparatus for simulating a traversing behavior of a narrow region, including:

The construction module is used for constructing a target model of a target pedestrian in a narrow area and determining motion related information of the target pedestrian; wherein the width of the narrow area is smaller than the shoulder width of the target pedestrian and larger than the chest thickness of the target pedestrian;

The processing module is used for determining a sideways constraint condition of the crossing behavior of the target pedestrian in the narrow area based on the target model, the width of the narrow area and the motion related information;

the construction module is also used for constructing a torsion social force model based on the sideways behavior;

And the simulation module is used for simulating the crossing behavior of the target pedestrian in the narrow area by utilizing the torsion social force model under the constraint of the lateral constraint condition to obtain a target behavior track of the target pedestrian.

In a third aspect of the disclosed embodiments, there is provided an electronic device, including: at least one processor; a memory for storing at least one processor-executable instruction; wherein the at least one processor is configured to execute instructions to implement the steps of the above-described method.

In a fourth aspect of the disclosed embodiments, a computer-readable storage medium is provided, which when executed by a processor of an electronic device, enables the electronic device to perform the steps of the above-described method.

The above-mentioned at least one technical scheme that the embodiment of the disclosure adopted can reach following beneficial effect: constructing a target model of a target pedestrian in a narrow area, and determining motion related information of the target pedestrian; the width of the narrow area is smaller than the shoulder width of the target pedestrian and larger than the chest thickness of the target pedestrian; based on the target model, the width of the narrow area and the motion related information, determining a lateral constraint condition of the crossing behavior of the target pedestrian in the narrow area; constructing a torsion social force model based on the sideways behavior; under the constraint of the lateral constraint condition, the crossing behavior of the target pedestrian in the narrow area is simulated by utilizing the torsion social force model, so that the target behavior track of the target pedestrian is obtained, the crossing behavior of the target pedestrian in the narrow area can be simulated based on the lateral behavior of the pedestrian, and the reality of the simulation is improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings that are required for the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and other drawings may be obtained according to these drawings without inventive effort for a person of ordinary skill in the art.

FIG. 1 illustrates a schematic diagram of a narrow zone traversing behavior provided by an exemplary embodiment of the present disclosure;

FIG. 2 illustrates a schematic diagram of rotational timing of traversing behavior of a stricture provided by exemplary embodiments of the present disclosure;

FIG. 3 illustrates a rotational schematic of an elliptical model of a pedestrian provided by an exemplary embodiment of the present disclosure;

FIG. 4 is a flow chart of a simulation method for traversing a stenosis provided by an exemplary embodiment of the present disclosure;

FIG. 5 shows a schematic diagram of an experimental setup for traversing a stenosis provided by an exemplary embodiment of the present disclosure;

FIG. 6 is a schematic diagram of a simulation apparatus for traversing a narrow area according to an exemplary embodiment of the present disclosure;

fig. 7 shows a schematic structural diagram of an electronic device provided by an exemplary embodiment of the present disclosure;

Fig. 8 shows a schematic structural diagram of a computer system provided in an exemplary embodiment of the present disclosure.

Detailed Description

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure have been shown in the accompanying drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustration purposes only and are not intended to limit the scope of the present disclosure.

It should be understood that the various steps recited in the method embodiments of the present disclosure may be performed in a different order and/or performed in parallel. Furthermore, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.

The term "including" and variations thereof as used herein are intended to be open-ended, i.e., including, but not limited to. The term "based on" is based at least in part on. The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments. Related definitions of other terms will be given in the description below. It should be noted that the terms "first," "second," and the like in this disclosure are merely used to distinguish between different devices, modules, or units and are not used to define an order or interdependence of functions performed by the devices, modules, or units.

It should be noted that references to "one", "a plurality" and "a plurality" in this disclosure are intended to be illustrative rather than limiting, and those of ordinary skill in the art will appreciate that "one or more" is intended to be understood as "one or more" unless the context clearly indicates otherwise.

The names of messages or information interacted between the various devices in the embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

As an important component of transportation travel, pedestrian comfort and safety have been the focus of research. Over the past few decades, scholars have conducted extensive research on pedestrian dynamics and have proposed a variety of microscopic simulation models to simulate pedestrian behavior. In particular, the cellular automaton model (Cellular Automata Model, CAM) and the social force model (Social Force Model, SFM) are representative of a rule-based model in discrete space and a force-based model in continuous space, respectively. CAM and SFM have some drawbacks.

For example, the result of CAM is unpredictable because the movement between meshes depends on probability. When the transition probabilities are the same, most students use roulette to determine the behavior of pedestrians, which causes a large error and poor credibility. Therefore, the CAM cannot truly simulate the interaction effect generated by different travel behaviors of heterogeneous populations.

For example, the running speed of the SFM is slower, and the obvious defects of particle blindness, pedestrian overlapping, high algorithm complexity and the like exist, so that many scholars propose CAM based on the intelligent agent and SFM based on the intelligent agent, and add heterogeneous factors such as physiological, psychological or trip characteristics of pedestrians into the model, and improve the microscopic pedestrian simulation model so as to improve the reality of simulation.

However, many scholars ignore the most common travel behavior of pedestrians: and (5) setting aside. In field studies, it was found that people prefer to do overrun, avoidance and narrow space through small angular rotations of the body rather than choose to change direction of movement, stop movement or detour as is done with current simulation results. Unlike turning behavior, lateral behavior changes the space occupied by a pedestrian by body rotation so that the pedestrian maintains a distance from a wall of a narrow area or other pedestrians, without changing the walking direction.

Therefore, in order to solve the above-mentioned problems, the embodiments of the present disclosure provide a simulation method of crossing behavior of a narrow area, which increases torsion force based on the conventional SFM according to the biomechanics principle, and proposes a concept of a will to lean. The concept establishes the relation between the torsion force and the repulsive force, so that the theoretical situation and the actual situation of SFM simulation are more consistent. Meanwhile, in view of the limitations of the existing simulation schemes, the exemplary embodiments of the present disclosure establish a torsion social force model for the crossing behavior of a narrow region, and perform a great number of practical experiments to verify the reliability of the torsion social force model.

The simulation method for the crossing behavior of the narrow area provided by the embodiment of the disclosure can be executed by the terminal or a chip applied to the terminal.

By way of example, the above-described terminals may include one or more of a cell phone, a tablet computer, a wearable device, a vehicle-mounted device, a notebook computer, an ultra-mobile Personal computer (ultra-mobile Personal computer, UMPC), a netbook, a palm DIGITAL ASSISTANT, PDA, and a wearable device based on augmented reality (augmented reality, AR) and/or Virtual Reality (VR) technology, etc., to which the exemplary embodiments of the present disclosure are not particularly limited.

1. Determining lateral behavior

In order to most truly simulate microscopic behaviors of pedestrians, exemplary embodiments of the present disclosure represent the bodies of pedestrians using elliptical models, and attempt to calculate distances between the elliptical models as distances between pedestrians in order to subsequently correct a social force model based on torsion forces. In the rectangular coordinate system, a _i represents a major half axis of an ellipse model of the ith pedestrian, b _i represents a minor half axis of the ellipse model of the ith pedestrian, 2a _i represents a shoulder width of the ith pedestrian, 2b _i represents a thickness of a chest of the ith pedestrian, and θ _i represents a rotation angle of the ith pedestrian; wherein a _i and b _i are both constant, and a _i>b_i.

Based on this, the exemplary embodiments of the present disclosure may timely simulate the lateral behavior of a pedestrian, discuss the sideways constraint conditions of the traversing behavior in a narrow area, and give the occurrence conditions of the corresponding sideways.

It should be noted that the exemplary embodiments of the present disclosure define the range of the angle that is ignored regardless of the rotation angle caused by the slight shaking of the body of the pedestrian during the movement asWhereinIndicating the rotation angle caused by slight body shaking of pedestrians during the moving process. Meanwhile, the exemplary embodiments of the present disclosure consider that the rotation of the agent that temporarily changes the moving direction is controlled by the driving force, not within the scope of the discussion of the exemplary embodiments of the present disclosure.

In traversing a narrow area, the roll constraints of the pedestrian may include roll angle constraints, roll distance constraints, and roll time constraints.

(1) Determining roll angle constraints

This situation often occurs on a narrow area or shortcut through which pedestrians need to lean to change posture to pass, due to the narrow entrance width of the narrow area or shortcut, but the destination can be reached faster.

Fig. 1 shows a schematic diagram of a traversing behavior of a stenosis area provided by an exemplary embodiment of the present disclosure. As shown in fig. 1, taking a narrow area as an example, the width (L) of the narrow area is smaller than the shoulder width (2 a) of the pedestrian and larger than the chest thickness (2 b) of the pedestrian, and when the body rotation width (d) behind the side body of the pedestrian is smaller than or equal to the width (L) of the narrow area, the pedestrian can complete the traversing behavior by leaning on the side. Therefore, the rotation angle (θ) of the pedestrian can be calculated from the width of the narrow area, and the restriction of the roll angle at which the pedestrian walks sideways in the narrow area can be obtained.

Therefore, in the crossing behavior of the narrow area, the rotation angle constraint (i.e., the roll angle constraint) of the pedestrian is as follows:

（1）

assuming that the psychological distance between the pedestrian and the wall of the narrow area is [ ] in the sideways state ) Very small,A constant may be used, but this constant cannot be ignored, otherwise a large error in the torsion social force model may occur. At this time, assume thatSubstitution into equation (1) can result in the minimum rotation angle. Wherein the minimum rotation angle can be represented by the following formula (2):

（2）

Wherein, May be a constant obtained by practical experiments.

While prior studies have considered that pedestrians return from a rotated posture to an original walking posture immediately after passing through a narrow area. However, the process of restoring the original body posture of the pedestrian after completing the lateral behavior requires time, although this time is short. Therefore, in order to ensure the authenticity of the simulation result, θ=0 is set within T _p after the pedestrian passes through the narrow area, and T _p represents the time required for the rotational posture of the pedestrian to return to the original walking posture, where T _p is a constant.

Based on this, the present disclosure example embodiments make the assumption: it takes time to return from the rotational posture to the original walking posture, which should not be ignored.

(2) Determining a roll distance constraint and a roll time constraint

After determining the rotation angle of the pedestrian sideways in a narrow area or shortcut scene, the sideways moment of the pedestrian sideways needs to be discussed as well. The present disclosure may calculate a distance (D _T) between the rotation start position of the pedestrian and the fixed obstacle, which may be a roll constraint condition. Here, the fixed obstacle may be a wall of a narrow area.

In this case, the pedestrian need only interact with the fixed obstacle. Accordingly, the exemplary embodiments of the present disclosure need only find an acceptable minimum rotational distance between a pedestrian and a fixed obstacle.

Fig. 2 illustrates a schematic diagram of rotational timing of crossing behavior of a stenosis region provided by an exemplary embodiment of the present disclosure. As shown in the figure 2 of the drawings,Representing the initial position of a pedestrian,Representing the edge position of a wall in a narrow area,Representing the intersection point of the X-axis of the horizontal line where the initial position of the pedestrian is located and the projection of the edge position of the wall of the narrow area in the X-axis direction,Representing the rotation start position of pedestrian,Indicating the position of the pedestrian rotating to the wall of the confined area.

Then, can pass throughAndCalculationAndOf (3), whereinRepresenting the expected speed of the pedestrian at time t,Indicating the moment of onset of rotation of the target pedestrian, i.e. the time of roll,Representing the time of rotation of a pedestrian,，The experimentally measured constants are indicated for the angular velocity.

It is obvious that the process is not limited to,Then:

（3）

Wherein, Indicating the distance between the rotation start position of the pedestrian and the wall of the narrow area.

At this time, it can be considered that。

Therefore, substituting the above formula, the restriction of the sideways distance of the pedestrian in the crossing behavior of the narrow area can be obtained as:

（4）

in addition, the restriction of the pedestrian's roll time in the crossing behavior of the narrow area can be obtained as follows:

（5）

2. Torsional social force model

According to a conventional social force model (Social Force Model, SFM), a motion model of an ith pedestrian in a complex environment is represented by a driving force of the ith pedestrian, an interaction force between the ith pedestrian and other pedestrians such as the jth pedestrian, and an interaction force between the ith pedestrian and a fixed obstacle. The social force model can be represented by the following formula:

（6）

（7）

（8）

（9）

Wherein m _i represents the mass of the ith pedestrian, i.e., the target pedestrian, v _i represents the actual speed of the ith pedestrian, v _j represents the actual speed of the jth pedestrian, i.e., the non-target pedestrian, F _i represents the driving force of the ith pedestrian, F _ij represents the interaction force between the ith pedestrian and the jth pedestrian, J represents the total number of pedestrians other than the ith pedestrian, F _iw represents the interaction force between the ith pedestrian and the fixed obstacle, W represents the total number of fixed obstacles, Representing the initial speed of the ith pedestrian,Unit vector representing the i-th pedestrian pointing at the desired target at time t,Representing the expected speed of the ith pedestrian at time t,A _i represents a certain characteristic time, B _i represents the intensity of social force, A _i and B _i are constants, r _ij represents the radius sum of the ith pedestrian and the jth pedestrian, d _ij represents the centroid distance between the ith pedestrian and the jth pedestrian, d _iw represents the centroid distance between the ith pedestrian and the fixed obstacle, n _ij represents the normalized vector of the jth pedestrian pointing to the ith pedestrian, n _iw represents the normalized vector of the jth pedestrian pointing to the fixed obstacle, k _n represents the body compression coefficient, k _t represents the sliding friction coefficient, t _ij represents the tangential direction of the ith pedestrian and the jth pedestrian, t _iw represents the tangential direction of the ith pedestrian and the fixed obstacle,Indicating that the ith pedestrian and the jth pedestrian or fixed obstacle are not in contact with each other. Here, the fixed obstacle may correspond to a wall of a narrow area in an exemplary embodiment of the present disclosure.

The original social force model obviously cannot truly and effectively simulate the rotation behavior of pedestrians. Thus, to better simulate the rotational behavior of pedestrians, exemplary embodiments of the present disclosure propose a torsional social force model (T-SFM) in which two elements are added: torsional force and rotational willingness.

(1) Torsional force

Based on the observed results, the exemplary embodiments of the present disclosure consider that only the shoulder and core of the pedestrian exert forces to rotate the upper body and develop their own torque to accomplish the lateral behavior. The original walking speed and walking direction are not changed. According to biomechanical principles, posture regulation of the human body is achieved by contraction and relaxation of muscles. When the body is to be rotated, the muscles adjust the center of gravity of the body, thereby affecting the rotational inertia. Specifically, when a pedestrian wants to rotate quickly, muscles contract and move the body's center of gravity inward, thereby reducing the rotational inertia, and thus increasing the rotational speed, completing the lateral behavior quickly. Conversely, when a human body tries to slow down the rotation speed, the muscles thereof are relaxed, causing the center of gravity of the human body to move outward, thereby increasing the rotation inertia and slowing down the rotation speed. In addition, the human body can also change the rotation speed by adjusting the muscle strength. As the muscle strength increases, the body can produce more torque, thereby increasing the rotational speed and the sideways speed.

Thus, the torsional force is related to the moment of inertia and the torque. Fig. 3 shows a rotational schematic of an elliptical model of a pedestrian provided by an exemplary embodiment of the present disclosure. As shown in fig. 3, according to the description of the bio-dynamics, the pedestrian represented by the elliptical model will complete a rotation about a virtual axis OM perpendicular to the center point of the ellipse. Assuming that the elliptical model of the pedestrian is an ellipse with uniformly distributed mass, the equation of the ellipse is:

，（10）

the moment of inertia can be expressed by the following formula:

（11）

wherein I represents the moment of inertia of the elliptical model, D represents the plane integration region, m represents the mass of the elliptical model, Representing the density of the elliptical model.

According to the generalized polar transformation, then,

（12）

（13）

Wherein r represents the polar diameter,，Polar angle representing polar coordinates,。

At this time, there are,

（14）

In addition, according to the relation between torque and moment of inertia, and the relation between torque and torque force, the following formula can be obtained:

（15）

wherein F _T represents torsion force, l represents moment arm, and ，Representing angular acceleration,W represents the angular velocity,，Representing the rotation angle,，Indicating the rotation time.

Thus, it is possible to obtain:

（16）

Based on this, the torsion of the i-th pedestrian can be obtained as:

（17）

(2) Rotation willingness

In the conventional social force model, collisions between pedestrians are avoided by means of psychological repulsive forces. However, when pedestrians are overtaken or overrun, the psychological repulsive force is changed. Accordingly, exemplary embodiments of the present disclosure correct a psychological repulsive force of a social force model according to a dynamic density of pedestrians, and increase collision avoidance force and a willingness to lean on a side in a twisted social force model to improve a conventional social force model.

Wherein, in the social force model, the psychological repulsive force can be expressed as:。

In the torsion social force model, firstly, the dimensionless product of the crowd density around pedestrians and the pedestrian area is calculated:

，

Wherein, Representing the dynamic density of pedestrians,。

Then, the intensity of the social acting force is adjusted to beThe scope of the social effort is adjusted toWherein, the method comprises the steps of, wherein,Representing adjustment coefficient,. Thus, pedestrians can adjust psychological repulsive force according to the environment, and more behaviors are completed.

Meanwhile, in order to limit unnecessary contact and collision of pedestrians in overrun or avoidance behavior, the exemplary embodiments of the present disclosure further increase collision avoidance force in the torsional social force model as a constraint condition. Wherein, collision avoidance force can be expressed as:

（18）

（19）

Wherein, Representing the collision force between the ith pedestrian and the jth pedestrian,Representing the collision force between the ith pedestrian and the wall of the confined area,Representing the intensity of the collision force,Representing the range of impact forces,AndAre all constant.

To avoid repulsive forces interfering with lateral behavior, exemplary embodiments of the present disclosure also add a roll willingness as a constraint in the torsional social force model. Wherein, the willingness to roll over can be expressed as:

（20）

Based on this, the torsional social force model can be expressed as:

（21）

（22）

（23）

（24）

（25）

（26）

（27）

（28）

（29）

Wherein, Representing the acceleration of the ith pedestrian at time t,Indicating the position of the ith pedestrian at time t,The initial position of the i-th pedestrian at the initial time is indicated.

Based on this, the exemplary embodiments of the present disclosure propose a simulation method of the crossing behavior of a narrow area, which may be performed by a terminal or by a chip applied to the terminal. The relevant content of the terminal can be referred to in the foregoing, and will not be described in detail herein.

Fig. 4 is a flow chart illustrating a simulation method of crossing behavior of a narrow area according to an exemplary embodiment of the present disclosure. As shown in fig. 4, the simulation of the crossing behavior of the narrow region includes:

S401, constructing a target model of a target pedestrian in a narrow area, and determining motion related information of the target pedestrian; the width of the narrow area is smaller than the shoulder width of the target pedestrian and larger than the chest thickness of the target pedestrian;

S402, determining a sideways constraint condition of crossing behaviors of a target pedestrian in a narrow area based on the target model, the width of the narrow area and the motion related information;

S403, constructing a torsion social force model based on the sideways behavior;

s404, under the constraint of the lateral constraint condition, simulating the crossing behavior of the target pedestrian in the narrow area by using the torsion social force model to obtain the target behavior track of the target pedestrian.

Specifically, the above-mentioned target model may be an elliptical model in the foregoing, 2 times of the major half axis of the elliptical model is used to represent the shoulder width of the target pedestrian, 2 times of the minor half axis of the elliptical model is used to represent the chest thickness of the target pedestrian, and the width of the narrow area is smaller than the shoulder width of the target pedestrian and larger than the chest thickness of the target pedestrian, and at this time, the target pedestrian needs to lean on to change its posture to pass through the narrow area.

The above-described movement-related information is related to the position information and the cornering behavior or the rotation behavior of the target pedestrian. Exemplary embodiments of the present disclosure may determine a roll constraint condition of a crossing behavior of a target pedestrian in a narrow area based on a target model, a width of the narrow area, and motion-related information.

Meanwhile, the method and the device can construct a torsion social force model based on the sideways behavior, and simulate the crossing behavior of the target pedestrian in the narrow area by using the torsion social force model under the constraint of the sideways constraint condition to obtain the target behavior track of the target pedestrian. The torsion social force model can simulate the sideways behavior of the target pedestrian in the crossing behavior, and the reality of the simulation result is improved.

According to the technical scheme of the example embodiment of the disclosure, a target model of a target pedestrian in a narrow area is constructed, and motion related information of the target pedestrian is determined; the width of the narrow area is smaller than the shoulder width of the target pedestrian and larger than the chest thickness of the target pedestrian; based on the target model, the width of the narrow area and the motion related information, determining a lateral constraint condition of the crossing behavior of the target pedestrian in the narrow area; constructing a torsion social force model based on the sideways behavior; under the constraint of the lateral constraint condition, the crossing behavior of the target pedestrian in the narrow area is simulated by utilizing the torsion social force model, so that the target behavior track of the target pedestrian is obtained, the crossing behavior of the target pedestrian in the narrow area can be simulated based on the lateral behavior of the pedestrian, and the reality of the simulation is improved.

In some embodiments, the motion-related information may include a body rotation width that is less than or equal to a width of the stricture, and the roll constraint may include a roll angle constraint; based on the target model, the width of the narrow area and the motion related information, determining the lateral constraint condition of the crossing behavior of the target pedestrian in the narrow area can comprise:

based on the target model, the width of the stricture, and the body rotation width, a roll angle constraint is calculated.

For example, the roll angle constraint calculation formula may be:

（1）

Wherein, The rotation angle of the target pedestrian, namely, the roll angle, a represents the major half axis of the elliptical model of the target pedestrian, b represents the minor half axis of the elliptical model of the target pedestrian, 2a represents the shoulder width of the target pedestrian, 2b represents the chest thickness of the target pedestrian, a and b are constants, a > b, L represents the width of a narrow area, and d represents the body rotation width behind the side body of the target pedestrian;

Assume that Then:

（2）

Wherein, theta _min represents the minimum rotation angle of the target pedestrian, The psychological distance between the target pedestrian and the wall of the narrow area is represented as a constant obtained through practical experiments.

In some embodiments, the motion-related information may further include an initial position, a desired speed, and a rotational angular speed, and the roll constraint conditions further include a roll time constraint; based on the target model, the width of the narrow area and the motion related information, determining the lateral constraint condition of the crossing behavior of the target pedestrian in the narrow area can further comprise:

Calculating the rotation time of the target pedestrian based on the rotation angular velocity and the roll angle constraint;

based on the target model, the initial position, the desired speed, and the rotation time, a roll time constraint is calculated.

For example, the calculation formula of the rotation time of the target pedestrian may beWhereinRepresenting the time of rotation of the target pedestrian,，The experimentally measured constant is represented for representing the rotational angular velocity of the target pedestrian.

For example, the calculation formula of the roll time constraint may be:

，

Wherein, Indicating the moment of onset of rotation of the target pedestrian, i.e. the time of roll,Representing the initial position of the target pedestrian,Representing the edge position of a wall in a narrow area,Representing the intersection point of the X-axis of the horizontal line where the initial position of the target pedestrian is located and the projection of the edge position of the wall of the narrow area in the X-axis direction,Representing the rotation start position of the target pedestrian,Representing the position of the target pedestrian rotated to the wall of the narrow area,，，Representing the expected speed of the target pedestrian at the t-th moment,The psychological distance between the target pedestrian and the wall of the narrow area is represented by a constant obtained through practical experiments, and L represents the width of the narrow area.

In some embodiments, the roll constraint may also include a roll distance constraint; based on the target model, the width of the narrow area and the motion related information, determining the lateral constraint condition of the crossing behavior of the target pedestrian in the narrow area can further comprise:

calculating a roll distance constraint based on the target model, the initial position, the desired speed, the rotation time, the psychological distance, and the roll time constraint;

for example, the calculation formula of the roll distance constraint may be:

，

Wherein, Representing the distance between the target pedestrian and the wall of the narrow area at the rotation start time; /(I)

Assume thatThen:

。

in some embodiments, constructing a twist social force model based on roll behavior may include:

Acquiring lateral action acting forces related to the lateral action of the target pedestrian, wherein the lateral action acting forces comprise driving force of the target pedestrian, interaction force between the target pedestrian and the wall of the narrow area, collision force between the target pedestrian and the wall of the narrow area and sideward willingness of the target pedestrian;

A torsion social force model based on the sideways behavior is constructed based on the driving force of the target pedestrian, the interaction force between the target pedestrian and the wall of the narrow area, the collision force between the target pedestrian and the wall of the narrow area, and the intention of the target pedestrian to sideways.

Specifically, since the target pedestrian, i.e., the i-th pedestrian in the foregoing and the wall of the narrow area may be involved in the crossing behavior of the narrow area, and the non-target pedestrian, i.e., the j-th pedestrian in the foregoing, at this time, it is known in connection with the foregoing description that the lateral behavior force related to the lateral behavior of the target pedestrian may include: the driving force of the target pedestrian, the interaction force between the target pedestrian and the wall of the narrow area, the collision force between the target pedestrian and the wall of the narrow area, and the intention of the target pedestrian to lean.

Illustratively, the torsional social force model is represented by the following formula:

（30）

（31）

（32）

（33）

（34）

（35）

（36）

（37）

（38）

where m represents the mass of the target pedestrian, v represents the actual speed of the target pedestrian, F represents the driving force of the target pedestrian, F _w represents the interaction force between the target pedestrian and the wall of the narrow area, Representing the collision force between the target pedestrian and the walls of the narrow area, W representing the total number of walls of the narrow area,Representing the intention of the target pedestrian to lean around,Representing the torsion of the target pedestrian,Representing the initial speed of the target pedestrian,Unit vector indicating that the target pedestrian points to the desired target at time t,Representing the expected speed of the target pedestrian at the time t,A represents the strength of social acting force, B represents the range of social acting force, A and B are constants,Represents an adjustment coefficient, r represents a radius of a target pedestrian, d _w represents a centroid distance between the target pedestrian and a wall of a narrow area, n _w represents a normalized vector of the target pedestrian directed toward the wall of the narrow area, k _n represents a body compression coefficient, k _t represents a sliding friction coefficient, t _w represents a tangential direction of the target pedestrian and the wall of the narrow area,Wall representing target pedestrian and narrow area not touching each other,Representing the intensity of the collision force,Representing the range of impact forces,AndAre all constant,Representing acceleration of the target pedestrian at time t, a representing the major half axis of the elliptical model of the target pedestrian, t _r representing the rotation time of the target pedestrian, b representing the minor half axis of the elliptical model of the target pedestrian,Representing the position of the target pedestrian at the time t,The initial position of the target pedestrian at the initial time is indicated.

Based on this, the exemplary embodiments of the present disclosure conducted simulation experiments and emulation experiments to verify the authenticity and popularity of the torsional social force model.

1. Simulation experiment: verifying authenticity

1. Setup and data collection of practical experiments

From the foregoing, it follows that the lateral behavior of a pedestrian is related to the angle of rotation or roll, the roll distance, and the roll time. In order to verify the accuracy of the model and calibrate the model parameters, the exemplary embodiments of the present disclosure perform a number of practical experiments.

In the exemplary embodiment of the present disclosure, a corresponding experimental scene is built by using a carton with a maximum roll angle of 0.8m by 0.5m by 0.6m, and schematic diagrams of experimental devices are drawn respectively, and fig. 5 is a schematic diagram of an experimental device for traversing behaviors of a narrow area provided in the exemplary embodiment of the present disclosure. Note that each square in the figure represents three stacked cartons (0.8 m x 0.5 x 1.8 m), which ensures that the shoulders of the pedestrian must be restrained by the walls. This was ignored by previous studies. The shoulder is the widest part of the pedestrian body model and the lateral behavior of the pedestrian may exceed the set boundaries if the shoulder is not constrained. Thus, the exemplary embodiments of the present disclosure improve the authenticity from a setup perspective as compared to previous studies.

The experiment recruited a total of 12 male volunteers and 5 female volunteers, numbered 1 to 17, respectively. In addition, the exemplary embodiments of the present disclosure also prepared some color caps and shoulder stickers for each member, and specific information of the volunteers is shown in table 1, and table 1 shows specific information of the volunteers provided by the exemplary embodiments of the present disclosure. In addition, the exemplary embodiments of the present disclosure use the Canon maximum roll angle G7X Mark III maximum roll angle camera to shoot perpendicular to the ground, and the video range may cover the experimental area; and a maximum roll angle GoPro HERO11 Black Mini is set in front of the channel in each case for extracting the distance between the pedestrian and the wall of the narrow area or other pedestrians. Exemplary embodiments of the present disclosure use a video processing platform Ulead Video Studio (UVS) and trace analysis software PeTrack (PT) to process video data.

TABLE 1 specific information of volunteers

In addition, the walking speed and the angular speed in table 1 are three digits after the decimal point and two digits after the decimal point, respectively. In the calculations, the exemplary embodiments of the present disclosure use raw data without fractional reserves.

Detailed setup of experiments for crossing behavior in stenotic regions: the channel width of the narrow area is respectively set to be L=0.3m, 0.4m, 0.5m and 0.6m, and a vertical camera is arranged above the narrow channel to record the walking process of pedestrians. After that, 17 pedestrians are required to reach the destination through the narrow passage without changing the traveling direction and speed. Thus, the pedestrian parameters can be calibrated by 68 sets of video data.

2. Data processing and analysis of practical experiments

In experiments, the roll angle or the rotation angleDistance between the pedestrians before the sideways and the wall or other pedestrians in the narrow area, i.e. sideways distanceAnd roll timeIs obtained from PT at a frequency of 25Hz (25 frames=1 second).

(1) Roll angle

The experimental result shows that the maximum roll angle of the pedestrian is the maximum roll angleAnd is inversely related to the width L of the channel. With increasing L,Tapering, consistent with the assumptions of the exemplary embodiments of the present disclosure.

Meanwhile, pedestrians have two rotation directions, and most pedestrians rotate leftwards) A small number of right-hand rotations). This result shows that pedestrians have different direction selections while traveling sideways. Further analysis showed that pedestrian No. 12 always rotated to the right, while pedestrian No. 2 rotated to the left and right. It follows that the course of the sidewalk is closely related to the decision of the pedestrian itself. In experiments of crossing behavior of a narrow area, the direction of rotation does not affect the final result, so further analysis is not performed here by the exemplary embodiments of the present disclosure.

In addition, if the shoulder width and chest thickness of a pedestrian are significantly greater than those of other pedestrians, the walking pattern of the pedestrian becomes transverse as the pedestrians walk sideways through the tunnel, thereby being forced to change the walking speed. It is to be noted that the present disclosure example embodiments do not list the pedestrian as an abnormal value because it is not excluded that there is a relatively strong person in actual situations, although the speed of the pedestrian in the rotational position is set to remain unchanged. Thus, the presence of this pedestrian will better verify the universality of the model proposed by the exemplary embodiments of the present disclosure.

(2) Roll distance and roll time

From the above description, it will be readily appreciated that in the assumption of an exemplary embodiment of the present disclosureAndThe negative correlation is presented and the correlation is performed,Decreasing with increasing L, andIncreasing with increasing L. However, due to the heterogeneity of pedestrians, the exemplary embodiments of the present disclosure cannot determine whether such a negative correlation exists in an actual experiment. Thus, the present disclosure example embodiments extract/>, in each set of experimentsAndAnd a comparative analysis was performed thereon.

The results show that when a pedestrian interacts with only a wall in a narrow area, the moment of rotation is indeed related to L, and that these two parametersAndThere is a negative correlation with the rotation timing. At the same time, when L increases to a point where most people do not need to lean through a narrow passage,AndThe variation amplitude of (c) becomes smaller and gradually becomes stable.

(3) Reset time

In processing data, exemplary embodiments of the present disclosure find that the results of practical experiments confirmI.e. the walker needs a certain time to revert to the original walking posture. Thus, the present disclosure exemplary embodiments also extract/>, at different L, for each pedestrianTo quantitatively analyze this problem.

The results show that the rotation angle decreases with increasing channel width, thus resetting the timeAnd will decrease accordingly. However, its average value is within 6-14 frames, i.e., 0.24-0.56 seconds, and in the assumptions of the exemplary embodiments of the present disclosure, lateral behavior will only change walking posture, not walking speed. Therefore, in the torsion social force model, if the setting of the reset time satisfies the maximum condition, all conditions can be satisfied without affecting the simulation result.

Furthermore, the exemplary embodiments of the present disclosure also find that men reset more time than women. Since the body size of a male is generally larger than that of a female, the rotation angle of the male is larger, resulting in longer reset time. However, the rest time of the two is only different by less than 2 frames, namely only 0.08 seconds, which is almost negligible. Accordingly, the present disclosure exemplary embodiments ignore the influence of gender on the reset time.

To sum up, at present, reset time is added in the torsion social force modelIs reasonable, the exemplary embodiments of the present disclosure combine experimental results with characteristic times of conventional SFM, set=0.5s。

(4) Psychological distance

The video recorded by the camera is placed in front of the channel, and the exemplary embodiments of the present disclosure process the video using PT software. By checking the pedestrian height and scene data, the distance between each pedestrian and the wall of the narrow area can be obtained. If the pedestrians do not lean, the minimum distance between the pedestrians and the wall of the narrow area during walking is extracted, so that the psychological distance of each pedestrian under different L settings is obtained。

When the width of the aisle meets the requirement that pedestrians pass directly, i.e., without having to lean on their side, most pedestrians choose to pass from the side closer to the cartons instead of passing from the middle of the two cartons as contemplated by the exemplary embodiments of the present disclosure, which results in a situation where the average psychological distances at different L are not greatly different. The reason for this result may be that the experiment starts with l=0.3m, gradually increasing the length of L, giving pedestrians a certain habituation. However, this does not affect the end result, since the psychological distance that a pedestrian gets with a sideways situation is accurate.

Meanwhile, the exemplary embodiments of the present disclosure count psychological distance results of pedestrians of different sexes, and find that the psychological distance of males is generally smaller than that of females, which accords with normal cognition.

Therefore, if parameters that follow the distribution of the form maximum roll angle [2,3] (cm) are roughly set according to the average psychological distance in the torsion social force model, a non-negligible error may occur in the simulation result. Accordingly, the exemplary embodiments of the present disclosure fully take into account the heterogeneity of pedestrians, and set the male psychological distance to follow the pattern maximum roll angle [1.9-2.1] (cm) distribution, and the female psychological distance to follow the pattern maximum roll angle [3.0-3.2] (cm) distribution.

3. Setting up a simulation environment

The present disclosure example embodiments will change the body model of the pedestrian and add lateral behavior models. While many conventional torsional social force models based on SFM may meet the requirements of the exemplary embodiments of the present disclosure, after comparing the operability of the underlying logic modifications, the exemplary embodiments of the present disclosure select Anylogic Professional 8.7.0 with JAVA2.0 as the basic torsional social force model to modify, and the simulation will run in Intel (R) Core (TM) i5-10210U 1.60GHZ PC and 4GB memory.

First, the exemplary embodiments of the present disclosure require a change in the body model. Through the agent module of Anylogic, the exemplary embodiment of the present disclosure changes the two-dimensional model of the pedestrian from the original circular shape to an elliptical shape, and establishes 17 elliptical models according to the pedestrian body parameters (including the pedestrian's mass, shoulder width, chest circumference and sex) recorded in table 1, with pedestrian numbers 1 to 17.

Then, exemplary embodiments of the present disclosure use STATE DIAGRAM modules to add roll states and rotation conditions for each elliptical model. From the body model, exemplary embodiments of the present disclosure set a roll angle constraint and relate that angle to the body posture. Meanwhile, exemplary embodiments of the present disclosure construct a roll distance constraint and a roll time constraint by adding transition conditions, and when the above roll constraint conditions satisfy the conditions, the elliptical model will undergo a posture change. When the lateral behavior is completed, the posture of the pedestrian is still changed under the influence of the transition condition, namely, when the distance between the pedestrian and the wall of the narrow area or other pedestrians is larger than the maximum psychological distance, the reset rotation condition is triggered. After the reset time is over, the posture of the behavior body is restored to the original walking state, so that the lateral behavior is completed.

Further, the exemplary embodiments of the present disclosure use a social force setting module of software that changes the conventional SFM according to the proposed improved SFM, which changes the repulsive force magnitude when the pedestrian is in a sideways posture, increasing the sideways willingness and torsion. In addition, in order to ensure the accuracy of the simulation result, the exemplary embodiments of the present disclosure also set psychological distance ranges under different conditions according to the experimental result.

Finally, the exemplary embodiments of the present disclosure construct a simulation environment and pedestrian walking logic. And according to the actual experimental result, simulation parameters such as walking speed, angular speed, reset time and the like of the pedestrians are set, and the establishment of the social force model for twisting the lateral behaviors of the pedestrians under three conditions is completed.

4. Qualitative results of simulation experiments

The model of the exemplary embodiment of the present disclosure can effectively simulate the sideways behavior of pedestrians. The pedestrians can change the body posture through rotation, so that more reasonable travel behaviors are completed. Thus, the exemplary embodiments of the present disclosure consider the model proposed by the exemplary embodiments of the present disclosure to be effective from a qualitative point of view.

5. Quantitative results of simulation experiments

To further verify the effectiveness of the torsional social force model, exemplary embodiments of the present disclosure select these indicators of roll angle, roll distance, and roll time for quantitative evaluation. The present disclosure example embodiments extract absolute values of the roll angle, the roll distance, and the roll time of pedestrians at different channel widths, respectively. Since pedestrians in the torsion social force model do not generate body shake similar to that when a real pedestrian walks, it is meaningless to compare the rotation angles at each frame. Thus, the exemplary embodiments of the present disclosure verify the effectiveness of the torsional social force model proposed by the exemplary embodiments of the present disclosure using only the comparison result of the roll angle.

(1) Roll angle

First, the exemplary embodiments of the present disclosure compare the actual experimental and simulated maximum roll angles, all of which are larger than the simulated maximum roll angle, and many numerical errors are larger. However, the simulation result is obtained under ideal conditions under all conditions, and therefore, an error between the simulation value and the true value cannot be used as an evaluation criterion of the simulation result. Thus, the exemplary embodiments of the present disclosure give an acceptable range, i.e., an upper limit of 90 degrees (acceptable maximum roll angle) and a lower limit of the simulated maximum roll angle. If the maximum roll angle of the practical experiment is within the acceptable range, the simulation result is reasonable, and the simulation requirement of the lateral behavior can be met.

In particular, since pedestrians in practical experiments are affected by individual heterogeneity, their selection and behavior is not only regularly reproducible but also unpredictable. The torsional social force model proposed by the exemplary embodiments of the present disclosure does not contain all heterogeneity of pedestrians, that is, the model is only to simulate the lateral behavior of pedestrians, and cannot accurately predict the tilting angle, the roll distance, and the roll time of pedestrians. Thus, the roll angle obtained by the model can be regarded as the minimum rotation angle at which the pedestrian is rolled over to complete the traversing behavior. That is, the exemplary embodiments of the present disclosure consider that in practical experiments, if the roll angle is smaller than the analog value of the exemplary embodiments of the present disclosure, the traversing behavior cannot be completed. In other words, the exemplary embodiments of the present disclosure consider the simulation model to be effective as long as the angle at which the pedestrian completes the roll-over behavior in the real experiment is greater than the angle simulated by the exemplary embodiments of the present disclosure.

The exemplary embodiments of the present disclosure note that the smaller the gap between the true value and the simulated value, the higher the accuracy of the torsional social force model is explained, but according to the influence of the pedestrian heterogeneity, the exemplary embodiments of the present disclosure consider the primary task of the model to satisfy all cases, i.e., the true value of all cases is between the simulated value and 90 °. On the basis of meeting the model universality, the precision is further improved.

(2) Roll distance and roll time

The exemplary embodiment of the disclosure quantitatively analyzes the error of the lateral body distance D _T, and excludes the situation that the torsional social force model judges that the lateral movement is not needed and the lateral movement occurs in the actual experiment, wherein the average error of D _T is 11.51cm, the ratio of the error of D _T to the error of less than 10cm is 75%, and the ratio of less than 5cm is 66.7%. The error is caused by the individual difference, and within an acceptable range, the simulation result is not approximately considered to be affected, which can prove that the torsion social force model proposed by the exemplary embodiment of the present disclosure is reliable.

In addition, the exemplary embodiments of the present disclosure quantitatively analyze the error of T _b, and find that the error of T _b is only 25 frames (1 second), and the average error is 9 frames (0.36 seconds). This error is within acceptable limits, and exemplary embodiments of the present disclosure believe that the simulation results are truly reliable. The increasing trend of T _b further demonstrates the reliability of the model.

2. Simulation experiment: verifying prevalence

The reliability and effectiveness of the model proposed by the exemplary embodiments of the present disclosure are demonstrated by comparison of actual experimental and simulation results, but all comparisons are now special cases (all parameters are input according to data of 17 volunteers). To further demonstrate the universality of the model proposed by the exemplary embodiments of the present disclosure, the exemplary embodiments of the present disclosure change model parameters to general input parameters and run a torsional social force model. The result is used for verifying whether the torsional social force model can truly and effectively simulate the lateral behaviors of pedestrians.

1. Parameter calibration

Based on the results of the above-described actual experiments, exemplary embodiments of the present disclosure may obtain the parameter settings in table 2 and perform calibration, respectively. Table 2 shows the parameter settings of the torsional social force model provided by exemplary embodiments of the present disclosure.

TABLE 2 parameter settings for torsion social force model

2. Setup and simulation

To verify the effectiveness of the torsional social force model, exemplary embodiments of the present disclosure purposely select the channel widths for the three cases as l=0.3 m, 0.8m, 1.4m, and 1.0m, respectively, when establishing the simulation environment.

Meanwhile, the exemplary embodiments of the present disclosure construct the same four simulation environments, the original model does not change the underlying properties of the body model, but the body model is changed to an ellipse, i.e., the body parameters are set according to table 2, and all pedestrians in the original model do not have rotation behavior.

The specific settings of the original model and the torsion social force model are as follows: 5 men and 5 women are randomly generated for simulation, and errors caused by parameter randomness are eliminated.

Accordingly, exemplary embodiments of the present disclosure select a typical snapshot for comparative analysis.

3. Verification

According to the independent simulation results of the torsion social force model, the exemplary embodiments of the present disclosure can see that after the parameters are changed into the distribution form, the lateral behaviors in all cases can be effectively simulated, and abnormal situations such as deadlock, irregular collision and the like do not occur. Thus, the present disclosure example embodiments may consider that the torsional social force model may effectively simulate lateral behavior in different situations.

In the original model, after the pedestrian catches up with the front pedestrian, the following, repeated collision and extrusion situations can occur, and finally, the pedestrian falls into the dead zone. In the torsion social force model, when the pedestrian reaches the overrun position, the overrun behavior is reasonably realized through the rotation behavior.

On the other hand, comparing the simulation results of the two models, it can be found that the simulation results of the original model have many problems, such as unreasonable collision, overlapping, deadlock, and the like, which are avoided by the torsion social force model proposed by the exemplary embodiment of the present disclosure. Meanwhile, the calculation time difference of the two models occurs in the model construction process. Specifically, twisting the social force model requires a longer time to complete the model construction, but when the simulation begins, the computation time for both models is substantially the same.

In a word, the comparison result shows that the torsion social force model provided by the exemplary embodiment of the disclosure has universality and can effectively simulate lateral behaviors under various conditions. Furthermore, the results also demonstrate that it is necessary and feasible to incorporate lateral behavior in a torsional social force model.

The foregoing has been mainly presented in terms of the teachings of the presently disclosed embodiments. It will be appreciated that, in order to achieve the above-described functions, the electronic device includes corresponding hardware structures and/or software modules that perform the respective functions. Those of skill in the art will readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is implemented as hardware or computer software driven hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.

The embodiment of the disclosure may divide the functional units of the electronic device according to the above method example, for example, each functional module may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The integrated modules may be implemented in hardware or in software functional modules. It should be noted that, in the embodiment of the present disclosure, the division of the modules is merely a logic function division, and other division manners may be implemented in actual practice.

In the case of dividing each functional module by corresponding each function, the exemplary embodiments of the present disclosure provide a simulation apparatus of a traversing behavior of a narrow area, which may be an electronic device or a chip applied to the electronic device. Fig. 6 is a schematic structural diagram of a simulation apparatus for traversing a narrow area according to an exemplary embodiment of the present disclosure. As shown in fig. 6, the apparatus 600 includes:

The construction module 601 is configured to construct a target model of a target pedestrian in a narrow area, and determine motion related information of the target pedestrian; wherein the width of the narrow area is smaller than the shoulder width of the target pedestrian and larger than the chest thickness of the target pedestrian;

a processing module 602, configured to determine a sideways constraint condition of a traversing behavior of the target pedestrian in the narrow area based on the target model, the width of the narrow area, and the motion-related information;

the construction module 601 is further configured to construct a torsion social force model based on the roll behavior;

And the simulation module 603 is configured to simulate the traversing behavior of the target pedestrian in the narrow area by using the torsion social force model under the constraint of the roll constraint condition, so as to obtain a target behavior track of the target pedestrian.

In some embodiments, the exercise-related information includes a body rotation width that is less than or equal to a width of the stricture, the roll constraint condition includes a roll angle constraint;

the processing module 602 is further configured to calculate the roll angle constraint based on the target model, the width of the stenosis region, and the body rotation width.

In some embodiments, the roll angle constraint is calculated as:

，/>

Assume that Then:

，

In some embodiments, the motion-related information further includes an initial position, a desired speed, and a rotational angular speed, and the roll constraint condition further includes a roll time constraint;

The processing module 602 is further configured to calculate a rotation time of the target pedestrian based on the rotation angular velocity and the roll angle constraint; calculating the roll time constraint based on the target model, the initial position, the desired speed, and the rotation time;

the calculation formula of the roll time constraint is as follows:

，

Wherein, Indicating the moment of onset of rotation of the target pedestrian, i.e. the time of roll,Representing the initial position of the target pedestrian,Representing the edge position of a wall in a narrow area,Representing the intersection point of the X-axis of the horizontal line where the initial position of the target pedestrian is located and the projection of the edge position of the wall of the narrow area in the X-axis direction,Representing the rotation start position of the target pedestrian,Representing the position of the target pedestrian rotated to the wall of the narrow area,，，Representing the expected speed of the target pedestrian at the t-th moment,Representing the psychological distance between the target pedestrian and the wall of the narrow area, L representing the width of the narrow area, is a constant obtained through practical experimentsRepresenting the time of rotation of the target pedestrian,，The experimentally measured constant is represented for representing the rotational angular velocity of the target pedestrian.

In some embodiments, the roll constraint further comprises a roll distance constraint; the processing module 602 is further configured to calculate the roll distance constraint based on the target model, the initial position, the desired speed, the rotation time, the psychological distance, and the roll time constraint;

The calculation formula of the roll distance constraint is as follows:

，

Wherein, Representing the distance between the target pedestrian and the wall of the narrow area at the rotation start time;

Assume that Then: /(I)

。

In some embodiments, the building module 601 is further configured to obtain lateral behavior forces related to lateral behaviors of the target pedestrian, the lateral behavior forces including a driving force of the target pedestrian, an interaction force between the target pedestrian and a wall of a narrow area, a collision force between the target pedestrian and a wall of a narrow area, and a willingness to lean of the target pedestrian; and constructing a torsion social force model based on the sideways behavior based on the driving force of the target pedestrian, the interaction force between the target pedestrian and the wall of the narrow area, the collision force between the target pedestrian and the wall of the narrow area and the sideways willingness of the target pedestrian.

In some embodiments, the torsional social force model is represented by the following formula:

，

The embodiment of the disclosure also provides an electronic device, including: at least one processor; a memory for storing at least one processor-executable instruction; wherein at least one processor is configured to execute instructions to implement the steps of the above-described methods disclosed in embodiments of the present disclosure.

Fig. 7 shows a schematic structural diagram of an electronic device provided in an exemplary embodiment of the present disclosure. As shown in fig. 7, the electronic device 700 includes at least one processor 701 and a memory 702 coupled to the processor 701, the processor 701 may perform the respective steps of the above-described methods disclosed in the embodiments of the present disclosure.

The processor 701 may also be referred to as a central processing unit (Central Processing Unit, CPU), which may be an integrated circuit chip with signal processing capabilities. The steps of the above-described methods disclosed in the embodiments of the present disclosure may be accomplished by instructions in the form of integrated logic circuits or software in hardware in the processor 701. The processor 701 may be a general purpose processor, a digital signal processor (DIGITAL SIGNAL Processing, DSP), an ASIC, an off-the-shelf programmable gate array (Field-programmable GATE ARRAY, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the embodiments of the present disclosure may be embodied directly in hardware, in a decoded processor, or in a combination of hardware and software modules in a decoded processor. The software modules may reside in a memory 702 such as random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The processor 701 reads the information in the memory 702 and, in combination with its hardware, performs the steps of the method described above.

In addition, various operations/processes according to the present disclosure, in the case of being implemented by software and/or firmware, may be installed from a storage medium or network to a computer system having a dedicated hardware structure, for example, a computer system 800 shown in fig. 8, which is capable of performing various functions including functions such as those described above, and the like, when various programs are installed. Fig. 8 shows a schematic structural diagram of a computer system provided in an exemplary embodiment of the present disclosure.

Computer system 800 is intended to represent various forms of digital electronic computing devices, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 8, the computer system 800 includes a computing unit 801, and the computing unit 801 can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 802 or a computer program loaded from a storage unit 808 into a Random Access Memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the computer system 800 can also be stored. The computing unit 801, the ROM 802, and the RAM 803 are connected to each other by a bus 804. An input/output (I/O) interface 805 is also connected to the bus 804.

Various components in computer system 800 are connected to I/O interface 805, including: an input unit 806, an output unit 807, a storage unit 808, and a communication unit 809. The input unit 806 may be any type of device capable of inputting information to the computer system 800, and the input unit 806 may receive input numeric or character information and generate key signal inputs related to user settings and/or function control of the electronic device. The output unit 807 may be any type of device capable of presenting information and may include, but is not limited to, a display, speakers, video/audio output terminals, vibrators, and/or printers. The storage unit 808 may include, but is not limited to, magnetic disks, optical disks. The communication unit 809 allows the computer system 800 to exchange information/data with other devices over a network, such as the internet, and may include, but is not limited to, modems, network cards, infrared communication devices, wireless communication transceivers and/or chipsets, e.g., bluetooth (TM) devices, wiFi devices, wiMax devices, cellular communication devices, and/or the like.

The computing unit 801 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 801 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 801 performs the various methods and processes described above. For example, in some embodiments, the above-described methods disclosed by embodiments of the present disclosure may be implemented as a computer software program tangibly embodied on a machine-readable medium, e.g., the storage unit 808. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device via the ROM 802 and/or the communication unit 809. In some embodiments, the computing unit 801 may be configured by any other suitable means (e.g., by means of firmware) to perform the above-described methods disclosed by embodiments of the present disclosure.

The disclosed embodiments also provide a computer-readable storage medium, wherein instructions in the computer-readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the above-described method disclosed by the disclosed embodiments.

A computer readable storage medium in embodiments of the present disclosure may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium described above can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specifically, the computer-readable storage medium described above may include one or more wire-based electrical connections, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device.

The disclosed embodiments also provide a computer program product comprising a computer program, wherein the computer program, when executed by a processor, implements the above-described methods of the disclosed embodiments.

In an embodiment of the present disclosure, computer program code for performing the operations of the present disclosure may be written in one or more programming languages, including but not limited to an object oriented programming language such as Java, smalltalk, C ++, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of remote computers, the remote computers may be connected to the user computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to external computers.

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The modules, components or units referred to in the embodiments of the present disclosure may be implemented by software or hardware. Where the name of a module, component or unit does not in some cases constitute a limitation of the module, component or unit itself.

The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.

The above description is merely illustrative of some embodiments of the present disclosure and of the principles of the technology applied. It will be appreciated by persons skilled in the art that the scope of the disclosure referred to in this disclosure is not limited to the specific combinations of features described above, but also covers other embodiments which may be formed by any combination of features described above or equivalents thereof without departing from the spirit of the disclosure. Such as those described above, are mutually substituted with the technical features having similar functions disclosed in the present disclosure (but not limited thereto).

Although some specific embodiments of the present disclosure have been described in detail by way of example, it should be understood by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present disclosure. It will be appreciated by those skilled in the art that modifications may be made to the above embodiments without departing from the scope and spirit of the disclosure. The scope of the present disclosure is defined by the appended claims.

Claims

1. A simulation method of crossing behavior of a narrow area is characterized by comprising the following steps:

Constructing a torsion social force model based on the sideways behavior;

2. The method of claim 1, wherein the movement related information comprises a body rotation width that is less than or equal to a width of the stricture, the roll constraint condition comprising a roll angle constraint; the determining a roll constraint condition of the crossing behavior of the target pedestrian in the narrow area based on the target model, the width of the narrow area and the motion related information comprises the following steps:

The roll angle constraint is calculated based on the target model, the width of the stenosis region, and the body rotation width.

3. The method of claim 2, wherein the roll angle constraint is calculated by the formula:

，

Assume that Then:

，

4. The method of claim 2, wherein the motion related information further comprises an initial position, a desired speed, and a rotational angular speed, and the roll constraint condition further comprises a roll time constraint; the determining a roll constraint condition of the crossing behavior of the target pedestrian in the narrow area based on the target model, the width of the narrow area and the motion related information further comprises:

Calculating a rotation time of the target pedestrian based on the rotation angular velocity and the roll angle constraint;

Calculating the roll time constraint based on the target model, the initial position, the desired speed, and the rotation time;

the calculation formula of the roll time constraint is as follows:

，

5. The method of claim 4, wherein the roll constraint further comprises a roll distance constraint; the determining a roll constraint condition of the crossing behavior of the target pedestrian in the narrow area based on the target model, the width of the narrow area and the motion related information further comprises:

Calculating the roll distance constraint based on the target model, the initial position, the desired speed, the rotation time, the psychological distance, and the roll time constraint;

The calculation formula of the roll distance constraint is as follows:

，

Assume that Then:

。

6. the method of claim 1, wherein the constructing a torsional social force model based on roll behavior comprises:

Acquiring lateral behavior acting forces related to the lateral behavior of the target pedestrian, wherein the lateral behavior acting forces comprise driving force of the target pedestrian, interaction force between the target pedestrian and a wall of a narrow area, collision force between the target pedestrian and the wall of the narrow area and a sideward willingness of the target pedestrian;

and constructing a torsion social force model based on the sideways behavior based on the driving force of the target pedestrian, the interaction force between the target pedestrian and the wall of the narrow area, the collision force between the target pedestrian and the wall of the narrow area and the sideways willingness of the target pedestrian.

7. The method according to any one of claims 1 to 6, wherein the torsional social force model is represented by the following formula:

，

8. A device for simulating crossing behavior in a narrow area, comprising:

9. An electronic device, comprising:

At least one processor;

a memory for storing the at least one processor-executable instruction;

Wherein the at least one processor is configured to execute the instructions to implement the steps of the method according to any one of claims 1 to 7.

10. A computer readable storage medium, characterized in that instructions in the computer readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the steps of the method according to any one of claims 1-7.