CN113420415A - Intersection bidirectional pedestrian simulation method based on perception area comfort - Google Patents
Intersection bidirectional pedestrian simulation method based on perception area comfort Download PDFInfo
- Publication number
- CN113420415A CN113420415A CN202110584535.8A CN202110584535A CN113420415A CN 113420415 A CN113420415 A CN 113420415A CN 202110584535 A CN202110584535 A CN 202110584535A CN 113420415 A CN113420415 A CN 113420415A
- Authority
- CN
- China
- Prior art keywords
- pedestrian
- target
- target pedestrian
- speed
- sub
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 230000008447 perception Effects 0.000 title claims abstract description 24
- 238000004088 simulation Methods 0.000 title claims abstract description 23
- 238000000034 method Methods 0.000 title claims abstract description 21
- 230000002457 bidirectional effect Effects 0.000 title claims abstract description 18
- 230000006870 function Effects 0.000 claims abstract description 6
- 238000004364 calculation method Methods 0.000 claims description 8
- 230000004888 barrier function Effects 0.000 claims description 3
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 230000000903 blocking effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/15—Correlation function computation including computation of convolution operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Analysis (AREA)
- Computational Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Mathematical Physics (AREA)
- General Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Health & Medical Sciences (AREA)
- Strategic Management (AREA)
- Primary Health Care (AREA)
- Computing Systems (AREA)
- Marketing (AREA)
- General Health & Medical Sciences (AREA)
- Economics (AREA)
- Algebra (AREA)
- General Business, Economics & Management (AREA)
- Educational Administration (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- Development Economics (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses an intersection bidirectional pedestrian simulation method based on perception area comfort, which comprises the following steps: reading all pedestrian microscopic data in a target pedestrian perception area; acquiring the size of a pedestrian crossing, the corresponding green light duration and the perception radius of a target pedestrian; rasterizing a sensing area, dividing the sensing area into sub-areas, and acquiring the number of pedestrians in the sub-areas; calculating the comfort degree of each subarea and the discomfort degree of each moving direction according to the space discomfort coefficient of each subarea, and determining the moving direction of the target pedestrian; and determining the moving speed of the target pedestrian and updating the position of the target pedestrian. According to the invention, on the basis of the rasterized sensing region, the mutual avoidance function among pedestrians in the range and the function of obstacles and vehicles in the environment on target pedestrians can be quickly and comprehensively considered, and the directions with fewer pedestrians are searched, so that a reasonable judgment and decision basis for the moving direction and the speed can be provided for the target pedestrians, and accurate and quick simulation is realized.
Description
Technical Field
The invention relates to the field of pedestrian simulation, in particular to an intersection bidirectional pedestrian simulation method based on the comfort level of a perception area.
Background
The walking is used as an original travel mode driven by the physical strength of the user, and the flexible pedestrian traffic can effectively and flexibly link various travel modes. The pedestrian crossing street is taken as an important part of pedestrian traffic, particularly urban traffic, ensures that the pedestrian crossing street is safe, smooth, comfortable, fast and efficient, and draws more and more attention.
Due to the rapid development of cities and the limitation of land resources, the rapid increase of population scale causes the cities to become crowded, the congestion interweaving of bidirectional pedestrians during street crossing is more obvious, and the pedestrians are more disordered during the bidirectional pedestrian interweaving. At present, few researches are carried out on pedestrian traffic, a mature and complete theoretical system is lacked, and modeling on street pedestrian flow is lacked; the existing model is not real enough when describing the phenomenon of bidirectional pedestrian flow interweaving; the calculation speed and the simulation speed of partial models still need to be improved, and the conditions of low density and high density of pedestrians cannot be covered.
Disclosure of Invention
The purpose of the invention is as follows: in view of the above problems, the present invention aims to provide an intersection bidirectional pedestrian simulation method based on the comfort level of a sensing area.
The technical scheme is as follows: the invention discloses an intersection bidirectional pedestrian simulation method based on perception area comfort, which comprises the following steps:
(1) reading all pedestrian microscopic data in a target pedestrian sensing area according to a pedestrian information database, wherein the sensing area is an area which can be observed and sensed by a pedestrian, the comfort level of the target pedestrian can be influenced by the pedestrian and objects existing in the area, when most of the sensing area is invaded, the target pedestrian can feel oppressed and uncomfortable and is eagerly to find a more comfortable sensing area, and the microscopic data comprises the maximum walking speed, running speed, current moving speed and position of the pedestrian at the current moment;
(2) acquiring the size of a pedestrian crossing, the corresponding green light time and the perception radius of a target pedestrian, wherein the perception radius is a circle radius taking the target pedestrian as the center of a circle;
(3) rasterizing a sensing area, dividing the sensing area into sub-areas, and acquiring the number of pedestrians in the sub-areas;
(4) calculating the comfort degree of each subarea and the discomfort degree of each moving direction according to the space discomfort coefficient of each subarea, and determining the moving direction of the target pedestrian;
(5) and calculating the pressure of the target pedestrian from the signal lamp, determining the moving speed of the target pedestrian, updating the position of the target pedestrian, and completing the simulation of the pedestrian passing through the pedestrian crossing.
Further, the sensing area in the step 1 is a semicircle taking the position of the target pedestrian as the center of a circle, and the symmetry axis of the semicircle is vertical to the center line of the road; the current moving speed is a vector and indicates the direction and the speed of the pedestrian.
Further, step 3 rasterizing the sensing region includes: the method comprises the steps of firstly, equally dividing a semicircular sensing area of a target pedestrian into p sub-sector areas with the serial number of i, i being 1,2i,j。
Further, step 4 constructs discomfort F of each sub-area in the sensing areai,jThe model has the expression as follows:
Fi,j＝fi,jni,j
fi,jthe discomfort coefficient of the sector numbered i and the annular overlapped area numbered j;
building discomfort degree F of target pedestrian in all directionsiThe model has the expression as follows:
σa,iattraction force f for destinationaThe factor of action of, σl,iLeft boundary without safety factor fb,lThe factor of action of, σr,iNo safety factor f for right boundaryb,rR is the radius of perception, llIs the distance, l, of the target pedestrian from the left boundary of the crosswalkrThe distance between the target pedestrian and the right boundary of the pedestrian crosswalk;
and selecting the direction corresponding to the maximum comfort degree and the minimum discomfort degree as the moving direction of the target pedestrian, wherein the moving direction of the sub-sector of the target pedestrian is the center line of the current sub-sector.
Further, the uncomfortable degree F corresponding to the moving directioniDetermining the moving speed of the target pedestrian, and constructing a speed calculation model as follows:
to avoid discomfort FiWhen the value is zero, the upper formula is meaningless, and the order is F ═ Fi+1, the update rate model is:
target pedestrian receives pressure from signal light at the end of signal light, needs to accelerate or run through crosswalk, with FgRepresenting the ratio of the time expected to pass and the time remaining, FgObtained by calculation according to the following model:
in the formula TgThe total duration of the green light is t, and the current display time of the green light is t;
when F is presentg>1 represents that the target pedestrian cannot pass through before the end of the green light according to the current speed, and the moving speed of the target pedestrian is calculated according to the following formula:
σgis a function factor of the signal lamp pressure, vrIs the running speed of the pedestrian;
the updated position coordinate (x ', y') model has the expression:
beta is an included angle between the moving direction and the center line of the road, (x, y) is the current position coordinate of the target pedestrian, the x axis is parallel to the center line of the road, the y axis is parallel to the center line of the pedestrian crossing, delta t is the updating step length, the step 1 is returned to for circulation after the updating, and the circulation is finished until the target pedestrian reaches the other side from one side of the road.
Further, if the sensing area in step 1 includes an obstacle, equivalently converting the obstacle into the number of people in a row according to the floor area of the obstacle, wherein the conversion expression is as follows:
wherein n isdjIs the equivalent pedestrian number, SwIs the floor area of the obstacle, S0The equivalent pedestrian speed is zero, and the position coordinate is the position coordinate of the barrier.
Has the advantages that: compared with the prior art, the invention has the following remarkable advantages:
1. on the basis of the rasterized sensing area, the mutual avoidance function among pedestrians in the range and the effect of obstacles and vehicles in the environment on target pedestrians can be quickly and comprehensively considered, the directions with fewer pedestrians are searched, and then reasonable judgment and decision basis of the moving direction and the speed can be provided for the target pedestrians, so that accurate and quick simulation is realized;
2. determining a sensing area according to the areas sensed and considered by the pedestrians crossing the street, rasterizing the sub-areas, and determining the pedestrians and the objects in each sub-area to avoid huge calculation caused by searching the positions of other pedestrians, calculating the distance between the target pedestrian and other pedestrians and mutual avoidance acting force in the space, so that the positions, the distances and the quantity of the pedestrians and the objects nearby the target pedestrian can be quickly determined;
3. the influence of the last stage of the green light on the target pedestrian is considered, and the depicting capability of the simulation method on the scene is improved;
4. the method is suitable for the conditions of low-density, medium-density and high-density pedestrians, can truly depict the interleaving phenomenon of the bidirectional pedestrian flow, and avoids the blocking phenomenon caused by the fact that two pedestrians cannot avoid opposite pedestrians when the bidirectional pedestrians are crossed under the high-density simulation condition.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a schematic diagram of a pedestrian situation in a perception area of a pedestrian crossing according to an embodiment.
Detailed Description
The flow chart of the intersection bidirectional pedestrian simulation method based on the comfort level of the perception area is shown in fig. 1, the method of the embodiment is used for simulating the situation that a certain target pedestrian passes through a pedestrian crossing with the width of 5m and the length of 30m, the perception radius is 1.5m, the information of the target pedestrian is shown in the following table 1, and (x and y) are current-time position coordinates of the target pedestrian, wherein the x axis of an established coordinate axis is parallel to the central line of a road, the y axis is parallel to the central line of the pedestrian crossing, the direction is shown in fig. 2, the number of the target pedestrian is 0, the numbers 1-5 are other pedestrians in the target pedestrian perception area at the current time, the places A and the places B are two end points of the pedestrian crossing, a road is arranged between the places C and the places D, and the central line of the pedestrian crossing is perpendicular to the central line of the road.
TABLE 1
Green light time Tg25s, 15s at the current time t, 0.1s at the simulation step length delta t, and the maximum speed v of the target pedestrianmax2.5m/s, running speed vr5.0m/s, destination attractionForce faLeft and right boundary safety factor f 2l＝fr＝6。
The method comprises the following steps:
(1) reading all pedestrian microscopic data in a target pedestrian sensing area according to a pedestrian information database, wherein the microscopic data comprises the maximum walking speed, running speed, current moving speed and position of a pedestrian at the current moment;
the sensing area is a semicircle with the target pedestrian position as the center of a circle as shown in fig. 2, the current moving speed is a vector, and the direction and the speed of the pedestrian are noted.
If the sensing area comprises the obstacles, equivalently converting the obstacles into the number of people in a row according to the floor area of the obstacles, wherein the conversion expression is as follows:
wherein n isdjIs the equivalent pedestrian number, SwIs the floor area of the obstacle, S0The equivalent pedestrian speed is zero, and the position coordinate is the position coordinate of the barrier.
(2) Acquiring the size of a pedestrian crossing, the corresponding green light time and the perception radius of a target pedestrian, wherein the perception radius is a circle radius taking the target pedestrian as the center of a circle;
(3) rasterizing a sensing area, dividing the sensing area into sub-areas, and acquiring the number of pedestrians in the sub-areas;
the rasterized perception region includes: the method comprises the steps of firstly, equally dividing a semicircular sensing area of a target pedestrian into p sub-sector areas, wherein the number of the sub-sector areas is i, i is 1,2,i,jp and q are respectively 3, and the number of pedestrians in each sub-area in fig. 2 is shown in table 2.
TABLE 2
(4) Calculating the comfort degree of each subarea and the discomfort degree of each moving direction according to the space discomfort coefficient of each subarea, and determining the moving direction of the target pedestrian;
building discomfort F for sub-regions within a perception regioni,jThe model has the expression as follows:
Fi,j＝fi,jni,j
fi,jthe space discomfort coefficient is slightly smaller than other sectors because the target pedestrian is eager for advancing and has slightly lower requirement on the middle sub-sector area.
When i is 1 or i is 3, fi,1＝1，fi,2＝3，fi,3＝8；
When i is 2, fi,1＝0.8，fi,2＝2.7，fi,3＝6.4；
Building discomfort degree F of target pedestrian in all directionsiThe model has the expression as follows:
σa,iattraction force f for destinationaThe action factor of (3) is 1 when it acts and 0 when it does not act, i.e., σ is 2a,i1, otherwise σa,i＝0；
σl,iLeft boundary without safety factor fb,lThe action factor of (a) is 1 when acting and 0 when not acting, i is 1 and ll<When R is sigmal,i1, otherwise σl,i＝0；
σr,iNo safety factor f for right boundaryb,rThe action factor of (a) is 1 when acting and 0 when not acting, i is 3 and lr<When R is sigmar,i1, otherwise σr,i＝0；
R is the radius of perception,/lIs the distance between the target pedestrian and the left boundary of the pedestrian crossing，lrThe distance between the target pedestrian and the right boundary of the pedestrian crosswalk;
when i is 3, then σa,i＝0；ll>R, then σl,i0; i is 3 and lr<R, then σr,i＝1；fa＝2，fb,l＝6，fb,r＝6，R＝1.5；
The same procedure can calculate F1＝7，F2＝4.4：
And selecting the direction corresponding to the maximum comfort degree and the minimum discomfort degree as the moving direction of the target pedestrian, wherein the moving direction of the sub-sector of the target pedestrian is the center line of the current sub-sector. Due to F3At a minimum, the direction of movement of the target pedestrian is direction 3, and the angle β with the positive direction of the x-axis is 30 °.
(5) And calculating the pressure of the target pedestrian from the signal lamp, determining the moving speed of the target pedestrian, updating the position of the target pedestrian, and completing the simulation of the pedestrian passing through the pedestrian crossing.
Discomfort degree F corresponding to moving directioniDetermining the moving speed of the target pedestrian, and constructing a speed calculation model as follows:
to avoid discomfort FiWhen the value is zero, the upper formula is meaningless, and the order is F ═ Fi+1, the update rate model is:
wherein F3＝5.2，vmax＝2.5m/s
F′＝F3+1＝5.2+1＝6.2
Target pedestrian receives pressure from signal light at the end of signal light, needs to accelerate or run through crosswalk, with FgRepresenting the ratio of the time expected to pass and the time remaining, FgObtained by calculation according to the following model:
in the formula TgThe total duration of the green light is t, and the current display time of the green light is t; wherein T isg＝25s，t＝15s，lf15 m; when F is presentg>1 represents that the target pedestrian cannot pass through before the end of the green light according to the current speed, and the moving speed of the target pedestrian is calculated according to the following formula:
σgis a function factor of signal lamp pressure, when Fg>1, i.e. the pedestrian cannot pass at the current speed before the end of the green light, σg1, otherwise σg＝0；vrRunning speed for the target pedestrian;
the updated position coordinate (x ', y') model has the expression:
beta is an included angle between the moving direction and the center line of the road, beta is 30 degrees, (x, y) is (2.1,1.2), and delta t is 0.1s, which is an updating step length;
(x′,y′)＝(3.7,15)+(2.1,1.2)×0.1＝(3.91,15.12)
the coordinates of other pedestrians at the next moment can be obtained according to the same steps.
Claims (6)
1. An intersection bidirectional pedestrian simulation method based on perception area comfort is characterized by comprising the following steps:
(1) reading all pedestrian microscopic data in a target pedestrian sensing area according to a pedestrian information database; the microscopic data comprise the maximum walking speed, running speed, current moving speed and position of the pedestrian at the current moment;
(2) acquiring the size of a pedestrian crossing, the corresponding green light time and the perception radius of a target pedestrian, wherein the perception radius is a circle radius taking the target pedestrian as the center of a circle;
(3) rasterizing a sensing area, dividing the sensing area into sub-areas, and acquiring the number of pedestrians in the sub-areas;
(4) calculating the comfort degree of each subarea and the discomfort degree of each moving direction according to the space discomfort coefficient of each subarea, and determining the moving direction of the target pedestrian;
(5) and determining the moving speed of the target pedestrian according to the remaining green light passing time, updating the position of the target pedestrian, and completing the simulation of the target pedestrian passing through the pedestrian crossing.
2. The intersection bidirectional pedestrian simulation method according to claim 1, wherein the sensing area in step 1 is a semicircle with the target pedestrian position as a center, and a symmetry axis of the semicircle is perpendicular to a road center line; the current moving speed is a vector and indicates the direction and the speed of the pedestrian.
3. The intersection bidirectional pedestrian simulation method according to claim 2, wherein the rasterizing sensing area of step 3 comprises: the method comprises the steps of firstly, equally dividing a semicircular sensing area of a target pedestrian into p sub-sector areas with the serial number of i, i being 1,2i,j。
4. The intersection bidirectional pedestrian simulation method according to claim 3, wherein the step 4 constructs discomfort degrees F of sub-areas in the perception areai,jThe model has the expression as follows:
Fi,j＝fi,jni,j
fi,jthe discomfort coefficient of the sector numbered i and the annular overlapped area numbered j;
constructing a fan-shaped uncomfortable degree F of a target pedestrian with the number iiThe model has the expression as follows:
σa,iattraction force f for destinationaThe factor of action of, σl,iLeft boundary without safety factor fb,lThe factor of action of, σr,iNo safety factor f for right boundaryb,rR is the radius of perception, llIs the distance, l, of the target pedestrian from the left boundary of the crosswalkrThe distance between the target pedestrian and the right boundary of the pedestrian crosswalk;
and selecting the direction corresponding to the minimum discomfort degree as the moving direction of the target pedestrian, wherein the moving direction of the sub-sector where the target pedestrian is located is the central line of the current sub-sector.
5. The intersection bidirectional pedestrian simulation method according to claim 4, characterized in that step 5 comprises:
discomfort degree F corresponding to moving directioniDetermining the moving speed of the target pedestrian, and constructing a speed calculation model as follows:
to avoid discomfort FiWhen the value is zero, the upper formula is meaningless, and the order is F ═ Fi+1, the update rate model is:
during the remaining time of the green light, it is necessary to accelerate or run through the crosswalk, with FgRepresenting the ratio of the time expected to pass and the time remaining, FgObtained by calculation according to the following model:
in the formula TgThe total duration of the green light is t, and the current display time of the green light is t;
when F is presentg>1 represents that the target pedestrian cannot pass through before the end of the green light according to the current speed, and the moving speed of the target pedestrian is calculated according to the following formula:
σgis a function factor of the signal lamp pressure, vrIs the running speed of the pedestrian;
the updated position coordinate (x ', y') model has the expression:
beta is an included angle between the moving direction and a road center line, (x, y) are coordinates of the current position of the target pedestrian, the x axis is parallel to the road center line, the y axis is parallel to the center line of the pedestrian crossing, delta t is an updating step length, the step (1) is returned to carry out circulation after updating until the target pedestrian reaches the other side from one side of the road, and the circulation is finished.
6. The intersection bidirectional pedestrian simulation method according to claim 1, wherein if the sensing area includes the obstacle in step 1, the obstacle is equivalently converted into the number of people in a row according to the floor area of the obstacle, and the conversion expression is as follows:
wherein n isdjIs the equivalent pedestrian number, SwIs the floor area of the obstacle, S0The equivalent pedestrian speed is zero, and the position coordinate is the position coordinate of the barrier.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110584535.8A CN113420415B (en) | 2021-05-27 | 2021-05-27 | Intersection bidirectional pedestrian simulation method based on comfort level of sensing area |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110584535.8A CN113420415B (en) | 2021-05-27 | 2021-05-27 | Intersection bidirectional pedestrian simulation method based on comfort level of sensing area |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113420415A true CN113420415A (en) | 2021-09-21 |
| CN113420415B CN113420415B (en) | 2024-06-14 |
Family
ID=77713121
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110584535.8A Active CN113420415B (en) | 2021-05-27 | 2021-05-27 | Intersection bidirectional pedestrian simulation method based on comfort level of sensing area |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113420415B (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008129874A (en) * | 2006-11-21 | 2008-06-05 | Hitachi Ltd | Traffic flow simulation device, traffic flow simulation method, and traffic flow simulation program |
| CN105678034A (en) * | 2016-03-14 | 2016-06-15 | 东南大学 | Pedestrian crossing time model and signalized intersection pedestrian crosswalk width optimizing method |
| WO2016133422A1 (en) * | 2015-02-20 | 2016-08-25 | Общество С Ограниченной Ответственностью "Логос - Агентные Технологии" | Method for creating a simulation model of the movement of transport and pedestrian traffic |
| CN106846828A (en) * | 2016-11-30 | 2017-06-13 | 东南大学 | A kind of opposite pedestrian stream crossing facilities canalization method of lower high density of signal control |
| CN108320513A (en) * | 2018-03-30 | 2018-07-24 | 南京理工大学 | Pedestrian's street crossing behavior analysis method when a kind of green light flash signal |
| CN111291469A (en) * | 2020-01-17 | 2020-06-16 | 东南大学 | Pedestrian crossing mixed traffic flow simulation method and system based on multiple intelligent agents |
| CN112395769A (en) * | 2020-11-25 | 2021-02-23 | 盐城工学院 | Pedestrian movement simulation method oriented to ordered activities |
-
2021
- 2021-05-27 CN CN202110584535.8A patent/CN113420415B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008129874A (en) * | 2006-11-21 | 2008-06-05 | Hitachi Ltd | Traffic flow simulation device, traffic flow simulation method, and traffic flow simulation program |
| WO2016133422A1 (en) * | 2015-02-20 | 2016-08-25 | Общество С Ограниченной Ответственностью "Логос - Агентные Технологии" | Method for creating a simulation model of the movement of transport and pedestrian traffic |
| CN105678034A (en) * | 2016-03-14 | 2016-06-15 | 东南大学 | Pedestrian crossing time model and signalized intersection pedestrian crosswalk width optimizing method |
| CN106846828A (en) * | 2016-11-30 | 2017-06-13 | 东南大学 | A kind of opposite pedestrian stream crossing facilities canalization method of lower high density of signal control |
| CN108320513A (en) * | 2018-03-30 | 2018-07-24 | 南京理工大学 | Pedestrian's street crossing behavior analysis method when a kind of green light flash signal |
| CN111291469A (en) * | 2020-01-17 | 2020-06-16 | 东南大学 | Pedestrian crossing mixed traffic flow simulation method and system based on multiple intelligent agents |
| CN112395769A (en) * | 2020-11-25 | 2021-02-23 | 盐城工学院 | Pedestrian movement simulation method oriented to ordered activities |
Non-Patent Citations (3)
| Title |
|---|
| 何大治;李晓克;李明明;: "考虑视域影响的疏散行为建模及双向行人流仿真", 浙江大学学报(工学版), no. 06 * |
| 吴娇蓉;刘学丽;: "行人交织区运行状态分级方法与调控流程", 同济大学学报(自然科学版), no. 04 * |
| 沙云飞;史其信;: "基于离散势能场的行人仿真模型研究", 公路工程, no. 02 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113420415B (en) | 2024-06-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11554785B2 (en) | Driving scenario machine learning network and driving environment simulation | |
| US11216004B2 (en) | Map automation—lane classification | |
| JP3902543B2 (en) | Road traffic simulation device | |
| CN104899357B (en) | A kind of topological data extracting method based on AutoCAD level-crossing engineering drawings | |
| JP3370555B2 (en) | Pedestrian information provision system | |
| US7155376B2 (en) | Traffic data management and simulation system | |
| CN108088456A (en) | A kind of automatic driving vehicle local paths planning method with time consistency | |
| CN109947090A (en) | Non- chocking limit for automatic driving vehicle planning | |
| CN107609633A (en) | The position prediction model construction method of vehicle traveling influence factor based on deep learning in car networking complex network | |
| US8894413B2 (en) | Architecture, method, and program for generating realistic vehicular mobility patterns | |
| Qu et al. | Modeling detour behavior of pedestrian dynamics under different conditions | |
| CN112800157B (en) | Dynamic occupying grid model construction method and application architecture design method thereof | |
| JP2013508692A (en) | Additional map generation, refinement and expansion using GPS trajectories | |
| Sarmady et al. | Modeling groups of pedestrians in least effort crowd movements using cellular automata | |
| Wang et al. | Automatic high-fidelity 3D road network modeling based on 2D GIS data | |
| CN106920278B (en) | Flyover three-dimensional modeling method based on Reeb graph | |
| CN106127855B (en) | A kind of magnanimity road network refines the rendering method of threedimensional model in real time | |
| CN114509065B (en) | Map construction method, system, vehicle terminal, server and storage medium | |
| CN109374005B (en) | Ship internal path planning method based on ship VR model | |
| KR20220083975A (en) | Trajectory planning methods, devices, instruments, storage media and program products | |
| CN106530779A (en) | Path planning method and system based on urban traffic control signal lights | |
| CN105183769A (en) | In-situ visualization method for trajectory data based on stream data cube | |
| CN104406590A (en) | Road grade-based shortest route-planning algorithm | |
| CN113420415A (en) | Intersection bidirectional pedestrian simulation method based on perception area comfort | |
| JP2012164159A (en) | Risk determination device, risk determination program, and risk determination method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant |