CN116362062B - Simulation method for pedestrian traveling avoidance, electronic equipment and storage medium - Google Patents
Simulation method for pedestrian traveling avoidance, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN116362062B CN116362062B CN202310636978.6A CN202310636978A CN116362062B CN 116362062 B CN116362062 B CN 116362062B CN 202310636978 A CN202310636978 A CN 202310636978A CN 116362062 B CN116362062 B CN 116362062B
- Authority
- CN
- China
- Prior art keywords
- pedestrian
- pedestrians
- grid
- hedging
- constructing
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 38
- 238000004088 simulation Methods 0.000 title claims abstract description 29
- 238000001514 detection method Methods 0.000 claims abstract description 8
- 238000004590 computer program Methods 0.000 claims description 14
- 238000004364 calculation method Methods 0.000 abstract description 9
- 238000010586 diagram Methods 0.000 description 4
- 230000006399 behavior Effects 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 230000004888 barrier function Effects 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 238000003491 array Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000006698 induction Effects 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
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
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application provides a simulation method for pedestrian traveling avoidance, electronic equipment and a storage medium, and belongs to the technical field of pedestrian traveling avoidance simulation. The method comprises the following steps: s1, setting grid angles, opposite grid offset, surrounding pedestrian detection ranges and constructing virtual wall parameters; s2, constructing a pedestrian grid; s3, storing pedestrian position information into a grid; s4, obtaining opposite-impact grid and pedestrian set; s5, constructing a virtual wall; s6, calculating social force born by the pedestrians, and adjusting the advancing direction according to the social force born by the pedestrians. The method solves the technical problem of poor simulation efficiency caused by poor calculation performance and large calculation amount in the prior art.
Description
Technical Field
The application relates to a simulation method for pedestrian traveling avoidance, in particular to a simulation method for pedestrian traveling avoidance, electronic equipment and a storage medium, and belongs to the technical field of pedestrian traveling avoidance simulation.
Background
There are two kinds of usual pedestrian microscopic travel simulation models, one is a cellular automaton model, and the other is a social force model. When the two models simulate the real pedestrian flows, the most common problem is that the phenomenon of opposite collision occurs between pedestrians, namely, pedestrians running oppositely do not avoid each other during running, and the process of collision occurs. When such a hedging phenomenon gradually expands, a certain degree of congestion is caused, unlike the phenomenon actually observed. Real-world pedestrians can often avoid in advance when encountering opposite impact, and congestion is not caused. In view of the above, the method for constructing a background field in the prior achievements and referring to the social force model is disclosed, the anisotropism of pedestrian speed and conflict induction is considered, and a pedestrian conflict avoidance mechanism is introduced to improve the original model, so that a simulation method for pedestrian traveling avoidance simulation is formed.
Yu L Y Influence of the exits' configuration on evacuation process in a room without obstacle J. Physica, a. Statistical mechanics and its applications, 2015, 420 (Null) states that the improvement in the endo-visual pulling method to calculate the background field treats the pedestrian as a movable obstacle increases the element value occupied by the pedestrian. In the method, pedestrians are regarded as movable barriers in the actual simulation process, and when the front-back movement directions of two pedestrians are close to or consistent with each other. And, regard pedestrian in front as the obstacle, pedestrian in back can appear and bypass the situation; after pedestrians are taken as moving barriers, acting forces among pedestrians are calculated, so that calculation of forces is repeated, and simulation accuracy is affected; meanwhile, the calculation performance of the background field is poor, and the calculation amount is larger as the number of the simulation persons is larger, so that the simulation efficiency is poor.
Disclosure of Invention
The following presents a simplified summary of the application in order to provide a basic understanding of some aspects of the application. It should be understood that this summary is not an exhaustive overview of the application. It is not intended to identify key or critical elements of the application or to delineate the scope of the application. Its purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is discussed later.
In view of the above, the application provides a simulation method for pedestrian traveling avoidance, electronic equipment and a storage medium for solving the technical problems of poor simulation efficiency caused by poor calculation performance and large calculation amount in the prior art.
The first scheme is a simulation method for pedestrian traveling avoidance, comprising the following steps:
s1, setting grid angles, opposite grid offset, surrounding pedestrian detection ranges and constructing virtual wall parameters;
s2, constructing a pedestrian grid;
s3, storing pedestrian position information into a grid;
s4, obtaining opposite-impact grid and pedestrian set;
s5, constructing a virtual wall;
s6, calculating social force born by the pedestrians, and adjusting the advancing direction according to the social force born by the pedestrians.
Preferably, the mesh angle is set to 45 °; the offset grid offset is set to 1.
Preferably, the surrounding pedestrian detection range is set to 200cm; the distance of pedestrians constructing the virtual wall is set to 60cm.
Preferably, the method for constructing the pedestrian mesh is as follows: calculating the number N of grids according to the set grid Angle, wherein N=360 degrees/Angle; and creating N pedestrian position information storage grids according to the building size.
Preferably, the position information is stored in the grid corresponding to the sequence number according to the current angle of the pedestrian, and the formula is as follows: idx=ca/Angle, when grid angle=0°, grid number is 0; where Idx represents the grid number and CA represents the current angle of the pedestrian.
Preferably, the method for acquiring the hedging grid and the pedestrian set is as follows:
acquiring a hedging grid set:
according to the current angle of the pedestrian, calculating the grid sequence number of the horizontal right opposite surface, wherein the formula is as follows:
Idx= （CA+180°）/ Angle；
according to the offset of the hedging grids, obtaining a hedging grid set;
acquiring a hedging pedestrian set:
and traversing all pedestrians of the hedging grid according to the current positions of the pedestrians, and putting pedestrians with the distance smaller than the searching range of surrounding pedestrians into the hedging pedestrian set.
Preferably, the method for constructing the virtual wall is as follows: and traversing the opposite-impact pedestrian set, calculating the distance between every two pedestrians, constructing a virtual wall according to the positions of the two pedestrians when the distance between the pedestrians is smaller than the distance between the pedestrians for constructing the virtual wall, and putting the pedestrians into a list without calculating the acting force of the pedestrians.
Preferably, the method for calculating the social force suffered by the pedestrian is as follows:
resultant force of pedestrians=self-driving of pedestrians+wall force+inter-pedestrian force
Wall force = building wall + virtual wall force
Inter-pedestrian effort = surrounding people-effort for not calculating pedestrian effort list.
The second scheme is an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the step of the simulation method for pedestrian traveling avoidance in the first scheme when executing the computer program.
A third aspect is a computer readable storage medium, on which a computer program is stored, where the computer program when executed by a processor implements the simulation method for pedestrian travel avoidance of the first aspect.
The beneficial effects of the application are as follows: according to the application, the grid angle, the offset of the hedging grid, the detection range of surrounding pedestrians, the construction of virtual wall parameters, the construction of the pedestrians grid and the pedestrian position data are set, and the hedging grid and the pedestrian set are obtained, so that the virtual wall is constructed, the social force born by the pedestrians is finally calculated, and the advancing direction is adjusted according to the social force born by the pedestrians; the method solves the technical problem of poor simulation efficiency caused by poor calculation performance and large calculation amount in the prior art. The method realizes the optimization of the pedestrian travelling path, reduces the probability of pedestrian travelling conflict, and improves the simulation efficiency and the authenticity. The accurate modeling and simulation of pedestrian behaviors can better predict and control the behaviors of pedestrians in crowded scenes, so that the problems in the aspects of personnel evacuation, safety, management and the like are improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
FIG. 1 is a schematic flow diagram of a simulation method for pedestrian travel avoidance;
FIG. 2 is a schematic diagram of pedestrian versus pedestrian position;
FIG. 3 is a schematic illustration of pedestrian hedging relationship;
fig. 4 is a schematic diagram of the conversion of a heddle person into an obstacle.
Detailed Description
In order to make the technical solutions and advantages of the embodiments of the present application more apparent, the following detailed description of exemplary embodiments of the present application is provided in conjunction with the accompanying drawings, and it is apparent that the described embodiments are only some embodiments of the present application and not exhaustive of all embodiments. It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other.
Embodiment 1, referring to fig. 1 to 4, describes a simulation method for pedestrian travel avoidance, which includes the following steps:
s1, setting grid angles, opposite grid offset, surrounding pedestrian detection ranges and constructing virtual wall parameters, wherein the parameters can be calibrated according to the needs of simulation scenes;
the grid angle was set at 45 °.
The offset grid offset is set to 1;
the surrounding pedestrian detection range is set to 200cm;
the distance of pedestrians constructing a virtual wall is set to be 60cm;
see, table 1 for details;
table 1 parameter setting table
S2, constructing a pedestrian grid for storing pedestrian position information of different angles in real time, wherein the relation between the grid serial number and the pedestrian angle is shown as a table 2 grid serial number and pedestrian angle relation table; (mesh size 20cm x 20 cm);
the method for constructing the pedestrian grid comprises the following steps:
calculating the number N of grids according to the set grid Angle, wherein N=360 degrees/Angle;
and creating N pedestrian position information storage grids according to the building size.
TABLE 2 grid sequence number and pedestrian Angle relationship Table
S3, storing pedestrian position information into a grid;
storing the position information into grids with corresponding serial numbers according to the current angle of the pedestrian, wherein the formula is as follows:
idx=ca/Angle, when grid angle=0°, grid number is 0;
wherein Idx represents a grid sequence number, and CA represents a current angle of the pedestrian;
s4, obtaining opposite-impact grid and pedestrian set;
acquiring a hedging grid set:
according to the current angle of the pedestrian, calculating the grid sequence number of the horizontal right opposite surface, wherein the formula is as follows:
Idx= （CA+180°）/ Angle；
according to the offset of the hedging grids, obtaining a hedging grid set;
for example: the current angle ca=50°, aoffset=1, the front hedging number is 4 and the surrounding two grid numbers are the grid numbers where 3 and 5 are located, respectively, i.e. the hedging grid set is {3,4,5}.
Acquiring a hedging pedestrian set:
and traversing all pedestrians of the hedging grid according to the current positions of the pedestrians, and putting pedestrians with the distance smaller than the searching range of surrounding pedestrians into the hedging pedestrian set.
Referring to fig. 2, a schematic diagram of the relationship between pedestrians and positions of pedestrians is shown, and 6 pedestrians within a range of 2 meters around a pedestrian { ped, 60 ° } are respectively: { ped, 30 ° }, { ped, 80 ° }, { ped4,172 ° }, { ped5,262 ° }, { ped6,258 ° }, { ped7,210 ° }, according to the method of obtaining the set of hedging pedestrians, the hedging relationship is obtained by obtaining the hedging conforming to the hedging behavior { ped5,262 ° }, { ped6,258 ° }, { ped7,210 ° }, referring to fig. 3, the pedestrian hedging relationship is schematically shown.
S5, constructing a virtual wall;
traversing the opposite-impact pedestrian set, calculating the distance between every two pedestrians, constructing a virtual wall according to the positions of the two pedestrians when the distance between the pedestrians is smaller than the distance between the pedestrians for constructing the virtual wall, and putting the pedestrians into a list without calculating the acting force of the pedestrians; referring to fig. 4, a hedging pedestrian is converted into an obstacle schematic;
s7, calculating social force born by the pedestrians, and adjusting the advancing direction according to the social force born by the pedestrians.
Resultant force of pedestrians=self-driving of pedestrians+wall force+inter-pedestrian force
Wall force = building wall + virtual wall force
Inter-pedestrian effort = surrounding people-effort for not calculating pedestrian effort list.
In embodiment 2, the computer device of the present application may be a device including a processor and a memory, for example, a single chip microcomputer including a central processing unit. And the processor is used for executing the computer program stored in the memory to realize the steps of the method for passing the automatic driving vehicle at the no-signal crossing.
The processor may be a central processing unit (Central Processing Unit, CPU), other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data (such as audio data, phonebook, etc.) created according to the use of the handset, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash Card (Flash Card), at least one disk storage device, flash memory device, or other volatile solid-state storage device.
Embodiment 3, computer-readable storage Medium embodiment
The computer readable storage medium of the present application may be any form of storage medium that is readable by a processor of a computer device, including but not limited to, a nonvolatile memory, a volatile memory, a ferroelectric memory, etc., on which a computer program is stored, and when the processor of the computer device reads and executes the computer program stored in the memory, the steps of a method for passing an autonomous vehicle at a no-signal intersection as described above can be implemented.
The computer program comprises computer program code which may be in source code form, object code form, executable file or in some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.
While the application has been described with respect to a limited number of embodiments, those skilled in the art, having benefit of the above description, will appreciate that other embodiments are contemplated within the scope of the application as described herein. Furthermore, it should be noted that the language used in the specification has been principally selected for readability and instructional purposes, and may not have been selected to delineate or circumscribe the inventive subject matter. Accordingly, many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the appended claims. The disclosure of the present application is intended to be illustrative, but not limiting, of the scope of the application, which is defined by the appended claims.
Claims (3)
1. The simulation method for pedestrian traveling avoidance is characterized by comprising the following steps of:
s1, setting grid angles, opposite grid offset, surrounding pedestrian detection ranges and constructing virtual wall parameters;
setting the grid angle to be 45 degrees; setting offset of the hedging grid to be 1;
setting the detection range of surrounding pedestrians to be 200cm; setting the distance between pedestrians constructing a virtual wall to be 60cm;
s2, constructing a pedestrian grid, wherein the method comprises the following steps of: calculating the number N of grids according to the set grid Angle, wherein N=360 degrees/Angle; according to the building size, N pedestrian position information storage grids are created;
s3, storing pedestrian position information into a grid, wherein the method comprises the following steps: storing the position information into grids with corresponding serial numbers according to the current angle of the pedestrian, wherein the formula is as follows: idx=ca/Angle, when grid angle=0°, grid number is 0; wherein Idx represents a grid sequence number, and CA represents a current angle of the pedestrian;
s4, obtaining a hedging grid and a pedestrian set, wherein the method comprises the following steps:
acquiring a hedging grid set:
according to the current angle of the pedestrian, calculating the grid sequence number of the horizontal right opposite surface, wherein the formula is as follows:
Idx= （CA+180°）/ Angle；
according to the offset of the hedging grid, obtaining a hedging grid set;
acquiring a hedging pedestrian set:
traversing all pedestrians of the hedging grid according to the current positions of the pedestrians, and putting pedestrians with the distance smaller than the searching range of surrounding pedestrians into a hedging pedestrian set;
s5, constructing a virtual wall, wherein the method comprises the following steps of: traversing the opposite-impact pedestrian set, calculating the distance between every two pedestrians, constructing a virtual wall according to the positions of the two pedestrians when the distance between the pedestrians is smaller than the distance between the pedestrians for constructing the virtual wall, and putting the pedestrians into a list without calculating the acting force of the pedestrians;
s6, calculating social force born by the pedestrians, and adjusting the advancing direction according to the social force born by the pedestrians;
the method for calculating the social force suffered by the pedestrians is as follows:
social force of pedestrians=self-driving force of pedestrians+wall force+inter-pedestrian force
Wall force = building wall force + virtual wall force
Inter-pedestrian effort = effort of surrounding people-effort of pedestrians in the pedestrian effort list is not calculated.
2. An electronic device comprising a memory and a processor, the memory storing a computer program, the processor implementing the steps of a pedestrian avoidance simulation method of claim 1 when the computer program is executed.
3. A computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements a pedestrian crossing simulation method as claimed in claim 1.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310636978.6A CN116362062B (en) | 2023-06-01 | 2023-06-01 | Simulation method for pedestrian traveling avoidance, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310636978.6A CN116362062B (en) | 2023-06-01 | 2023-06-01 | Simulation method for pedestrian traveling avoidance, electronic equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116362062A CN116362062A (en) | 2023-06-30 |
| CN116362062B true CN116362062B (en) | 2023-10-20 |
Family
ID=86909392
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310636978.6A Active CN116362062B (en) | 2023-06-01 | 2023-06-01 | Simulation method for pedestrian traveling avoidance, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116362062B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105955797A (en) * | 2016-04-28 | 2016-09-21 | 中山大学 | GPU-based crowd real-time simulation method adopting social force model |
| CN107103150A (en) * | 2017-05-11 | 2017-08-29 | 山东师范大学 | A kind of two-way simulation method of pedestrian stream and system with avoidance mechanism |
| CN113536613A (en) * | 2021-09-17 | 2021-10-22 | 深圳市城市交通规划设计研究中心股份有限公司 | Crowd evacuation simulation method and device, terminal equipment and storage medium |
| CN114547905A (en) * | 2022-02-28 | 2022-05-27 | 西南交通大学 | Pedestrian trajectory simulation method, device and equipment and readable storage medium |
| CN115186516A (en) * | 2022-09-06 | 2022-10-14 | 深圳市城市交通规划设计研究中心股份有限公司 | Pedestrian simulation model construction method of traffic hub, electronic device and storage medium |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11407431B2 (en) * | 2019-11-22 | 2022-08-09 | Samsung Electronics Co., Ltd. | System and method for object trajectory prediction in an autonomous scenario |
-
2023
- 2023-06-01 CN CN202310636978.6A patent/CN116362062B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105955797A (en) * | 2016-04-28 | 2016-09-21 | 中山大学 | GPU-based crowd real-time simulation method adopting social force model |
| CN107103150A (en) * | 2017-05-11 | 2017-08-29 | 山东师范大学 | A kind of two-way simulation method of pedestrian stream and system with avoidance mechanism |
| CN113536613A (en) * | 2021-09-17 | 2021-10-22 | 深圳市城市交通规划设计研究中心股份有限公司 | Crowd evacuation simulation method and device, terminal equipment and storage medium |
| CN114547905A (en) * | 2022-02-28 | 2022-05-27 | 西南交通大学 | Pedestrian trajectory simulation method, device and equipment and readable storage medium |
| CN115186516A (en) * | 2022-09-06 | 2022-10-14 | 深圳市城市交通规划设计研究中心股份有限公司 | Pedestrian simulation model construction method of traffic hub, electronic device and storage medium |
Non-Patent Citations (3)
| Title |
|---|
| Characteristic time based social force model improvement and exit assignment strategy for pedestrian evacuation;Xiao Song 等;Physica A;第530-548页 * |
| 基于领域驱动设计的自主式交通系统架构分析系统应用一以自主驾驶车辆过交叉路口避让行人场景为例;冯相龙 等;第十七届中国智能交通年会科技论文集;第208-209页 * |
| 考虑行人微观差异的社会力避让模型与仿真;李一波 等;交通运输研究;第9卷(第2期);第33-41页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116362062A (en) | 2023-06-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10755120B2 (en) | End-to-end lightweight method and apparatus for license plate recognition | |
| CN113486531A (en) | Vehicle driving path planning method, equipment and system | |
| CN108645411B (en) | Robot path planning method and device based on particle swarm algorithm and terminal equipment | |
| CN113362491B (en) | Vehicle track prediction and driving behavior analysis method | |
| CN112307978B (en) | Target detection method and device, electronic equipment and readable storage medium | |
| CN113536613B (en) | Crowd evacuation simulation method and device, terminal equipment and storage medium | |
| CN113609784B (en) | Traffic limit scene generation method, system, equipment and storage medium | |
| US10109097B2 (en) | Dynamic collision avoidance for crowd simulation over structured paths that intersect at waypoints | |
| CN112734810B (en) | Obstacle tracking method and device | |
| US20220198225A1 (en) | Method and system for determining action of device for given state using model trained based on risk-measure parameter | |
| CN116362062B (en) | Simulation method for pedestrian traveling avoidance, electronic equipment and storage medium | |
| CN117111578A (en) | Automatic driving system detection blind area guiding fuzzy test method and system | |
| CN111177927A (en) | Vehicle reference driving line construction method, electronic device and storage medium | |
| CN111611703B (en) | Sand table deduction method, device and equipment based on digital twin and storage medium | |
| CN117975418A (en) | Traffic sign detection method based on improved RT-DETR | |
| CN115577574A (en) | Method, device and equipment for calculating position of diversion rail and readable storage medium | |
| CN113759973B (en) | Target search control method and system for unmanned aerial vehicle cluster | |
| CN114167857B (en) | Control method and device of unmanned equipment | |
| CN116466704A (en) | Obstacle avoidance optimization method, device, equipment and storage medium | |
| CN115328118A (en) | Path determining method and device, readable storage medium and electronic equipment | |
| CN114841084B (en) | Aerial image-based personnel evacuation simulation method, system and equipment | |
| CN114802260B (en) | Simulation scene construction method based on natural driving data of road side equipment | |
| Lawniczak et al. | Biomimicry Based Learning Outcomes of Simple Cognitive Agents | |
| CN115630583B (en) | Method, device, equipment and medium for generating simulated vehicle driving state | |
| CN115908788A (en) | Target detection model training method based on double-stage loss function |
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 | ||
| GR01 | Patent grant |