CN115909851A - Immersive driving simulation system for rail transit vehicle and application method thereof - Google Patents
Immersive driving simulation system for rail transit vehicle and application method thereof Download PDFInfo
- Publication number
- CN115909851A CN115909851A CN202211537968.9A CN202211537968A CN115909851A CN 115909851 A CN115909851 A CN 115909851A CN 202211537968 A CN202211537968 A CN 202211537968A CN 115909851 A CN115909851 A CN 115909851A
- Authority
- CN
- China
- Prior art keywords
- event
- driving simulation
- rail transit
- model
- semantics
- 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
- 238000004088 simulation Methods 0.000 title claims abstract description 72
- 238000000034 method Methods 0.000 title claims abstract description 30
- 230000004044 response Effects 0.000 claims abstract description 48
- 230000008859 change Effects 0.000 claims abstract description 16
- 238000009877 rendering Methods 0.000 claims abstract description 12
- 230000007613 environmental effect Effects 0.000 claims description 10
- 230000000007 visual effect Effects 0.000 claims description 7
- 238000006243 chemical reaction Methods 0.000 claims description 6
- 238000013507 mapping Methods 0.000 claims description 6
- 239000011521 glass Substances 0.000 claims description 3
- 238000012549 training Methods 0.000 abstract description 18
- 238000005516 engineering process Methods 0.000 abstract description 8
- 230000009467 reduction Effects 0.000 abstract description 7
- 238000004519 manufacturing process Methods 0.000 abstract description 5
- 230000007246 mechanism Effects 0.000 abstract description 4
- 238000010586 diagram Methods 0.000 description 10
- 238000004590 computer program Methods 0.000 description 7
- 230000008569 process Effects 0.000 description 7
- 230000006870 function Effects 0.000 description 5
- 238000011161 development Methods 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 230000008901 benefit Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011022 operating instruction Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Images
Classifications
-
- 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
- Processing Or Creating Images (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses an immersive rail transit vehicle driving simulation system and an application method thereof, wherein the immersive rail transit vehicle driving simulation system comprises a VR intelligent terminal, a driving simulation unit and a rail transit digital twin unit, wherein the VR intelligent terminal is used for receiving an operation instruction and outputting a virtual reality scene; the driving simulation unit is used for obtaining an operation instruction and converting the operation instruction into an event, obtaining a response event list causing scene change through the rail transit digital twin unit, dynamically rendering and updating a virtual reality scene according to the response event list, and transmitting the virtual reality scene to the wearable VR intelligent terminal. The invention can realize linkage with the data of real vehicle operation, completely copy the real world operation state, provide training environment closer to the real world for training trainees, realize digital reduction of the real world, and greatly improve the updating efficiency and the reduction degree of the driving simulation unit and reduce the content manufacturing cost by utilizing automatic reconstruction and mechanism attachment technology.
Description
Technical Field
The invention relates to the technical field of rail transit driving virtual simulation, in particular to a rail transit vehicle immersive driving simulation system and an application method thereof.
Background
At present, the urbanization process of China is accelerated, and the rail transit which is taken as the main force of urban traffic is rapidly developed, so that the demand on train drivers is rapidly increased. The training and skill improvement tasks of drivers are increasingly heavy, and qualified rail vehicle drivers can be efficiently cultured only by a more professional and effective training method, so that the safe running of rail transit vehicles is guaranteed. The day by day, the difference of the related technologies of urban rail transit also provides great challenges for the comprehensive quality of rail transit drivers. With the rapid updating and iteration of the technology, the learning cost of the rail driver for a brand-new driving system is increased day by day, the traditional driving simulation training system is limited by the problems of development cost, technical bottleneck and the like, and the new technology and the new method of rail transit are difficult to be rapidly updated into the driving training system, so that the current driving simulation training system cannot meet the training requirements of rail transit drivers in the new era in terms of simulation degree, updating speed and coordination capacity. Therefore, a new generation of rail transit driving simulation unit with high simulation degree and updating iteration speed is needed.
Disclosure of Invention
The technical problems to be solved by the invention are as follows: aiming at the problems in the prior art, the invention provides the immersive driving simulation system for the rail transit vehicle and the application method thereof, the immersive driving simulation system can be linked with the running data of the real vehicle, the running state of the real world is completely copied, a training environment closer to the real world is provided for training trainees, the digital reduction of the real world is realized, meanwhile, the automatic reconstruction and mechanism attachment technology is utilized, the updating efficiency and the reduction degree of a driving simulation unit are greatly improved, and the content manufacturing cost is reduced.
In order to solve the technical problems, the invention adopts the technical scheme that:
an immersive driving simulation system for rail transit vehicles comprises a VR intelligent terminal, a driving simulation unit and a rail transit digital twin unit which are sequentially connected, wherein the VR intelligent terminal is used for receiving an operation instruction of a user and outputting a virtual reality scene of a traffic vehicle cockpit to the user; the driving simulation unit is used for obtaining an operation instruction sent by the wearable VR intelligent terminal, converting the operation instruction into an event causing scene change, sending the event to the rail transit digital twin unit to obtain a response event list causing the scene change, dynamically rendering and updating a virtual reality scene of a traffic vehicle cockpit according to the response event list causing the scene change, and transmitting the virtual reality scene to the wearable VR intelligent terminal.
Optionally, the VR smart terminal is in the shape of a wearable helmet.
Optionally, the virtual reality scene of the traffic vehicle cab comprises part or all of visual images, sounds, cab states, travel route states and environmental landscapes during driving.
The invention also provides an application method of the immersive rail transit vehicle driving simulation system, which comprises the following steps:
s101, when detecting that a user operates a target object model in a virtual reality scene, a VR intelligent terminal sends an operation instruction to a driving simulation unit;
s102, after receiving an operation instruction, the driving simulation unit acquires a model state of a target object model, converts the model state into a corresponding operation semantic, converts the operation semantic into a corresponding trigger event, and sends the trigger event to the rail transit digital twin unit;
s103, after receiving the trigger event, the rail transit digital twin unit acquires a response event list corresponding to the trigger event and returns the response event list to the driving simulation unit;
s104, after receiving the response event list, the driving simulation unit reversely converts the response event into corresponding operation semantics for each response event, and then reversely converts the operation semantics into corresponding model states; rendering the state change of the corresponding object model in the virtual reality scene according to all the obtained model states, and transmitting the rendering result to the VR intelligent terminal so as to return a picture after the user operates the target object model in the virtual reality scene to the user.
Optionally, the step S102 of converting the model state into the corresponding operation semantics means that the model state is retrieved from a preset relationship table between the model state and the operation semantics to obtain the operation semantics corresponding to the model state; the step S104 of reversely converting the operation semantics into the corresponding model state means that the operation semantics are retrieved from a preset model state and an operation semantics relation table to obtain a model state corresponding to the operation semantics; the model state and operation semantic relation table comprises a mapping relation between the model state and the operation semantics.
Optionally, the step S102 of converting the operation semantics into the corresponding trigger event refers to retrieving a preset operation semantics and event relation table from the operation semantics to obtain the trigger event corresponding to the model state; in the step S104, reversely converting the response event into the corresponding operation semantics means that the preset operation semantics and event relation table is retrieved for the response event to obtain the operation semantics corresponding to the response event; the operation semantic and event relation table comprises mapping relations between operation semantics and events.
Optionally, the step S103 of obtaining the response event list corresponding to the trigger event refers to retrieving a preset event association model graph network based on the trigger event to obtain the response event list corresponding to the trigger event, where a node in the event association model graph network is a trigger event or a response event, and an edge is an association relationship between events.
Optionally, the operation instruction in step S101 includes a model number and a model state of the target object model.
Optionally, before the step S101, the driving simulation unit further initializes a virtual reality scene, where an object model in the virtual reality scene includes an object model of a cabin body of the cockpit, an object model of an operating component in the cockpit, and an environmental landscape model corresponding to a glass region in the cabin body of the cockpit, so as to simulate a part or all of a visual image, a sound, a state of the cockpit, a state of an operation line, and an environmental landscape during driving.
Optionally, before step S101, initializing a model state and operation semantic relation table and an operation semantic and event relation table for the driving simulation unit to implement the relation conversion between the model state and the operation semantic and the relation conversion between the operation semantic and the event, and initializing an event association model map network for the rail transit digital twin unit to obtain a response event list corresponding to the trigger event.
Compared with the prior art, the invention mainly has the following advantages: (1) The immersive driving simulation system for the rail transit vehicle can realize linkage with data of real vehicle operation, completely copy the operation state of the real world, and provide a training environment closer to the real training environment for trainees. (2) The immersive driving simulation system for the rail transit vehicle realizes digital reduction of the real world, and simultaneously utilizes automatic reconstruction and mechanism attachment technology, thereby greatly improving the updating efficiency and the reduction degree of the driving simulation unit and reducing the content manufacturing cost.
Drawings
Fig. 1 is a schematic structural diagram of an immersive driving simulation system of a rail transit vehicle according to an embodiment of the present invention.
FIG. 2 is a flow chart of a method according to an embodiment of the present invention.
Fig. 3 is a structural example of an event correlation model graph network according to an embodiment of the present invention.
FIG. 4 is a schematic diagram illustrating a search process of an event correlation model graph network according to an embodiment of the present invention.
Detailed Description
As shown in fig. 1, the immersive driving simulation system for the rail transit vehicle in the embodiment includes a VR intelligent terminal, a driving simulation unit and a rail transit digital twin unit, which are connected in sequence, wherein the VR intelligent terminal is used for receiving an operation instruction of a user and outputting a virtual reality scene of a traffic vehicle cockpit to the user; the driving simulation unit is used for obtaining an operation instruction sent by the wearable VR intelligent terminal, converting the operation instruction into an event causing scene change, sending the event to the rail transit digital twin unit to obtain a response event list causing the scene change, dynamically rendering and updating a virtual reality scene of a traffic vehicle cockpit according to the response event list causing the scene change, and transmitting the virtual reality scene to the wearable VR intelligent terminal.
In this embodiment, the VR intelligent terminal is wearable helmet-shaped. In addition, other forms may be employed as desired to facilitate interaction with the user. In order to improve the sense of reality of the virtual reality scene, in the embodiment, the virtual reality scene of the traffic vehicle cockpit comprises all visual images, sounds, cockpit states, running line states and environmental landscapes in the driving process, so that the immersive virtual reality scene is depicted, the running state of the real world is completely duplicated, and a training environment which is closer to the reality is provided for trainees. It should be noted that the factors of the virtual reality scene may also be based on the selected portion, and the purpose of implementing an immersive virtual reality scene may also be achieved more or less. Wearable VR intelligent terminal drives analog system program through the installation, realizes immersive virtual reality scene, and visual image, sound, cockpit state information, operation circuit state information and the environmental landscape of real reduction driving in-process, virtual reality scene can change according to the operating instruction of difference.
As shown in fig. 2, the application method of the immersive driving simulation system for the rail transit vehicle in the embodiment includes:
s101, when detecting that a user operates a target object model in a virtual reality scene, a VR intelligent terminal sends an operation instruction to a driving simulation unit;
s102, after receiving an operation instruction, the driving simulation unit acquires a model state of a target object model, converts the model state into a corresponding operation semantic, converts the operation semantic into a corresponding trigger event, and sends the trigger event to the rail transit digital twin unit;
s103, after receiving the trigger event, the rail transit digital twin unit acquires a response event list corresponding to the trigger event and returns the response event list to the driving simulation unit;
s104, after receiving the response event list, the driving simulation unit reversely converts the response event into corresponding operation semantics for each response event, and then reversely converts the operation semantics into corresponding model states; rendering the state change of the corresponding object model in the virtual reality scene according to all the obtained model states, and transmitting the rendering result to the VR intelligent terminal so as to return a picture after the user operates the target object model in the virtual reality scene to the user.
In this embodiment, the step S102 of converting the model state into the corresponding operation semantics refers to retrieving a preset relationship table between the model state and the operation semantics from the model state to obtain the operation semantics corresponding to the model state; the step S104 of reversely converting the operation semantics into the corresponding model state means that the operation semantics are retrieved from a preset model state and an operation semantics relation table to obtain a model state corresponding to the operation semantics; the model state and operation semantic relation table comprises a mapping relation between the model state and the operation semantics.
In this embodiment, the step S102 of converting the operation semantics into the corresponding trigger event refers to retrieving a preset operation semantics and event relation table from the operation semantics to obtain a trigger event corresponding to the model state; the step S104 of reversely converting the response event into the corresponding operation semantics refers to retrieving a preset operation semantics and event relation table from the response event to obtain the operation semantics corresponding to the response event; the operation semantic and event relation table comprises mapping relations between operation semantics and events.
In this embodiment, the step S103 of obtaining the response event list corresponding to the trigger event refers to retrieving a preset event association model graph network based on the trigger event to obtain the response event list corresponding to the trigger event, where a node in the event association model graph network is a trigger event or an association relationship between a response event and an edge in the event association model graph network.
In this embodiment, the operation instruction in step S101 includes a model number and a model state of the target object model.
In this embodiment, before step S101, the driving simulation unit further initializes a virtual reality scene, where an object model in the virtual reality scene includes an object model of a cabin body of the cockpit, an object model of an operating component in the cockpit, and an environmental landscape model corresponding to a glass region in the cabin body of the cockpit, so as to simulate part or all of a visual image, sound, a state of the cockpit, a state of an operation line, and an environmental landscape during driving.
In this embodiment, before step S101, the method further includes initializing a model state and operation semantic relation table and an operation semantic and event relation table for the driving simulation unit to implement the relation conversion between the model state and the operation semantic and the relation conversion between the operation semantic and the event, and initializing an event association model map network for the rail transit digital twin unit to obtain a response event list corresponding to the trigger event.
Taking the example of realizing train motion control by a driving operating rod of a subway vehicle, a related target object model comprises the driving operating rod and a bogie, and the driving operating rod and the bogie are respectively numbered as S001 and S002.
Defining the model states of the operating rod as forward (1-100%), backward (1-100%) and homing, wherein the operating semantics of the operating rod are forward power output (1-100%), backward power output (1-27%) and no output; defining triggering events of the operating lever as EC001, EC002 and EC003, and no response event (only operation is needed and no response linkage operation is needed); defining the model states of the bogie as forward rotation (linear speed of 0-30.55 m/s), reverse rotation (0-33.55 m/s) and no rotation, and stopping the bogie when the operation semantics are forward (highest speed of 30.55 m/s) and backward (highest speed of 8.33 m/s); the trigger event numbers of the bogie are defined as EZ001, EZ002, EZ003, and the response event numbers are RZ001, RZ002, RZ003.
In this embodiment, a preset relationship table between the model state and the operation semantic is shown in table 1.
Table 1: and the model state and operation semantic relation table.
In this embodiment, a preset operation semantic and event relation table is shown in table 2.
Table 2: and operating a semantic and event relation table.
| Operational semantics | Triggering event | Responding to events |
| Positive power output of operating lever | EC001 | Is free of |
| Reverse power output of operating lever | EC002 | Is composed of |
| Operating lever without output | EC003 | Is free of |
| The bogie is advanced | EZ001 | RZ001 |
| Bogie retreat | EZ002 | RZ002 |
| Bogie stopping | EZ003 | RZ003 |
In this embodiment, the preset event association model graph network nodes are triggering events or response events, and the edges are association relations between the events, and the specific configuration is as shown in fig. 3, where the related event relations can be summarized and summarized as shown in table 3.
Table 3: and summarizing event relations of the event association model graph network.
| Event(s) | Correlating events |
| EC001 | ED001 |
| EC001 | EE001 |
| ED001 | RZ001 |
| ... | ... |
As shown in fig. 4, in this embodiment, EC001 is used as a starting point of a graph network, a breadth-first algorithm is used in the directed graph network to sequentially search for a next node of a directed edge, and when no edge node exists, the node is added to a result list until all nodes are edge-free nodes. According to the method, all the final associated event lists (RZ 001, ED001, EE 001) of the node EC001 in the directed graph network can be reached.
The user pushes the operation forward by 50% (the position rotates forward by 50% of the travel) in the VR intelligent terminal, and the VR intelligent terminal transmits the operation instruction (the position of the operating rod is pushed forward by 50%) to the driving simulation unit. After the driving simulation unit receives an operation instruction of the VR intelligent terminal, according to the model state of the operation rod (pushed by 50%), the model state and operation semantic relation table is searched to obtain the operation semantic [ the forward power output of the operation rod ], and the operation semantic and event relation table is searched to obtain the event EC001. The driving simulation unit transmits the event EC001 into the rail transit digital twin unit. And the rail transit digital twin unit searches the event association model graph network according to the event EC001 to obtain the association events ED001, EE001 and RZ001. The rail transit digital twin unit transmits ED001, EE001 and RZ001 back to the driving analog unit. (taking RZ001 as an example), after the driving simulation unit receives an RZ001 event transmitted by the rail transit digital twin unit, retrieving the operation semantic and event relation table to obtain an operation semantic (advancing of a bogie), and retrieving the model state and the operation semantic relation table to obtain a model state which is forward rotation (state) of the bogie (model). And the driving simulation unit assembles a model number S002 and a state (forward rotation) according to the obtained model and the model state, renders the state change of the model, and transmits the rendering result to the VR intelligent terminal so as to finally present the rendering result to the user.
The immersive driving simulation system for the rail transit vehicle can be linked with the running data of the real vehicle, completely repeatedly carves the running state of the real world, provides a training environment which is closer to the real world for training students, achieves digital restoration of the real world, greatly improves the updating efficiency and the restoration degree of a driving simulation unit by using automatic reconstruction and mechanism attachment technologies, and reduces the content manufacturing cost. The immersive rail transit vehicle driving simulation system not only realizes virtual reality immersive vehicle driving simulation training in the traditional sense, but also integrates real running data and physical rules, so that the training process is closer to the experience of the real world, and a better training effect is realized. Different from a conventional driving simulation system, the immersive driving simulation system for the rail transit vehicle combines driving simulation and digital twinning technology through semantics and events, simplifies the development process of the driving simulation by combining the semantic understanding process of simulating state change with the event rule matching of digital twinning, can realize driving related functions by defining semantics and events, greatly improves the development efficiency of the driving simulation system, and reduces the development cost.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-readable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein. The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments, and all technical solutions belonging to the idea of the present invention belong to the protection scope of the present invention. It should be noted that modifications and embellishments within the scope of the invention may occur to those skilled in the art without departing from the principle of the invention, and are considered to be within the scope of the invention.
Claims (10)
1. The immersive driving simulation system for the rail transit vehicle is characterized by comprising a VR intelligent terminal, a driving simulation unit and a rail transit digital twin unit which are sequentially connected, wherein the VR intelligent terminal is used for receiving an operation instruction of a user and outputting a virtual reality scene of a cockpit of the rail transit vehicle to the user; the driving simulation unit is used for obtaining an operation instruction sent by the wearable VR intelligent terminal, converting the operation instruction into an event causing scene change, sending the event to the rail transit digital twin unit to obtain a response event list causing the scene change, dynamically rendering and updating a virtual reality scene of a traffic vehicle cockpit according to the response event list causing the scene change, and transmitting the virtual reality scene to the wearable VR intelligent terminal.
2. The rail transit vehicle immersive driving simulation system of claim 1, wherein the VR smart terminal is in a wearable helmet-like shape.
3. The immersive driving simulation system for rail transit vehicles of claim 1 or 2, wherein the virtual reality scene of the cockpit of the transit vehicle comprises part or all of visual images, sounds, cockpit states, travel route states and environmental landscapes during driving.
4. A method for applying the immersive driving simulation system for the rail transit vehicle as claimed in any one of claims 1 to 3, wherein the method comprises:
s101, when detecting that a user operates a target object model in a virtual reality scene, a VR intelligent terminal sends an operation instruction to a driving simulation unit;
s102, after receiving an operation instruction, the driving simulation unit obtains a model state of a target object model, converts the model state into corresponding operation semantics, converts the operation semantics into corresponding trigger events, and sends the trigger events to the rail transit digital twin unit;
s103, after receiving the trigger event, the rail transit digital twin unit acquires a response event list corresponding to the trigger event and returns the response event list to the driving simulation unit;
s104, after receiving the response event list, the driving simulation unit reversely converts the response event into corresponding operation semantics for each response event, and then reversely converts the operation semantics into corresponding model states; rendering the state change of the corresponding object model in the virtual reality scene according to all the obtained model states, and transmitting the rendering result to the VR intelligent terminal so as to return a picture after the user operates the target object model in the virtual reality scene to the user.
5. The application method of the immersive rail transit vehicle driving simulation system of claim 4, wherein the step S102 of converting the model state into the corresponding operation semantics means that the model state is retrieved from a preset model state and operation semantics relation table to obtain the operation semantics corresponding to the model state; the step S104 of reversely converting the operation semantics into the corresponding model state means that the operation semantics are retrieved from a preset model state and an operation semantics relation table to obtain a model state corresponding to the operation semantics; the model state and operation semantic relation table comprises a mapping relation between the model state and the operation semantics.
6. The application method of the rail transit vehicle immersive driving simulation system according to claim 5, wherein the step S102 of converting the operation semantics into the corresponding trigger events refers to retrieving a preset operation semantics and event relation table from the operation semantics to obtain the trigger events corresponding to the model states; the step S104 of reversely converting the response event into the corresponding operation semantics refers to retrieving a preset operation semantics and event relation table from the response event to obtain the operation semantics corresponding to the response event; the operation semantic and event relation table comprises mapping relations between operation semantics and events.
7. The application method of the immersive rail transit vehicle driving simulation system of claim 6, wherein the step S103 of obtaining the response event list corresponding to the trigger event refers to retrieving a preset event association model graph network based on the trigger event to obtain the response event list corresponding to the trigger event, wherein nodes in the event association model graph network are the trigger event or the response event, and edges are the association relationship between the events.
8. The method for applying the immersive driving simulation system of the rail transit vehicle as claimed in claim 7, wherein the operation instruction in step S101 includes a model number and a model state of the target object model.
9. The application method of the rail transit vehicle immersive driving simulation system of claim 8, wherein the step S101 is preceded by initializing a virtual reality scene by a driving simulation unit, wherein an object model in the virtual reality scene comprises an object model of a cabin body of the cockpit, an object model of an operating component in the cockpit, and an environmental landscape model corresponding to a glass region in the cabin body of the cockpit, so as to simulate part or all of visual images, sounds, cabin states, operating line states and environmental landscape during driving.
10. The application method of the immersive rail transit vehicle driving simulation system of claim 4, wherein step S101 is preceded by initializing a model state and operation semantic relation table and an operation semantic and event relation table for the driving simulation unit to realize the relation conversion between the model state and the operation semantic and the relation conversion between the operation semantic and the event, and initializing an event correlation model map network for the rail transit digital twin unit to obtain a response event list corresponding to the trigger event.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211537968.9A CN115909851B (en) | 2022-12-01 | 2022-12-01 | Rail transit vehicle immersive driving simulation system and application method thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211537968.9A CN115909851B (en) | 2022-12-01 | 2022-12-01 | Rail transit vehicle immersive driving simulation system and application method thereof |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115909851A true CN115909851A (en) | 2023-04-04 |
| CN115909851B CN115909851B (en) | 2024-06-11 |
Family
ID=86475977
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211537968.9A Active CN115909851B (en) | 2022-12-01 | 2022-12-01 | Rail transit vehicle immersive driving simulation system and application method thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115909851B (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107945609A (en) * | 2017-12-23 | 2018-04-20 | 河南智盈电子技术有限公司 | A kind of rail traffic vehicle braking simulation training system based on virtual reality technology |
| US20180286268A1 (en) * | 2017-03-28 | 2018-10-04 | Wichita State University | Virtual reality driver training and assessment system |
| CN109933208A (en) * | 2019-04-11 | 2019-06-25 | 湖北航天技术研究院特种车辆技术中心 | A kind of operation behavior recognition methods and system based on virtual reality |
| CN113312397A (en) * | 2021-05-12 | 2021-08-27 | 上海申通地铁集团有限公司 | Full-automatic operation simulation method and system for rail transit, medium and electronic equipment |
| CN113485392A (en) * | 2021-06-17 | 2021-10-08 | 广东工业大学 | Virtual reality interaction method based on digital twins |
| KR20220081880A (en) * | 2020-12-09 | 2022-06-16 | (주) 아인스에스엔씨 | Apparatus for real time analysis and real time operation visualization for discrete event system using digital twin |
| KR20220092300A (en) * | 2020-12-24 | 2022-07-01 | (주)액츄얼뷰 | Education and training system for urban railway engineers and its operation method by nested interlocking execution based on digital twins |
-
2022
- 2022-12-01 CN CN202211537968.9A patent/CN115909851B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180286268A1 (en) * | 2017-03-28 | 2018-10-04 | Wichita State University | Virtual reality driver training and assessment system |
| CN107945609A (en) * | 2017-12-23 | 2018-04-20 | 河南智盈电子技术有限公司 | A kind of rail traffic vehicle braking simulation training system based on virtual reality technology |
| CN109933208A (en) * | 2019-04-11 | 2019-06-25 | 湖北航天技术研究院特种车辆技术中心 | A kind of operation behavior recognition methods and system based on virtual reality |
| KR20220081880A (en) * | 2020-12-09 | 2022-06-16 | (주) 아인스에스엔씨 | Apparatus for real time analysis and real time operation visualization for discrete event system using digital twin |
| KR20220092300A (en) * | 2020-12-24 | 2022-07-01 | (주)액츄얼뷰 | Education and training system for urban railway engineers and its operation method by nested interlocking execution based on digital twins |
| CN113312397A (en) * | 2021-05-12 | 2021-08-27 | 上海申通地铁集团有限公司 | Full-automatic operation simulation method and system for rail transit, medium and electronic equipment |
| CN113485392A (en) * | 2021-06-17 | 2021-10-08 | 广东工业大学 | Virtual reality interaction method based on digital twins |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115909851B (en) | 2024-06-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106502402A (en) | A kind of Three-Dimensional Dynamic Scene Teaching system and method | |
| CN104867176A (en) | Cryengine-based interactive virtual deduction system | |
| CN202171880U (en) | A three-dimensional visual simulation driving system | |
| CN112508960A (en) | Low-precision image semantic segmentation method based on improved attention mechanism | |
| CN106548503B (en) | A kind of animation synthesizing method based on command stream three-dimensional character | |
| CN110544314B (en) | Fusion method, system, medium and equipment of virtual reality and simulation model | |
| CN114296424B (en) | Simulation test system and method | |
| CN114821492A (en) | YOLOv 4-based road vehicle detection system and method | |
| CN109118874A (en) | A kind of aircraft driving training system and method based on virtual reality | |
| CN108922307A (en) | Drive simulating training method, device and driving simulation system | |
| US10994202B2 (en) | Simulated previews of dynamic virtual cameras | |
| CN204440491U (en) | A kind of augmented reality system with a key screenshotss sharing function | |
| CN117315132A (en) | Cloud exhibition hall system based on meta universe | |
| CN115909851B (en) | Rail transit vehicle immersive driving simulation system and application method thereof | |
| CN115222847A (en) | Animation data generation method and device based on neural network and related products | |
| CN104091360A (en) | Method and device for generating movement data through dynamic cinema | |
| CN113079366A (en) | 4D riding scene simulation system | |
| CN116245986A (en) | Virtual sign language digital person driving method and device | |
| CN114491787A (en) | Multi-vehicle multi-simulator linkage driving system and data processing method thereof | |
| CN114202564A (en) | High-speed target tracking method and system based on event camera | |
| Ansari et al. | Simulation of steering a self-driving car using 1) PID controller 2) neural network | |
| Cui et al. | A Wireless Virtual Reality-Based Multimedia-Assisted Teaching System Framework under Mobile Edge Computing | |
| Wang et al. | Multi-objective optimization based deep reinforcement learning for autonomous driving policy | |
| CN117528197A (en) | High-frame-rate playback type quick virtual film making system | |
| CN111915672A (en) | Target labeling method and device based on 3D virtual driving scene |
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 |