CN114462225A - Rapid construction system for hybrid traffic simulation supporting environment under vehicle-road cooperation - Google Patents
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Abstract
The invention provides a system for quickly constructing a hybrid traffic simulation supporting environment under the cooperation of a vehicle and a road. The system comprises; the hybrid traffic subject model library construction module is used for constructing and storing a moving object model in a hybrid traffic environment; the matching and extracting module of the dynamic element model is used for receiving dynamic object information and scene information collected by the internet-connected vehicle and the intelligent roadside, drawing the dynamic object simulation model, matching a vehicle main body model with the highest similarity to the dynamic object simulation model, generating an optimal scene drawing sequence, and sending the vehicle main body model and the optimal scene drawing sequence to the internet-connected vehicle; and the scene drawing and optimizing module under the cooperative vehicle-road perception is used for generating an optimal scene drawing sequence of the subject vehicle according to the vehicle subject model and the optimal scene drawing sequence. The invention can provide a simulation verification environment for the function test of the vehicle-road cooperative system, and has great significance for improving the simulation efficiency of the vehicle-road cooperative system, reducing the test cost and popularizing the technology.
Description
Technical Field
The invention relates to the technical field of traffic simulation, in particular to a hybrid traffic simulation supporting environment rapid construction system under vehicle-road cooperation.
Background
Under the support of increasingly mature vehicle-road cooperative technology, the information interaction and sharing capability among vehicles is enhanced, the traditional traffic environment mainly based on manually driven vehicles is converted into a novel hybrid traffic environment mixed by manual/intelligent/internet/intelligent internet vehicles, the typical scene types of hybrid traffic are more and the expression is complex, the frequent information interaction behaviors among the devices such as vehicle-vehicle and vehicle-road and the complex motion trend among the vehicles are difficult to give real-time and visual graphic expression forms only by the conventional simulation, the virtual visual simulation technology which is widely applied in recent years can timely carry out omnibearing three-dimensional display and feedback on simulation results, and the virtual visual simulation technology is widely applied in the fields of aviation, navigation, railway, automatic control simulation and the like and becomes a practical simulation method.
The real-time rapid construction of the virtual traffic environment is an important step of intelligent traffic virtual scene simulation, the traditional simulation environment generation usually adopts a manual generation method, and the simulation environment is manufactured by hand drawing according to an aerial map or a satellite map. Aiming at the situation, how to quickly construct a reliable, credible and efficient hybrid traffic simulation environment under the condition of quick change of the traffic environment, reproduce a huge and complex real traffic scene, provide quick visual service of the environment for users, and have great significance for realizing preliminary performance evaluation and function verification of a vehicle-road cooperative system, improving the simulation efficiency, reducing the test cost and popularizing the technology.
At present, a method for quickly constructing a hybrid traffic simulation support environment under the cooperation of a vehicle and a road for a user does not exist.
Disclosure of Invention
The embodiment of the invention provides a hybrid traffic simulation support environment rapid construction system under vehicle-road cooperation so as to realize a self-adaptive hybrid traffic environment cooperative construction method.
In order to achieve the purpose, the invention adopts the following technical scheme.
A hybrid traffic simulation support environment rapid construction system under vehicle-road cooperation comprises: the system comprises a hybrid traffic subject model base construction module, a dynamic element model matching and extracting module and a scene drawing and optimizing module under cooperative vehicle and road perception;
the hybrid traffic subject model library construction module is used for constructing and storing a moving object model in a hybrid traffic environment and providing a model hierarchical index, wherein the moving object comprises vehicle subjects with different intelligent levels;
the matching and extracting module of the dynamic element model is used for receiving dynamic object information and scene information collected by the internet-connected vehicle and the intelligent roadside, drawing a dynamic object simulation model, matching a vehicle main body model with the highest similarity to the dynamic object simulation model in the mixed traffic main body model library, generating an optimal scene drawing sequence according to the received scene information, and sending the vehicle main body model and the optimal scene drawing sequence to the internet-connected vehicle;
and the scene drawing and optimizing module under the cooperative vehicle-road perception is used for generating a main vehicle optimal scene drawing sequence of the networked vehicle according to the received vehicle main model and the optimal scene drawing sequence and sending the main vehicle optimal scene drawing sequence to other surrounding networked vehicles.
Preferably, the hybrid traffic subject model library construction module and the dynamic element model matching and extracting module are arranged in a data center, and the scene drawing and optimizing module is arranged in an internet vehicle under the cooperative perception of the vehicle and the road.
Preferably, the hybrid traffic subject model base building module is specifically configured to store moving object models in a classified manner by using a multimedia database technology, decompose each moving object into model elements, classify, organize and manage the intelligent levels, models and uses of subject vehicles by matching with behavioral characteristic logics of different moving objects, analyze vehicle elements by using an analytic hierarchy process, decompose vehicles into model elements of multiple levels, form a hierarchical structure model index which is associated with each other and has a membership relationship, and build a moving object model index table.
Preferably, the matching and extracting module of the dynamic element model is specifically configured to obtain environment information through an intelligent road side device and other networked intelligent vehicles, perform organic segmentation and remodeling on the environment data, extract typical hierarchical structure features, and generate an optimal scene drawing sequence; and obtaining dynamic object information through the vehicle-mounted and road-side environment sensing units, performing preliminary block data dimension reduction, segmentation processing and reconstruction on the dynamic object information, extracting the hierarchical structure characteristics of the dynamic objects in each block, drawing a dynamic object simulation model, and matching a moving object model with the highest similarity to the dynamic object simulation model in the mixed traffic main body model library by using a characteristic association function.
Preferably, the scene drawing and optimizing module under the cooperative vehicle-road perception is specifically configured to generate a main vehicle drawing sequence according to a received vehicle main model, perform time synchronization and reliability discrimination on the received optimal scene drawing sequence generated by the matching and extracting module of other internet vehicles and dynamic element models and the main vehicle drawing sequence generated by the self-generating module, perform sequence slice division on the received information, perform cross validation and optimization on redundant region drawing sequences, perform combined validation on the remaining drawing region sequences, generate the main vehicle optimal scene drawing sequence of the main vehicle at the current time by using an adaptive scene drawing sequence optimization function, and send the main vehicle optimal scene drawing sequence to the internet vehicles on the same planning path through a wireless network.
Preferably, the scene drawing and optimizing module under cooperative vehicle-road perception specifically determines the length of each section of the slice sequence of the generated optimal scene drawing sequence of the subject vehicle according to the optimal simulation step length of the drawing unit, each initial scene drawing sequence is determined according to the last sequence optimization result, the optimization index set consists of drawing time consumption, information redundancy, information reliability, environment coverage, environment fitting degree and scene drawing balance, and the index weight is dynamically adjusted according to the preference of the importance degree of the index designed under different scene complexities.
According to the technical scheme provided by the embodiment of the invention, the method can provide a simulation verification environment for the function test of the vehicle-road cooperative system, and has great significance for improving the simulation efficiency of the vehicle-road cooperative system, reducing the test cost and popularizing the technology.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is an implementation schematic diagram of a hybrid traffic simulation support environment rapid construction system under vehicle-road cooperation according to an embodiment of the present invention;
fig. 2 is a processing flow chart of a scene rendering sequence collaborative generation module under cooperative vehicle-road awareness according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or coupled. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
For the convenience of understanding the embodiments of the present invention, the following description will be further explained by taking several specific embodiments as examples in conjunction with the drawings, and the embodiments are not to be construed as limiting the embodiments of the present invention.
An implementation schematic diagram of a system for quickly constructing a hybrid traffic simulation support environment under vehicle-Road cooperation according to an embodiment of the present invention is shown in fig. 1, where a processing process of the system is jointly completed by an internet vehicle, an RSU (Road Side Unit), a detection device, a data center, and other objects, and the system includes: the system comprises a hybrid traffic subject model base building module, a dynamic element model matching and extracting module and a scene drawing and optimizing module under cooperative vehicle and road perception.
The mixed traffic subject model library construction module is used for constructing and storing the moving object model in the mixed traffic environment and providing the hierarchical index of the model. The moving object comprises vehicle bodies with different intelligent levels, and the moving object model is hierarchically classified, organized and managed; the module is disposed in a data center.
The matching and extracting module of the dynamic element model is used for receiving dynamic object information and scene information collected by the networked vehicles and the intelligent roadside, processing and analyzing the data of the dynamic object information, extracting the hierarchical structure characteristics of the dynamic object, drawing a dynamic object simulation model, matching a vehicle main body model with the highest similarity to the drawn dynamic object simulation model in the mixed traffic main body model library by using a characteristic association function, and generating an optimal scene drawing sequence according to the received scene information. And sending the vehicle body model obtained by matching, the relevant model characteristics and the optimal scene drawing sequence to the networked vehicle. The module is disposed in a data center.
And the scene drawing and optimizing module under the cooperative vehicle and road perception is used for generating a main vehicle optimal scene drawing sequence of the networked vehicle based on an adaptive scene drawing sequence optimizing function according to the received vehicle main model and the optimal scene drawing sequence, and sending the optimal scene drawing sequence to other networked vehicles around. And carrying out combined verification on the optimal scene drawing sequence and the subject vehicle drawing sequence sent by other surrounding networked vehicles. The module is arranged on an internet vehicle.
Specifically, the hybrid traffic body model library construction module is used for constructing and storing a moving object model in a hybrid traffic environment. The mixed traffic main body model library stores moving object models in a classified manner through a multimedia database technology, wherein the moving objects are traffic participants with multiple intelligent levels such as manual/internet/intelligent internet vehicles, and the mixed traffic main body model library comprises simple, microscopic and operable model elements obtained by decomposing each complex object and is matched with behavior characteristic logics of different moving objects, so that the representation problems of different intelligent levels, various forms and different configurations of vehicle main bodies in a mixed traffic scene are solved. The vehicle models are all simple models with rigid body characteristics and no textures, are combined and approximated by simple geometric shapes such as spheres, capsules, box-packed shapes, polygons and the like, and meanwhile, the hierarchical classification organization and management of simulation models are carried out on the mixed traffic main body model library.
The mixed traffic subject model library classifies, organizes and manages the intelligent level, model and application of subject vehicles, analyzes vehicle elements by an analytic hierarchy process, decomposes vehicles into a plurality of levels of model elements, and forms a hierarchical structure model index which is related to each other and has membership. Meanwhile, a common index table is also constructed to store vehicle models and other model combinations frequently used in the operation scene, so that the models in different traffic operation environments can be quickly called.
The matching and extracting module of the dynamic element model mainly aims at dynamic moving objects, obtains dynamic object information through vehicle-mounted and roadside environment sensing units (cameras, laser radars, radars and the like), and performs information processing and correlation matching on geometric parameters and motion state information of the dynamic objects. And acquiring more environmental information including over-the-horizon environmental information outside a self-perception area through intelligent road side equipment and other networked intelligent vehicles, organically segmenting and reshaping the environmental data by using a uniform format data structure, extracting typical hierarchical structure characteristics, and generating an optimal scene drawing sequence. And performing preliminary block data dimensionality reduction, segmentation processing and reconstruction on the dynamic object information according to the multidimensional characteristics of the vehicle road body and the vehicle hierarchical structure, extracting the hierarchical structure characteristics of the dynamic objects in each block, and drawing a dynamic object simulation model. And matching the moving object model with the highest similarity to the dynamic object simulation model in the mixed traffic main body model library by using the characteristic association function. The feature weights of the feature correlation function may be trained offline by feature data fitting and neural networks.
And the scene drawing and optimizing module under the cooperative vehicle and road perception is used for generating a scene drawing sequence under a mixed scene and optimizing the drawing of the scene drawing sequence. The processing flow chart of the scene rendering sequence collaborative generation module under the cooperative vehicle-road perception provided by the embodiment of the invention is shown in fig. 2. The method comprises the steps that a main vehicle receives an optimal scene drawing sequence generated by other internet vehicles and intelligent roadside under a good communication environment, after time synchronization and credibility judgment are carried out on the optimal scene drawing sequence and the main vehicle drawing sequence generated by the main vehicle, sequence slice division is carried out on received information, a redundant region drawing sequence is cross verified and optimized, a residual drawing region sequence is combined and verified, finally, the main vehicle optimal scene drawing sequence of the main vehicle at the current moment is generated, the main vehicle optimal scene drawing sequence is sent to the internet vehicles on other same planning paths through a wireless network, the updating speed of moving objects in the virtual traffic environment of the main vehicle is optimized, and the cooperativity, the accuracy, the comprehensiveness and the rapidity of the drawing sequence are achieved.
The optimal scene drawing sequence of the main vehicle is determined and generated by an adaptive scene drawing sequence optimization function, the length of each section of slice sequence is determined by the optimal simulation step length of a drawing unit, each initial scene drawing sequence is determined according to the last sequence optimization result, an optimization index set is composed of drawing time consumption, information redundancy, information reliability, environment coverage, environment fitting degree and scene drawing balance, and index weight is dynamically adjusted according to the preference of index importance degree designed under different scene complexity.
Under the cooperative sensing of the vehicle and the road, the scene drawing and optimizing module can perform target association and tracking on the detected new dynamic object in the scene drawing process, draw the dynamic object simulation model and store the dynamic object simulation model as a new node, and only needs to dynamically update the model position in the subsequent drawing process; for other static real objects, a road network, surrounding buildings and the like are constructed in advance in an off-line generation mode, when a scene is drawn, a road center line is determined based on a Cartesian coordinate system frame, the geometric shape of a road is decomposed based on a Frenet coordinate system frame, a road node topological connection model is established, and then the road is drawn in an incremental mode from the road center line to the nodes of two side lanes and the road boundary by using an interactive geometric shape mapping method; and performing three-dimensional redundant surface reduction on objects in the far-end traffic area and the non-target routing area.
Sequence optimization in the scene drawing and optimizing module under the cooperative perception of the vehicle and the road is mainly to construct an adaptive scene drawing sequence optimization function to optimize the sequence of environment drawing and dynamic object state updating, and to perform cooperative processing and combination of the vehicle and road drawing sequence under the support of the vehicle networking, so as to improve the accuracy and coverage rate of virtual traffic environment construction. And then, extracting a model according to the environment drawing sequence to draw a scene, wherein different drawing strategies are adopted for different objects in the drawing process. The dynamic object utilizes the behavior characteristic logic distributed by the model base to track the target, and only needs to update the three-dimensional graphic position after the initial drawing; and other static object models are generated in an off-line mode, when in drawing, the road utilizes the advantage of Frenet coordinate system that only transverse and longitudinal parameters are required to express the road structure, so that the calculation of curvature when the road is drawn is reduced, and the three-dimensional redundant surface reduction is carried out on other objects so as to simplify the drawing process of non-important models.
In summary, the embodiment of the present invention provides a system for quickly constructing a hybrid traffic simulation support environment under vehicle-road cooperation, so as to implement self-adaptive construction of a hybrid traffic simulation support environment under multi-intelligent traffic entity cooperation, solve the disadvantage that a traditional environment construction method cannot acquire a traffic operation state in real time from multiple directions, effectively improve the drawing efficiency, accuracy and coverage rate of the construction of the traffic simulation environment, reproduce a huge and complex real traffic scene, and have important significance for implementing preliminary performance evaluation and function verification of the vehicle-road cooperation system, improving simulation efficiency, reducing test cost and promoting technology.
Those of ordinary skill in the art will understand that: the figures are merely schematic representations of one embodiment, and the blocks or flow diagrams in the figures are not necessarily required to practice the present invention.
From the above description of the embodiments, it is clear to those skilled in the art that the present invention can be implemented by software plus necessary general hardware platform. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which may be stored in a storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments or some parts of the embodiments.
All the embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for apparatus or system embodiments, since they are substantially similar to method embodiments, they are described in relative terms, as long as they are described in partial descriptions of method embodiments. The above-described embodiments of the apparatus and system are merely illustrative, and the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (6)
1. A hybrid traffic simulation support environment rapid construction system under vehicle-road cooperation is characterized by comprising the following components: the system comprises a hybrid traffic subject model base construction module, a dynamic element model matching and extracting module and a scene drawing and optimizing module under cooperative vehicle and road perception;
the hybrid traffic subject model library construction module is used for constructing and storing a moving object model in a hybrid traffic environment and providing a model hierarchical index, wherein the moving object comprises vehicle subjects with different intelligent levels;
the matching and extracting module of the dynamic element model is used for receiving dynamic object information and scene information collected by the internet-connected vehicle and the intelligent roadside, drawing a dynamic object simulation model, matching a vehicle main body model with the highest similarity to the dynamic object simulation model in the mixed traffic main body model library, generating an optimal scene drawing sequence according to the received scene information, and sending the vehicle main body model and the optimal scene drawing sequence to the internet-connected vehicle;
and the scene drawing and optimizing module under the cooperative vehicle-road perception is used for generating a main vehicle optimal scene drawing sequence of the networked vehicle according to the received vehicle main model and the optimal scene drawing sequence and sending the main vehicle optimal scene drawing sequence to other surrounding networked vehicles.
2. The system of claim 1, wherein the hybrid traffic subject model library construction module and the dynamic element model matching and extracting module are arranged in a data center, and the scene drawing and optimizing module under the cooperative vehicle-road perception is arranged in an internet vehicle.
3. The system of claim 1, wherein the hybrid transportation subject model base building module is specifically configured to store moving object models by classification through a multimedia database technology, decompose each moving object into model primitives, and perform classification organization and management on intelligence level, model number and usage of a subject vehicle by matching with behavioral characteristic logic of different moving objects, analyze vehicle elements through a hierarchical analysis method, decompose vehicles into model primitives of multiple levels, form a hierarchical structure model index associated with each other and having a membership relationship, and build a moving object model index table.
4. The system according to claim 1, wherein the matching and extracting module of the dynamic element model is specifically configured to acquire environmental information through an intelligent roadside device and other networked intelligent vehicles, perform organic segmentation and remodeling on environmental data, extract typical hierarchical structure features, and generate an optimal scene drawing sequence; and obtaining dynamic object information through the vehicle-mounted and road-side environment sensing units, performing preliminary block data dimension reduction, segmentation processing and reconstruction on the dynamic object information, extracting the hierarchical structure characteristics of the dynamic objects in each block, drawing a dynamic object simulation model, and matching a moving object model with the highest similarity to the dynamic object simulation model in the mixed traffic main body model library by using a characteristic association function.
5. The system according to claim 1, wherein the scene drawing and optimizing module under the cooperative vehicle-road perception is specifically configured to generate a main vehicle drawing sequence according to a received vehicle main model, perform time synchronization and reliability discrimination on the received optimal scene drawing sequence generated by the matching and extraction module of other internet vehicles and the dynamic element model and the main vehicle drawing sequence generated by the optimal scene drawing sequence, perform sequence slice division on the received information, cross-verify and optimize the redundant region drawing sequence, perform combined verification on the remaining drawing region sequence, generate the main vehicle optimal scene drawing sequence of the main vehicle at the current time by using an adaptive scene drawing sequence optimization function, and send the main vehicle optimal scene drawing sequence to the internet vehicles on the same other planned paths through a wireless network.
6. The system according to claim 5, wherein the scene drawing and optimizing module under cooperative vehicle-road perception specifically determines the length of each section of a slice sequence of a generated optimal scene drawing sequence of the subject vehicle according to the optimal simulation step length of a drawing unit, each initial scene drawing sequence is determined according to the last sequence optimization result, the optimization index set is composed of drawing time consumption, information redundancy, information reliability, environmental coverage, environmental fitness and scene drawing balance, and the index weight is dynamically adjusted according to the preference of the importance degree of the index designed under different scene complexities.
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| CN115688484A (en) * | 2022-11-30 | 2023-02-03 | 西部科学城智能网联汽车创新中心(重庆)有限公司 | WebGL-based V2X simulation method and system |
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| CN115688484A (en) * | 2022-11-30 | 2023-02-03 | 西部科学城智能网联汽车创新中心(重庆)有限公司 | WebGL-based V2X simulation method and system |
| CN115688484B (en) * | 2022-11-30 | 2023-07-25 | 西部科学城智能网联汽车创新中心(重庆)有限公司 | V2X simulation method and system based on WebGL |
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