A C-V2X application scenario test method based on virtual distribution

Abstract

The present application relates to the technical field of Internet of Vehicles communication test, in particular to a C-V2X application scene test method based on virtual delivery, comprising: acquiring virtual traffic participant types, dynamic behavior trajectories, position information and signal lamp state time sequence input by a test configuration interface, completing space-time logic verification and consistency arrangement through an improved scene arrangement algorithm, and generating a virtual traffic scene description file containing complete space-time information. The file is parsed into a roadside unit broadcast message sequence conforming to the C-V2X protocol and is delivered to a real roadside unit, the roadside unit broadcasts virtual scene messages according to the time sequence to build a wireless virtual test environment, and a to-be-tested vehicle terminal is monitored and its response behavior data is captured. The scheme optimizes the space-time rationality of the scene, builds a test environment relying on real roadside hardware, and improves the authenticity and reliability of C-V2X scene test.

Description

Technical Field

[0001] This invention relates to the field of vehicle-to-everything (V2X) communication testing technology, and in particular to a C-V2X application scenario testing method based on virtual distribution. Background Technology

[0002] Current C-V2X application scenario testing primarily employs three methods: pure software simulation, physical road testing, and dedicated signal simulation equipment. Software simulation merely constructs a digital scenario within a computer and lacks a real wireless communication link. Physical road testing relies on real vehicles, pedestrians, and roadside facilities, resulting in high deployment and adjustment costs. Signal simulation equipment generates messages through protocol simulation and does not rely on real roadside unit hardware for operation. Existing scenario orchestration methods only involve simple input and combination of virtual traffic participants, trajectories, locations, and traffic light parameters, without conducting multi-element spatiotemporal correlation verification.

[0003] Existing testing methods cannot guarantee the consistency of spatiotemporal logic within the virtual scenario, leading to potential conflicts between dynamic behavior trajectories and traffic light timings, and poor consistency of scenario parameters. Simulated signals exhibit characteristic differences from the wireless signals broadcast by real roadside units, and the receiving environment of the vehicle-mounted terminal under test does not match actual road conditions. Scenario messages cannot be transmitted through real roadside hardware, resulting in a disconnect between the virtual testing environment and the real C-V2X communication link.

[0004] In complex traffic scenarios, spatiotemporal distortions of parameters can reduce test reliability, and wireless signals emitted by non-real roadside units can affect the accuracy of terminal response acquisition. Therefore, it is necessary to perform spatiotemporal logic verification and consistency orchestration on scenario elements, and to broadcast virtual scenario messages through real roadside unit devices to form a virtual test scenario that matches the communication environment of real vehicles. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing a C-V2X application scenario testing method based on virtual delivery.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a C-V2X application scenario testing method based on virtual delivery, comprising: The test scenario element parameters input by the user through the test configuration interface are obtained. The test scenario element parameters include virtual traffic participant type, dynamic behavior trajectory, location information and traffic light status sequence. An improved scene orchestration algorithm is used to perform spatiotemporal logic verification and consistency orchestration on the element parameters of the test scene, generating a virtual traffic scene description file containing complete spatiotemporal information; The virtual traffic scene description file is parsed into a roadside unit broadcast message sequence that conforms to the C-V2X communication protocol standard, and the broadcast message sequence is sent to the designated real roadside unit device; The real roadside unit device is controlled to continuously broadcast virtual scene messages to the outside world according to the timing and content of the broadcast message sequence, so as to construct a virtual test environment composed of wireless signals; Monitor the vehicle-mounted terminal device under test that is connected to the virtual test environment, and capture the response behavior data of the vehicle-mounted terminal device under test to the virtual scene messages.

[0007] As a further aspect of the present invention, the improved scene orchestration algorithm is used to perform spatiotemporal logic verification and consistency orchestration on the element parameters of the test scene, generating a virtual traffic scene description file containing complete spatiotemporal information, specifically as follows: Receive the test scenario element parameters and, based on the predefined traffic element data model, instantiate the test scenario element parameters into virtual traffic objects with unique identifiers; For each virtual traffic object, extract its behavioral trajectory and temporal constraints on state changes, and construct a global spatiotemporal conflict detection map based on the improved scene orchestration algorithm; In the global spatiotemporal conflict detection graph, virtual traffic objects are used as nodes, and any two virtual traffic objects that have overlapping spatial locations or contradictory behavioral logic at the same point in time are used as edges. Traverse the global spatiotemporal conflict detection graph, detect and mark all edges with conflicts, including spatial location conflicts, movement trajectory intersection conflicts, and conflicts between traffic light status and traffic flow direction; Based on the marked conflict results, the behavior trajectory or state sequence of the virtual traffic objects with conflicts are automatically adjusted. The automatic adjustment includes delay, path fine-tuning or state remapping, until there are no conflicting edges in the global spatiotemporal conflict detection graph. All the adjusted virtual traffic objects and their final confirmed behavior trajectories, spatial locations, and state sequences are integrated and encapsulated into a structured virtual traffic scene description file.

[0008] As a further aspect of the present invention, a global spatiotemporal conflict detection graph is constructed based on the improved scene orchestration algorithm, wherein the working principle of the improved scene orchestration algorithm is as follows: A four-dimensional spatiotemporal state vector is established for each virtual traffic object. The four-dimensional spatiotemporal state vector includes a three-dimensional geographic coordinate dimension and a time dimension. In a four-dimensional spatiotemporal continuum, for each virtual traffic object, the spatiotemporal volume it occupies during the duration of its behavior is calculated. The spatiotemporal volume is formed by scanning the shape envelope of the virtual traffic object along its motion trajectory in the time dimension. Calculate the intersection between the spatiotemporal volumes of any two virtual traffic objects. If the intersection is not empty, it is determined that there is a potential conflict between the two virtual traffic objects within the spatiotemporal intersection range. Connect two virtual traffic objects with potential conflicts in the global spatiotemporal conflict detection graph with an edge, and assign the edge the conflict time window and conflict spatial range attributes; A virtual clock progression mechanism is introduced to simulate scene progression with discrete time steps. Within each time step, the spatiotemporal volume of the virtual traffic objects is dynamically updated based on their real-time motion state, and the global spatiotemporal conflict detection map is updated in real time.

[0009] As a further aspect of the present invention, the virtual traffic scene description file is parsed into a roadside unit broadcast message sequence conforming to the C-V2X communication protocol standard, specifically as follows: Read the virtual traffic scene description file and split it into a series of discrete scene snapshots sorted by timestamp according to the timeline; For each discrete scene snapshot, the current state information of all virtual traffic objects contained therein is encoded according to the message format defined in the C-V2X communication protocol; The encoded discrete state messages are arranged in order of their corresponding timestamps, and necessary protocol headers, time synchronization information and message sequence numbers are inserted to generate the original broadcast message sequence. Based on the communication interface requirements and data throughput capabilities of the target roadside unit equipment, the original broadcast message sequence is encapsulated and grouped to form a final broadcast message sequence that can be sent.

[0010] As a further aspect of the present invention, the broadcast message sequence is sent to the designated real roadside unit device, specifically as follows: Establish a secure data transmission link with the designated actual roadside unit device; Calculate the planned sending time for each message based on the timestamps of the messages in the broadcast message sequence and the preset test start time; After the test is started, according to the planned sending time, the messages in the broadcast message sequence are sent to the actual roadside unit device in real time or at a preset multiplier through the data transmission link. Monitor the sending status buffer of the actual roadside unit device to ensure that messages are sent in a timely manner and record the actual message delivery log.

[0011] As a further aspect of the present invention, the real roadside unit device is controlled to continuously broadcast virtual scene messages according to the timing and content of the broadcast message sequence, specifically as follows: The actual roadside unit device receives the broadcast message sequence and stores it in its internal message sending queue; The actual roadside unit device, based on its own clock, sequentially retrieves messages from the message sending queue according to the timestamp information carried in the message and modulates them into radio frequency signals; The modulated radio frequency signal is broadcast through the antenna of the actual roadside unit device at a specified C-V2X communication channel and power. During the broadcast, the power, frequency, and modulation quality of the broadcast signal are monitored simultaneously to ensure that the broadcast content is consistent with the broadcast message sequence.

[0012] As a further aspect of the present invention, monitoring the vehicle-mounted terminal device under test connected to the virtual test environment specifically includes: Within the communication range of the actual roadside unit equipment, scan and identify all vehicle-mounted devices that send C-V2X access requests; From the in-vehicle devices that send access requests, pre-registered in-vehicle terminal devices to be tested are selected based on device identifiers; Establish a logical connection with the selected vehicle-mounted terminal devices to be tested, and monitor all C-V2X communication data of them in the virtual test environment.

[0013] As a further aspect of the present invention, capturing the response behavior data of the vehicle-mounted terminal device under test to the virtual scene message specifically includes: Record each frame of virtual scene message received by the vehicle-mounted terminal device under test and broadcast by the real roadside unit device, including message content and receiving timestamp; Capture all C-V2X messages sent by the vehicle-mounted terminal device under test after receiving the virtual scene message, including basic vehicle safety messages, event trigger messages, or application layer interaction messages; Record all internal state changes and early warning decision logs of the vehicle-mounted terminal device under test. The internal state changes include changes in risk assessment level and changes in driving advice. The received virtual scene messages, sent C-V2X messages, and internal state change and early warning decision logs are aligned and correlated according to the timeline to form a complete response behavior data stream.

[0014] As a further aspect of the present invention, the automatic adjustment of the behavior trajectory or state sequence of conflicting virtual traffic objects specifically includes: For detected spatial location conflicts, depending on the priority of the virtual traffic objects, apply an offset vector perpendicular to their original direction of movement to the object with lower priority, or insert a brief pause in their trajectory. For detected motion trajectory intersections and conflicts, calculate the conflict point and adjust the speed curve of at least one virtual traffic object so that the time of its passage through the conflict point is staggered. If a conflict is detected between the traffic light status and the traffic flow direction, the timing of the traffic light status switching will be adjusted to ensure that the traffic light status is "allow passage" when the right-of-way is granted to a specific traffic flow. After each adjustment, the spatiotemporal volume of the relevant virtual traffic objects is recalculated, and the global spatiotemporal conflict detection graph is updated. Conflict detection and adjustment are performed iteratively until all conflicts are eliminated.

[0015] As a further aspect of the present invention, in the four-dimensional spatiotemporal continuum, calculating the spatiotemporal volume occupied by each virtual traffic object during its behavior duration specifically involves: Obtain the 3D shape envelope dimensions of the virtual traffic object and its complete motion trajectory function during the duration of the behavior; In the time dimension, the duration of the behavior is sampled at discrete time points to obtain a series of sampled time points; At each sampling time point, the three-dimensional spatial position and orientation of the virtual traffic object are calculated based on the motion trajectory function, and the three-dimensional spatial region occupied by the virtual traffic object at the sampling time point is determined based on its three-dimensional shape envelope size. By performing spatial union and temporal continuity interpolation along the time axis on the three-dimensional spatial regions occupied by the virtual traffic objects at all sampling time points, a continuous four-dimensional spatiotemporal volume is formed.

[0016] Compared with the prior art, the advantages and positive effects of the present invention are as follows: The improved scene orchestration algorithm performs spatiotemporal logic verification on virtual traffic participant types, dynamic behavior trajectories, location information, and traffic light status timing. It completes consistent orchestration of multi-element parameters according to a unified spatiotemporal framework, forming a virtual traffic scene description file containing complete spatiotemporal information. Within the scene, various parameters are mutually adapted in spatial distribution and temporal progression; the positional changes of dynamic behavior trajectories maintain a continuous correspondence with temporal nodes; and traffic light status switching forms a synergistic relationship with the movement timing of traffic participants. There are no spatiotemporal contradictions or logical conflicts among the parameters. The scene description file can completely record standardized spatiotemporal correlation data, and various scene elements are integrated under unified constraints, maintaining the coherence and logical rationality of the scene data.

[0017] The virtual traffic scenario description file can be parsed into a sequence of roadside unit broadcast messages conforming to the C-V2X communication protocol standard. These message sequences can be directly sent to designated real roadside unit devices. The real roadside units continuously broadcast virtual scenario messages according to the timing and content set in the message sequence, forming a closed virtual test environment through the wireless signals of the real hardware. When the vehicle-mounted terminal under test (V2D) accesses the test environment, the protocol format and link characteristics of the received signals are consistent with the actual roadside unit broadcast signals, eliminating the characteristic differences between simulated signals and real hardware signals. The V2D operates under communication conditions close to actual working conditions, and its response behavior to virtual scenario messages can be stably captured. The data acquisition conditions for the response behavior are consistent with the actual working state of the V2D, the message transmission timing is stable during the test, and the authenticity and reliability of the terminal response data are maintained. Attached Figure Description

[0018] Figure 1 This is a state diagram of a C-V2X application scenario testing method based on virtual delivery as described in this invention; Figure 2 A flowchart for performing spatiotemporal logic verification and consistency orchestration for the improved scene orchestration algorithm; Figure 3 A flowchart illustrating the work done to improve the scene orchestration algorithm. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0020] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0021] See Figure 1 This invention provides a testing method for C-V2X application scenarios based on virtual delivery, the specific method including: At the start of the test, the system retrieves user-inputted test scenario element parameters from the test configuration interface. These parameters include virtual traffic participant types, dynamic behavior trajectories, location information, and traffic light status timing. After obtaining the parameters, the system uses an improved scenario orchestration algorithm to perform spatiotemporal logic verification and consistency orchestration on these test scenario element parameters, ultimately generating a structured file containing complete spatiotemporal information, namely the virtual traffic scenario description file. The system parses and converts this virtual traffic scenario description file into a sequence of data packets conforming to the C-V2X communication protocol standard, namely the roadside unit broadcast message sequence, and sends this sequence to a designated real roadside unit device via the communication link. After receiving the sent message sequence, the real roadside unit device continuously broadcasts wireless signals to the outside world through its radio frequency unit according to the time sequence and message content, thereby constructing a virtual test environment composed of standard C-V2X wireless signals. The system monitors and identifies the vehicle-mounted terminal devices under test connected to this virtual test environment, capturing all C-V2X communication data, status changes, and decision logs generated by the device after receiving virtual scenario messages, forming complete response behavior data.

[0022] In one embodiment of the invention, an example scenario involves an intersection with traffic light control, see reference. Figure 2 The test scenario element parameters specify the types of virtual traffic participants, including a car and a truck. The dynamic behavior trajectory defines the car traveling straight in a north-south direction and the truck turning left in an east-west direction. The location information defines their respective starting coordinates and lanes. The traffic light status sequence defines the on and off times of the east-west green light and the north-south red light. After the test scenario element parameters input into the test configuration interface are received, the system instantiates the test scenario element parameters into uniquely identified virtual traffic objects based on the predefined traffic element data model. After instantiation, the car is assigned the identifier Vehicle_Car_001, the truck is assigned the identifier Vehicle_Truck_002, and the traffic light is assigned the identifier TrafficLight_003. For virtual traffic objects of cars and trucks, the system extracts the temporal constraints of their behavior trajectories and state changes. The constraint for virtual traffic objects of cars is that they must pass through the conflict area within the time window when the traffic light TrafficLight_003 displays a green light for the north-south direction. The constraint for virtual traffic objects of trucks is that they must complete the left turn within the time window when the traffic light TrafficLight_003 displays a green light for the east-west direction. Based on the improved scene orchestration algorithm, the system constructs a global spatiotemporal conflict detection map.

[0023] In some embodiments, the global spatiotemporal conflict detection graph uses virtual traffic objects as nodes and edges representing the spatial overlap or behavioral logical contradictions of any two virtual traffic objects at the same time point. For a car virtual traffic object and a truck virtual traffic object, the system calculates the intersection point of their behavioral trajectories. The intersection point is located in the central area of ​​the intersection. The system checks whether the car virtual traffic object and the truck virtual traffic object simultaneously occupy the intersection point at the same time point. Data comparison shows that before the adjustment, the two were at the same time point. If the position coordinates of the cars coincide, the system determines that there is a conflict in the movement trajectories and establishes a connecting edge in the graph. For the virtual traffic objects of cars and traffic lights, the system checks whether the time when the car virtual traffic object plans to pass through the conflict area falls within the red light period of the north-south direction of traffic light TrafficLight_003. Data comparison shows that the car virtual traffic object plans to pass through the conflict area at the time when the car virtual traffic object plans to pass through the conflict area. It passed through in seconds, while the traffic light TrafficLight_003 was... Instant If the traffic light is red in the north-south direction, the system determines that there is a conflict between the traffic light status and the traffic flow direction and establishes another connecting edge in the graph. After traversing the global spatiotemporal conflict detection graph, the system detects and marks all conflicting edges. Conflicts include trajectories crossing between virtual car traffic objects and virtual truck traffic objects, and conflicts between traffic light status and traffic flow direction between virtual car traffic objects and virtual traffic light traffic objects.

[0024] Optionally, based on the conflict results, the system automatically adjusts the behavior trajectory or state sequence of conflicting virtual traffic objects. For the intersection and conflict of motion trajectories between car virtual traffic objects and truck virtual traffic objects, the system calculates the coordinates of the conflict point as ( , The system adjusts the speed curve of at least one virtual traffic object. The system selects to adjust the speed curve of the truck virtual traffic object. The original speed curve of the truck virtual traffic object is... The original planned time to reach the point of conflict was The planned time for the virtual car to pass through the conflict point is seconds. The system introduces a minimum safe time interval. The adjusted time for virtual truck traffic objects to pass through the conflict point Must meet The speed adjustment formula is: in: This represents the adjusted speed function of the truck virtual traffic object. This represents the total distance traveled by the truck virtual traffic object from its origin to the point of conflict. This represents the total travel time required for the virtual truck to travel at its original speed. This indicates the time delay calculated by the system to ensure time staggering; the data comparison shows the time before adjustment. Seconds, after adjustment seconds, greater than the set value The conflict was resolved within seconds. Regarding the conflict between the traffic light state and traffic flow direction between the car virtual traffic object and the traffic light TrafficLight_003, the system adjusted the state switching timing of the traffic light virtual traffic object. In the original timing, the north-south red light was... Instant The system will turn on the green light for north-south directions from 1 second to 2 seconds. Seconds ahead of time Seconds, to ensure that the virtual traffic object of the car is in When a car passes through a conflict zone, the traffic light status is "allowed to proceed." Data comparison shows that before the adjustment, the virtual traffic object of the car... Facing a red light, the virtual traffic object of the car is adjusted. The light turns green in seconds.

[0025] Understandably, after each adjustment, the system recalculates the spatiotemporal state of the relevant virtual traffic objects and updates the global spatiotemporal conflict detection graph, iteratively performing conflict detection and adjustment. After the first adjustment, the edge between the car and truck virtual traffic objects in the global spatiotemporal conflict detection graph is removed, but the edge between the car and traffic light virtual traffic objects is also removed due to timing adjustments, and the system detects that there are no longer conflicting edges in the graph. After all conflicts are eliminated, the system integrates all adjusted virtual traffic objects and their final confirmed behavioral trajectories, spatial locations, and state timing sequences, encapsulating them into a structured virtual traffic scene description file. The file contains the final trajectory point sequence of the car virtual traffic object, the adjusted speed curve and trajectory point sequence of the truck virtual traffic object, and the corrected state switching time point list of the traffic light virtual traffic object.

[0026] In some embodiments, for other types of conflicts, such as spatial location conflicts, the system processes them according to the priority of the virtual traffic objects. In another example scenario, a high-priority emergency vehicle virtual traffic object and a low-priority ordinary vehicle virtual traffic object have a spatial location conflict. The system applies an offset vector perpendicular to the original direction of movement to the low-priority ordinary vehicle virtual traffic object. The magnitude of the offset vector is determined by the outer envelope dimensions of the two virtual traffic objects and the minimum safe distance. Data comparison shows that the outer envelope dimensions of the two virtual traffic objects before the offset vector is applied are at the same time point. The overlap is eliminated when the trajectory of a virtual traffic object (e.g., a single second overlap) is shifted laterally after applying an offset vector. This automatic adjustment process continues until no conflicting edges remain in the global spatiotemporal conflict detection graph. The resulting virtual traffic scene description file is then used for subsequent parsing and distribution.

[0027] In one embodiment of the invention, an example scenario involves a multi-lane urban road, see reference. Figure 3 The test scenario element parameters define three virtual traffic objects: a car, a bus, and a pedestrian. The dynamic behavior trajectory of the car virtual traffic object is to travel along the leftmost lane at a constant speed. For a straight-ahead vehicle, the dynamic behavior trajectory of the virtual bus is a lane change from the right lane to the left lane. For a pedestrian, the dynamic behavior trajectory is crossing from one side of the road to the other. Location information defines their initial coordinates and lane affiliation. The system instantiates these parameters into uniquely identified virtual traffic objects based on a predefined traffic element data model. For each virtual traffic object, an improved scene orchestration algorithm establishes a four-dimensional spatiotemporal state vector, which includes three geographic coordinate dimensions and one time dimension. For a car virtual traffic object, its four-dimensional spatiotemporal state vector is represented as follows: in: , , It is over time The changing geographic coordinates, for both virtual bus and virtual pedestrian traffic objects, are represented by their four-dimensional spatiotemporal state vectors as follows: and .

[0028] In some embodiments, within a four-dimensional spatiotemporal continuum, the spatiotemporal volume occupied by each virtual traffic object is calculated during its behavior duration. The system obtains the three-dimensional shape envelope size of the car virtual traffic object and its position within the behavior duration. Complete motion trajectory function within In the time dimension, the duration of the behavior is represented by discrete points in time. Sampling is performed at intervals of 100°C. A series of sampling time points were obtained. At each sampling time point Above, based on the motion trajectory function Calculate the three-dimensional spatial position of the virtual traffic object of the car Based on its three-dimensional shape envelope dimensions, the virtual traffic object of the car at the sampling time point is determined. The three-dimensional space occupied by the top The three-dimensional shape envelope of the virtual car traffic object is the length. ,width ,high ,but It is a Centered on, with , , This represents the region of the axis-aligned bounding box. It also represents the 3D spatial region occupied by the virtual car traffic object at all sampling time points. By performing spatial union operations and temporal continuity linear interpolation along the time axis, a continuous four-dimensional spacetime volume is formed. spacetime The mathematical expression for it is its point set in four-dimensional space. The same calculation process is performed on the virtual traffic objects of buses and pedestrians to obtain their respective spatiotemporal volumes. and .

[0029] Optionally, the intersection of the spatiotemporal volumes of any two virtual traffic objects can be calculated. The system calculates the spatiotemporal volume of the car virtual traffic object. Spatiotemporal Entity of Virtual Transportation Objects for Buses Intersection between The calculation uses a discrete sampling point detection method. If there is at least one sampling time point... Make three-dimensional space region and If the intersection is not empty, then the spacetime volume intersection is determined. Not empty; data comparison is displayed at time points. Second, and The overlapping area on the two-dimensional plane projection reaches The system determines that a potential conflict exists between two virtual transportation objects (car and bus) within the spatiotemporal intersection area. The two potentially conflicting virtual transportation objects are connected by an edge in the global spatiotemporal conflict detection graph, and the edge is assigned conflict time window and conflict spatial range attributes. The system adds an edge between the nodes "car virtual transportation object" and "bus virtual transportation object" in the global spatiotemporal conflict detection graph, with the conflict time window attribute recorded as follows: Seconds, the conflict space range is the range of two-dimensional plane coordinates. .

[0030] Understandably, the improved scene orchestration algorithm introduces a virtual clock advancement mechanism, using discrete time steps. Simulated scenario progression, time step Set as Seconds. Within each time step, the spatiotemporal volume of the virtual traffic object is dynamically updated based on its real-time motion state. At each second, the virtual traffic objects of cars, buses, and pedestrians are recalculated based on the motion trajectory function. Three-dimensional spatial region of seconds , , And update the spacetime based on this. , , Boundary representation. Real-time updates of the global spatiotemporal conflict detection map; the system... Within a time step of seconds, it was detected and No overlap, but with Since there is overlap, the edge between the car virtual traffic object and the bus virtual traffic object is removed in the global spatiotemporal conflict detection graph, while the edge between the car virtual traffic object and the pedestrian virtual traffic object is added and the corresponding attributes are recorded.

[0031] In some embodiments, for the spatiotemporal volume calculation of a pedestrian virtual traffic object, its three-dimensional shape envelope dimension is length. ,width ,high The duration of the behavior is The three-dimensional spatial area occupied by virtual traffic objects of pedestrians at all sampling time points Spatial union and temporal continuity interpolation are performed along the time axis to form a spacetime volume. Calculate the intersection of spacetime volumes. The data comparison is displayed at the sampling time points. Second, and If there is overlap and the intersection is not empty, the system determines that a potential conflict exists and marks the corresponding edge in the global spatiotemporal conflict detection graph. This can be understood as the virtual clock advancement mechanism continuously running, at each time step... The system dynamically calculates and updates the spatiotemporal volume and conflict detection map until it covers the entire duration of the behavior of all virtual traffic objects, providing input for subsequent conflict resolution and automatic adjustment.

[0032] In one embodiment of the invention, an example scenario involves a roundabout test scenario defined by a virtual traffic scenario description file, the virtual traffic scenario description file containing a time range from milliseconds to The complete spatiotemporal information in milliseconds describes the state changes of multiple vehicles with different trajectories and a set of traffic lights. The system reads the virtual traffic scene description file and breaks it down into a series of discrete scene snapshots ordered by timestamps, according to the timeline defined in the file. The time interval between the discrete scene snapshots is... milliseconds, therefore a total of milliseconds were generated. Each discrete scene snapshot records the complete state of all virtual traffic objects at that moment.

[0033] In some embodiments, for each discrete scene snapshot, the system encodes the current state information of all virtual traffic objects contained therein according to the message format defined in the C-V2X communication protocol, for timestamps... A millisecond snapshot of a discrete scene, containing a car identified as Veh_A and a set of traffic lights identified as TL_Intersec_1, is encoded using the ASN.1PER compression rule. The encoded discrete state messages are arranged according to their corresponding timestamps, and necessary protocol headers, time synchronization information, and message sequence numbers are inserted to generate the original broadcast message sequence. The original broadcast message sequence is a strictly time-incrementing list of messages, as shown in Table 1. Table 1: Original Broadcast Message Sequence Fragments Optionally, based on the communication interface requirements and data throughput capacity of the target roadside unit device, the original broadcast message sequence is encapsulated and grouped to form a final broadcast message sequence that can be sent. The target roadside unit device receives the data through an Ethernet interface, and its maximum transmission unit per packet is [missing information]. Bytes are the number of bytes that the system uses to encapsulate the original broadcast message sequence into groups. Determined by the formula: in: For the fixed length of the packet protocol header, The maximum possible length of a single message in the original broadcast message sequence is determined by calculation. The system will each A sequence of consecutive timestamped messages is encapsulated within a single data packet. After the broadcast message sequence is formed, the system executes a distribution operation, establishing a secure data transmission link based on the TCP protocol between the system and the designated real roadside unit device, and performing two-way authentication.

[0034] Understandably, the system calculates the planned transmission time for each message based on the timestamp carried by each message in the broadcast message sequence and the preset test start time. The preset test start time is 2024-05-20 10:00:00.000 real-world time. For a message with sequence number 150 and a timestamp of 15000 milliseconds, its planned transmission time is 2024-05-20 10:00:15.000 real-world time. After the test starts, the system, based on the calculated planned transmission time, sends the messages in the broadcast message sequence to the actual roadside unit devices in real time through the established data transmission link. The error between the message transmission time and the planned transmission time is controlled within ±1 millisecond. During the transmission process, the system monitors the transmission status buffer of the actual roadside unit devices to ensure that messages are sent in a timely manner and records the actual message transmission log. The actual message transmission log records the sequence number, planned transmission time, actual transmission time, and acknowledgment status of each message.

[0035] In some embodiments, the message encapsulation and grouping strategy can be adjusted. In another example, where the data throughput of the target real roadside unit device is low, the system adopts a time window grouping strategy, dividing the message into fixed time windows. All messages within a millisecond are encapsulated into a single data packet for delivery. Understandably, the recorded message delivery logs are used for subsequent analysis of message delivery timeliness and integrity, providing a basis for evaluating the timing fidelity of the virtual test environment.

[0036] In practical implementation, the "ASN.1PER compression rule" used in the encoding process is a key technology unique to the message sequence generation stage of this project. Its implementation relies on a strict syntax and encoding rule system. Abstract Syntax Notation I defines the structure, type and constraints of message data, while the compression encoding rule specifies how to efficiently and unambiguously convert data structures that conform to the description of Abstract Syntax Notation I into compact binary bit streams. The project first strictly defines the syntax structure of all messages to be encoded, such as basic vehicle safety messages and traffic light phase and timing messages, using the Abstract Syntax Notation I language, based on the national standard document of the C-V2X communication protocol. These definitions are stored in module files with the extension ".asn". The module files specify in detail the data elements contained in each message, the data type of the elements, the order of the elements, and the optional constraints. For example, the "BasicSafetyMessage" module defines fields such as "msgID", "secMark", and "pos", and sets the value range of the "latitude" subfield in the "pos" field. Subsequently, the system calls the integrated Abstract Syntax Notation compilation and encoding library at runtime. The encoding library reads these predefined Abstract Syntax Notation module files and builds the corresponding data structure templates in memory. When a discrete scene snapshot needs to be encoded, the system fills the state information of the virtual traffic objects in the snapshot into the corresponding data structure instance in memory according to the one-to-one correspondence of fields. The filling process will perform real-time verification of type and value range. Next, the compression coding rule encoder is activated. The encoder does not simply convert the value of each data field directly into binary. Instead, it encodes the data according to a complex set of compression rules. The compression coding rule encoder analyzes the actual value of the data field. For integer data, the compression coding rule encoder may use an "unaligned" method, encoding only the minimum number of bits that can represent the value. For integer fields with a known range, the compression coding rule encoder will perform range offset to further reduce bit overhead. For optional fields, the compression coding rule encoder uses a single flag bit to indicate its presence or absence. For sequence structures, the compression coding rule encoder usually does not directly encode the length field, but relies on the end marker of the context. The entire encoding process is automatically completed by the encoding library. Finally, it outputs a binary string of variable length, but whose syntax and semantics strictly conform to the standard. This binary string is the message payload that can be directly used for wireless transmission. The uniqueness of this project lies in the seamless integration of this standardized encoding process with the virtualized scene snapshot data source, realizing a fully automatic conversion from virtual parameters to standard protocol message bit streams.

[0037] In practical implementation, when the data throughput capacity of the target roadside unit equipment is limited, the system adopts a unique message encapsulation method called "time window grouping strategy." Its implementation process differs significantly from the fixed message quantity grouping strategy. The core of the time window grouping strategy lies in aggregating messages based on time, rather than message quantity. The system first sets a fixed time window length. Time window length The value needs to be determined comprehensively based on the maximum throughput of the actual roadside unit device, network link latency, and message density of the test scenario. For example, on devices with low data throughput, the time window length... It may be set to 50 milliseconds to reduce the packet sending frequency. During the preparation phase, the system iterates through the original broadcast message sequence, allocates each message to a specific time window according to its planned sending timestamp, and the time window is divided starting from the test start time, with the first time window covering... The time range, the second window covers Similarly, the system creates a list of buffers corresponding to time windows. During the allocation process, the system reads a message from the original broadcast message sequence, calculates the index of the time window to which its planned transmission time belongs, and then stores the complete content of the message (including its protocol header, timestamp, sequence number, and encoded payload) into the buffer of the corresponding window. The storage order of all messages within the same time window is consistent with their original timestamp order. When the deadline of a certain time window arrives, or when the system is ready to send a data packet to the actual roadside unit device, the encapsulation process begins. The system extracts all messages in the buffer of that time window and generates a new packet header for this data packet. The packet header contains metadata such as the start time of the time window and the number of messages contained in the window. Subsequently, the system concatenates all messages in the buffer in order and adds this new packet header to the beginning to form a complete data packet. This data packet is sent to the actual roadside unit device as a whole through a secure link. After receiving the data packet, the actual roadside unit device first parses the packet header to determine that it is a time window packet, then unpacks it to extract all the independent messages in the window, and then inserts them precisely into the corresponding position of the message sending queue inside the device according to the timestamp carried by each message. The advantage of this strategy is that it can smooth traffic bursts at the network transport layer, integrate a large number of messages generated in a short period of time into a few data packets for sending, effectively reducing the requirements on the real-time processing capability and instantaneous bandwidth of the network interface of the actual roadside unit device receiver, and ensuring the overall reliability of message delivery in a resource-constrained environment.

[0038] In one embodiment of the present invention, an example scenario involves a test at an urban intersection, where a real roadside unit device receives a sequence of broadcast messages, the sequence of broadcast messages containing a time span. Within milliseconds The message types include basic vehicle safety messages and traffic light phase and timing messages. The actual roadside unit (Roadside Unit) stores the received broadcast message sequence in its internal message sending queue, which uses a ring buffer structure with timestamp priority. Based on its own clock, the actual Roadside Unit retrieves messages sequentially from the message sending queue according to the timestamp information carried in the messages and modulates them into radio frequency signals. The local clock of the actual Roadside Unit is precisely synchronized with the test system via the IEEE 1588v2 protocol, with a synchronization accuracy error of less than [value missing]. Microseconds.

[0039] In some embodiments, the process of retrieving a message from the message sending queue and modulating it into a radio frequency signal involves channel coding of the message's binary payload using an LDPC coding scheme. After coding, digital modulation is performed using quadrature phase shift keying (QPSK) to generate a center frequency of [missing information]. The baseband signal. The modulated radio frequency signal is broadcast via the antenna of the actual roadside unit equipment on a specified C-V2X communication channel and at a specified power. The specified communication channel is CH188, corresponding to the center frequency. The specified transmission power is During the broadcast, the power, frequency, and modulation quality of the broadcast signal are monitored synchronously to ensure that the broadcast content is consistent with the broadcast message sequence. This monitoring function is performed by an RF sampling and feedback module integrated within the actual roadside unit equipment. The monitored data includes the average power of the RF signal within each time slot. Center frequency offset And the magnitude of the error vector.

[0040] Optionally, the specific parameters of signal monitoring and their association with the broadcast message sequence are recorded and compared through a processing status table. See Table 2 for the recorded content. Table 2: Correlation Table between Message Sending and Radio Frequency Monitoring During broadcasting, modulation quality is assessed by calculating the error vector magnitude. The demodulated signal is compared with the reference signal by the feedback module, and the calculation formula is as follows: in: Indicates the magnitude of the error vector. Indicates the number of sampling points. and Indicates the first Measured in-phase and quadrature components at each sampling point and Indicates the first Ideal in-phase and quadrature components of each sampling point This represents the imaginary unit. A data comparison shows that all messages recorded in Table 1... The values ​​are all less than the requirements of the protocol. The threshold indicates that the modulation quality meets the requirements.

[0041] It is understandable that monitoring the transmission power ensures the consistency of signal strength, and the slight deviation between the measured center frequency and the nominal frequency is acceptable. All within the allowed frequency tolerance of the equipment Within. In some embodiments, when the average power of the radio frequency signal of a message is detected... With set power The deviation exceeds At this time, the system will record a power anomaly event, but the broadcasting process will not be interrupted. It can be understood that by synchronously monitoring and recording the power, frequency, and modulation quality parameters of the radio frequency signal, and associating them with the messages in the original broadcast message sequence, it is possible to confirm that the content of the wireless signal broadcast by the actual roadside unit device is consistent with the content defined in the broadcast message sequence at the physical layer.

[0042] In one embodiment of the present invention, an example scenario involves a virtual test environment of an intersection being constructed by a real roadside unit device. The real roadside unit device continuously broadcasts virtual scenario messages on a designated communication channel, and its signal coverage area is a radius of [radius] centered on the roadside unit device. The circular area. Within the communication range of the actual roadside unit device, the system scans the wireless channel using a monitoring probe. The scanning probe listens for all access request messages sent on the predefined C-V2X channel and identifies all on-board devices that send C-V2X access requests. In one scan cycle, the monitoring probe captures three different device identifiers: OBU_ID_Alpha, OBU_ID_Beta, and OBU_ID_Gamma, corresponding to three vehicles that have entered the communication range.

[0043] In some embodiments, from the in-vehicle devices that send access requests, the system filters out pre-registered in-vehicle terminal devices to be tested based on device identifiers. The system maintains a list of registered in-vehicle terminal device identifiers to be tested, which includes OBU_ID_Alpha and OBU_ID_Gamma, but not OBU_ID_Beta. The system compares the scanned identifiers OBU_ID_Alpha, OBU_ID_Beta, and OBU_ID_Gamma with the registration list. If the comparison result shows that OBU_ID_Alpha and OBU_ID_Gamma exist in the list, but OBU_ID_Beta does not, the system identifies OBU_ID_Alpha and OBU_ID_Gamma as in-vehicle terminal devices to be tested, and marks OBU_ID_Beta as an environmental interference device and filters it out. The system establishes a logical connection with the selected vehicle-mounted terminal devices under test and listens to all their C-V2X communication data in the virtual test environment. The system establishes a logical link by sending specific connection management messages to OBU_ID_Alpha and OBU_ID_Gamma, and then begins to listen to and record all wireless signals originating from these two device identifiers.

[0044] Optionally, the system captures the response behavior data of the vehicle-mounted terminal device under test (V2D) to virtual scene messages. The system records each frame of virtual scene messages broadcast by the real roadside unit (Roadside Unit) received by the V2D V2D terminal device. The recorded information includes the message content and the receiving timestamp. For the V2D V2D terminal device OBU_ID_Alpha, its receiving log records a SPAT message with a timestamp of T_r1=2024-01-1514:30:05.123, the message content of which indicates the traffic light status is red. The system also captures all C-V2X messages sent by the V2D V2D terminal device after receiving the virtual scene message, including basic vehicle safety messages, event-triggered messages, or application-layer interaction messages. After OBU_ID_Alpha receives the aforementioned SPAT message, the system captures that it sent a basic vehicle safety message with a timestamp of T_s1=2024-01-1514:30:05.156, the message containing vehicle speed, position, and emergency braking status flags.

[0045] It is understandable that the system simultaneously records all internal state changes and warning decision logs of the under-test vehicle terminal device. Internal state changes include changes in risk assessment level and driving advice. For the under-test vehicle terminal device OBU_ID_Alpha, its internal risk assessment module outputs a log entry indicating a change in risk assessment level after time T_r1, changing the level from "no risk" to "forward collision warning," and the driving advice from "maintain current state" to "suggest deceleration." The calculation of the risk assessment level L_r may involve parsing the received message; an exemplary quantitative assessment formula is as follows: in: This represents the calculated risk assessment level value. and These are preset weighting coefficients. This represents the relative speed parsed from the virtual scene message. It is a risk function in relation to relative velocity. This indicates the distance between the vehicle and the target object, as parsed from the virtual scene message. It is a preset distance threshold. It is a risk function related to distance, and a risk level value. Exceeding the threshold The system triggers state changes. Received virtual scenario messages, sent C-V2X messages, and internal state change and early warning decision logs are aligned and correlated along a timeline to form a complete response behavior data stream. The system merges the SPAT message received by OBU_ID_Alpha at time T_r1, the BSM message sent at time T_s1, and the risk assessment level change logs recorded between T_r1 and T_s1, using their respective timestamps as a basis, into the same timeline data stream.

[0046] Optionally, in another example, after receiving a virtual scenario message containing a "construction ahead" event identifier, the OBU_ID_Gamma, the vehicle-mounted terminal device under test, sends a specific application-layer interaction message, namely a "workshop collaboration pass request" message. Simultaneously, its internal state change log records a change in "driving mode suggestion" from "autonomous driving" to "request for manual intervention." These data are captured and correlated. It can be understood that the resulting response behavior data stream is a multi-dimensional data sequence with strictly increasing timestamps, containing input stimuli, communication outputs, and internal state changes, used for subsequent analysis of the vehicle-mounted terminal device's functionality and performance.

[0047] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A testing method for C-V2X application scenarios based on virtual delivery, characterized in that, Includes the following steps: The test scenario element parameters input by the user through the test configuration interface are obtained. The test scenario element parameters include virtual traffic participant type, dynamic behavior trajectory, location information and traffic light status sequence. An improved scene orchestration algorithm is used to perform spatiotemporal logic verification and consistency orchestration on the element parameters of the test scene, generating a virtual traffic scene description file containing complete spatiotemporal information; The virtual traffic scene description file is parsed into a roadside unit broadcast message sequence that conforms to the C-V2X communication protocol standard, and the broadcast message sequence is sent to the designated real roadside unit device; The real roadside unit device is controlled to continuously broadcast virtual scene messages to the outside world according to the timing and content of the broadcast message sequence, so as to construct a virtual test environment composed of wireless signals; Monitor the vehicle-mounted terminal device under test that is connected to the virtual test environment, and capture the response behavior data of the vehicle-mounted terminal device under test to the virtual scene messages.

2. The C-V2X application scenario testing method based on virtual delivery according to claim 1, characterized in that, The improved scene orchestration algorithm is used to perform spatiotemporal logic verification and consistency orchestration on the element parameters of the test scene, generating a virtual traffic scene description file containing complete spatiotemporal information, specifically: Receive the test scenario element parameters and, based on the predefined traffic element data model, instantiate the test scenario element parameters into virtual traffic objects with unique identifiers; For each virtual traffic object, extract its behavioral trajectory and temporal constraints on state changes, and construct a global spatiotemporal conflict detection map based on the improved scene orchestration algorithm; In the global spatiotemporal conflict detection graph, virtual traffic objects are used as nodes, and any two virtual traffic objects that have overlapping spatial locations or contradictory behavioral logic at the same point in time are used as edges. Traverse the global spatiotemporal conflict detection graph, detect and mark all edges with conflicts, including spatial location conflicts, movement trajectory intersection conflicts, and conflicts between traffic light status and traffic flow direction; Based on the marked conflict results, the behavior trajectory or state sequence of the virtual traffic objects with conflicts are automatically adjusted. The automatic adjustment includes delay, path fine-tuning or state remapping, until there are no conflicting edges in the global spatiotemporal conflict detection graph. All the adjusted virtual traffic objects and their final confirmed behavior trajectories, spatial locations, and state sequences are integrated and encapsulated into a structured virtual traffic scene description file.

3. The C-V2X application scenario testing method based on virtual delivery according to claim 2, characterized in that, The improved scene orchestration algorithm constructs a global spatiotemporal conflict detection graph. The working principle of the improved scene orchestration algorithm is as follows: A four-dimensional spatiotemporal state vector is established for each virtual traffic object. The four-dimensional spatiotemporal state vector includes a three-dimensional geographic coordinate dimension and a time dimension. In a four-dimensional spatiotemporal continuum, for each virtual traffic object, the spatiotemporal volume it occupies during the duration of its behavior is calculated. The spatiotemporal volume is formed by scanning the shape envelope of the virtual traffic object along its motion trajectory in the time dimension. Calculate the intersection between the spatiotemporal volumes of any two virtual traffic objects. If the intersection is not empty, it is determined that there is a potential conflict between the two virtual traffic objects within the spatiotemporal intersection range. Two virtual traffic objects with potential conflicts are connected by an edge in the global spatiotemporal conflict detection graph, and the edge is assigned conflict time window and conflict spatial range attributes. A virtual clock progression mechanism is introduced to simulate scene progression with discrete time steps. Within each time step, the spatiotemporal volume of the virtual traffic objects is dynamically updated based on their real-time motion state, and the global spatiotemporal conflict detection map is updated in real time.

4. The C-V2X application scenario testing method based on virtual delivery according to claim 1, characterized in that, The virtual traffic scene description file is parsed into a roadside unit broadcast message sequence conforming to the C-V2X communication protocol standard, specifically as follows: Read the virtual traffic scene description file and split it into a series of discrete scene snapshots sorted by timestamp according to the timeline; For each discrete scene snapshot, the current state information of all virtual traffic objects contained therein is encoded according to the message format defined in the C-V2X communication protocol; The encoded discrete state messages are arranged in order of their corresponding timestamps, and necessary protocol headers, time synchronization information and message sequence numbers are inserted to generate the original broadcast message sequence. Based on the communication interface requirements and data throughput capabilities of the target roadside unit equipment, the original broadcast message sequence is encapsulated and grouped to form a final broadcast message sequence that can be sent.

5. A testing method for C-V2X application scenarios based on virtual delivery according to claim 4, characterized in that, The broadcast message sequence is sent to the designated real roadside unit device, specifically as follows: Establish a secure data transmission link with the designated actual roadside unit device; Calculate the planned sending time for each message based on the timestamps of the messages in the broadcast message sequence and the preset test start time; After the test is started, according to the planned sending time, the messages in the broadcast message sequence are sent to the actual roadside unit device in real time or at a preset multiplier through the data transmission link. Monitor the sending status buffer of the actual roadside unit device to ensure that messages are sent in a timely manner and record the actual message delivery log.

6. The C-V2X application scenario testing method based on virtual delivery according to claim 1, characterized in that, The real roadside unit device is controlled to continuously broadcast virtual scene messages according to the timing and content of the broadcast message sequence, specifically as follows: The actual roadside unit device receives the broadcast message sequence and stores it in its internal message sending queue; The actual roadside unit device, based on its own clock, sequentially retrieves messages from the message sending queue according to the timestamp information carried in the message and modulates them into radio frequency signals; The modulated radio frequency signal is broadcast through the antenna of the actual roadside unit device at a specified C-V2X communication channel and power. During the broadcast, the power, frequency, and modulation quality of the broadcast signal are monitored simultaneously to ensure that the broadcast content is consistent with the broadcast message sequence.

7. A testing method for C-V2X application scenarios based on virtual delivery according to claim 1, characterized in that, Monitoring the vehicle-mounted terminal device under test connected to the virtual test environment specifically includes: Within the communication range of the actual roadside unit equipment, scan and identify all vehicle-mounted devices that send C-V2X access requests; From the in-vehicle devices that send access requests, pre-registered in-vehicle terminal devices to be tested are selected based on device identifiers; Establish a logical connection with the selected vehicle-mounted terminal devices to be tested, and monitor all C-V2X communication data of them in the virtual test environment.

8. A testing method for C-V2X application scenarios based on virtual delivery according to claim 7, characterized in that, Capturing the response behavior data of the vehicle-mounted terminal device under test to the virtual scene messages, specifically: Record each frame of virtual scene message received by the vehicle-mounted terminal device under test and broadcast by the real roadside unit device, including message content and receiving timestamp; Capture all C-V2X messages sent by the vehicle-mounted terminal device under test after receiving the virtual scene message, including basic vehicle safety messages, event trigger messages, or application layer interaction messages; Record all internal state changes and early warning decision logs of the vehicle-mounted terminal device under test. The internal state changes include changes in risk assessment level and changes in driving advice. The received virtual scene messages, sent C-V2X messages, and internal state change and early warning decision logs are aligned and correlated according to the timeline to form a complete response behavior data stream.

9. A testing method for C-V2X application scenarios based on virtual distribution according to claim 2, characterized in that, The automatic adjustment of the behavior trajectory or state sequence of conflicting virtual traffic objects specifically includes: For detected spatial location conflicts, depending on the priority of the virtual traffic objects, apply an offset vector perpendicular to their original direction of movement to the object with lower priority, or insert a brief pause in their trajectory. For detected motion trajectory intersections and conflicts, calculate the conflict point and adjust the speed curve of at least one virtual traffic object so that the time of its passage through the conflict point is staggered. If a conflict is detected between the traffic light status and the traffic flow direction, the timing of the traffic light status switching will be adjusted to ensure that the traffic light status is "allow passage" when the right-of-way is granted to a specific traffic flow. After each adjustment, the spatiotemporal volume of the relevant virtual traffic objects is recalculated, and the global spatiotemporal conflict detection graph is updated. Conflict detection and adjustment are performed iteratively until all conflicts are eliminated.

10. A C-V2X application scenario testing method based on virtual delivery according to claim 3, characterized in that, In the four-dimensional spatiotemporal continuum, the spatiotemporal volume occupied by each virtual traffic object during its behavior duration is calculated as follows: Obtain the 3D shape envelope dimensions of the virtual traffic object and its complete motion trajectory function during the duration of the behavior; In the time dimension, the duration of the behavior is sampled at discrete time points to obtain a series of sampled time points; At each sampling time point, the three-dimensional spatial position and orientation of the virtual traffic object are calculated based on the motion trajectory function, and the three-dimensional spatial region occupied by the virtual traffic object at the sampling time point is determined based on its three-dimensional shape envelope size. By performing spatial union and temporal continuity interpolation along the time axis on the three-dimensional spatial regions occupied by the virtual traffic objects at all sampling time points, a continuous four-dimensional spatiotemporal volume is formed.

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