Multi-vehicle automatic driving simulation system and method supporting DORA middleware

Abstract

The invention relates to a multi-vehicle automatic driving simulation system and method supporting DORA middleware, and belongs to the technical field of automatic driving. The system comprises a simulation platform and a domain controller group. The simulation platform comprises a multi-vehicle Dora-bridge, traffic scene simulation software and vehicle dynamics simulation software, the multi-vehicle Dora-bridge receives multi-vehicle state data, sensor data and vehicle cooperative control information generated by the traffic scene simulation software, and the multi-vehicle Dora-bridge publishes the multi-vehicle state data, the sensor data and the vehicle cooperative control information in the form of a DORA topic for each domain controller to subscribe; meanwhile, control instructions issued by the domain controllers in the form of DORA topics are received and issued to the vehicle dynamics simulation software. The domain controller group comprises a plurality of domain controllers, each domain controller corresponds to one automatic driving vehicle, and software of the domain controller group consists of a plurality of DORA function nodes to realize an automatic driving function. According to the invention, an effective solution is provided for simulation of the multi-vehicle automatic driving system based on the DORA middleware, the development efficiency is improved, and the development cost is reduced.

Description

Technical Field

[0001] This invention belongs to the field of autonomous driving technology and relates to a multi-vehicle autonomous driving simulation system and method that supports DORA middleware. Background Technology

[0002] System simulation is an indispensable core technology in the research and development of autonomous driving for intelligent vehicles. By constructing highly realistic virtual environments, it provides repeatable and controllable test scenarios for autonomous driving algorithms, effectively solving the pain points of long cycles, high costs, and high risks associated with real-vehicle road testing. In the virtual environment, researchers can flexibly configure key parameters such as traffic participant density, weather and lighting conditions, and road topology to achieve closed-loop verification of the entire chain of perception, decision-making, and control of the autonomous driving system. Compared to traditional real-vehicle testing, simulation technology can improve verification efficiency by several orders of magnitude while minimizing hardware losses and safety risks, making it a key infrastructure driving the rapid iteration of autonomous driving technology.

[0003] As a high-performance middleware, DORA (Dataflow-Oriented Robotics Architecture) demonstrates significant advantages in autonomous driving system development thanks to its unique dataflow-driven architecture. This architecture decouples the strong relationships between modules such as sensor data processing, decision planning, and control execution, constructing a modular and scalable system framework, making it particularly suitable for complex scenarios such as multi-sensor fusion and heterogeneous computing. Its dynamic dataflow scheduling mechanism effectively coordinates heterogeneous computing resources such as CPUs, GPUs, and AI accelerators, improving system throughput while ensuring real-time performance, providing strong underlying support for the development of advanced autonomous driving systems.

[0004] However, existing autonomous driving simulation solutions generally suffer from two major technical bottlenecks: First, most simulation platforms adopt a monolithic architecture design, making it difficult to support large-scale deployment in multi-vehicle collaborative simulation scenarios; second, the lack of deep adaptation to the DORA middleware leads to performance losses in key aspects such as data flow scheduling and computing resource allocation. Especially in multi-vehicle interaction scenarios, existing solutions often exhibit timing errors and computing resource contention due to their inability to accurately simulate the data flow transmission characteristics under the DORA architecture, severely restricting the development efficiency and verification reliability of DORA-based autonomous driving systems. Therefore, developing a dedicated multi-vehicle collaborative simulation system and supporting verification methods that support the DORA middleware has become an urgent need to overcome current autonomous driving R&D bottlenecks and accelerate the deployment of advanced autonomous driving technologies.

[0005] Currently, in the existing technology, the Chinese patent application "Middleware-based Network Communication Autonomous Driving Simulation Test System and Test Method" discloses a test system that includes a simulator and middleware, which aims to solve the problem of image quality degradation after ISP processing in autonomous driving closed-loop HiL testing. However, this patent does not support autonomous driving systems based on DORA middleware, nor does it support multi-vehicle simulation testing.

[0006] Chinese patent application “Middleware Adaptation Method, System and Vehicle for Heterogeneous Autonomous Driving Systems” discloses a middleware adaptation technology applicable to heterogeneous autonomous driving systems, aiming to solve the problems of long development cycle and poor compatibility of different middleware adaptation in heterogeneous systems. However, this patent does not support autonomous driving systems based on DORA middleware, nor does it support multi-vehicle simulation testing. Summary of the Invention

[0007] In view of this, the purpose of this invention is to provide a multi-vehicle autonomous driving simulation system and method that supports DORA middleware. By connecting traffic scene simulation software, vehicle dynamics simulation software and autonomous driving algorithms based on DORA middleware on the domain controller group through multi-vehicle Dora-bridge, it provides an effective solution for DORA middleware-based multi-vehicle autonomous driving system simulation, improves development efficiency and reduces development costs.

[0008] To achieve the above objectives, the present invention provides the following technical solution: A multi-vehicle autonomous driving simulation system supporting DORA middleware comprises two parts: a simulation platform and a domain controller group, wherein: The simulation platform comprises three parts: a multi-vehicle Dora-bridge, traffic scenario simulation software, and vehicle dynamics simulation software. The multi-vehicle Dora-bridge serves as the interaction layer between the traffic scenario simulation software, the vehicle dynamics simulation software, and the domain controller software. It receives multi-vehicle state data, sensor data, and vehicle cooperative control messages generated by the traffic scenario simulation software and publishes them as DORA topics for subscription by each domain controller. Simultaneously, it receives control commands published by each domain controller using DORA topics and distributes them to the vehicle dynamics simulation software.

[0009] Domain Controller Group: This group comprises multiple domain controllers, each corresponding to an autonomous vehicle. DORA-based vehicle autonomous driving software runs on each domain controller, which consists of multiple DORA functional nodes to achieve autonomous driving functionality. The autonomous driving software obtains vehicle status, sensor data, and vehicle cooperative control messages from the multi-vehicle Dora-bridge of the simulation platform. After processing by the algorithm module, it generates control command information for the corresponding vehicle and publishes it to the simulation platform via DORA topics.

[0010] Furthermore, the vehicle status data acquisition and transmission node in the multi-vehicle Dora-bridge is characterized by: In the multi-vehicle Dora-bridge, the vehicle status data acquisition and transmission node receives the status data of each vehicle in the traffic scenario simulation software, parses and identifies the vehicle ID corresponding to the data, updates the message list according to the vehicle ID, and publishes it in the DORA topic format for use by the DORA-based autonomous driving software in the domain controller.

[0011] Furthermore, the lidar point cloud acquisition and transmission node in the multi-vehicle Dora-bridge is characterized by: In the multi-vehicle Dora-bridge, the LiDAR point cloud acquisition and transmission node receives environmental point cloud data from multiple radars on each vehicle in the traffic scene simulation software. It parses and identifies the vehicle ID and the corresponding LiDAR ID of the data, updates the message list based on the vehicle ID and the corresponding LiDAR ID, and publishes it in the DORA topic format for use by the DORA-based autonomous driving software in the domain controller.

[0012] Furthermore, the GNSS positioning data acquisition and transmission node in the multi-vehicle Dora-bridge is characterized by: In the multi-vehicle Dora-bridge, the GNSS positioning data acquisition and transmission node receives GNSS positioning data from each vehicle in the traffic scenario simulation software, parses and identifies the vehicle ID corresponding to the data, updates the message list according to the vehicle ID, and publishes it in the DORA topic format for use by the DORA-based autonomous driving software in the domain controller.

[0013] Furthermore, the camera image data acquisition and transmission node in the multi-vehicle Dora-bridge is characterized by: In the multi-vehicle Dora-bridge, the camera image data acquisition and transmission node receives image data from multiple cameras on each vehicle in the traffic scene simulation software. It parses and identifies the vehicle ID and the corresponding camera ID of the data, updates the message list based on the vehicle ID and the corresponding camera ID, and publishes it in the DORA topic format for use by the DORA-based autonomous driving software in the domain controller.

[0014] Furthermore, the millimeter-wave / ultrasonic radar data acquisition and transmission node in the multi-vehicle Dora-bridge is characterized by: In the multi-vehicle Dora-bridge, the millimeter-wave / ultrasonic radar data acquisition and transmission node receives obstacle distance, speed, and orientation data detected by multiple radars on each vehicle in the traffic scenario simulation software. It parses and identifies the corresponding vehicle ID and radar ID of the data, updates the message list based on the vehicle ID and radar ID of the corresponding vehicle, and publishes it in the DORA topic format for use by the DORA-based autonomous driving software in the domain controller.

[0015] Furthermore, the collaborative control node in the multi-vehicle Dora-bridge is characterized by: In the multi-vehicle Dora-bridge, the collaborative control node receives collaborative control parameter data such as position, speed, and steering of each vehicle from the traffic scenario simulation software, parses and identifies the corresponding vehicle ID, updates the message list according to the vehicle ID, and publishes it in the DORA topic format for use by the DORA-based autonomous driving software in the domain controller.

[0016] Furthermore, the vehicle control command receiving and transmission node in the multi-vehicle Dora-bridge is characterized by: In the multi-vehicle Dora-bridge, the vehicle control command receiving and transmission node receives control command messages from each vehicle issued by the domain controller, parses them, and sends them to the vehicle dynamics simulation software according to the corresponding vehicle ID, driving the corresponding virtual vehicle to perform the corresponding actions.

[0017] This invention also provides a multi-vehicle autonomous driving simulation method supporting DORA middleware, the steps of which are as follows: 1. Simulation Platform Loading and Initialization of Simulation Scene: The traffic scene simulation software loads the simulation scene and configures the LiDAR, cameras, millimeter-wave / ultrasonic radar and other sensors, as well as GNSS, for each vehicle according to the simulation scene description file; the vehicle dynamics simulation software initializes the vehicle parameters and status according to the simulation scene description file; the multi-vehicle Dora-bridge initializes the message queues for each topic according to the simulation scene description file. 2. Multi-vehicle Dora-bridge Data Acquisition and Publishing: The multi-vehicle Dora-bridge vehicle status data acquisition and transmission node collects vehicle status data from multiple vehicles in the traffic scene simulation software and publishes it using the DORA topic; the LiDAR scene point cloud data acquisition and transmission node collects scene point cloud data corresponding to the LiDAR sensor and publishes it using the DORA topic; the GNSS positioning data acquisition and transmission node collects GNSS positioning data from each vehicle and publishes it using the DORA topic; the camera image data acquisition and transmission node collects scene video data and publishes it using the DORA topic; the millimeter-wave / ultrasonic radar data acquisition and transmission node collects obstacle distance, speed, and orientation data and publishes it using the DORA topic; the cooperative control node collects cooperative control messages containing vehicle cooperative control parameter information and publishes them in the DORA topic format. 3. Domain Controller Data Reception and Processing: For domain controller i in the domain controller group, its DORA node obtains the corresponding vehicle status and sensor data from each data transmission node of the multi-vehicle Dora-bridge, and obtains cooperative control messages from the cooperative control node of the multi-vehicle Dora-bridge, which are then processed by the autonomous driving function node on the domain controller. 4. Domain Controller Control Command Generation and Publication: The domain controller receives data from multiple vehicles via the Dora-bridge, processes it through the autonomous driving function node on the domain controller, generates control commands corresponding to vehicle i, and publishes them in the DORA topic format. 5. Multi-vehicle Dora-bridge control command reception and transmission: In the simulation platform, the vehicle control command reception and transmission node of the multi-vehicle Dora-bridge subscribes to the control command topic published by the domain controller i, obtains the control command of the corresponding vehicle i, and transmits it to the vehicle dynamics simulation software. 6. Virtual vehicle dynamics state update in vehicle dynamics simulation software: The vehicle dynamics simulation software receives control commands from vehicle i from the multi-vehicle Dora-bridge, calculates vehicle driving behavior data based on the vehicle dynamics model, and sends it to the corresponding virtual vehicle in the traffic scene simulation software. 7. Vehicle and Scene Status Update in Traffic Scene Simulation Software: The virtual vehicle in the traffic scene simulation software receives the virtual vehicle dynamics status from the vehicle dynamics simulation software and executes the parsed control commands, including steering, torque adjustment, deceleration and braking, gear shifting, etc., and updates the corresponding vehicle status in the simulation scene. 8. Repeat steps 2 to 7 to achieve multi-vehicle autonomous driving simulation that supports DORA middleware.

[0018] Furthermore, the specific implementation process for loading and initializing the simulation scene on the simulation platform described in step 1 is as follows: 1.1 After the traffic scene simulation software starts, the simulation platform loads the simulation scene; the traffic scene simulation software initializes various sensor parameters according to the simulation scene description file, including the detection frequency and detection range of the lidar, the frame rate, resolution, and field of view of the camera, and the sampling rate and positioning accuracy of the GNSS; the vehicle dynamics simulation software initializes vehicle parameters and status according to the simulation scene description file; the multi-vehicle Dora-bridge initializes the message queues of each topic according to the simulation scene description file. 1.2 Subsequently, the parsed scene information and the initialized sensor parameters, vehicle parameters and status are passed to the topic message queues of the multi-vehicle Dora-bridge.

[0019] Furthermore, the specific implementation process for the multi-vehicle Dora-bridge data collection and publishing described in step 2 is as follows: For data sent from the simulation platform to the domain controller, including vehicle status data, sensor data, and cooperative control messages, the multi-vehicle Dora-bridge converts it from the simulation platform's initial format into the DORA topic format for publication.

[0020] Furthermore, the specific implementation process for receiving and transmitting multi-vehicle Dora-bridge control commands in step 5 is as follows: For vehicle control topics published by autonomous driving system software based on DORA middleware, the multi-vehicle Dora-bridge receives them, parses and converts them into control commands for the corresponding vehicles according to the format requirements of the vehicle dynamics simulation software, and then transmits them to the vehicle dynamics simulation software.

[0021] The beneficial effects of this invention are as follows: This invention provides a multi-vehicle autonomous driving simulation system and method that supports DORA middleware.

[0022] This invention addresses the application needs of DORA middleware in the development of multi-vehicle autonomous driving systems. By connecting traffic scene simulation software, vehicle dynamics simulation software, and autonomous driving algorithms based on DORA middleware on domain controller groups through multi-vehicle Dora-bridge, it provides an effective solution for DORA middleware-based multi-vehicle autonomous driving system simulation, improving development efficiency and reducing development costs.

[0023] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0024] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein: Figure 1 A preferred embodiment of the present invention provides an overall architecture diagram of a multi-vehicle autonomous driving simulation system supporting DORA middleware; Figure 2 The simulation method flowchart provided by this invention; Figure 3 This is a schematic diagram of the vehicle status message list in the multi-vehicle Dora-bridge provided by the present invention; Figure 4 This is a schematic diagram of the lidar point cloud data message list in the multi-vehicle Dora-bridge provided by the present invention; Figure 5 This is a schematic diagram of the collaborative control message list in the multi-vehicle Dora-bridge provided by the present invention. Detailed Implementation

[0025] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0026] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures, and should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0027] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "front," and "rear" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present 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. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present invention. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0028] Figure 1 The diagram illustrates a multi-vehicle autonomous driving simulation system supporting DORA middleware according to the present invention. The system includes a simulation platform supporting multi-vehicle Dora-bridge and a domain controller group supporting DORA middleware, wherein: The simulation platform comprises three parts: a multi-vehicle Dora-bridge, traffic scenario simulation software, and vehicle dynamics simulation software. The multi-vehicle Dora-bridge serves as the interaction layer between the traffic scenario simulation software, the vehicle dynamics simulation software, and the domain controller software. It receives multi-vehicle state data, sensor data, and vehicle cooperative control messages generated by the traffic scenario simulation software and publishes them as DORA topics for subscription by each domain controller. Simultaneously, it receives control commands published by each domain controller using DORA topics and distributes them to the vehicle dynamics simulation software.

[0029] Domain Controller Group: This group comprises multiple domain controllers, each corresponding to an autonomous vehicle. DORA-based vehicle autonomous driving software runs on each domain controller, which consists of multiple DORA functional nodes to achieve autonomous driving functionality. The autonomous driving software obtains vehicle status, sensor data, and vehicle cooperative control messages from the multi-vehicle Dora-bridge of the simulation platform. After processing by the algorithm module, it generates control command information for the corresponding vehicle and publishes it to the simulation platform via DORA topics.

[0030] Figure 2 This is a flowchart of the simulation method provided by the present invention, the details of which are as follows: 1. Simulation Platform Loading and Initialization of Simulation Scene: The traffic scene simulation software loads the simulation scene and configures the LiDAR, cameras, millimeter-wave / ultrasonic radar and other sensors, as well as GNSS, for each vehicle according to the simulation scene description file; the vehicle dynamics simulation software initializes the vehicle parameters and status according to the simulation scene description file; the multi-vehicle Dora-bridge initializes the message queues for each topic according to the simulation scene description file. 2. Multi-vehicle Dora-bridge Data Acquisition and Publishing: The multi-vehicle Dora-bridge vehicle status data acquisition and transmission node collects vehicle status data from multiple vehicles in the traffic scene simulation software and publishes it using the DORA topic; the LiDAR scene point cloud data acquisition and transmission node collects scene point cloud data corresponding to the LiDAR sensor and publishes it using the DORA topic; the GNSS positioning data acquisition and transmission node collects GNSS positioning data from each vehicle and publishes it using the DORA topic; the camera image data acquisition and transmission node collects scene video data and publishes it using the DORA topic; the millimeter-wave / ultrasonic radar data acquisition and transmission node collects obstacle distance, speed, and orientation data and publishes it using the DORA topic; the cooperative control node collects cooperative control messages containing vehicle cooperative control parameter information and publishes them in the DORA topic format. 3. Domain Controller Data Reception and Processing: For domain controller i in the domain controller group, its DORA node obtains the corresponding vehicle status and sensor data from each data transmission node of the multi-vehicle Dora-bridge, and obtains cooperative control messages from the cooperative control node of the multi-vehicle Dora-bridge, which are then processed by the autonomous driving function node on the domain controller. 4. Domain Controller Control Command Generation and Publication: The domain controller receives data from multiple vehicles via the Dora-bridge, processes it through the autonomous driving function node on the domain controller, generates control commands corresponding to vehicle i, and publishes them in the DORA topic format. 5. Multi-vehicle Dora-bridge control command reception and transmission: In the simulation platform, the vehicle control command reception and transmission node of the multi-vehicle Dora-bridge subscribes to the control command topic published by the domain controller i, obtains the control command of the corresponding vehicle i, and transmits it to the vehicle dynamics simulation software. 6. Virtual vehicle dynamics state update in vehicle dynamics simulation software: The vehicle dynamics simulation software receives control commands from vehicle i from the multi-vehicle Dora-bridge, calculates vehicle driving behavior data based on the vehicle dynamics model, and sends it to the corresponding virtual vehicle in the traffic scene simulation software. 7. Vehicle and Scene Status Update in Traffic Scene Simulation Software: The virtual vehicle in the traffic scene simulation software receives the virtual vehicle dynamics status from the vehicle dynamics simulation software and executes the parsed control commands, including steering, torque adjustment, deceleration and braking, gear shifting, etc., and updates the corresponding vehicle status in the simulation scene. 8. Repeat steps 2 to 7 to achieve multi-vehicle autonomous driving simulation that supports DORA middleware.

[0031] Figure 3 This is a list of vehicle status messages during data processing in the multi-vehicle Dora-bridge simulation platform of the system of this invention. The specific contents are as follows: For vehicle status data, the message format is vehicle ID + vehicle status information such as speed and attitude. The multi-vehicle Dora-bridge receives vehicle status information such as speed and attitude from traffic scenario simulation software, parses and identifies the vehicle ID corresponding to the data, then updates the message list according to the vehicle ID and publishes it in DORA topic format. Each controller in the domain controller group subscribes to this message and obtains the vehicle status information corresponding to its own vehicle based on its own vehicle ID for subsequent processing.

[0032] Figure 4 This is a list of lidar point cloud data messages during data processing in the multi-vehicle Dora-bridge simulation platform of the system of this invention. The specific contents are as follows: For LiDAR point cloud data, the message format is vehicle ID + IDs of each radar on the vehicle + environmental point cloud data. After receiving the environmental point cloud data detected by the LiDAR in the traffic scene simulation software, the multi-vehicle Dora-bridge LiDAR point cloud acquisition and transmission node parses and identifies the vehicle ID and the corresponding LiDAR ID on the vehicle. Then, it updates the message list according to the vehicle ID and the corresponding radar ID on the vehicle and publishes it in the DORA topic format. Each controller in the domain controller group subscribes to this message, obtains the environmental point cloud data corresponding to its own vehicle according to its own vehicle ID, and provides it for subsequent processing. This provides multi-source sensor information for the precise positioning, environmental perception, obstacle recognition, and other functions of the DORA-based autonomous driving software in the domain controller.

[0033] Figure 5 This is the list of cooperative control messages in the multi-vehicle Dora-bridge simulation platform of the system of this invention. The specific contents are as follows: For vehicle cooperative control messages, these messages are interactive cooperative control messages, and the message format is vehicle ID + cooperative control information such as position, speed, and steering. The multi-vehicle Dora-bridge receives the cooperative control parameter information such as position, speed, and steering of each vehicle in the traffic scenario simulation software, parses and identifies the vehicle ID corresponding to the data, updates the message list according to the vehicle ID, and then publishes it in the DORA topic format. Each controller in the domain controller group subscribes to this message, reads all vehicle cooperative control information, and uses it for subsequent processing.

[0034] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A multi-vehicle autonomous driving simulation system supporting DORA middleware, characterized in that, The system consists of a simulation platform and a domain controller group, wherein: The simulation platform comprises three parts: a multi-vehicle Dora-bridge, traffic scenario simulation software, and vehicle dynamics simulation software. The multi-vehicle Dora-bridge serves as the interaction layer between the traffic scenario simulation software, the vehicle dynamics simulation software, and the domain controller software. It receives multi-vehicle state data, sensor data, and vehicle cooperative control messages generated by the traffic scenario simulation software and publishes them as DORA topics for subscription by each domain controller. Simultaneously, it receives control commands published by each domain controller using DORA topics and distributes them to the vehicle dynamics simulation software. Domain Controller Group: This group consists of multiple domain controllers, each corresponding to an autonomous vehicle. DORA-based autonomous driving software runs on each domain controller. This software is composed of multiple DORA functional nodes to achieve autonomous driving functionality. The autonomous driving software obtains the vehicle status, sensor data, and vehicle cooperative control messages of the corresponding vehicle from the multi-vehicle Dora-bridge of the simulation platform. After processing by the algorithm module, it generates control command information for the corresponding vehicle and publishes it to the simulation platform via DORA topics.

2. The multi-vehicle autonomous driving simulation system supporting DORA middleware according to claim 1, characterized in that, The multi-vehicle Dora-bridge consists of vehicle status data acquisition and transmission nodes, lidar point cloud acquisition and transmission nodes, GNSS positioning data acquisition and transmission nodes, camera image data acquisition and transmission nodes, millimeter-wave / ultrasonic radar data acquisition and transmission nodes, collaborative control nodes, and vehicle control command receiving and transmission nodes.

3. The multi-vehicle autonomous driving simulation system supporting DORA middleware according to claim 2, characterized in that, The vehicle status data acquisition and transmission node and the lidar point cloud acquisition and transmission node include: Vehicle Status Data Acquisition and Transmission Node: The vehicle status data acquisition and transmission node in the multi-vehicle Dora-bridge receives the status data of each vehicle in the traffic scenario simulation software, parses and identifies the vehicle ID corresponding to the data, updates the message list according to the vehicle ID, and publishes it in the DORA topic format for use by the DORA-based autonomous driving software in the domain controller. LiDAR point cloud acquisition and transmission node: The LiDAR point cloud acquisition and transmission node in the multi-vehicle Dora-bridge receives environmental point cloud data from multiple radars on each vehicle in the traffic scene simulation software, parses and identifies the vehicle ID and the corresponding LiDAR ID of the data, updates the message list according to the vehicle ID and the corresponding LiDAR ID of the vehicle, and publishes it in the DORA topic format for use by the DORA-based autonomous driving software in the domain controller.

4. The multi-vehicle autonomous driving simulation system supporting DORA middleware according to claim 3, characterized in that, The GNSS positioning data acquisition and transmission node, camera image data acquisition and transmission node, and millimeter-wave / ultrasonic radar data acquisition and transmission node specifically include: GNSS positioning data acquisition and transmission node: The GNSS positioning data acquisition and transmission node in the multi-vehicle Dora-bridge receives GNSS positioning data from each vehicle in the traffic scenario simulation software, parses and identifies the vehicle ID corresponding to the data, updates the message list according to the vehicle ID, and publishes it in DORA topic format for use by the DORA-based autonomous driving software in the domain controller. Camera image data acquisition and transmission node: The camera image data acquisition and transmission node in the multi-vehicle Dora-bridge receives image data from multiple cameras on each vehicle in the traffic scene simulation software, parses and identifies the vehicle ID and the corresponding camera ID of the data, updates the message list according to the vehicle ID and the corresponding camera ID of the vehicle, and publishes it in the DORA topic format for use by the DORA-based autonomous driving software in the domain controller. Millimeter-wave / ultrasonic radar data acquisition and transmission node: The millimeter-wave / ultrasonic radar data acquisition and transmission node in the multi-vehicle Dora-bridge receives obstacle distance, speed, and orientation data detected by multiple radars on each vehicle in the traffic scenario simulation software. It parses and identifies the vehicle ID and radar ID corresponding to the data, updates the message list based on the vehicle ID and radar ID, and publishes it in DORA topic format for use by the DORA-based autonomous driving software in the domain controller.

5. The multi-vehicle autonomous driving simulation system supporting DORA middleware according to claim 4, characterized in that, The collaborative control node and the vehicle control command receiving and transmitting node specifically include: Cooperative control node: In the multi-vehicle Dora-bridge, the cooperative control node receives cooperative control parameter data such as position, speed, and steering of each vehicle in the traffic scenario simulation software, parses and identifies the vehicle ID corresponding to the data, updates the message list according to the vehicle ID, and publishes it in DORA topic format for use by the DORA-based autonomous driving software in the domain controller. Vehicle control command receiving and transmitting node: In the multi-vehicle Dora-bridge, the vehicle control command receiving and transmitting node receives control command messages from each vehicle issued by the domain controller, parses them, and sends them to the vehicle dynamics simulation software according to the corresponding vehicle ID, driving the corresponding virtual vehicle to perform the corresponding actions.

6. A multi-vehicle autonomous driving simulation method supporting DORA middleware, characterized in that, The method employs the system described in any one of claims 1 to 5, and specifically includes the following steps: 1) Simulation platform loading and initialization of simulation scenarios: The traffic scenario simulation software loads the simulation scenario and configures the LiDAR, cameras, millimeter-wave / ultrasonic radar and other sensors and GNSS of each vehicle according to the simulation scenario description file; the vehicle dynamics simulation software initializes the vehicle parameters and status according to the simulation scenario description file; the multi-vehicle Dora-bridge initializes the message queues of each topic according to the simulation scenario description file. 2) Multi-vehicle Dora-bridge data acquisition and publishing: The vehicle status data acquisition and transmission node of the multi-vehicle Dora-bridge collects vehicle status data of multiple vehicles in the traffic scene simulation software and publishes it with the DORA topic; the LiDAR scene point cloud data acquisition and transmission node collects scene point cloud data corresponding to the LiDAR sensor and publishes it with the DORA topic; the GNSS positioning data acquisition and transmission node collects GNSS positioning data of each vehicle and publishes it with the DORA topic; the camera image data acquisition and transmission node collects scene video data and publishes it with the DORA topic; the millimeter-wave / ultrasonic radar data acquisition and transmission node collects obstacle distance, speed, azimuth, and other data and publishes it with the DORA topic; the cooperative control node collects cooperative control messages containing vehicle cooperative control parameter information and publishes them in the format of the DORA topic. 3) Domain controller data reception and processing: For domain controller i in the domain controller group, the DORA node on it obtains the corresponding vehicle status and sensor data from each data transmission node of the multi-vehicle Dora-bridge, and obtains the cooperative control message from the cooperative control node of the multi-vehicle Dora-bridge, which is then processed by the autonomous driving function node on the domain controller. 4) Domain controller control command generation and publication: The data received by the domain controller from the multi-vehicle Dora-bridge is processed by the autonomous driving function node on the domain controller to generate the control command corresponding to vehicle i and publish it in the DORA topic format. 5) Multi-vehicle Dora-bridge control command reception and transmission: The vehicle control command reception and transmission node of the multi-vehicle Dora-bridge in the simulation platform subscribes to the control command topic published by the domain controller i, obtains the control command of the corresponding vehicle i, and transmits it to the vehicle dynamics simulation software. 6) Virtual vehicle dynamics state update in vehicle dynamics simulation software: The vehicle dynamics simulation software receives control commands from vehicle i from the multi-vehicle Dora-bridge, calculates vehicle driving behavior data based on the vehicle dynamics model, and sends it to the corresponding virtual vehicle in the traffic scene simulation software. 7) Vehicle and scene status update in traffic scene simulation software: The virtual vehicle in the traffic scene simulation software receives the virtual vehicle dynamics status from the vehicle dynamics simulation software and executes the parsed control commands, including steering, torque adjustment, deceleration and braking, gear shifting, etc., and updates the corresponding vehicle status in the simulation scene. 8) Repeat steps 2) to 7) to implement multi-vehicle autonomous driving simulation that supports DORA middleware.

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