An information interaction method for an autonomous driving vehicle

Abstract

The present invention relates to the technical field of automatic driving control, and specifically discloses an information interaction method of an automatic driving vehicle, including: setting a data center, integrating the information obtained by the perception module, positioning module, regulation and control module and the bottom layer of the vehicle according to a set integration mechanism through the data center, and standardizing the data according to a set data output format; setting an interaction module, the interaction module receives the real-time data and signals integrated by the data center, and performs signal arbitration, signal preprocessing, signal classification, scene processing and signal output processing to coordinate data transmission and interaction between modules; performing information interaction of starting and activating the automatic driving system of the vehicle, vehicle-side control, cloud scheduling and remote control through the interaction module; transmitting the processed and interacted data to the execution system at the bottom layer of the vehicle to control the driving of the vehicle. The present invention can improve the operating efficiency and reliability of automatic driving vehicles.

Description

Technical Field

[0001] The present invention relates to the technical field of autonomous driving control, and more specifically, to an information interaction method for an autonomous driving vehicle. Background Art

[0002] With the development of autonomous driving technology, vehicles need to rely on multiple software modules to process various complex information during driving, including perception, decision-making, planning and control. The efficient coordination and information transmission of each module are crucial to the safety and accuracy of the autonomous driving system. However, existing autonomous driving systems are usually composed of multiple independent modules, each of which handles different types of perception, decision-making, planning and control tasks. In the actual operation process, the data integration between different modules is often not efficient enough, resulting in untimely information transmission or inconsistent data, which may cause the interaction between the software modules to usually face problems such as communication delay, data inconsistency and resource competition, which in turn causes slow system response, wrong decision-making or unstable operation. At the same time, the interface standards of each module are not unified, which makes the expansion and maintenance of the system more difficult. At the control level, the independent operation of multiple modules may cause unreasonable resource allocation, resulting in a decrease in the overall response speed of the system, which in turn reduces the safety of vehicle autonomous driving and makes users have a poor experience of autonomous driving. Therefore, how to provide an effective information interaction method that can quickly and reliably transmit key information between multiple modules to ensure the real-time, stability and safety of the autonomous driving system has become an important research direction in the current technical field. Summary of the invention

[0003] The present invention provides an information interaction method for an autonomous driving vehicle, which solves the problems of slow response, data inconsistency and resource competition in the interaction between software modules in the autonomous driving system of existing vehicles, can improve the real-time, stability and safety of the vehicle's autonomous driving system, improve the operating efficiency and reliability of the autonomous driving vehicle, and enable the autonomous driving vehicle to achieve more efficient, stable and safe operation in complex road environments.

[0004] To achieve the above objectives, the present invention provides the following technical solutions:

[0005] An information interaction method for an autonomous driving vehicle, comprising:

[0006] Setting up a data center, integrating the information obtained by the perception module, positioning module, regulation and control module and the vehicle bottom layer in the vehicle according to a set integration mechanism, and standardizing the data according to a set data output format;

[0007] An interaction module is provided, wherein the interaction module receives the real-time data and signals integrated by the data center, and performs signal arbitration, signal preprocessing, signal classification, scene processing and signal output processing to coordinate data transmission and interaction between various modules inside the vehicle;

[0008] The interaction module is used to enable and activate the vehicle's automatic driving system, perform vehicle-side control, cloud scheduling, and remote control information interaction;

[0009] The processed and interacted data is passed to the vehicle's underlying execution system to control the vehicle's driving.

[0010] Preferably, it also includes:

[0011] The interactive module receives preset instructions or remote instructions and is responsible for activating and starting the autonomous driving system. Once the autonomous driving system is successfully activated, the interactive module synchronizes initialization data with the perception module, positioning module, regulation and control module and the vehicle bottom layer to ensure the normal operation of each module.

[0012] Preferably, it also includes:

[0013] The interactive module receives the vehicle's decision data in real time, and accurately transmits the generated control instructions to the vehicle's underlying execution system to control the vehicle's key operations of acceleration, deceleration, braking and parking.

[0014] Preferably, it also includes:

[0015] When manual intervention is required or the vehicle detects an abnormality, the interactive module automatically transfers the vehicle control to the driver according to the takeover mode to ensure driving safety.

[0016] Preferably, it also includes:

[0017] In the cloud scheduling scenario, the interaction module receives instructions from the cloud, converts the cloud instructions into corresponding driving control instructions, and transmits them to the vehicle's automatic driving system to guide the vehicle to drive to the destination according to the cloud scheduling arrangements.

[0018] Preferably, it also includes:

[0019] In the remote driving scenario, the interaction module receives remote control instructions from the remote operator and converts the remote control instructions into corresponding execution instructions to the underlying execution system of the vehicle to control the vehicle in real time.

[0020] Preferably, the data center integrates the information obtained by the perception module, positioning module, regulation and control module and the vehicle bottom layer in the vehicle according to a set integration mechanism, including:

[0021] Acquiring surrounding information of the vehicle from the perception module;

[0022] Acquiring real-time positioning information of the vehicle from the positioning module;

[0023] Acquire the current vehicle control information from the control module, wherein the control information includes: driving strategy, control instructions and planned path;

[0024] Acquire current status data of the vehicle from the bottom layer of the vehicle;

[0025] The surrounding information, positioning information, regulatory information and current status data corresponding to the vehicle are classified and scenario data integrated according to the information source and usage scenario to filter out the data required in different scenarios.

[0026] Preferably, the signal arbitration, signal preprocessing, signal classification, scene processing and signal output include:

[0027] During vehicle-side control and cloud-based scheduling, roads are divided into public roads and loop roads based on site information;

[0028] For public roads, the target station will be directly sent by the vehicle display module to directly convey the name of the target station, and the station distance will be calculated by the navigation module and then passed to the interaction module, and the interaction module will then feed back the two station information results of the target station and the station distance to the navigation module;

[0029] For the ring road, the distance between the current position and the next station is calculated according to the map and station files imported by the data center and the positioning information, and the calculated station and the calculated distance are fed back to the navigation module.

[0030] Preferably, the signal arbitration, signal preprocessing, signal classification, scene processing and signal output also include:

[0031] Priority comparison and signal classification are performed based on the received information sources. During signal classification, the signal sources are arranged and combined to be refined, and then processed according to the priorities corresponding to the classified signals, thereby completing the startup and activation of the autonomous driving system, vehicle-side control, cloud scheduling and / or remote driving.

[0032] Preferably, the signal arbitration, signal preprocessing, signal classification, scene processing and signal output also include:

[0033] Perform scenario processing for starting autonomous driving, manual takeover, braking, and stop signal judgment based on signal combinations;

[0034] When the activation button and the start autopilot button are triggered, and the detection signal is in a normal state, an autopilot activation command is issued to enter the autopilot start scene, otherwise it is not activated;

[0035] When receiving the takeover signal, issue an exit command for autonomous driving to enter the manual takeover scenario, and send a takeover command prompt;

[0036] When a brake button signal is received, a corresponding brake command is output according to the brake button level to enter the brake scene;

[0037] When a stop signal is received, the stop signal judgment scene is entered to perform site stop and signal stop judgments on the stop signal. In the signal stop scene, automatic driving is exited upon receipt of a stop signal, and a vehicle stop instruction is sent. In the site stop scene, automatic driving is exited upon receipt of a site arrival signal, and a site stop instruction is sent.

[0038] The present invention provides an information interaction method for an autonomous driving vehicle. A data center is set up to aggregate and integrate data, an interaction module is set up to obtain real-time data from the data center for processing and distribution, and the processed data is transmitted to the underlying execution system of the vehicle. This solves the problems of slow response, data inconsistency and resource competition in the interaction between software modules in the autonomous driving system of existing vehicles. The real-time, stability and safety of the vehicle's autonomous driving system can be improved, the operating efficiency and reliability of the autonomous driving vehicle can be improved, and the autonomous driving vehicle can be operated more efficiently, stably and safely in complex road environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the specific embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below.

[0040] Figure 1 It is a schematic diagram of an information interaction method for an autonomous driving vehicle provided by the present invention.

[0041] Figure 2 It is a schematic diagram of data transmission among various modules inside a vehicle provided by an embodiment of the present invention.

[0042] Figure 3 It is a flow chart of data processing performed by the interactive module provided in an embodiment of the present invention.

[0043] Figure 4 It is a schematic diagram of site information processing provided by an embodiment of the present invention.

[0044] Figure 5 It is a schematic diagram of signal processing provided by an embodiment of the present invention.

[0045] Figure 6It is a schematic diagram of scene processing provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0046] In order to enable persons skilled in the art to better understand the solutions of the embodiments of the present invention, the embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings and implementation modes.

[0047] In view of the problems of slow response, data inconsistency and resource competition in the interaction between modules during the current vehicle automatic driving, the present invention provides an information interaction method for an automatic driving vehicle, which solves the problems of slow response, data inconsistency and resource competition in the interaction between software modules in the automatic driving system of existing vehicles, can improve the real-time, stability and safety of the vehicle automatic driving system, improve the operating efficiency and reliability of the automatic driving vehicle, and enable the automatic driving vehicle to achieve more efficient, stable and safe operation in complex road environments.

[0048] like Figure 1 As shown, an information interaction method for an autonomous driving vehicle includes:

[0049] S1: Setting up a data center, integrating the information obtained by the perception module, positioning module, regulation and control module and the vehicle bottom layer in the vehicle according to a set integration mechanism through the data center, and standardizing the data according to a set data output format;

[0050] S2: Setting an interaction module, the interaction module receives the real-time data and signals integrated by the data center, and performs signal arbitration, signal preprocessing, signal classification, scene processing and signal output processing to coordinate data transmission and interaction between modules inside the vehicle;

[0051] S3: information interaction of starting and activating the vehicle's automatic driving system, vehicle-side control, cloud scheduling and remote control through the interaction module;

[0052] S4: The processed and interacted data is passed to the underlying execution system of the vehicle to control the vehicle's driving.

[0053] Specifically, Figure 2As shown in the figure, the data of the data center is composed of the vehicle bottom layer, perception module, positioning module and regulation and control module, and different data are forwarded to the interaction module, among which the perception module and positioning module data are sent to the regulation and control module, and the regulation and control module transmits the data to the data center, and at the same time directly sends part of the data to the vehicle bottom layer. Among them, the perception module is used to collect information about the surrounding of the vehicle; the positioning module is used to accurately locate the vehicle according to Beidou satellite signals or GPS satellite signals; the regulation and control module is used to make driving strategies and path planning according to the surrounding information and vehicle positioning information of the vehicle; the vehicle bottom layer obtains the current state data of the vehicle, such as speed, direction, power system status, etc., and controls the vehicle to travel according to the planned path at the required speed and expected turning angle according to the control signal. The interaction module plays the role of the core hub, responsible for coordinating the data transmission and interaction between the internal modules of each vehicle, and can coordinate according to the signal priority. The interaction module first obtains real-time data and signals from the data center, and performs signal arbitration, signal preprocessing, signal classification, scene processing and signal output processing on these data to coordinate the transmission and interaction of data of each module according to priority or other set rules, and then transmits the processed data to the execution system of the vehicle bottom layer. At the same time, the interactive module is also responsible for the four important functions of starting and activating the autonomous driving system, vehicle-side control, cloud scheduling, and remote control, ensuring the stability and flexibility of the system in different scenarios. This method avoids resource competition between modules through unified data processing, allowing the system to reasonably allocate resources on an efficient basis, further improving the system's response speed and stability.

[0054] In one embodiment, the data center is integrated into the domain controller of the vehicle, which can be implemented by hardware or software. When implemented by hardware, it can be composed of a microprocessor. The data center is connected to the vehicle controller signal of the vehicle, receives the data from the vehicle's perception module, positioning module, regulation and control module and the vehicle's bottom layer, and performs data integration according to the set integration mechanism. Through an effective data integration mechanism, the data center uniformly manages and processes information from different modules, avoids the problem of repeated information processing and transmission delay, and ensures data consistency and overall collaboration of the system.

[0055] In one embodiment, the interaction module is integrated in the domain controller of the vehicle, and can be implemented by a microprocessor or a software module. In hardware implementation, the data center is provided with interfaces and standardized interfaces corresponding to each module, and the interaction module adopts a standardized interface. The interaction module and the data center and each module exchange data through the standardized interface. The standardized interface helps to reduce the complexity of system integration, simplifies data interaction between different modules, and improves the flexibility of system expansion.

[0056] The interactive module is responsible for data aggregation, processing and distribution in the vehicle. It is not only responsible for obtaining real-time data from the data center, but also for transmitting the processed data to the vehicle's underlying execution system to ensure efficient and reliable information interaction between modules within the system. Through the interactive module, the information interaction of the opening and activation of the autonomous driving system, vehicle-side control, cloud scheduling and remote control can be made unified in the control mechanism of information interaction, and multiple modules can be coordinated and managed, so that resources can be reasonably allocated, the collaborative efficiency between modules can be improved, and conflicts and competition between modules can be avoided, thereby improving the overall performance and reliability of the system.

[0057] The method also includes: receiving preset instructions or remote instructions through the interaction module, being responsible for activating and starting the autonomous driving system. Once the autonomous driving system is successfully activated, the interaction module performs initialization data synchronization with the perception module, positioning module, regulation and control module and the vehicle bottom layer to ensure the normal operation of each module.

[0058] Specifically, the interaction module obtains data from the perception module, positioning module, regulation and control module and the underlying layer of the vehicle through the data center, and interacts with the autonomous driving system. In the interaction module, according to preset instructions or remote instructions, the interaction module is responsible for activating and starting the autonomous driving system, integrating the corresponding data of the vehicle's perception module, positioning module and regulation and control module, and sending the refined information to the underlying execution system of the vehicle, thereby realizing autonomous driving control.

[0059] The method also includes: receiving the vehicle's decision data in real time through the interactive module, and accurately transmitting the generated control instructions to the vehicle's underlying execution system to control the vehicle's key operations of acceleration, deceleration, braking and parking.

[0060] In practical applications, for vehicle-side control, the interaction module can manage key vehicle operations, including acceleration, deceleration, braking, and parking. It receives data from the decision module in real time and accurately transmits the generated control instructions to the underlying execution system of the vehicle. For example, when an emergency is detected, the interaction module can quickly issue a braking command to ensure that the vehicle stops in time.

[0061] The method also includes: when manual intervention is required or the vehicle detects an abnormality, the interactive module automatically transfers the vehicle control right to the driver according to the takeover mode to ensure driving safety.

[0062] In one embodiment, the interactive module is communicatively connected to the vehicle management system and is provided with a takeover mode, which can automatically transfer the vehicle control to the driver when manual intervention is required or the system detects an abnormality, thereby ensuring driving safety.

[0063] The method also includes: in a cloud-based scheduling scenario, the interaction module receives instructions from the cloud, converts the cloud-based instructions into corresponding driving control instructions, transmits them to the vehicle's automatic driving system, and guides the vehicle to drive to the destination according to the cloud-based scheduling arrangements.

[0064] Specifically, the interaction module is an important communication bridge between the vehicle and the cloud dispatch system. In the cloud dispatch function, the interaction module receives instructions from the cloud, such as the target location, vehicle start and stop, etc., and converts them into specific driving control instructions, which are passed to the vehicle's control module to guide the vehicle to drive to the destination according to the cloud dispatch arrangement.

[0065] The method also includes: in a remote driving scenario, the interaction module receives remote control instructions from a remote operator, and converts the remote control instructions into corresponding execution instructions to the underlying execution system of the vehicle to control the vehicle in real time.

[0066] Specifically, in the remote driving scenario, the interaction module acts as the communication interface between the vehicle and the remote control center. The remote operator uses remote control instructions to enable the interaction module to control the vehicle in real time, and the interaction module is responsible for converting these remote control instructions into underlying execution actions.

[0067] Furthermore, the data center integrates the information obtained by the perception module, positioning module, regulation and control module and the vehicle bottom layer in the vehicle according to the set integration mechanism, and standardizes the data according to the set data output format, including:

[0068] Acquiring surrounding information of the vehicle from the perception module;

[0069] Acquiring real-time positioning information of the vehicle from the positioning module;

[0070] Acquire the current vehicle control information from the control module, wherein the control information includes: driving strategy, control instructions and planned path;

[0071] Acquire current status data of the vehicle from the bottom layer of the vehicle;

[0072] The surrounding information, positioning information, regulatory information and current status data corresponding to the vehicle are classified and scenario data integrated according to the information source and usage scenario to filter out the data required in different scenarios.

[0073] Specifically, the data center classifies and integrates the data of the perception module, positioning module, regulation and control module and the bottom layer of the vehicle according to the receiving port, data source, data type and / or application scenario, and standardizes the data according to the set data output format to form a unified data format and standard. At the same time, data from different data sources can be merged into a unified database, providing a unified data output interface, thereby achieving data consistency and efficiency.

[0074] Further, if Figure 3 As shown, the integration process of the interaction module includes: obtaining input, signal arbitration, signal preprocessing, signal classification, scene processing and signal output.

[0075] For input, the data center obtains key information, including vehicle bottom-level information, positioning module information, regulation and control module information, etc. It obtains the vehicle's current status data from the bottom of the vehicle, obtains the vehicle's real-time location from the positioning module, and obtains the current driving strategy, control instructions and planned path from the regulation and control module to facilitate real-time adjustment of driving behavior. In addition, the map and site files imported by the data center are crucial for path planning and navigation. During autonomous driving, the system will automatically determine whether the necessary map and site files are missing, and check to confirm whether all necessary map and site files are complete. If the files are missing, feedback will be sent to the system, and the vehicle will not be able to enter the autonomous driving mode to ensure the integrity of the information and the efficient operation of the system.

[0076] For signal arbitration, since there are many signals obtained from the data center and the signals are obtained from different source modules, different data need to be used at different stages in different scenarios. Therefore, arbitration is performed on different signals to correspond to different scenarios according to different signals, and then the data required for different scenarios are filtered out.

[0077] At the same time, since the vehicle may request access to the same data at multiple devices or nodes at the same time, it will cause resource competition problems. This requires the establishment of an efficient arbitration mechanism for the signal to achieve data access priority. When performing signal arbitration in the interactive module, centralized arbitration or distributed arbitration can be used. The arbitration rules can reasonably allocate resources according to the signal priority, or polling rules can be used. At the same time, based on the arbitration scheme and arbitration rules, the arbitration logic is implemented by setting algorithms or hardware to solve the access conflicts of data reading and output, which can improve the efficiency of data reading.

[0078] In addition to signal arbitration, since the interaction module also needs to pass the target site information to the navigation, the signal preprocessing stage mainly processes the site sending conditions, target site processing and site distance calculation.

[0079] Furthermore, the signal arbitration, signal preprocessing, signal classification, scene processing and signal output processing include:

[0080] During vehicle-side control and cloud-based scheduling, roads are divided into public roads and ring roads based on site information.

[0081] For public roads, the target site will be directly sent by the vehicle display module to send site instructions and directly convey the target site name. The site distance will be calculated by the navigation module and then passed to the interaction module. The interaction module will then feed back the two site information results of the target site and the site distance to the navigation module.

[0082] For the ring road, the distance between the current position and the next station is calculated according to the map and station files imported by the data center and the positioning information, and the calculated station and the calculated distance are fed back to the navigation module.

[0083] In one embodiment, the processing of site information is required in vehicle-side control and cloud-side scheduling, and the site information includes the calculation site and the site distance. Figure 4 As shown, considering the complexity of roads, roads are divided into two types: public roads and ring roads. On public roads, site information is directly obtained by the navigation and display modules, while on ring roads, relevant information needs to be matched and calculated by itself. Ultimately, the information processed by the two types of roads will be fed back to the navigation module.

[0084] On public roads, the display module will directly send site instructions to the target site and directly convey the name of the target site. The distance to the site will be calculated by the navigation module and then passed to the interaction module. The interaction module will then feed back the two site information results of the target site and the site distance to the navigation module.

[0085] Loop road: Calculate the next station information based on the collected map and the positioning information transmitted by the navigation system and send it to the navigation module. Update the next station information each time the autonomous driving mode is entered. The station will not be updated within the station range. Calculate the distance between the current position and the next station based on the positioning information and map information transmitted by the navigation system in real time, and send the distance information to the navigation module in real time.

[0086] Furthermore, the signal arbitration, signal preprocessing, signal classification, scene processing and signal output processing also include:

[0087] Priority comparison and signal classification are performed based on the received information sources. During signal classification, the signal sources are arranged and combined to be refined, and then processed according to the priorities corresponding to the classified signals, thereby completing the startup and activation of the autonomous driving system, vehicle-side control, cloud scheduling and / or remote driving.

[0088] In one embodiment, if Figure 5As shown in the figure, in order to ensure cloud scheduling and remote control, the input signal is distinguished from the signal source. The button, cloud and remote control can divide the signal into 7 combinations of button, remote control signal, cloud signal, button + remote control, button + cloud, remote control + cloud, button + remote control + cloud, so as to facilitate the subsequent signal classification and processing. According to the signal source and priority comparison, the signal priority can be: button signal > remote control signal > cloud signal.

[0089] The specific scenarios under the 7 signal combinations are processed, including starting automatic driving, parking, taking over, etc. The signal arbitration, signal preprocessing, signal classification, scenario processing and signal output also include:

[0090] Based on the signal combination, scenario processing is performed for starting autonomous driving, manual takeover, braking and stop signal judgment.

[0091] When the activation button and the button to start automatic driving are triggered, and the detection signal is in normal state, the command to activate automatic driving is issued to enter the automatic driving start scene, otherwise it will not be activated.

[0092] When a takeover signal is received, an exit command for autonomous driving is issued to enter the manual takeover scenario, and a takeover command prompt is sent.

[0093] When the brake button signal is received, the corresponding brake command is output according to the brake button level to enter the brake scene.

[0094] When a stop signal is received, the stop signal judgment scene is entered to perform site stop and signal stop judgments on the stop signal. In the signal stop scene, automatic driving is exited upon receipt of a stop signal, and a vehicle stop instruction is sent. In the site stop scene, automatic driving is exited upon receipt of a site arrival signal, and a site stop instruction is sent.

[0095] In practical applications, such as Figure 6 As shown in the figure, the scene processing includes: starting automatic driving, manual takeover, braking and stop signal judgment, and judging the stop signal to correspond to the station parking scene and signal parking scene. The data center integrates the corresponding data based on different scenarios, and can refine the required data to the underlying execution system of the vehicle, which can improve the response speed and reliability of the system. The interactive module enables the system to switch between different scenarios, including remote control and cloud scheduling, which can enhance the flexibility and adaptability of the system, which ensures that the autonomous driving vehicle can operate stably under changing road conditions and scenarios.

[0096] It can be seen that the present invention provides an information interaction method for an autonomous driving vehicle, which aggregates and integrates data by setting a data center, and sets an interaction module to obtain real-time data from the data center for processing and distribution, and transmits the processed data to the underlying execution system of the vehicle, thereby solving the problems of slow response, data inconsistency and resource competition in the interaction between software modules in the autonomous driving system of existing vehicles, and can improve the real-time, stability and safety of the vehicle's autonomous driving system, improve the operating efficiency and reliability of the autonomous driving vehicle, and enable the autonomous driving vehicle to achieve more efficient, stable and safe operation in complex road environments.

[0097] The above describes in detail the structure, features and effects of the present invention based on the embodiments shown in the drawings. The above is only a preferred embodiment of the present invention, but the present invention is not limited to the scope of implementation shown in the drawings. Any changes made in accordance with the concept of the present invention, or modifications to equivalent embodiments with equivalent changes, which still do not exceed the spirit covered by the description and drawings, should be within the protection scope of the present invention.

Claims

1. An information interaction method for an autonomous driving vehicle, characterized in that: include: Setting up a data center, integrating the information obtained by the perception module, positioning module, regulation and control module and the vehicle bottom layer in the vehicle according to a set integration mechanism, and standardizing the data according to a set data output format; An interaction module is provided, the data center forwards different data to the interaction module, the interaction module receives the real-time data and signals integrated by the data center, and performs signal arbitration, signal preprocessing, signal classification, scene processing and signal output processing to coordinate data transmission and interaction between various modules inside the vehicle; The interaction module is used to enable and activate the vehicle's automatic driving system, perform vehicle-side control, cloud scheduling, and remote control information interaction; The processed and interacted data is passed to the vehicle's underlying execution system to control the vehicle's driving; The integration process of the interaction module includes: obtaining input, signal arbitration, signal preprocessing, signal classification, scene processing and signal output; For obtaining input, the interaction module first obtains real-time data and signals from the data center; For signal arbitration, arbitration is performed on different signals to correspond to different scenarios according to different signals, thereby filtering out the data required in different scenarios; at the same time, an arbitration mechanism is established to achieve the priority of data access; For signal preprocessing, the site sending conditions, target sites and site distance calculations are also processed.

2. The information interaction method of the autonomous driving vehicle according to claim 1, characterized in that: Also includes: The interactive module receives preset instructions or remote instructions and is responsible for activating and starting the autonomous driving system. Once the autonomous driving system is successfully activated, the interactive module synchronizes initialization data with the perception module, positioning module, regulation and control module and the vehicle bottom layer to ensure the normal operation of each module.

3. The information interaction method of the autonomous driving vehicle according to claim 2, characterized in that: Also includes: The interactive module receives the vehicle's decision data in real time, and accurately transmits the generated control instructions and corresponding data to the vehicle's underlying execution system to control the vehicle's key operations of acceleration, deceleration, braking and parking.

4. The information interaction method of the autonomous driving vehicle according to claim 3, characterized in that: Also includes: When manual intervention is required or the vehicle detects an abnormality, the interaction module automatically exits the automatic driving according to the takeover mode and transfers the vehicle control to the driver to ensure driving safety.

5. The information interaction method of the autonomous driving vehicle according to claim 4, characterized in that: Also includes: In the cloud scheduling scenario, the interaction module receives instructions from the cloud, converts the cloud instructions into corresponding driving control instructions, and transmits them to the vehicle's automatic driving system to guide the vehicle to drive to the destination according to the cloud scheduling arrangements.

6. The information interaction method of the autonomous driving vehicle according to claim 5, characterized in that: Also includes: In the remote driving scenario, the interaction module receives remote control instructions from the remote operator and converts the remote control instructions into corresponding execution instructions to the underlying execution system of the vehicle to control the vehicle in real time.

7. The information interaction method of the autonomous driving vehicle according to claim 6, characterized in that: The data center integrates the information obtained by the perception module, positioning module, regulation and control module and the vehicle bottom layer in the vehicle according to the set integration mechanism, including: Acquiring surrounding information of the vehicle from the perception module; Acquiring real-time positioning information of the vehicle from the positioning module; Acquire the current vehicle control information from the control module, wherein the control information includes: driving strategy, control instructions and planned path; Acquire current status data of the vehicle from the bottom layer of the vehicle; The surrounding information, positioning information, regulatory information and current status data corresponding to the vehicle are classified and scenario data integrated according to the information source and usage scenario to filter out the data required in different scenarios.

8. The information interaction method of the autonomous driving vehicle according to claim 7, characterized in that: The signal arbitration, signal preprocessing, signal classification, scene processing and signal output processing include: During vehicle-side control and cloud-based scheduling, roads are divided into public roads and loop roads based on site information; For public roads, the target station will be directly sent by the vehicle display module to directly convey the name of the target station, and the station distance will be calculated by the navigation module and then passed to the interaction module, and the interaction module will then feed back the two station information results of the target station and the station distance to the navigation module; For the ring road, the distance between the current position and the next station is calculated according to the map and station files imported by the data center and the positioning information, and the calculated station and the calculated distance are fed back to the navigation module.

9. The information interaction method of the autonomous driving vehicle according to claim 8, characterized in that: The signal arbitration, signal preprocessing, signal classification, scene processing and signal output processing also include: Priority comparison and signal classification are performed based on the received information sources. During signal classification, the signal sources are arranged and combined to be refined, and then processed according to the priorities corresponding to the classified signals, thereby completing the startup and activation of the autonomous driving system, vehicle-side control, cloud scheduling and / or remote driving.

10. The information interaction method of the autonomous driving vehicle according to claim 9, characterized in that: The signal arbitration, signal preprocessing, signal classification, scene processing and signal output processing also include: Perform scenario processing for starting autonomous driving, manual takeover, braking, and stop signal judgment based on signal combinations; When the activation button and the start autopilot button are triggered, and the detection signal is in a normal state, an autopilot activation command is issued to enter the autopilot start scene, otherwise it is not activated; When receiving the takeover signal, issue an exit command for autonomous driving to enter the manual takeover scenario, and send a takeover command prompt; When a brake button signal is received, a corresponding brake command is output according to the brake button level to enter the brake scene; When a stop signal is received, the stop signal judgment scene is entered to perform site stop and signal stop judgments on the stop signal. In the signal stop scene, automatic driving is exited upon receipt of a stop signal, and a vehicle stop instruction is sent. In the site stop scene, automatic driving is exited upon receipt of a site arrival signal, and a site stop instruction is sent.

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