A vehicle automatic driving data telemetry method and system

Abstract

The present invention discloses a vehicle automatic driving data telemetry method and system, wherein the vehicle-side ECU controls the access of multiple sensors, generates indicators Metrics, link Traces, and diagnostic information; the UDS protocol is used to aggregate the indicators to the central computing unit CCU; the CCU deploys the SOVD server, aggregates the indicators, links, and diagnostic information of the vehicle-side ECU, and processes the UDS and SOVD protocol adaptation conversion at the same time, and transmits the information to the telematic control unit TCU through the SOVD protocol; the TCU deploys the SOVD server and the 5G module, and uploads the information to the cloud server; the cloud server deploys the OpenTelemetry pipeline, receives the information sent by the TCU, stores it in the cloud server after sorting, and flexibly exports it to different customer groups. The present invention realizes the standardized processing of automatic driving data telemetry by deploying SOVD on the vehicle side and the OpenTelmetry pipeline on the cloud server.

Description

Technical Field

[0001] The present invention belongs to the technical field of autonomous driving, and in particular relates to a vehicle autonomous driving data telemetry method and system. Background Art

[0002] Traditional on-board diagnostic and logging systems mainly customize the information required for the vehicle body in a statically planned and pre-configured manner. With the ever-changing user needs in autonomous driving scenarios, traditional diagnostic and logging systems can no longer meet the flexible and changeable collection requirements, and traditional diagnostic and logging methods are also difficult to be compatible with cloud server formats.

[0003] ASAM launched the "Service-Oriented Vehicle Diagnostics SOVD" project in 2019. With the emergence of SOVD, the situation of vehicle-side dependence on UDS was solved and the vehicle-side export was unified. The standard aims to create a modern, simple diagnostic interface that can also access traditional ECUs and emerging software-based systems; another goal is to achieve unified access to remote, short-range and on-board diagnostic scenarios.

[0004] OpenTelemetry focuses on the unification of cloud data collection standards, specifically the data and data streams needed to most effectively acquire, detect, and improve application components. Data is only useful when it can be aggregated, analyzed, and visualized at scale. Although OpenTelemetry does not provide visualized data, it allows us to unify data collection and acquisition, allowing us to focus more on data post-processing and information mining. OpenTelemetry focuses on the main data categories we need to understand applications, allowing our applications to provide deeper insights into the performance and problems of complex modern application environments. By correlating data, adhering to semantics and standard practices, OpenTelemetry helps apply AI and ML technologies to solve complex problems, automate remediation, and demonstrate how to make cloud-native applications more adaptable and perform better. Cloud logs rely on DLT, etc. OpenTelemetry unifies cloud interfaces.

[0005] Therefore, the present invention provides a vehicle autonomous driving data telemetry method and system, which utilizes SOVD and OpenTelemetry cloud native technologies to achieve standardized collection and fusion of in-vehicle application data. Summary of the invention

[0006] In order to solve the deficiencies in the prior art, the purpose of the present invention is to provide a vehicle autonomous driving data telemetry method and system, respectively deploying SOVD on the vehicle side and OpenTelemetry on the cloud server to realize the standardized operation of vehicle-mounted autonomous driving data telemetry.

[0007] To achieve the purpose of the present invention, the technical solution adopted by the present invention is:

[0008] A vehicle autonomous driving data telemetry system, comprising a plurality of sensors, a plurality of vehicle-side ECUs, a central computing unit CCU, a telematic control unit TCU, and a cloud server;

[0009] The vehicle-side ECU controls the access of multiple sensors, obtains sensor information, and generates sensor metrics information, link traces information between ECUs, and ECU diagnostic information; it is aggregated to the central computing unit CCU through the UDS protocol;

[0010] The central computing unit CCU deploys the SOVD server, aggregates the indicators, links, and diagnostic information of the vehicle-side ECU, and processes the UDS and SOVD protocol adaptation conversion, and transmits it to the telematics control unit TCU through the SOVD protocol; the telematics control unit TCU deploys the SOVD server and 5G module, and then uploads it to the cloud server through the SOVD protocol;

[0011] The cloud server deploys the OpenTelemetry pipeline to receive metrics, link traces, and diagnostic information sent by the TCU. After being sorted by the OpenTelemetry pipeline, the information is stored in the cloud server.

[0012] Furthermore, after the ECU generates metrics, link traces, and diagnostic information, it can choose to transmit them to the CCU in real time or periodically through the UDS protocol and custom parts.

[0013] Furthermore, the various sensors include millimeter wave sensor Radar, Lidar, vehicle-mounted camera Camera, and ultrasonic radar USS.

[0014] Furthermore, the vehicle-side ECU supports the deployment of the SOVD server on the basis of compatibility with the traditional UDS. It can connect to the cloud-based OpenTelemetry pipeline through SOVD based on the metrics and link traces information defined by cloud users.

[0015] Furthermore, the cloud-based OpenTelemetry pipeline includes the SOVD client, OTLP receiver, data processing unit, SOVD dataset extension unit, health monitoring plug-in, and data export unit;

[0016] The SOVD client receives the SOVD information sent by the TCU and sends it to the data processing unit via the OTLP receiving end; the OTLP receiving end processes the SOVD and OTLP protocol adaptation conversion;

[0017] The data processing unit implements the parsing and storage of metrics, link traces, and diagnostic information through the SOVD data set extension unit. At the same time, it implements the status monitoring of the OpenTelemetry pipeline of the cloud server through the extended health monitoring plug-in.

[0018] The data export unit relies on the data processing and storage of the OpenTelemetry pipeline data processing unit to meet the data export needs of different customers.

[0019] A vehicle automatic driving data telemetry method comprises the following steps:

[0020] (1) The vehicle-side ECU generates sensor metrics information, link traces information between ECUs, and ECU diagnostic information. After the ECU generates relevant information, it can choose to transmit it to the CCU for processing in real time or periodically through the UDS protocol and custom parts.

[0021] (2) The vehicle-side CCU receives metrics, link traces, and diagnostic information from the ECU; it also processes the UDS and SOVD protocol adaptation conversions, and then transmits them to the TCU via the SOVD protocol;

[0022] (3) The vehicle-side TCU receives metrics, link traces, and diagnostic information aggregated by the CCU, and then transmits them to the cloud server through the SOVD protocol;

[0023] (4) The cloud server receives the SOVD information sent by the TCU, processes it through the OpenTelemetry pipeline, stores it in the cloud, and flexibly exports it to different customer groups.

[0024] The beneficial effect of the present invention is that, compared with the prior art, the present invention realizes standardized processing of autonomous driving data telemetry by deploying SOVD on the vehicle side and OpenTelmetry pipeline on the cloud server, and also provides more flexibility for autonomous driving SOA technology.

[0025] The present invention is applicable to the vehicle-cloud fusion scenario, and through deploying SOVD on the vehicle side and OpenTelmetry on the cloud side, it can realize the seamless integration of in-vehicle data tracking, collection, and uploading and cloud data post-processing and distribution. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a schematic diagram of the vehicle automatic driving data telemetry system according to the present invention;

[0027] Figure 2 This is the SOVD data model diagram on the vehicle side;

[0028] Figure 3 This is a diagram of the OpenTelemetry pipeline in the cloud. DETAILED DESCRIPTION

[0029] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the protection scope of this application.

[0030] like Figure 1 As shown, the vehicle automatic driving data telemetry system described in the present invention includes multiple sensors, such as Radar (millimeter wave sensor), Lidar (laser radar), Camera (vehicle-mounted camera), USS (Ultrasonic Sensor System), etc.; multiple vehicle-side ECUs, such as vehicle-side ECU1, ECU2, ECU3, and CCU (Central Compute Unit), TCU (Telematics Control Unit), execution components, and cloud servers.

[0031] The vehicle side supports SOVD service deployment on the basis of being compatible with traditional UDS. It can connect to the cloud OpenTelemetry pipeline through SOVD based on the metrics and link traces information defined by cloud users.

[0032] The vehicle-side ECU controls the access of multiple sensors, obtains sensor information, and generates sensor metrics information, traces information between ECUs, and ECU diagnostic information, which are aggregated to the central computing unit CCU through the UDS protocol; the central computing unit CCU deploys the SOVD server to aggregate the metrics, links, diagnostics and other information of multiple ECUs in the vehicle, and transmits them to the telematics control unit TCU through the SOVD protocol. The telematics control unit TCU deploys the SOVD server and 5G module, and then uploads them to the cloud server through the SOVD protocol. The cloud server deploys the OpenTelemetry pipeline, and the metrics, link traces, diagnostics and other information collected by the vehicle are sorted out by the OpenTelemetry pipeline and stored in the cloud server. OEM manufacturers and end users can easily track the vehicle's own safety status and safety hazard information.

[0033] like Figure 2 As shown in the figure, the SOVD data model diagram on the vehicle side includes the vehicle-side ECU that deploys the UDS protocol, the vehicle-side CCU and TCU that deploy the SOVD server, and the cloud server that deploys the OpenTelemetry pipeline.

[0034] The vehicle-side ECU is responsible for generating the metrics information of the sensor, the traces information between ECUs, and the ECU's own diagnosis information. After the ECU generates the relevant information, it can choose to transmit it to the CCU for processing in real time or periodically through the UDS protocol and the custom part.

[0035] The vehicle-side CCU is responsible for receiving metrics, link traces, diagnostic information, etc. gathered from the ECU side; at the same time, the CCU processes the UDS and SOVD protocol adaptation conversion, and then transmits it to the TCU via the SOVD protocol. The vehicle-side TCU is responsible for receiving metrics, link traces, diagnostic information, etc. gathered from the CCU side, and then transmits it to the cloud server via the SOVD protocol.

[0036] The cloud server is responsible for receiving the SOVD information sent by the TCU, which is sorted by the OpenTelemetry pipeline and stored in the cloud server.

[0037] like Figure 3 As shown in the figure, the schematic diagram of the cloud-based OpenTelemetry pipeline includes the SOVD client, OTLP receiver, data processing unit, SOVD dataset expansion unit, health monitoring plug-in, and data export unit.

[0038] Among them, the SOVD client is responsible for receiving the SOVD information sent by the vehicle-side TCU, and sending it to the data processing unit via the OTLP receiver; the OTLP receiver handles the SOVD and OTLP protocol adaptation conversion.

[0039] The data processing unit, through the SOVD data set extension unit, implements the parsing and storage of metrics, link traces, diagnosis and other information; at the same time, through the extended health monitoring plug-in, it implements the status monitoring of the OpenTelemetry pipeline of the cloud server.

[0040] The data export unit is used to export data processing results. Relying on the data processing and storage of the OpenTelemetry pipeline data processing unit, it can meet the data export needs of different manufacturers and customers.

[0041] The present invention also provides a vehicle automatic driving data telemetry method, comprising the steps of:

[0042] (1) The vehicle-side ECU is responsible for generating sensor metrics information, traces information between ECUs, and ECU self-diagnosis information. After the ECU generates relevant information, it can choose to transmit it to the CCU for processing in real time or periodically through the UDS protocol and custom parts.

[0043] (2) The vehicle-side CCU is responsible for receiving metrics, traces, diagnostic information, and other information gathered from the ECU. At the same time, the CCU processes the UDS and SOVD protocol adaptation conversions and then transmits them to the TCU via the SOVD protocol.

[0044] (3) The vehicle-side TCU is responsible for receiving metrics, traces, diagnostic information, and other information gathered by the CCU, and then transmitting it to the cloud server through the SOVD protocol;

[0045] (4) The cloud server is responsible for receiving the SOVD information sent by the TCU, processing it through the OpenTelemetry pipeline, cloud storage, and flexibly exporting it to different customer groups.

[0046] The beneficial effect of the present invention is that, compared with the prior art, the present invention realizes real-time or periodic generation of Metrics (indicators) and Traces (links) information for the vehicle side by deploying the OpenTelemetry pipeline on the cloud server, and completes unified and standardized access, processing, and export operations.

[0047] The present invention deploys a SOVD server on the vehicle side, which is compatible with the traditional ECU diagnosis and collection in the vehicle while achieving seamless connection with the OpenTelemetry pipeline on the cloud, forming a unified processing of on-board autonomous driving data.

[0048] The present invention can seamlessly integrate the SOA design, development, verification and other processes of the vehicle-mounted system, and provide a standardized and very convenient vehicle-cloud integration solution for key information of in-vehicle components such as sensors, actuators, ECUs, etc.

[0049] The applicant of the present invention has made a detailed explanation and description of the implementation examples of the present invention in conjunction with the drawings in the specification. However, those skilled in the art should understand that the above implementation examples are only preferred implementation schemes of the present invention, and the detailed description is only to help readers better understand the spirit of the present invention, but not to limit the scope of protection of the present invention. On the contrary, any improvements or modifications based on the inventive spirit of the present invention should fall within the scope of protection of the present invention.

Claims

1. A vehicle automatic driving data telemetry system, characterized in that: Including multiple sensors, multiple vehicle-side ECUs, central computing unit CCU, telematic control unit TCU, and cloud servers; The vehicle-side ECU controls the access of multiple sensors, obtains sensor information, and generates sensor metrics information, link traces information between ECUs, and ECU diagnostic information; Aggregated to the central computing unit CCU through the UDS protocol; The central computing unit CCU deploys the SOVD server, aggregates the indicators, links, and diagnostic information of the vehicle-side ECU, and processes the UDS and SOVD protocol adaptation conversion, and transmits it to the telematics control unit TCU through the SOVD protocol; the telematics control unit TCU deploys the SOVD server and 5G module, and then uploads it to the cloud server through the SOVD protocol; The cloud server deploys the OpenTelemetry pipeline to receive metrics, link traces, and diagnostic information sent by the TCU. After being sorted by the OpenTelemetry pipeline, the information is stored in the cloud server. The cloud-based OpenTelemetry pipeline includes the SOVD client, OTLP receiver, data processing unit, SOVD dataset expansion unit, health monitoring plug-in, and data export unit; The SOVD client receives the SOVD information sent by the TCU and sends it to the data processing unit via the OTLP receiving end; the OTLP receiving end processes the SOVD and OTLP protocol adaptation conversion; The data processing unit implements the parsing and storage of metrics, link traces, and diagnostic information through the SOVD data set extension unit. At the same time, it implements the status monitoring of the OpenTelemetry pipeline of the cloud server through the extended health monitoring plug-in. The data export unit relies on the data processing and storage of the OpenTelemetry pipeline data processing unit to meet the data export needs of different customers.

2. The vehicle automatic driving data telemetry system according to claim 1, characterized in that: After the ECU generates metrics, link traces, and diagnostic information, it can be transmitted to the CCU in real time or periodically through the UDS protocol and custom parts.

3. The vehicle automatic driving data telemetry system according to claim 1, characterized in that: Various sensors include millimeter wave sensor Radar, Lidar, vehicle-mounted camera Camera, and ultrasonic radar USS.

4. The vehicle automatic driving data telemetry system according to claim 1, characterized in that: The vehicle-side ECU supports the deployment of the SOVD server while being compatible with the traditional UDS. It can connect to the cloud-based OpenTelemetry pipeline through SOVD based on the metrics and link traces information defined by cloud users.

5. A vehicle automatic driving data telemetry method, based on the vehicle automatic driving data telemetry system according to any one of claims 1 to 4, characterized in that: Includes steps: (1) The vehicle-side ECU generates sensor metrics information, link traces information between ECUs, and ECU diagnostic information. After the ECU generates relevant information, it can be transmitted to the CCU for processing in real time or periodically through the UDS protocol and custom parts. (2) The vehicle-side CCU receives metrics, link traces, and diagnostic information from the ECU. It also processes the UDS and SOVD protocol adaptation conversions and then transmits them to the TCU via the SOVD protocol. (3) The vehicle-side TCU receives metrics, link traces, and diagnostic information gathered by the CCU, and then transmits them to the cloud server through the SOVD protocol; (4) The cloud server receives the SOVD information sent by the TCU, processes it through the OpenTelemetry pipeline, stores it in the cloud, and flexibly exports it to different customer groups.

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