Vibration noise monitoring method and device for unmanned online hailed car, and electronic equipment

Abstract

The invention provides a vibration noise monitoring method and device for an unmanned online hailed car and electronic equipment, and the method comprises the steps: obtaining the vibration noise information of a plurality of positions of the car through a sensor; acquiring driving state information of the vehicle; a corresponding relation table between the vibration noise information and the driving state information is created based on the time, the corresponding relation table is sent to a cloud server, and the cloud server analyzes the corresponding relation table to generate a monitoring result of the vehicle. Therefore, the purpose of filling the NVH performance monitoring blank after the vehicle is delivered can be achieved, and sufficient and real NVH data can be obtained for vehicle research and development and service quality improvement.

Description

Technical Field

[0001] This application relates to the field of vehicle design technology, and in particular to a method, device and electronic equipment for monitoring vibration and noise in an autonomous ride-hailing vehicle. Background Technology

[0002] With the rapid development of the automotive industry, ride-hailing services have become an important mode of transportation, and customers are placing higher demands on vehicle comfort and quietness. Currently, OEMs only monitor NVH (Noise, Vibration, and Harshness) performance of prototype vehicles during the R&D and prototyping phase. After vehicle delivery, there is a lack of effective NVH monitoring methods throughout the entire vehicle's lifecycle. Furthermore, due to privacy concerns surrounding private vehicles, it is difficult to deploy vibration and noise sensors comprehensively, resulting in the inability to obtain a large amount of real-world NVH data throughout the vehicle's lifecycle, thus hindering the continuous R&D and optimization of NVH performance. Summary of the Invention

[0003] This application aims to at least partially address one of the technical problems in the related art.

[0004] Therefore, the first objective of this application is to propose a vibration and noise monitoring method for driverless ride-hailing vehicles, which can fill the gap in NVH performance monitoring after vehicle delivery and obtain sufficient and accurate NVH data for vehicle research and development and service quality improvement.

[0005] The second objective of this invention is to provide a vibration and noise monitoring device for driverless ride-hailing vehicles.

[0006] The third objective of this invention is to provide an electronic device.

[0007] To achieve the above objectives, the first aspect of this application proposes a vibration and noise monitoring method for an autonomous ride-hailing vehicle, comprising the following steps: acquiring vibration and noise information at multiple locations of the vehicle using sensors, wherein the vibration and noise information includes engine noise signals, steering wheel vibration signals, passenger seat noise signals, driver seat noise signals, right rear seat noise signals, left rear seat noise signals, and driver seat rail vibration signals; acquiring vehicle driving status information; creating a correspondence table between vibration and noise information and driving status information based on time, and sending the correspondence table to a cloud server, wherein the cloud server analyzes the correspondence table to generate vehicle monitoring results.

[0008] The vibration and noise monitoring method for driverless ride-hailing vehicles according to embodiments of this application first acquires vibration and noise information at multiple locations on the vehicle using sensors, as well as the vehicle's driving status information. Then, a correspondence table between the vibration and noise information and the driving status information is created based on time, and this table is sent to a cloud server. The cloud server then analyzes the table to generate vehicle monitoring results. This method fills the monitoring gap in NVH performance after vehicle delivery and provides sufficient and accurate NVH data for vehicle development and service quality improvement.

[0009] In addition, the vibration and noise monitoring method for driverless ride-hailing vehicles according to the above embodiments of this application may also have the following additional technical features: In one embodiment of this application, both vibration noise information and driving status information include information acquisition time data.

[0010] In one embodiment of this application, when the vehicle's current trip is about to end, a vibration and noise rating survey form for the current trip is generated and displayed to the customer through the vehicle's central control screen; the evaluation information input by the customer through the central control screen is received and sent to the cloud server.

[0011] In one embodiment of this application, the cloud server is also used to generate monitoring results based on the evaluation information and the corresponding relationship table.

[0012] In one embodiment of this application, a preset reminder message is played via the vehicle's audio system when the vehicle's current trip is about to end.

[0013] In one embodiment of this application, there are multiple sensors, including an engine vibration sensor, a steering wheel vibration sensor, a passenger noise signal sensor, a driver noise signal sensor, a right rear seat noise signal sensor, a left rear seat noise signal sensor, and a driver's seat rail vibration sensor.

[0014] In one embodiment of this application, the engine vibration sensor is directly embedded in the engine body, the steering wheel vibration sensor is installed at the top of the steering wheel, the passenger noise signal sensor is installed inside the passenger seat headrest, the driver noise signal sensor is installed inside the driver seat headrest, the right rear seat noise signal sensor is installed inside the seat headrest, the left rear seat noise signal sensor is installed inside the seat headrest, and the driver seat rail vibration sensor is installed at the inner end of the driver seat rail.

[0015] In one embodiment of this application, the vibration noise information further includes an exhaust emission noise signal, and the sensor further includes an exhaust emission noise signal sensor, wherein the exhaust emission noise signal sensor is mounted on the exhaust pipe.

[0016] To achieve the above objectives, a second aspect of this application proposes a vibration and noise monitoring device for an autonomous ride-hailing vehicle, comprising: a first acquisition module, used to acquire vibration and noise information at multiple locations of the vehicle through sensors, wherein the vibration and noise information includes engine noise signal, steering wheel vibration signal, passenger seat noise signal, driver seat noise signal, right rear seat noise signal, left rear seat noise signal, and driver seat rail vibration signal; a second acquisition module, used to acquire vehicle driving status information; and a processing module, used to create a correspondence table between vibration and noise information and driving status information based on time, and send the correspondence table to a cloud server, wherein the cloud server analyzes the correspondence table to generate vehicle monitoring results.

[0017] The vibration and noise monitoring device for driverless ride-hailing vehicles according to embodiments of this application acquires vibration and noise information from multiple locations of the vehicle through a first acquisition module, acquires the vehicle's driving status information through a second acquisition module, and creates a correspondence table between the vibration and noise information and the driving status information based on time through a processing module. This correspondence table is then sent to a cloud server, which analyzes the table to generate vehicle monitoring results. This achieves the goal of filling the gap in NVH performance monitoring after vehicle delivery and obtaining sufficient and accurate NVH data for vehicle development and service quality improvement.

[0018] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the vibration and noise monitoring method for an unmanned ride-hailing vehicle as described in the first aspect of the application.

[0019] The electronic device in this application embodiment implements any of the above-mentioned vibration and noise monitoring methods for driverless ride-hailing vehicles when the processor executes a computer program, thereby filling the monitoring gap of NVH performance after vehicle delivery and obtaining sufficient and authentic NVH data for vehicle research and development and service quality improvement.

[0020] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0021] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart illustrating a vibration and noise monitoring method for an unmanned ride-hailing vehicle according to an embodiment of this application. Figure 2This is a sensor distribution diagram according to another embodiment of this application; Figure 3 A block diagram of a vibration and noise monitoring device for an autonomous ride-hailing vehicle according to an embodiment of this application; and Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0022] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0023] It should be noted that this application selects driverless ride-hailing vehicles as the monitoring object based on the following technical feasibility and necessity: Private cars involve personal privacy, making it difficult to obtain owner authorization for comprehensive sensor deployment; however, driverless ride-hailing vehicles, as commercial vehicles, have data collection falling under the scope of vehicle operation monitoring, possessing legality and public attributes; driverless ride-hailing vehicles are equipped with high-performance vehicle systems, multi-core processors, and large-capacity storage, meeting the real-time acquisition, caching, and preprocessing requirements of multi-channel vibration and noise data without additional hardware modifications, with significantly lower technical implementation costs than modifying private cars; the large-scale operation characteristics of driverless ride-hailing vehicles enable them to generate massive amounts of real-world NVH data throughout their entire lifecycle. Compared to traditional OEMs that can only obtain small sample data from R&D prototypes, this solution can obtain orders of magnitude more long-term data, covering more complex scenarios, climates, and usage intensity; driverless ride-hailing vehicles represent the future development direction of shared mobility, and with their deployment increasing exponentially, this solution will accumulate a valuable NVH database at the industry level, driving the vehicle NVH R&D model from "prototype testing" to "big data driven."

[0024] The vibration and noise monitoring method, device, and electronic equipment for driverless ride-hailing vehicles according to embodiments of this application are described below with reference to the accompanying drawings.

[0025] like Figure 1 As shown in the embodiments of this application, the vibration and noise monitoring method for driverless ride-hailing vehicles may include the following steps: Step S1: Obtain vibration and noise information at multiple locations on the vehicle using sensors. The vibration and noise information includes engine noise signal, steering wheel vibration signal, passenger side noise signal, driver side noise signal, right rear seat noise signal, left rear seat noise signal, and driver's seat rail vibration signal.

[0026] In the embodiments of this application, there may be multiple sensors, including sound sensors and vibration sensors, etc.

[0027] Specifically, during the vehicle's operation, vibration sensors and sound sensors installed on the vehicle acquire signals from their location in real time and transmit these signals to the vehicle terminal.

[0028] Specifically, in this embodiment of the application, the vibration and noise information may include engine noise signals, steering wheel vibration signals, passenger seat noise signals, driver seat noise signals, right rear seat noise signals, left rear seat noise signals, and driver seat rail vibration signals. For example... Figure 2 As shown, the engine vibration sensor is directly embedded in the body to ensure its reliability and lifespan; the steering wheel vibration sensor is installed at the top of the steering wheel; the passenger noise signal sensor is installed inside the passenger seat headrest; the driver noise signal sensor is installed inside the driver seat headrest; the right rear seat noise signal sensor is installed inside the seat headrest; the left rear seat noise signal sensor is installed inside the seat headrest; and the driver's seat rail vibration sensor is installed at the end of the inner rail.

[0029] The data acquisition process can employ conventional multi-channel synchronous acquisition methods in this field. For example, using a multi-channel data acquisition card built into the vehicle's infotainment system, with the engine vibration sensor as the reference channel, hardware synchronization of the signals from the other six sensors can be achieved. The sampling frequency is uniformly set to 2048Hz to ensure phase consistency of the signals at each measurement point. During the acquisition process, additional information such as the acquisition timestamp and vehicle VIN (Vehicle Identification Number) is included to provide a benchmark for subsequently establishing the time-series correspondence between vibration noise and driving status.

[0030] The sampling frequency is preferably 2048Hz, but can also be adjusted within the range of 1kHz-5kHz according to the analysis requirements.

[0031] Step S2: Obtain the vehicle's driving status information.

[0032] Specifically, in this embodiment, the driving state parameters include: speed, acceleration, braking rate, and steering speed. Driving state information is acquired in real time via the vehicle's CAN (Controller Area Network) bus or in-vehicle Ethernet. Vehicle speed and acceleration information originate from the vehicle control unit (VCU); braking rate information originates from the electronic stability control (ESC); and steering speed information originates from the electric power steering (EPS). The acquired raw signals are in CAN message format, parsed by the database container (DBC) and converted into physical quantities. These quantities are then timestamped with the vibration noise signal from step S1 to ensure a consistent vibration noise-driving state correspondence at the same time. All state parameters are resampled using the same sampling frequency as the vibration noise signal to eliminate time base bias.

[0033] Step S3: Create a correspondence table between vibration and noise information and driving status information based on time, and send the correspondence table to the cloud server. The cloud server analyzes the correspondence table to generate vehicle monitoring results.

[0034] Specifically, in this embodiment, the data alignment and table building process includes: timestamp standardization, extracting the data acquisition time data of each vibration and noise signal as a reference time axis, and converting the driving status message time data obtained from the CAN bus into the same clock reference; a data matching mechanism, adopting the nearest neighbor matching principle, selecting the driving status parameter with the smallest absolute time difference as the value of its corresponding operating status parameter for each vibration and noise data point, with a maximum allowable time deviation set at 10 milliseconds, and data exceeding this range being judged as invalid and discarded; and associating the data table structure, constructing a structured data table from the matched data, with each record containing a timestamp, the amplitude values ​​of six vibration and noise sensors, and four driving status parameters. In this embodiment, the data is temporarily stored in the vehicle system memory in JSON format, awaiting uploading.

[0035] In this embodiment, the upload process includes: data transmission, using the vehicle-mounted 5G or 4G communication module, the associated data table is packaged and uploaded in JSON format using the MQTT protocol, with each data packet not exceeding 128KB. TLS encryption is used during transmission to ensure data security. If communication is interrupted, the data is cached locally in the vehicle and automatically resumed after the network is restored; cloud storage, after the cloud server receives the data, it is categorized by vehicle VIN code and stored in a time-series database, and a timestamp-based index is established to support fast retrieval and batch export.

[0036] In this embodiment, the analysis process includes: statistical analysis, where the cloud server performs the following analyses: time-domain statistics, calculating the RMS value, peak factor, and kurtosis index of vibration noise at each measuring point to identify abnormal impacts; statistically analyzing the noise distribution in different vehicle speed ranges (e.g., 0-30km / h, 30-60km / h, and above 60km / h) to locate NVH problems under specific operating parameters; and trend prediction, constructing an NVH performance degradation curve based on continuous time data of the same vehicle to provide early warnings of potential faults. A visualized report containing vehicle NVH scores, exceeding measurement points, and trend warnings is generated for R&D personnel and the operation platform to make scheduling decisions.

[0037] This application first acquires vibration and noise information at multiple locations on the vehicle using sensors, as well as the vehicle's driving status information. Then, it creates a time-based mapping table between the vibration and noise information and the driving status information, and sends this table to a cloud server. The cloud server then analyzes the mapping table to generate vehicle monitoring results. This approach fills the monitoring gap in NVH performance after vehicle delivery and provides sufficient and accurate NVH data for vehicle development and service quality improvement.

[0038] In some embodiments of this application, both vibration noise information and driving status information include information acquisition time data.

[0039] Specifically, the requirement that both vibration and noise information and driving status information include data from the time of data acquisition is based on the following core considerations: vibration and noise signals and vehicle operating status are dynamically changing, and there is a strict causal relationship between the two. For example, a specific chassis noise may only be triggered when the vehicle travels over a bumpy road at a specific speed. Without a precise and unified time reference, it is impossible to accurately pair asynchronously acquired sensor data with driving status information.

[0040] This embodiment requires that both vibration and noise information and driving status information include information collection time data, providing a basis for creating a corresponding relationship table in step S3. This enables the cloud server to reproduce the complete vehicle operation scenario when the vibration and noise event occurs, thereby improving the accuracy of fault diagnosis and problem location. At the same time, it provides a continuous time series data foundation for analyzing the degradation trend of vehicle NVH performance over time.

[0041] In some embodiments of this application, the vibration and noise monitoring method for the driverless ride-hailing vehicle further includes: generating a vibration and noise rating survey form for the current trip when the current trip is about to end, displaying the vibration and noise rating survey form to the customer through the vehicle's central control screen, receiving the evaluation information input by the customer through the central control screen, and sending the evaluation information to the cloud server.

[0042] Specifically, when the system determines that the trip is about to end, for example, when the vehicle is about to reach its destination and begins to decelerate and stop, the vehicle's infotainment system automatically generates a vibration and noise rating questionnaire. This questionnaire is presented directly to the passenger via the central control screen of the driverless ride-hailing vehicle. Preferably, the questionnaire can be designed as a simple star rating or semantic scale, and the passenger completes and submits the evaluation via a touchscreen. After receiving the evaluation information, the system packages it together with the VIN code, trip ID, and timestamp of this trip.

[0043] This embodiment generates a vibration and noise rating questionnaire, accumulates passenger evaluation samples, and establishes a mapping relationship between objective parameters and subjective ratings, so that purely physical sensor data (such as acceleration and decibel values) can more accurately reflect people's real feelings.

[0044] In some embodiments of this application, the vibration and noise monitoring method for the driverless ride-hailing vehicle further includes: a cloud server generating monitoring results based on evaluation information and a corresponding relationship table.

[0045] Specifically, the cloud server uses the trip ID and timestamp as key indexes to accurately match the received evaluation information with the corresponding relationship table of this trip, forming a complete data record that integrates subjective and objective data; it accumulates massive amounts of subjective and objective matching data and analyzes the quantitative relationship between objective physical data and passengers' subjective feelings.

[0046] This embodiment introduces a passenger subjective evaluation mechanism, enabling the cloud server to establish a quantitative mapping relationship between objective vibration and noise parameters and subjective comfort perception. This solves the problem that purely physical data cannot directly reflect user experience and enhances the guiding value of monitoring results in vehicle NVH optimization.

[0047] In some embodiments of this application, when the journey of the driverless ride-hailing vehicle is about to end, a preset reminder message is played through the vehicle's audio system.

[0048] Specifically, the vehicle's infotainment system displays a survey form on the screen as the trip is about to end and automatically plays a voice reminder through the car's audio system.

[0049] This embodiment increases passenger attention and participation in the NVH rating survey by adding audio reminders, thereby accumulating a more sufficient sample of subjective evaluations.

[0050] In some embodiments of this application, the number of sensors is multiple, specifically including an engine vibration sensor, a steering wheel vibration sensor, a passenger noise signal sensor, a driver noise signal sensor, a right rear seat noise signal sensor, a left rear seat noise signal sensor, and a driver's seat rail vibration sensor.

[0051] Specifically, such as Figure 2 As shown, the engine vibration sensor is directly embedded in the engine body to obtain the most basic excitation signal; the steering wheel vibration sensor is installed at the top of the steering wheel to monitor the tactile vibration transmitted to the driver's hands; the passenger noise signal sensor, driver noise signal sensor, right rear seat noise signal sensor, and left rear seat noise signal sensor are respectively installed on the inner side of the headrest of the corresponding seats to accurately collect the noise level near each occupant's ear; the driver's seat rail vibration sensor is installed at the end of the inner rail of the driver's seat to monitor the overall perceptible vibration transmitted to the driver through the chassis and body.

[0052] This embodiment can comprehensively capture the auditory sensations of key locations in the passenger cabin by arranging noise sensors at the head of the driver, front passenger, and rear seats; and can directly obtain the tactile vibrations that have the most significant impact on the driver's sense of control and physical comfort by arranging vibration sensors on the steering wheel and driver's seat rail.

[0053] In another embodiment of this application, the sensor further includes an exhaust emission noise signal sensor, and correspondingly, the vibration noise information also includes an exhaust emission noise signal.

[0054] Specifically, the exhaust emission noise signal sensor is installed on the outer wall of the vehicle's exhaust pipe to collect exhaust system noise.

[0055] This embodiment provides a reference benchmark for cloud-based analysis by deploying exhaust emission noise signal sensors, helping to distinguish whether low-frequency noise originates from engine vibration or exhaust system vibration, thereby improving the completeness of vehicle NVH analysis.

[0056] In summary, the vibration and noise monitoring method for driverless ride-hailing vehicles according to the embodiments of this application first acquires vibration and noise information at multiple locations on the vehicle through sensors, as well as the vehicle's driving status information. Then, a correspondence table between the vibration and noise information and the driving status information is created based on time, and the correspondence table is sent to a cloud server so that the cloud server can analyze the correspondence table to generate vehicle monitoring results. This method can fill the monitoring gap in NVH performance after vehicle delivery and obtain sufficient and accurate NVH data for vehicle development and service quality improvement.

[0057] Corresponding to the above embodiments, this application also proposes a vibration and noise monitoring device for driverless ride-hailing vehicles.

[0058] like Figure 3 As shown, the vibration and noise monitoring device 100 for driverless ride-hailing vehicles in this application embodiment includes: a first acquisition module 110, a second acquisition module 120, and a processing module 130.

[0059] The first acquisition module 110 is used to acquire vibration and noise information at multiple locations on the vehicle through sensors. The vibration and noise information includes engine noise signal, steering wheel vibration signal, passenger side noise signal, driver side noise signal, right rear seat noise signal, left rear seat noise signal, and driver's seat rail vibration signal. The second acquisition module is used to acquire the vehicle's driving status information. The processing module is used to create a correspondence table between vibration and noise information and driving status information based on time, and send the correspondence table to a cloud server. The cloud server analyzes the correspondence table to generate vehicle monitoring results.

[0060] It should be noted that the above-described embodiments and explanations of the beneficial effects of the vibration and noise monitoring method for driverless ride-hailing vehicles also apply to the vibration and noise monitoring device for driverless ride-hailing vehicles in the embodiments of this application. To avoid redundancy, they will not be elaborated in detail here.

[0061] In summary, the vibration and noise monitoring device for driverless ride-hailing vehicles according to the embodiments of this application acquires vibration and noise information from multiple locations of the vehicle through the first acquisition module 110, acquires the vehicle's driving status information through the second acquisition module 120, and creates a correspondence table between the vibration and noise information and the driving status information based on time through the processing module 130. The correspondence table is then sent to a cloud server, which analyzes the table to generate vehicle monitoring results. This device can fill the gap in NVH performance monitoring after vehicle delivery and obtain sufficient and accurate NVH data for vehicle development and service quality improvement.

[0062] Corresponding to the above embodiments, this application also proposes an electronic device.

[0063] like Figure 4 As shown, the electronic device 200 of this application embodiment includes a memory 210, a processor 220, and a computer program stored in the memory and executable on the processor. The processor executes the program to implement any of the above-mentioned vibration and noise monitoring methods for driverless ride-hailing vehicles.

[0064] The electronic device according to the embodiments of this application implements any of the above-mentioned vibration and noise monitoring methods for driverless ride-hailing vehicles when the processor executes a computer program, thereby filling the monitoring gap of NVH performance after vehicle delivery and obtaining sufficient and authentic NVH data for vehicle research and development and service quality improvement.

[0065] Specifically, in the embodiments of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0066] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0067] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A method for monitoring vibration noise of an unmanned web hailing vehicle, characterized in that, The method comprises: obtaining vibration noise information at multiple positions of the vehicle through sensors, wherein the vibration noise information comprises engine noise signals, steering wheel vibration signals, co-pilot noise signals, main driver noise signals, right rear seat noise signals, left rear seat noise signals, and main driver seat rail vibration signals; obtaining driving state information of the vehicle; creating a correspondence table between the vibration noise information and the driving state information based on time, and sending the correspondence table to a cloud server, wherein the cloud server analyzes the correspondence table to generate a monitoring result of the vehicle. 2.The method of claim 1, wherein, Wherein, the vibration noise information and the driving state information both comprise information collection time data. 3.The method of claim 1, wherein, Further comprising: when the current trip of the vehicle is about to end, generating a vibration noise score questionnaire of the current trip of the vehicle, and displaying the vibration noise score questionnaire to the customer through the center console display screen of the vehicle; receiving evaluation information input by the customer through the center console display screen, and sending the evaluation information to the cloud server. 4.The method of claim 3, wherein, The cloud server is further used to generate the monitoring result according to the evaluation information and the correspondence table. 5.The method of claim 3, wherein, When the current trip of the vehicle is about to end, a preset reminder information is broadcast through the vehicle audio. 6.The method of claim 1, wherein, The number of sensors is multiple, and the sensors comprise an engine vibration sensor, a steering wheel vibration sensor, a co-pilot noise signal sensor, a main driver noise signal sensor, a right rear seat noise signal sensor, a left rear seat noise signal sensor, and a main driver seat rail vibration sensor. 7.The method of claim 6, wherein, Wherein, the engine vibration sensor is directly embedded in the engine body, the steering wheel vibration sensor is installed at the top end of the steering wheel, the co-pilot noise signal sensor is installed inside the head of the co-pilot seat, the main driver noise signal sensor is installed inside the head of the main driver seat, the right rear seat noise signal sensor is installed inside the head of the seat, the left rear seat noise signal sensor is installed inside the head of the seat, and the main driver seat rail vibration sensor is installed at the inner end of the main driver seat rail. 8.The method of claim 6, wherein, The vibration noise information further comprises an exhaust emission noise signal, and the sensors further comprise an exhaust emission noise signal sensor, wherein the exhaust emission noise signal sensor is installed on the exhaust emission pipe. 9.A device for monitoring vibration and noise of an unmanned web hailing vehicle, characterized in that, The method comprises: a first obtaining module for obtaining vibration noise information at multiple positions of the vehicle through sensors, wherein the vibration noise information comprises engine noise signals, steering wheel vibration signals, co-pilot noise signals, main driver noise signals, right rear seat noise signals, left rear seat noise signals, and main driver seat rail vibration signals; a second obtaining module for obtaining driving state information of the vehicle; a processing module for creating a correspondence table between the vibration noise information and the driving state information based on time, and sending the correspondence table to a cloud server, wherein the cloud server analyzes the correspondence table to generate a monitoring result of the vehicle.

10. An electronic device, comprising: The method comprises: A memory, a processor, and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the method for monitoring vibration and noise of an unmanned network car according to any one of claims 1-9.

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