CN114840240A - Vehicle OTA (over the air) upgrade safety control method, system and storage medium based on image scene recognition - Google Patents
Vehicle OTA (over the air) upgrade safety control method, system and storage medium based on image scene recognition Download PDFInfo
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Abstract
The invention discloses a vehicle OTA (over the air) upgrading safety control method, a vehicle OTA upgrading safety control system and a storage medium based on image scene recognition. After the upgrade package is downloaded, the vehicle machine calls a camera to acquire external environment information of the vehicle; the vehicle machine sends the acquired external environment information to a background to perform image scene recognition, and acquires a background recognition result; the vehicle machine acquires the internal environment information of the vehicle; the vehicle machine judges whether an upgrading condition is met or not according to the background recognition result and the internal environment information; if the upgrade condition is met, the car machine prompts a user to start an upgrade program; otherwise, the user is not prompted to start the upgrading program, and the reason for not starting the upgrading program is displayed. The invention can identify whether the environment around the vehicle is suitable for OTA upgrading or not through the image scene during upgrading, thereby avoiding the safety problem during upgrading and ensuring the safety of the vehicle and personnel during upgrading.
Description
Technical Field
The invention relates to the technical field of vehicle safety control, in particular to a vehicle OTA (over the air) upgrade safety control method, a vehicle OTA upgrade safety control system and a storage medium based on image scene recognition.
Background
The general process of OTA upgrading of vehicles in the current industry is that a user downloads an upgrading package on line at a vehicle end; and after the downloading is finished, the vehicle machine prompts the user to upgrade. If only vehicle-mounted software is involved, the upgrading control module can detect conditions such as vehicle speed, power supply gear, vehicle residual space and the like, and upgrading can be performed when the conditions are met. And if the upgrading relates to vehicle control software, such as a gateway, a controller such as a BCM (binary coded decimal) and the like, the conditions that the gear of the variable counter is P gear, the hand brake is pulled up, the battery power and the voltage are met are also met.
For upgrading related vehicle control software, although the conditions need to be met before upgrading, and the function of ensuring the safety of vehicles and personnel during upgrading is achieved, risks and problems still exist in the upgrading mode. For example, when a user drives to an intersection, if the user is a red light at the moment, the hand brake is pulled up when the user stops and waits, other conditions such as a power supply gear are also met, the condition for upgrading the vehicle control software is met, if the user starts upgrading at the moment, the gateway enters the flashing gear, other gears cannot be switched, the vehicle cannot drive, the gateway blocks the intersection, traffic is hindered, and even a traffic accident occurs because the vehicle cannot drive, and the consequence is unreasonable.
Therefore, how to further ensure the safety of the OTA upgrade of the vehicle and avoid the above risks is very necessary.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to solve the problem of potential safety hazard in vehicle OTA (over the air) upgrading in the prior art, and provides a vehicle OTA upgrading safety control method, a vehicle OTA upgrading safety control system and a storage medium based on image scene recognition, wherein whether the environment around a vehicle is suitable for OTA upgrading can be recognized through the image scene during upgrading, so that the safety problem during upgrading is avoided, and the safety of the vehicle and personnel during upgrading is ensured.
In order to solve the technical problems, the invention adopts the following technical scheme:
a vehicle OTA upgrade safety control method based on image scene recognition comprises the following steps,
after the upgrade package is downloaded, the vehicle machine calls a camera to acquire external environment information of the vehicle;
the vehicle machine sends the acquired external environment information to a background to perform image scene recognition, and acquires a background recognition result;
the vehicle machine acquires the internal environment information of the vehicle;
the vehicle machine judges whether an upgrading condition is met or not according to the background recognition result and the internal environment information;
if the upgrade condition is met, the car machine prompts a user to start an upgrade program; otherwise, the user is not prompted to start the upgrading program, and the reason for not starting the upgrading program is displayed;
wherein the external environment information includes image information of surroundings of the vehicle; the internal environment information comprises a power supply gear, battery electric quantity, a vehicle machine storage space and a transmission gear.
Further, when the upgrading condition is met, the vehicle machine prompts a user to start the upgrading program, and after receiving an instruction of confirming upgrading by the user, the vehicle machine calls the camera again to acquire external environment information of the vehicle, sends the external environment information to the background to perform image scene recognition, and acquires a background recognition result to confirm that the upgrading condition is met again.
Further, the car machine sends the acquired external environment information to a background for image scene recognition, and acquires the background recognition result,
the vehicle machine calls an open application programming interface of the background to send the external environment information to the background;
the background uses a convolutional neural network model to perform image scene recognition on the external environment information, and determines the current scene of the vehicle;
and the background returns the recognition result to the vehicle machine.
And further, the background returns the recognition result to the vehicle machine through interprocess communication.
Further, the returned identification result is JSON data about the scene; the fields of the data contain location information and road information.
Further, satisfying the following conditions is considered as satisfying the upgrade conditions:
the position information is a non-intersection and non-forbidden parking area; the road information is non-high speed, non-bridge and non-tunnel; and the number of the first and second electrodes,
the speed of a vehicle is 0, the power supply gear is an ON gear, the vehicle machine residual space is enough, the gear of a variable counter is a P gear, a hand brake is pulled up, and the electric quantity and the voltage of a battery are sufficient.
The invention also provides a vehicle OTA upgrading safety control system based on image scene recognition, which is used in the method and comprises a camera, a vehicle machine and a background; the vehicle machine comprises an image processing module and an upgrading control module; wherein the content of the first and second substances,
the camera is used for acquiring external environment information of the vehicle after receiving the call of the vehicle machine and sending the acquired external environment information to an image processing module of the vehicle machine;
the image processing module is used for processing the images in the acquired external environment information, including image enhancement and image coding compression; the image processing device is also used for calling a background open application programming interface to send the processed image to the background; the system is also used for receiving an identification result returned after the background carries out image scene identification, and further transmitting the identification result to the upgrading control module through interprocess communication;
the upgrading control module is used for judging whether upgrading conditions are met or not according to the background recognition result and the internal environment information;
the background is used for receiving the image processed by the image processing module; the convolutional neural network model is also used for carrying out image scene recognition on the acquired image, judging the current scene of the vehicle and returning scene information, namely the recognition result, to the image processing module.
Further, the camera is connected with the vehicle machine through an LVDS wire and is mounted on a certain node of the vehicle machine; the data of the camera can be transmitted to the image processing module through the related bottom layer drive.
Further, the background is prestored with a trained convolutional neural network model.
The invention also provides a storage medium, which stores one or more programs, and when the one or more programs are executed by a processor, the steps of the vehicle OTA upgrading safety control method based on the image scene recognition are executed.
Compared with the prior art, the invention has the following beneficial effects:
according to the method provided by the invention, before OTA upgrading of the vehicle, not only the internal environment of the vehicle is confirmed, but also the external environment of the vehicle is confirmed through the camera, the image of the external environment is identified through the trained convolutional neural network model of the background, and OTA upgrading of the vehicle is carried out after the external environment meeting the upgrading condition is confirmed, so that whether the environment around the vehicle is suitable for OTA upgrading can be identified through the image scene during upgrading, the safety problem during upgrading is avoided, particularly the safety problem during upgrading of vehicle control software can be effectively avoided, and the safety of the vehicle and personnel during upgrading is ensured.
Drawings
Fig. 1 is a flowchart of a vehicle OTA upgrade security control method based on image scene recognition according to the present invention.
Fig. 2 is a schematic diagram of a vehicle OTA upgrade security control system based on image scene recognition according to the present invention.
Fig. 3 is a flowchart of a vehicle OTA upgrade security control method based on image scene identification in embodiment 3 of the present invention.
Detailed Description
The invention will be further explained with reference to the drawings and the embodiments.
Example one
The embodiment discloses a vehicle OTA upgrading safety control method based on image scene recognition.
A vehicle OTA upgrading security control method based on image scene recognition is disclosed, referring to FIG. 1, comprising the following steps,
after the upgrade package is downloaded, the vehicle machine calls the camera to acquire the external environment information of the vehicle.
And the vehicle machine sends the acquired external environment information to the background to perform image scene recognition, and acquires a background recognition result.
The vehicle machine acquires the internal environment information of the vehicle.
And the vehicle machine judges whether the upgrading condition is met according to the background recognition result and the internal environment information.
And if the upgrading condition is met, the car machine prompts a user to start an upgrading program. Otherwise, the user is not prompted to start the upgrading program, and the reason for not starting the upgrading program is displayed.
Wherein the external environment information includes image information around the vehicle. The internal environment information comprises a power supply gear, battery electric quantity, a vehicle machine storage space and a transmission gear.
When the upgrading condition is met, the vehicle machine prompts a user to start the upgrading program, receives an instruction of the user for confirming upgrading, and then calls the camera again to obtain the external environment information of the vehicle, sends the external environment information to the background for image scene recognition, and obtains the recognition result of the background so as to confirm that the upgrading condition is met again.
Further, the car machine sends the acquired external environment information to a background for image scene recognition, and acquires the background recognition result,
and the vehicle machine calls an open application programming interface of the background to send the external environment information to the background.
And the background uses the convolutional neural network model to perform image scene recognition on the external environment information, and determines the current scene of the vehicle.
And the background returns the recognition result to the vehicle machine.
And when the system is specifically implemented, the background returns the recognition result to the vehicle machine through interprocess communication.
In specific implementation, the returned identification result is JSON data about the scene. The fields of the data contain location information and road information.
Further, satisfying the following conditions is considered as satisfying the upgrade conditions:
the position information is a non-intersection and non-forbidden parking area; the road information is non-high speed, non-bridge, non-tunnel.
The vehicle speed is 0, the power supply gear is an ON gear, the vehicle residual space is enough, the gear of the variable counter is a P gear, the hand brake is pulled up, and the electric quantity and the voltage of the battery are sufficient.
According to the method provided by the invention, before OTA upgrading of the vehicle, not only the internal environment of the vehicle is confirmed, but also the external environment of the vehicle is confirmed through the camera, the image of the external environment is identified through the trained convolutional neural network model of the background, and OTA upgrading of the vehicle is carried out after the external environment meeting the upgrading condition is confirmed, so that whether the environment around the vehicle is suitable for OTA upgrading can be identified through the image scene during upgrading, the safety problem during upgrading is avoided, particularly the safety problem during upgrading of vehicle control software can be effectively avoided, and the safety of the vehicle and personnel during upgrading is ensured.
Example two
On the basis of the first embodiment, the embodiment discloses a vehicle OTA upgrade security control system based on image scene recognition, which is used in the method.
The vehicle OTA upgrading safety control system based on image scene recognition is shown in figure 2 and comprises a camera, a vehicle machine and a background. The car machine comprises an image processing module and an upgrading control module. Wherein the content of the first and second substances,
the camera is used for acquiring external environment information of the vehicle after receiving the call of the vehicle machine and sending the acquired external environment information to the image processing module of the vehicle machine.
The image processing module is used for processing the images in the acquired external environment information, and the processing comprises image enhancement and image coding compression. And the image processing device is also used for calling a background open application programming interface to send the processed image to the background. And the system is also used for receiving an identification result returned after the background identifies the image scene, and further transmitting the identification result to the upgrading control module through interprocess communication.
And the upgrading control module is used for judging whether upgrading conditions are met or not according to the background recognition result and the internal environment information.
The background is used for receiving the image processed by the image processing module. The convolutional neural network model is also used for carrying out image scene recognition on the acquired image, judging the current scene of the vehicle and returning scene information, namely the recognition result, to the image processing module.
During specific implementation, the camera is connected with the vehicle machine through the LVDS wire and is mounted on a certain node of the vehicle machine. The data of the camera can be transmitted to the image processing module through the related bottom layer drive.
Further, the background is prestored with a trained convolutional neural network model.
Because the vehicle OTA upgrading safety control system based on the image scene recognition is provided, before the vehicle is subjected to OTA upgrading, the external environment of the vehicle can be confirmed through the camera, the image of the external environment is recognized through the trained convolutional neural network model at the background, after the external environment and the internal environment meeting the upgrading conditions are confirmed, the vehicle OTA upgrading is carried out, the safety problem during upgrading can be avoided, particularly, the safety problem existing during upgrading of vehicle control software can be effectively avoided, and the safety of the vehicle and personnel during upgrading is ensured.
EXAMPLE III
In order to further explain the practical effect of the vehicle OTA upgrade security control based on image scene identification, the embodiment discloses a vehicle OTA upgrade security control method based on image scene identification and an application scene.
Referring to fig. 3, at the car end, after the upgrade package is downloaded, the car machine can automatically call a camera to shoot, and perform scene recognition on the obtained image.
Specifically, when the user selects upgrading, the car machine automatically calls the camera to shoot the periphery of the car, and transmits the shot image to the image processing module in the car machine, and the module processes the image and transmits the image data to the background. And the background identifies the image scene so as to judge what scene is, and returns the result to the image processing module. And the image processing module transmits the obtained result information to the upgrading control module, and the upgrading control module judges whether the vehicle machine can be upgraded or not according to the scene information and the condition of the vehicle.
The camera is connected with the vehicle machine through the LVDS lines and is mounted on a certain node of the vehicle machine. The data of the camera can be transmitted to an image processing module of a Framework layer through related underlying drive.
The module processes the image and then calls a related open API (Application Programming Interface) in the background to transfer the image data to the background tsp. And the background uses a trained Convolutional Neural Network (CNN) to perform image scene recognition, so as to judge what scene is, and returns the result to the image processing module.
The result information can be further transmitted to an upgrade control module of an Application layer (i.e., Application layer) through aid l (interprocess communication). The information may be JSON data about a scene, and the fields of the data are: location information, road information (subsequently expandable).
If the external scene meets the upgrading requirement and the internal environment of the vehicle machine also meets the upgrading conditions (power supply gear, battery capacity, storage space, transmission gear and the like), the user is prompted, and the vehicle machine can be upgraded at present. If any is not satisfied, the user is not prompted and the upgrade conditions are checked again at intervals.
Specifically, the condition for satisfying the upgrade includes: the location information must be non-intersection, non-forbidden area. The road information must be non-high speed, non-bridge, non-tunnel. The state of the vehicle must meet the requirements that the vehicle speed is 0, the power supply gear is an ON gear, the residual space of the vehicle is enough, the gear of the variable counter is a P gear, the hand brake is pulled up, and the electric quantity and the voltage of the battery are sufficient.
In addition, after the user actively triggers the upgrade, in order to ensure that the conditions are met in real time, the external environment is shot again and recognized, and if the scene meets the upgrade requirement and the state of the vehicle machine also meets the upgrade conditions, the real process can be directly entered. If there are unsatisfied conditions, then the upgrade is not entered and the user is prompted for the reason for the inability to upgrade. Therefore, the safety of the vehicle and personnel during OTA upgrade of the vehicle is effectively ensured.
Example four
The embodiment discloses a storage medium on the basis of the first embodiment.
A storage medium storing one or more programs which, when executed by a processor, perform the steps of the image scene recognition based vehicle OTA upgrade security control method. . The computer readable storage medium may be a usb disk, hard disk, or other device with storage capabilities.
As mentioned above, the reminder system of the present invention is not limited to the configuration, and other systems capable of implementing the embodiments of the present invention may fall within the protection scope of the present invention.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention and not for limiting the technical solutions, and those skilled in the art should understand that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions, and all that should be covered by the claims of the present invention.
Claims (10)
1. A vehicle OTA upgrade safety control method based on image scene recognition is characterized by comprising the following steps,
after the upgrade package is downloaded, the vehicle machine calls a camera to acquire external environment information of the vehicle;
the vehicle machine sends the acquired external environment information to a background to perform image scene recognition, and acquires a background recognition result;
the vehicle machine acquires the internal environment information of the vehicle;
the vehicle machine judges whether an upgrading condition is met or not according to the background recognition result and the internal environment information;
if the upgrade condition is met, the car machine prompts a user to start an upgrade program; otherwise, the user is not prompted to start the upgrading program, and the reason for not starting the upgrading program is displayed;
wherein the external environment information includes image information around the vehicle; the internal environment information comprises a power supply gear, battery electric quantity, a vehicle machine storage space and a transmission gear.
2. The vehicle OTA upgrade security control method based on image scene recognition according to claim 1, wherein when the upgrade condition is satisfied, the vehicle machine prompts the user to start the upgrade program, and after receiving an instruction for the user to confirm the upgrade, the vehicle machine calls the camera again to acquire the external environment information of the vehicle, and sends the external environment information to the background to perform image scene recognition, and acquires the result of the background recognition to confirm that the upgrade condition is satisfied again.
3. The OTA upgrade security control method for vehicle based on image scene recognition according to claim 1, wherein the vehicle machine sends the acquired external environment information to the background for image scene recognition, and the acquiring the background recognition result comprises,
the vehicle machine calls an open application programming interface of the background to send the external environment information to the background;
the background uses a convolutional neural network model to perform image scene recognition on the external environment information, and determines the current scene of the vehicle;
and the background returns the recognition result to the vehicle machine.
4. The OTA vehicle upgrade security control method based on image scene recognition according to claim 3, wherein the background returns the recognition result to the vehicle machine through inter-process communication.
5. The vehicle OTA upgrade security control method based on image scene recognition according to claim 3 or 4, wherein the returned recognition result is JSON data about a scene; the fields of the data contain location information and road information.
6. The vehicle OTA upgrade security control method based on image scene recognition according to claim 1, wherein the following conditions are satisfied:
the position information is a non-intersection and non-forbidden parking area; the road information is non-high speed, non-bridge and non-tunnel; and the number of the first and second groups is,
the speed of a vehicle is 0, the power supply gear is an ON gear, the vehicle machine residual space is enough, the gear of a variable counter is a P gear, a hand brake is pulled up, and the electric quantity and the voltage of a battery are sufficient.
7. A vehicle OTA upgrade security control system based on image scene recognition is used in the method of any one of claims 1-6, and comprises a camera, a vehicle machine and a background; the car machine comprises an image processing module and an upgrading control module; wherein the content of the first and second substances,
the camera is used for acquiring external environment information of the vehicle after receiving the call of the vehicle machine and sending the acquired external environment information to an image processing module of the vehicle machine;
the image processing module is used for processing the images in the acquired external environment information, including image enhancement and image coding compression; the image processing device is also used for calling a background open application programming interface to send the processed image to the background; the system is also used for receiving an identification result returned after the background carries out image scene identification, and further transmitting the identification result to the upgrading control module through interprocess communication;
the upgrading control module is used for judging whether upgrading conditions are met or not according to the background recognition result and the internal environment information;
the background is used for receiving the image processed by the image processing module; the convolutional neural network model is also used for carrying out image scene recognition on the acquired image, judging the current scene of the vehicle and returning scene information, namely the recognition result, to the image processing module.
8. The vehicle OTA upgrade security control system based on image scene recognition according to claim 7, wherein the camera is connected to the vehicle via LVDS line and mounted on a certain node of the vehicle; the data of the camera can be transmitted to the image processing module through the related bottom layer drive.
9. The vehicle OTA upgrade security control system based on image scene recognition according to claim 7, wherein the background has a trained convolutional neural network model in advance.
10. A storage medium storing one or more programs which, when executed by a processor, perform the steps of the image scene recognition based vehicle OTA upgrade security control method according to any one of claims 1 to 6.
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| CN116954657A (en) * | 2023-07-19 | 2023-10-27 | 红石阳光(深圳)科技有限公司 | Policy control method and system for upgrading automobile OTA |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116954657A (en) * | 2023-07-19 | 2023-10-27 | 红石阳光(深圳)科技有限公司 | Policy control method and system for upgrading automobile OTA |
| CN116954657B (en) * | 2023-07-19 | 2024-04-12 | 红石阳光(深圳)科技有限公司 | Policy control method and system for upgrading automobile OTA |
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