CN111741105A - Real-time transmission system and method for problem data of intelligent driving system - Google Patents
Real-time transmission system and method for problem data of intelligent driving system Download PDFInfo
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Abstract
The invention provides a real-time transmission system for problem data of an intelligent driving system, which comprises the intelligent driving system, a central gateway, data transmission equipment, a rear-end cloud platform and a trigger switch, wherein the intelligent driving system, the central gateway, the data transmission equipment and the rear-end cloud platform are sequentially connected; the intelligent driving system, the central gateway, the data transmission equipment and the trigger switch are all arranged on the vehicle, and the rear-end cloud platform is remote; the intelligent driving system consists of sensing modules, each sensing module is provided with a data caching module, and the data caching module caches recent data in real time; the trigger switch sends out the latest data in the latest T time cached by all the data caching modules as problem data at the moment when the trigger switch passes T/2 after the trigger switch is triggered; the central gateway is set to receive the problem data and sends the problem data to the back-end cloud platform in real time through the data transmission equipment. The invention also provides a real-time transmission method. The system can efficiently and timely acquire problem data in real time and upload the problem data to a back-end cloud platform.
Description
Technical Field
The invention belongs to the field of intelligent driving systems, and particularly relates to a real-time transmission system and method for problem data of an intelligent driving system.
Background
In daily use of Advanced Driving Assistance (ADAS) systems and automatic driving Assistance (AD) systems (referred to as ADAS/AD systems for short) based on sensors such as millimeter wave radars and cameras, one of the most frequent user feedback problems is that the sensors and the ADAS/AD systems cannot be used normally, and alarm prompts are generated, so that user experience and subsequent purchase willingness are influenced. On the other hand, false alarm and false alarm of the ADAS/AD system in the using process of the vehicle also can affect the safety of users and vehicles. This results in a certain degree of poor customer acceptance of the ADAS/AD system, so that the mainframe factory configuration rate is low. Experience has shown that data of the vehicle and the ADAS/AD system (referred to as "problem data" for short) when the ADAS/AD system is abnormal is of great importance for analyzing and solving the problem. However, for various reasons, no effective method is available for obtaining the data.
Under the normal condition, when an automobile manufacturer and an ADAS/AD system supplier receive the ADAS/AD system report omission, false report, brake error, brake omission or other function abnormity fed back by a terminal user, the possible reason of system failure can be analyzed according to the description of the user, or the problem can be reproduced on site according to the scene described by a customer, data is collected, and reason analysis is carried out. The process is time consuming and labor intensive, and the problem is not necessarily reproducible under most conditions, so that the reason cannot be located and the problem cannot be solved. Therefore, timely, accurate and efficient data collection cannot be realized.
In addition, in general, an intelligent driving system needs to go through hundreds of kilometers, thousands of kilometers or tens of thousands of kilometers to generate an abnormality. If the actual vehicle is used for reproducing the fault and collecting data, huge financial investment is consumed, and the data collection cost is high.
In addition, in general, the intelligent driving system needs to be verified through road tests over long distances (thousands of kilometers, tens of thousands of kilometers or hundreds of thousands of kilometers) so as to obtain the approval of the automobile manufacturer. ADAS/AD suppliers usually collect a large amount of road test data and spend a large amount of manual labeling, so that limited problematic scenes and data are found, most of the data are invalid, and the software iterative upgrade is not facilitated.
Disclosure of Invention
The invention aims to provide a real-time problem data transmission system and method, which can efficiently and timely acquire problem data in real time and upload the problem data to a back-end cloud platform.
In order to achieve the purpose, the invention provides a real-time transmission system for problem data of an intelligent driving system, which comprises the intelligent driving system, a central gateway, data transmission equipment, a rear-end cloud platform and a trigger switch, wherein the intelligent driving system, the central gateway, the data transmission equipment and the rear-end cloud platform are sequentially connected; the intelligent driving system, the central gateway, the data transmission equipment and the trigger switch are all arranged on the vehicle, and the rear-end cloud platform is remote; the intelligent driving system consists of at least one sensing module, each sensing module is a sensor and is provided with a data caching module, and the data caching modules of all the sensing modules are set to cache the latest data from the vehicle and the intelligent driving system in real time; the trigger switch is set to send out the latest data in the latest T time cached by the data caching modules of all the sensing modules as problem data at the moment when the trigger switch passes T/2 after the trigger switch is triggered; the central gateway is configured to receive the problem data and send the problem data to the back-end cloud platform in real time through the data transmission device.
The number of the sensing modules is one or more; and when the number of the sensing modules is multiple, the multiple sensing modules are different types of sensors.
The sensor type of the sensing module at least comprises a millimeter wave radar and/or a camera.
The most recent data includes: vehicle data including voltage, vehicle speed, steering wheel angle, and yaw angle; sensor data; and critical data of the application function including a steering control signal, an acceleration/deceleration signal, an alarm signal, and a braking force request.
The vehicle data is stored in a perception module of any sensor type; the sensor data includes: millimeter wave radar data which comprises radar states, a target reflection point list and a tracking target list and is stored in a sensing module of a millimeter wave radar type; and/or camera data, including camera state, picture data and target list, stored in the sensing module of camera type; the location of the storage of the key data of the application function is determined by the type of the application function.
The trigger switch is directly connected with the intelligent driving system through a hard wire; or the trigger switch is connected with a controller on the vehicle, and the controller is connected with the central gateway through a bus; or the trigger switch is a button on a human-computer interaction interface, and the human-computer interaction interface is in communication connection with the central gateway.
Each perception module is provided with a communication module respectively, and the problem data is sent out by driving the communication module; and the central gateway is in communication connection with the back-end cloud platform through a data transmission device, and the data transmission device is configured to upload the problem data to the back-end cloud platform through a wireless network.
The intelligent driving system is an advanced driving assistance system or an automatic driving system.
In another aspect, a method for real-time transmission of problem data for a smart driving system includes:
s1: the data collection is carried out by adopting the real-time transmission system of the problem data of the intelligent driving system, and the data collection method comprises the following steps:
s11: the vehicle runs, the intelligent driving system is activated, and a data caching module of the intelligent driving system caches recent data in real time;
s12: when a driver finds that the intelligent driving system is abnormal, the driver presses down a trigger switch;
s13: the data caching module continues to cache the latest data in the T/2 time;
s14: at the moment when T/2 passes after the trigger switch is triggered, sending out the latest data in the latest T time in the data cache module as problem data, and sending the problem data to the back-end cloud platform through the central gateway;
s15: the back-end cloud platform receives the problem data and stores the problem data into a problem database;
in step S15, before storing in the question database, the method further includes performing a coarse classification on the question data, where the coarse classification is performed according to the scenario or according to the application function.
Each perception module is provided with a communication module respectively, and the problem data is sent out by driving the communication module;
the real-time transmission method of the problem data for the intelligent driving system further comprises the following steps:
s2: adopting the problem data to optimize the embedded software in the intelligent driving system to obtain new version software, comprising:
s21: adopting a rear-end cloud platform to refine, classify and arrange problem data;
s22: the problem data are led into an ADAS/AD off-line simulation system, so that abnormal problems corresponding to the problem data in the intelligent driving system can be reproduced in the ADAS/AD off-line simulation system;
s23: analyzing reasons of the problem data, and optimizing a software algorithm of embedded software of the intelligent driving system according to the reasons;
s24: verifying the optimized embedded software using an existing scene library database;
s25: repeating the step S23 and the step S24 until the abnormal problem is repaired, and obtaining verified embedded software;
s26: adding the data scene corresponding to the problem data into the existing scene library database;
s3: adopting new version software to carry out software iteration updating, comprising the following steps:
s31: encrypting the new version software by adopting a back-end cloud platform to generate an encrypted software package;
s32: the back-end cloud platform pushes a software upgrading notice to the vehicle periodically;
s33: a driver of the vehicle selecting a software update;
s34: the rear-end cloud platform verifies the legality of the vehicle;
s35: sending the encrypted software package to the data transmission equipment;
s36: the data transmission equipment verifies the validity of the encrypted software package and decrypts the encrypted software package;
s37: and upgrading the embedded software in the intelligent driving system through a central gateway and a boot loader of the intelligent driving system.
According to the real-time transmission system for the problem data of the intelligent driving system, the trigger switch is arranged, and the intelligent driving system, the central gateway and the rear-end cloud platform are sequentially connected, so that when all drivers have faults in use, the system can timely collect the data by pressing the trigger button by the drivers, and on one hand, the real-time sensor data, the vehicle information data and the scene when the problems occur are timely, efficiently and conveniently collected; on the other hand, data collection by manufacturers is not needed, so that the data collection cost is low; in addition, only the problem data when the driver presses the trigger button is collected, so the collected data basically belong to effective data, the data acquisition and labeling process is saved, and the labor cost is greatly reduced.
In addition, the real-time transmission system method for the problem data of the intelligent driving system uploads the problem data to a back-end cloud platform for a background engineer to analyze the data, provide a solution and optimize software. The optimized software can be pushed to a user, and the user can select to update the new software version through OTA at a proper time and update the system. Thus, a closed loop system of continuous data collection and software iterative upgrade is formed. The optimized system software can not only take care of the universality of the user, but also summarize the specificity of the user, and the convenience of software iteration and upgrading is improved.
Drawings
Fig. 1 is a schematic structural diagram of a problem data real-time transmission system for an intelligent driving system according to the present invention.
Fig. 2-4 are schematic diagrams of the architecture of a real-time problem data transmission system for an intelligent driving system according to three embodiments of the present invention.
Fig. 5 is a data collection flow chart of the real-time problem data transmission method for the intelligent driving system according to the invention.
Fig. 6 is a software optimization flowchart of the real-time problem data transmission method for the intelligent driving system according to the present invention.
Fig. 7 is a software iteration updating flow chart of the real-time transmission method of problem data for the intelligent driving system of the invention.
Detailed Description
The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
Fig. 1 shows a real-time transmission system for problem data of an intelligent driving system, which includes an intelligent driving system 100, a central gateway 3, a data transmission device 4, a back-end cloud platform 5, and a trigger switch 2 connected to the intelligent driving system 100. The intelligent driving system 100, the central gateway 3, the data transmission device 4 and the trigger switch 2 are all installed on a vehicle, and the rear-end cloud platform 5 is remote.
The intelligent driving system 100 is composed of at least one sensing module 1, and each sensing module 1 is a sensor. The number of the sensing modules is one or more, and when the number of the sensing modules 1 is more, the plurality of sensing modules 1 may be different types of sensors. The sensor type of the sensing module 1 may be, for example, a millimeter wave radar and/or a camera, etc. Therefore, the intelligent driving system 100 may be a single sensor composed of a millimeter wave radar or a camera, or a fusion system (1R1V) composed of a forward millimeter wave radar and a forward-looking camera, or a fusion system (3R1V) composed of a forward millimeter wave radar and two rear angle millimeter wave radars and a forward-looking camera, or a fusion system (5R1V) composed of a forward millimeter wave radar and four front and rear angle millimeter wave radars and a forward-looking camera. The smart driving system 100 is configured to implement a variety of application functions including, but not limited to: BSD, LCA, RCTA/B, FCTA/B, DOW, RCW, AEB, ACC, LKA, ELK, DCLC, TJA, TJP, target output, etc. In the present embodiment, the smart driving system 100 may be an ADAS system or an AD system.
Each perception module 1 has a data buffer module 11 and a communication module 12.
Wherein the data caching module 11 of all perception modules 1 is arranged to cache recent data from the vehicle and the intelligent driving system 100 in real time, e.g. arranged to store recent data for at least the latest T time. The recent data may or may not include "problem data" of the vehicle and the intelligent driving system 100 in the case of missing reports, false brakes, missed brakes, abnormal application functions of other intelligent driving systems 100, and the like. The data cache module 11 is an essential component of the perception module 1 of the intelligent driving system 100.
The communication module 12 is an interface of a bus network such as a vehicle-mounted ethernet or CAN/CANFD. A communication module 12 is connected to the central gateway 3.
Recent data typically includes, but is not limited to, the following:
1) vehicle data, including voltage, vehicle speed, steering wheel angle, yaw angle, etc., may be stored in any sensor type sensing module 1, for example, in a millimeter wave radar type sensing module 1, or in a camera type sensing module 1, but in any case, the vehicle data is stored in the intelligent driving system 100;
2) sensor data, the sensor data comprising:
millimeter wave radar data including radar states, a target reflection point list, a tracking target list and the like is stored in the sensing module 1 of the millimeter wave radar type; and/or
The camera data comprises a camera state, picture data, a target list and the like, and is stored in the sensing module 1 of the camera type; and
3) the key data of the application function, including the steering control signal, the acceleration/deceleration signal, the alarm signal, the braking force request, etc., are stored at specific locations determined by the type of the application function, and when the number of the sensing modules 1 is multiple, the key data may be stored in different sensing modules in a scattered manner. For example, the key data of a part of the application functions may be stored in the millimeter wave radar type perceiving module 1, and the key data of another part of the application functions may be stored in the camera perceiving module. In any case, however, critical data for the application function is stored in the smart driving system 100.
The trigger switch 2 is a trigger switch for data recording and transmission. The trigger switch 2 is set to send out the latest data within the T time (for example, T is 1 minute) buffered by the data buffer module 11 of all the sensing modules 1 as the problem data by driving the communication module 12 of all the sensing modules 1 at the time when T/2 passes after the trigger of the trigger switch. Once the driver notices that the intelligent driving system 100 has false alarm, false brake, brake leakage or other application function abnormality, the driver presses the trigger switch, and the intelligent driving system 100 sends out the problem data of the vehicle and the intelligent driving system 100 in the time T in the system cache at the moment when the T/2 passes after the trigger. The trigger switch can be a physical button switch, and can also be a soft switch on a central control display screen or other types of trigger signals. Wherein the size of T depends on the size of the data cache module 11. T ═ 1 minute is a relatively suitable value. In addition, T can be set to other values, and the value of T should be between [1 second, 10 minutes ].
The central gateway 3 is responsible for data interaction between bus networks (CAN/CAN-FD, LIN, Flexray, vehicle ethernet, etc.) on the vehicle, is configured to receive the problem data sent by the trigger switch 2, and sends the problem data to the back-end cloud platform 5 in real time through the data transmission device 4.
The back-end cloud platform 5 is configured to store the problem data for a back-end engineer to perform data analysis, to provide a solution, and to improve software. In addition, the back-end cloud platform 5 is further configured to send a notification to the user of the intelligent driving system 100 when a new version of software exists, so that the user can update the software through OTA as needed when appropriate.
The central gateway 3 is in communication connection with the back-end cloud platform 5 through a data transmission device 4, and the data transmission device 4 is configured to upload problem data to the back-end cloud platform 5 through a wireless network (such as 4G/5G). The data transfer device 4 may be a T-Box device.
Fig. 2-4 show the basic architecture of a problem data real-time transmission system for an intelligent driving system according to three embodiments of the present invention. The basic architecture of these three embodiments is substantially the same, and there is only a difference in the manner in which the trigger switch 2 is connected to the intelligent driving system 100. It should be noted that, although fig. 2-4 only list three different connection modes of the trigger switch 2 and the intelligent driving system 100 according to three embodiments of the present invention, in the present invention, the connection mode of the trigger switch 2 and the intelligent driving system 100 is not limited to these three embodiments.
As shown in fig. 2, the trigger switch 2 is directly connected to the intelligent driving system 100 through a hard wire.
As shown in fig. 3, the trigger switch 2 is connected to a controller (e.g., BCM) on the vehicle, and the controller is connected to the central gateway 3 via a bus. Thus, the controller receives the status signal of the trigger switch 2, and transmits the status signal to the central gateway 3 through the bus of the vehicle, and to the smart driving system 100 via the central gateway 3.
As shown in fig. 4, the trigger switch 2 is a soft switch and is a button on a human-machine interface (HMI), for example, a button on a software interface of a center control screen. The human-computer interaction interface is in communication connection with the central gateway 3, so that the central gateway 3 receives a signal from the trigger switch 2 of the human-computer interaction interface and sends the signal to the intelligent driving system 100.
Based on the real-time problem data transmission system for the intelligent driving system, the real-time problem data transmission method for the intelligent driving system comprises the following steps:
step S1: as shown in fig. 5, the real-time transmission system for problem data of the intelligent driving system is used for data collection, and specifically includes:
step S11: when the vehicle runs and the intelligent driving system 100 is activated, the data caching module 11 of the intelligent driving system 100 caches the latest data in real time;
step S12: when the driver finds that the intelligent driving system 100 is abnormal, the driver presses the trigger switch 2;
step S13: the data caching module 11 continues to cache the latest data of T/2 time;
step S14: at the moment when T/2 passes after the trigger switch 2 is triggered, sending out the latest data in the latest T time in the data cache module 11 as problem data, and sending the problem data to the back-end cloud platform 5 through the central gateway 3;
step S15: the back-end cloud platform receives the problem data and stores the problem data into a problem database;
before storing in the question database, the method further comprises the step of roughly classifying the question data, wherein the rough classification can be carried out according to scenes or application functions.
For example, according to the application function, the question data can be classified into the following categories:
1) AEB function vehicle target misinformation; 2) AEB function pedestrian target misinformation; 3) the AEB function vehicle target is reported in a missing mode; AEB function pedestrian target under-reporting, etc.
According to the scenario, the problem data can be classified into the following categories: 1) highway scenarios; 2)1.
A rural road scene; 3) a tunnel scene; 4) an on-off ramp scene, etc.
Further, step S2 may be further included: as shown in fig. 6, problem data is used to optimize the embedded software in the intelligent driving system 100, so as to obtain optimized embedded software.
The step S2 specifically includes:
step S21: a rear-end cloud platform 5 is adopted to refine, classify and arrange problem data;
among them, the refined classification can be performed according to various combinations of conditions.
For example: the conditions of the combination include: the method comprises the steps of false reporting of AEB function vehicle targets on expressways, missing reporting of AEB function vehicle targets on and off ramps and the like.
Step S22: the problem data is led into an ADAS/AD off-line simulation system so as to reproduce the abnormal problem corresponding to the problem data in the intelligent driving system 100 in the ADAS/AD off-line simulation system;
the intelligent driving system 100 is installed on a vehicle, and an embedded software is installed thereon. The ADAS/AD offline simulation system is a simulation development environment running on a computer, and is used for simulation, programming, algorithm development, bug repair, and the like of embedded software of the intelligent driving system 100.
Step S23: analyzing reasons of the problem data, and optimizing a software algorithm of embedded software of the intelligent driving system 100 according to the reasons;
for example, if it is found that the AEB function algorithm software, which is embedded software of the intelligent driving system 100, has a design bug, it is the AEB algorithm software that is optimized.
Step S24: verifying the optimized embedded software using an existing scene library database;
the data in the existing scene library database is summarized according to the requirements of the regulations and the experience (Lesson Learn). For example, the data for AEB functions in existing scene library databases are designed under C-NCAP 2021 and E-NCAP 2020.
Step S25: repeating the step S23 and the step S24 until the abnormal problem is repaired, and obtaining verified embedded software;
step S26: and adding the data scene corresponding to the problem data into the existing scene library database.
Therefore, the data in the existing scene library database can further comprise the problem data for verification in the next optimization, so that the existing scene library database is continuously enriched in iteration.
Step S27: and generating and releasing the verified embedded software as new version software.
Step S3: as shown in fig. 7, the software iterative update using the new version software specifically includes:
step S31: encrypting the new version software by adopting a back-end cloud platform 5 to generate an encrypted software package;
step S32: the back-end cloud platform 5 pushes a software upgrading notice to the vehicle regularly through the wireless network and the data transmission equipment 4;
step S33: a driver of the vehicle selecting a software update;
step S34: the rear-end cloud platform 5 verifies the legality of the vehicle;
step S35: the encrypted software package is sent to the data transmission equipment 4;
step S36: the data transmission device 4 verifies the validity of the encrypted software package and decrypts the encrypted software package.
Step S37: the embedded software in the intelligent driving system 100 is upgraded through the central gateway 3 and a Bootloader (Bootloader) of the intelligent driving system 100.
The embedded software can be upgraded integrally or only the abnormal part can be upgraded.
The above embodiments are merely preferred embodiments of the present invention, which are not intended to limit the scope of the present invention, and various changes may be made in the above embodiments of the present invention. All simple and equivalent changes and modifications made according to the claims and the content of the specification of the present application fall within the scope of the claims of the present patent application. The invention has not been described in detail in order to avoid obscuring the invention.
Claims (10)
1. A real-time transmission system for problem data of an intelligent driving system is characterized by comprising the intelligent driving system, a central gateway, data transmission equipment, a rear-end cloud platform and a trigger switch, wherein the intelligent driving system, the central gateway, the data transmission equipment and the rear-end cloud platform are sequentially connected; the intelligent driving system, the central gateway, the data transmission equipment and the trigger switch are all arranged on the vehicle, and the rear-end cloud platform is remote;
the intelligent driving system consists of at least one sensing module, each sensing module is a sensor and is provided with a data caching module, and the data caching modules of all the sensing modules are set to cache the latest data from the vehicle and the intelligent driving system in real time;
the trigger switch is set to send out the latest data in the latest T time cached by the data caching modules of all the sensing modules as problem data at the moment when the trigger switch passes T/2 after the trigger switch is triggered;
the central gateway is configured to receive the problem data and send the problem data to the back-end cloud platform in real time through the data transmission device.
2. The real-time transmission system of problem data for an intelligent driving system according to claim 1, wherein the number of the sensing modules is one or more; and when the number of the sensing modules is multiple, the multiple sensing modules are different types of sensors.
3. The real-time transmission system of problem data for a smart driving system according to claim 1 or 2, characterized in that the sensor type of the perception module comprises at least a millimeter wave radar and/or a camera.
4. The real-time transmission system of problem data for a smart driving system according to claim 3, wherein the recent data comprises:
vehicle data including voltage, vehicle speed, steering wheel angle, and yaw angle;
sensor data; and
and key data of the application function comprises a steering control signal, an acceleration/deceleration signal, an alarm signal and a braking force request.
5. The real-time transmission system of problem data for intelligent driving system according to claim 4, characterized in that the vehicle data is stored in a perception module of any sensor type;
the sensor data includes: millimeter wave radar data which comprises radar states, a target reflection point list and a tracking target list and is stored in a sensing module of a millimeter wave radar type; and/or camera data, including camera state, picture data and target list, stored in the sensing module of camera type;
the location of the storage of the key data of the application function is determined by the type of the application function.
6. The real-time transmission system of problem data for a smart driving system according to claim 1, wherein the trigger switch is directly connected to the smart driving system through a hard wire; or
The trigger switch is connected with a controller on the vehicle, and the controller is connected with the central gateway through a bus; or
The trigger switch is a button on a human-computer interaction interface, and the human-computer interaction interface is in communication connection with the central gateway.
7. The real-time transmission system of problem data for an intelligent driving system according to claim 1, wherein each sensing module has a communication module, and the problem data is transmitted by driving the communication module.
8. A real-time transmission method of problem data for an intelligent driving system, comprising:
step S1: data collection using a real-time transmission system of problem data of an intelligent driving system according to one of claims 1 to 7, comprising:
step S11: the vehicle runs, the intelligent driving system is activated, and a data caching module of the intelligent driving system caches recent data in real time;
step S12: when a driver finds that the intelligent driving system is abnormal, the driver presses down a trigger switch;
step S13: the data caching module continues to cache the latest data in the T/2 time;
step S14: at the moment when T/2 passes after the trigger switch is triggered, sending out the latest data in the latest T time in the data cache module as problem data, and sending the problem data to the back-end cloud platform through the central gateway;
step S15: and the back-end cloud platform receives the question data and stores the question data in a question database.
9. The method for transmitting the question data for the intelligent driving system according to claim 8, wherein in the step S15, before storing in the question database, the method further comprises performing a coarse classification on the question data, wherein the coarse classification is performed according to a scene or according to an application function.
10. The real-time transmission method of problem data for the intelligent driving system according to claim 8, wherein each sensing module has a communication module, and the problem data is transmitted by driving the communication module;
the real-time transmission method of the problem data for the intelligent driving system further comprises the following steps:
step S2: adopting the problem data to optimize the embedded software in the intelligent driving system to obtain new version software, comprising:
step S21: adopting a rear-end cloud platform to refine, classify and arrange problem data;
step S22: the problem data are led into an ADAS/AD off-line simulation system, so that abnormal problems corresponding to the problem data in the intelligent driving system can be reproduced in the ADAS/AD off-line simulation system;
step S23: analyzing reasons of the problem data, and optimizing a software algorithm of embedded software of the intelligent driving system according to the reasons;
step S24: verifying the optimized embedded software using an existing scene library database;
step S25: repeating the step S23 and the step S24 until the abnormal problem is repaired, and obtaining verified embedded software;
step S26: adding the data scene corresponding to the problem data into the existing scene library database;
step S3: adopting new version software to carry out software iteration updating, comprising the following steps:
step S31: encrypting the new version software by adopting a back-end cloud platform to generate an encrypted software package;
step S32: the back-end cloud platform pushes a software upgrading notice to the vehicle periodically;
step S33: a driver of the vehicle selecting a software update;
step S34: the rear-end cloud platform verifies the legality of the vehicle;
step S35: sending the encrypted software package to the data transmission equipment;
step S36: the data transmission equipment verifies the validity of the encrypted software package and decrypts the encrypted software package;
step S37: and upgrading the embedded software in the intelligent driving system through a central gateway and a boot loader of the intelligent driving system.
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