Intelligent driving assistance control method and system based on millimeter wave radar

Abstract

The application belongs to the technical field of driving control, and particularly relates to an intelligent driving auxiliary control method and system based on a millimeter wave radar, wherein the system comprises a millimeter wave radar detection module, a data fusion output module, a driving decision generation module, a driving auxiliary control module, an auxiliary control safety evaluation module and a vehicle-mounted display warning module; the application detects the environment by using multiple vehicle-mounted millimeter wave radar sensors, fuses the radar detection information and the monitoring data of the vehicle-mounted camera in multiple modes, generates an environment perception result, analyzes the environment perception result by using a deep learning algorithm to formulate a corresponding control strategy, executes corresponding operations based on the auxiliary control decision, significantly improves the driving safety and the intelligent and automatic level of the vehicle, can reasonably judge the auxiliary control safety and the radar cooperation operation reliability, facilitates users to take corresponding processing measures in time, further improves the driving safety and reduces the vehicle supervision difficulty.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of driving control, in particular to an intelligent driving assistance control method and system based on millimeter wave radar. BACKGROUND

[0002] An intelligent driving assistance system perceives the environment around the vehicle in real time through vehicle-mounted sensors, analyzes the driver's behavior and potential risks through algorithms, and provides assistance through sound and light prompts or active control to improve driving safety and comfort. In the Chinese invention patent with the publication number CN114212097A, an intelligent driving assistance control system and control method are disclosed. The technical solution combines a road accident risk map with vehicle motion conditions to determine whether the vehicle is experiencing sudden acceleration, poor braking, or poor steering. When the above conditions occur, the driver is prompted accordingly.

[0003] However, the above-mentioned technical solution focuses on the detection and analysis of vehicle driving conditions, and cannot effectively perceive the environment around the vehicle and make corresponding assistance control. It is also difficult to reasonably evaluate the safety of assistance control and the reliability of vehicle monitoring and operation. Users cannot take timely improvement and optimization measures, which is not conducive to improving driving safety and the level of vehicle intelligence and automation, and the difficulty of vehicle operation supervision is great.

[0004] In view of the above technical defects, a solution is proposed. SUMMARY

[0005] The present application provides an intelligent driving assistance control method and system based on millimeter wave radar, which solves the problem that the prior art cannot effectively perceive the environment around the vehicle and make corresponding assistance control, and it is difficult to reasonably evaluate the safety of assistance control and the reliability of vehicle monitoring and operation, which is not conducive to improving driving safety and the level of vehicle intelligence and automation, and the difficulty of vehicle operation supervision is great.

[0006] To achieve the above-mentioned purpose, the present application provides the following technical solution:

[0007] The intelligent driving assistance control system based on millimeter wave radar comprises a millimeter wave radar detection module, a data fusion output module, a driving decision generation module, a driving assistance control module, an auxiliary control safety evaluation module, and a vehicle-mounted display warning module. The millimeter wave radar detection module uses multiple vehicle-mounted millimeter wave radar sensors to obtain target distance, speed, angle, and height information, and sends the detection information to the data fusion output module. The data fusion output module performs multi-modal data fusion on the detection information of the millimeter wave radar detection module and the monitoring data of the vehicle-mounted camera, aligns the raw data of the same environmental information perceived by each sensor in time and space using the time-space synchronization principle, generates an environmental perception result, and outputs the environmental perception result to the driving decision generation module.

[0008] The driving decision generation module formulates an auxiliary control strategy according to the environment perception result provided by the data fusion output module, analyzes the auxiliary control strategy by using a deep learning algorithm to identify different types of obstacles and evaluate collision risks, and sends the auxiliary control strategy to a driving auxiliary control module. The driving auxiliary control module executes corresponding operations based on the auxiliary control strategy and sends execution information to a vehicle display warning module for display. The auxiliary control safety evaluation module analyzes the auxiliary control strategy to determine the safety of the auxiliary control, and generates an auxiliary control safety signal or an auxiliary control risk signal based on the analysis result. The auxiliary control safety signal or the auxiliary control risk signal is sent to the vehicle display warning module.

[0009] Further, the millimeter wave radar detection module includes a front radar and an angle radar. The front radar is installed in a vehicle logo or a vehicle head grille to detect obstacles in front of the vehicle. The angle radar is installed at four corners of the vehicle to monitor a blind area behind and on the sides of the vehicle.

[0010] Further, the specific analysis process of the auxiliary control safety evaluation module includes:

[0011] The time when the corresponding auxiliary control strategy is generated is collected and marked as a first feature time, and the time when the driving auxiliary control module executes the corresponding operation is collected and marked as a second feature time. The time difference between the second feature time and the first feature time is calculated to obtain a delay duration. The delay duration is compared with a corresponding preset delay duration threshold value. If the delay duration exceeds the corresponding preset delay duration threshold value, the corresponding delay duration is marked as a dangerous duration.

[0012] The number of dangerous durations in a unit of time is obtained, and a ratio between the number of dangerous durations and the number of delay durations is calculated to obtain a dangerous time ratio value. The dangerous time ratio value is compared with a preset dangerous time ratio threshold value. If the dangerous time ratio value exceeds the preset dangerous time ratio threshold value, an auxiliary control risk signal is generated.

[0013] If the dangerous time ratio value does not exceed the preset dangerous time ratio threshold value, an excess value of the dangerous duration compared with the corresponding preset delay duration threshold value is marked as a time excess monitoring value. The mean value of all time excess monitoring values in a unit of time is calculated to obtain a time excess performance value, and the maximum time excess monitoring value in a unit of time is marked as a time excess amplitude value.

[0014] The dangerous time ratio value, the time excess performance value, and the time excess amplitude value are weighted and summed to obtain an auxiliary control efficiency value. The auxiliary control efficiency value is compared with a preset auxiliary control efficiency threshold value. If the auxiliary control efficiency value exceeds the preset auxiliary control efficiency threshold value, an auxiliary control risk signal is generated. If the auxiliary control efficiency value does not exceed the preset auxiliary control efficiency threshold value, an auxiliary control safety signal is generated.

[0015] Further, the auxiliary control safety evaluation module is in communication connection with the operation reliability evaluation module, the auxiliary control safety evaluation module sends an auxiliary control safety signal to the operation reliability evaluation module, when the operation reliability evaluation module receives the auxiliary control safety signal, the cooperation state of all millimeter wave radars on the vehicle is analyzed to judge the operation reliability, and a reliability qualified signal or a reliability abnormal signal is generated accordingly, and the reliability qualified signal or the reliability abnormal signal is sent to the vehicle-mounted display early warning module.

[0016] Further, the specific analysis process of the operation reliability evaluation module is as follows:

[0017] The radar monitoring evaluation value of all millimeter wave radars is obtained, the radar monitoring evaluation value is compared with a preset radar monitoring evaluation threshold value, if the radar monitoring evaluation value exceeds the preset radar monitoring evaluation threshold value, the corresponding millimeter wave radar is marked as a non-optimal operation radar, if the radar monitoring evaluation value does not exceed the preset radar monitoring evaluation threshold value, the current time is taken as the end time and the backtracking period with the set time length P1 is traced back, all fault information of the corresponding millimeter wave radar in the vehicle operation process in the backtracking period is obtained;

[0018] All faults of the corresponding millimeter wave radar in the vehicle operation process are classified, the occurrence number of the corresponding type fault is marked as a radar fault detection value, a set of preset detection influence weight values corresponding to each type of fault is set in advance, the radar fault detection value of the corresponding type fault is multiplied by the corresponding preset detection influence weight value to obtain a radar fault analysis value, and the radar fault analysis values of all types of faults of the corresponding millimeter wave radar in the backtracking period are summed to obtain a radar fault decision value;

[0019] The radar fault decision value is compared with a preset radar fault decision threshold value, if the radar fault decision value exceeds the preset radar fault decision threshold value, the corresponding millimeter wave radar is marked as a non-optimal operation radar, if there is a non-optimal operation radar on the vehicle, a reliability abnormal signal is generated.

[0020] Further, the operation reliability evaluation module is in communication connection with the radar monitoring evaluation module, the radar monitoring evaluation module detects, evaluates and analyzes the quality state of all millimeter wave radars on the vehicle one by one, and obtains the radar monitoring evaluation value of the corresponding millimeter wave radar, and sends the radar monitoring evaluation value of the corresponding millimeter wave radar to the auxiliary control safety evaluation module.

[0021] Further, the specific analysis process of the radar monitoring evaluation module is as follows:

[0022] The total running time of the corresponding millimeter wave radar in the historical stage is obtained and is marked as a radar running value, and the temperature of the corresponding millimeter wave radar and the humidity of the environment are collected; if the temperature of the corresponding millimeter wave radar or the humidity of the environment exceeds the corresponding preset threshold value, it is judged that the corresponding millimeter wave radar is in a high-temperature and high-humidity state, the total time length of the corresponding millimeter wave radar in the high-temperature and high-humidity state in the historical stage is obtained and is marked as a high-temperature and high-humidity time value;

[0023] The vibration amplitude and vibration frequency of the corresponding millimeter wave radar are collected; if the vibration amplitude or vibration frequency of the corresponding millimeter wave radar exceeds the corresponding preset threshold value, it is judged that the corresponding millimeter wave radar is in an abnormal vibration state, and the total time length of the corresponding millimeter wave radar in the abnormal vibration state in the historical stage is obtained and is marked as a mechanical abnormal vibration time value;

[0024] The number of times that the single continuous time length of the corresponding millimeter wave radar in the high-temperature and high-humidity state or the single continuous time length of the corresponding millimeter wave radar in the abnormal vibration state in the historical stage exceeds the corresponding preset continuous time length threshold value is obtained and is marked as a risk storage frequency; the radar monitoring evaluation value of the corresponding millimeter wave radar is calculated by weighted summation of the radar running value, the high-temperature and high-humidity time value, the mechanical abnormal vibration time value, and the risk storage frequency.

[0025] Further, if there is no non-optimal radar on the vehicle, a plurality of detection periods are set during the vehicle operation in the tracing period; if a millimeter wave radar fails in the corresponding detection period, the corresponding detection period is marked as an exploration period; the number of exploration periods in the tracing period is obtained and is compared with the total number of detection periods to obtain an exploration detection value; the exploration detection value is compared with a preset exploration detection threshold value; if the exploration detection value exceeds the preset exploration detection threshold value, a reliability abnormal signal is generated;

[0026] If the exploration detection value does not exceed the preset exploration detection threshold value, the radar monitoring evaluation value of all millimeter wave radars on the vehicle is calculated to obtain a radar quality evaluation value, and the radar fault decision value of all millimeter wave radars on the vehicle is calculated to obtain a radar abnormal evaluation value; the reliability feature coefficient is calculated by weighted summation of the exploration detection value, the radar quality evaluation value, and the radar abnormal evaluation value;

[0027] The reliability feature coefficient is compared with a preset reliability feature coefficient threshold value; if the reliability feature coefficient exceeds the preset reliability feature coefficient threshold value, a reliability abnormal signal is generated; if the reliability feature coefficient does not exceed the preset reliability feature coefficient threshold value, a reliability qualified signal is generated.

[0028] Further, the application also provides an intelligent driving auxiliary control method based on a millimeter wave radar, comprising the following steps:

[0029] Step one, using multiple vehicle-mounted millimeter wave radar sensors for target detection;

[0030] Step two, based on millimeter wave radar detection information and vehicle-mounted camera monitoring data, multi-modal data fusion is carried out and the environment perception result is output;

[0031] Step three, based on the environment perception result, the corresponding auxiliary control strategy is formulated;

[0032] Step four, based on the auxiliary control decision, the corresponding operation is executed;

[0033] Step five, judge the safety of auxiliary control, when generating the auxiliary control risk signal, make the vehicle-mounted display warning module display and warn.

[0034] Compared with the prior art, the beneficial effects of the present application are:

[0035] 1、In the present application, by using multiple vehicle-mounted millimeter wave radar sensors for environment detection, radar detection information and vehicle-mounted camera monitoring data are fused and environment perception results are generated, according to the environment perception results and using deep learning algorithm for analysis to formulate the corresponding control strategy, based on the auxiliary control decision, the corresponding operation is executed, and through the auxiliary control safety evaluation module for analysis to judge the safety of auxiliary control, when generating the auxiliary control risk signal, remind the user to suspend driving and take corresponding investigation and treatment measures, which significantly improves the driving safety and the level of vehicle intelligence and automation;

[0036] 2、In the present application, the auxiliary control safety signal is sent to the running reliability evaluation module by the auxiliary control safety evaluation module, when the running reliability evaluation module receives the auxiliary control safety signal, the cooperation condition of all millimeter wave radars on the vehicle is analyzed to judge the running reliability, when the reliability abnormal signal is generated, the user is reminded to drive carefully and the millimeter wave radars of the vehicle are checked and repaired in time, which further improves the driving safety and significantly reduces the difficulty of vehicle supervision. BRIEF DESCRIPTION OF DRAWINGS

[0037] In order to facilitate the understanding of those skilled in the art, the present application will be further described below in conjunction with the drawings;

[0038] Figure 1 The system block diagram of example one in the present application;

[0039] Figure 2 The system block diagram of example two and example three in the present application;

[0040] Figure 3 The method flow chart of example four in the present application. DETAILED DESCRIPTION

[0041] With reference to the accompanying drawings, the technical solutions in the embodiments of the present application will be clearly and completely described below, obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work belong to the protection scope of the present application.

[0042] Embodiment one: as shown in the present application, the intelligent driving auxiliary control system based on millimeter wave radar includes a millimeter wave radar detection module, a data fusion output module, a driving decision generation module, a driving auxiliary control module, an auxiliary control safety evaluation module and a vehicle display warning module. Figure 1

[0043] The millimeter wave radar detection module obtains target distance, speed, angle and height information by using multiple vehicle-mounted millimeter wave radar sensors (the millimeter wave radar sensor can provide accurate target position, speed and angle information by transmitting and receiving millimeter wave signals to realize real-time sensing of the environment around the vehicle, and the 4D millimeter wave radar can also output height information to construct a three-dimensional point cloud and more accurately identify obstacles), and sends the detection information to the data fusion output module. Preferably, the millimeter wave radar detection module includes a front radar and an angle radar, wherein the front radar is installed in the vehicle logo or the vehicle head grille to detect obstacles in front of the vehicle, and the angle radar is installed at the four corners of the vehicle to monitor the blind area behind the vehicle.

[0044] The data fusion output module performs multi-modal data fusion on the detection information of the millimeter wave radar detection module and the monitoring data of the vehicle-mounted camera, aligns the original data of the same environmental information sensed by each sensor in time and space by using the time-space synchronization principle, generates an environmental perception result, and outputs the environmental perception result to the driving decision generation module.

[0045] The driving decision generation module analyzes the environmental perception result provided by the data fusion output module to identify different types of obstacles and evaluate the collision risk (i.e., further processing the fused environmental perception result, such as target detection, tracking and classification, etc., evaluating the collision risk and formulating the corresponding control strategy according to the processed information, for example, in adaptive cruise control, adjusting the vehicle speed according to the distance and speed of the preceding vehicle; in automatic emergency braking, deciding whether to trigger emergency braking and the strength of braking according to the collision risk level), formulating the corresponding auxiliary control strategy (such as adjusting the vehicle speed, triggering emergency braking, providing warning information, etc.) accordingly, and sending the auxiliary control strategy to the driving auxiliary control module. The driving auxiliary control module executes the corresponding operation based on the auxiliary control decision, and sends the execution information to the vehicle display warning module for display, which significantly improves the driving safety and the intelligent and automatic level of the vehicle. ​

[0046] The auxiliary control safety evaluation module judges the auxiliary control safety by analysis, generates an auxiliary control safety signal or an auxiliary control risk signal according to the judgment, and sends the auxiliary control safety signal or the auxiliary control risk signal to the vehicle-mounted display warning module for display. When the vehicle-mounted display warning module receives the auxiliary control risk signal, it issues a corresponding warning to remind the user to suspend driving and take corresponding investigation and processing measures, so as to ensure the response efficiency of subsequent driving auxiliary control execution and further improve driving safety. The specific analysis process of the auxiliary control safety evaluation module is as follows:

[0047] The generation time of the corresponding auxiliary control strategy is collected and marked as the first feature time, and the time when the driving auxiliary control module executes the corresponding operation is collected and marked as the second feature time. The time difference between the second feature time and the first feature time is calculated to obtain the delay duration. The delay duration is compared with the corresponding preset delay duration threshold value. If the delay duration exceeds the corresponding preset delay duration threshold value, it means that the execution of the corresponding auxiliary control strategy is relatively slow. Then, the corresponding delay duration is marked as a dangerous duration.

[0048] The number of dangerous durations in a unit time is obtained, and a ratio calculation is performed between the number of dangerous durations and the number of delay durations to obtain a dangerous time occupancy value. The dangerous time occupancy value is compared with a preset dangerous time occupancy threshold value. If the dangerous time occupancy value exceeds the preset dangerous time occupancy threshold value, it means that the driving auxiliary control execution efficiency in a unit time is relatively poor. Then, an auxiliary control risk signal is generated.

[0049] If the dangerous time occupancy value does not exceed the preset dangerous time occupancy threshold value, the excess value of the dangerous duration compared with the corresponding preset delay duration threshold value is marked as a time excess monitoring value. The mean value of all time excess monitoring values in a unit time is calculated to obtain a time excess performance value, and the maximum time excess monitoring value in a unit time is marked as a time excess amplitude value.

[0050] The auxiliary control efficiency value is calculated by weighted summation of the dangerous time occupancy value, the time excess performance value, and the time excess amplitude value. That is, the dangerous time occupancy value, the time excess performance value, and the time excess amplitude value are respectively multiplied by the corresponding preset weight coefficient, and the sum of the three product results is marked as the auxiliary control efficiency value. The larger the value of the auxiliary control efficiency value, the worse the comprehensive performance of the driving auxiliary control execution efficiency in a unit time.

[0051] The auxiliary control efficiency value is compared with a preset auxiliary control efficiency threshold value. If the auxiliary control efficiency value exceeds the preset auxiliary control efficiency threshold value, it means that the comprehensive performance of the driving auxiliary control execution efficiency in a unit time is relatively poor. Then, an auxiliary control risk signal is generated. If the auxiliary control efficiency value does not exceed the preset auxiliary control efficiency threshold value, it means that the comprehensive performance of the driving auxiliary control execution efficiency in a unit time is relatively good. Then, an auxiliary control safety signal is generated.

[0052] Embodiment two: as shown, the difference between this embodiment and embodiment one is that the auxiliary control safety evaluation module is in communication connection with the operation reliability evaluation module, the auxiliary control safety evaluation module sends the auxiliary control safety signal to the operation reliability evaluation module, and the operation reliability evaluation module analyzes the cooperation state of all millimeter wave radars on the vehicle to judge the operation reliability when receiving the auxiliary control safety signal; Figure 2 Accordingly, the reliability qualified signal or the reliability abnormal signal is generated, and the reliability qualified signal or the reliability abnormal signal is sent to the vehicle-mounted display warning module for display, and the vehicle-mounted display warning module issues a corresponding warning when receiving the reliability abnormal signal to remind the user to drive carefully and timely check and repair the millimeter wave radar of the vehicle, further improve the driving safety of the subsequent driving safety, and significantly reduce the supervision difficulty of the vehicle; the specific analysis process of the operation reliability evaluation module is as follows:

[0053] The radar monitoring evaluation value of all millimeter wave radars is obtained, the radar monitoring evaluation value is compared with the preset radar monitoring evaluation threshold value, if the radar monitoring evaluation value exceeds the preset radar monitoring evaluation threshold value, it indicates that the quality state of the corresponding millimeter wave radar is poor, which is not conducive to ensure its smooth and stable operation, then the corresponding millimeter wave radar is marked as a non-optimal operation radar;

[0054] If the radar monitoring evaluation value does not exceed the preset radar monitoring evaluation threshold value, the current time is taken as the end time and the backtracking period with a set time length P1 is traced back, preferably, P1 = 15 days; all fault information of the corresponding millimeter wave radar in the vehicle operation process in the backtracking period is obtained;

[0055] All faults of the corresponding millimeter wave radar in the vehicle operation process are classified, the occurrence number of the corresponding type fault is marked as the radar fault detection value, a set of preset detection influence weight values with a value greater than zero corresponding to each type of fault is set in advance, and the higher the adverse influence degree of the corresponding type fault on the smooth and stable operation of the millimeter wave radar, the greater the value of the preset detection influence weight value matched therewith; the radar fault detection value of the corresponding type fault is multiplied by the corresponding preset detection influence weight value to obtain the radar fault analysis value, and the radar fault analysis values of all types of faults of the corresponding millimeter wave radar in the backtracking period are summed to obtain the radar fault decision value;

[0056]

[0057] ​The radar fault decision value is compared with a preset radar fault decision threshold value. If the radar fault decision value exceeds the preset radar fault decision threshold value, it indicates that the corresponding millimeter wave radar performs poorly, and the corresponding millimeter wave radar is marked as a non-optimal operation radar. If there is a non-optimal operation radar on the vehicle, it indicates that the radar monitoring operation reliability of the vehicle is poor, and the driving safety risk is high, and a reliability anomaly signal is generated.

[0058] Further, if there is no non-optimal operation radar on the vehicle, a plurality of detection periods are set during the vehicle operation in the tracing period. If a millimeter wave radar fails in the corresponding detection period, it indicates that there is a safety risk in the driving assistance control of the corresponding detection period, and the corresponding detection period is marked as an exploration period.

[0059] The number of exploration periods in the tracing period is obtained, and a ratio calculation is performed between the number of exploration periods and the total number of detection periods to obtain an exploration detection value. The exploration detection value is compared with a preset exploration detection threshold value. If the exploration detection value exceeds the preset exploration detection threshold value, it indicates that the radar monitoring operation reliability of the vehicle is poor, and it is not conducive to ensuring the safe driving of the vehicle, and a reliability anomaly signal is generated.

[0060] If the exploration detection value does not exceed the preset exploration detection threshold value, the radar monitoring evaluation values of all millimeter wave radars on the vehicle are averaged to obtain a radar quality evaluation value, and the radar fault decision values of all millimeter wave radars on the vehicle are averaged to obtain a radar anomaly evaluation value.

[0061] The exploration detection value, the radar quality evaluation value, and the radar anomaly evaluation value are weighted and summed to obtain a reliability feature coefficient. That is, the exploration detection value, the radar quality evaluation value, and the radar anomaly evaluation value are respectively assigned corresponding preset weight coefficients, and the exploration detection value, the radar quality evaluation value, and the radar anomaly evaluation value are respectively multiplied by the corresponding preset weight coefficients, and the sum of the three groups of product results is marked as the reliability feature coefficient. Moreover, the larger the value of the reliability feature coefficient, the worse the comprehensive radar monitoring operation reliability of the vehicle.

[0062] The reliability feature coefficient is compared with a preset reliability feature coefficient threshold value. If the reliability feature coefficient exceeds the preset reliability feature coefficient threshold value, it indicates that the comprehensive radar monitoring operation reliability of the vehicle is poor, which is not conducive to ensuring the safe driving of the vehicle, and a reliability anomaly signal is generated. If the reliability feature coefficient does not exceed the preset reliability feature coefficient threshold value, it indicates that the comprehensive radar monitoring operation reliability of the vehicle is good, and a reliability qualified signal is generated.

[0063] Embodiment three: as Figure 2As shown, the difference between this embodiment and embodiment one and embodiment two is that the running reliability evaluation module is in communication connection with the radar monitoring and evaluation module, the radar monitoring and evaluation module detects, evaluates and analyzes the quality status of all millimeter wave radars on the vehicle one by one, and accordingly obtains the radar monitoring and evaluation value of the corresponding millimeter wave radar;

[0064] The radar monitoring and evaluation value of the corresponding millimeter wave radar is sent to the auxiliary control safety evaluation module, which not only can reasonably analyze and accurately judge the quality status of each millimeter wave radar on the vehicle, but also can provide data support for the analysis process of the running reliability evaluation module to ensure the accuracy of the analysis result; the specific analysis process of the radar monitoring and evaluation module is as follows:

[0065] The total running time of the corresponding millimeter wave radar in the historical stage is obtained and marked as a radar running value, and the temperature of the corresponding millimeter wave radar and the humidity of the environment are collected; if the temperature of the corresponding millimeter wave radar or the humidity of the environment exceeds the corresponding preset threshold value, it is judged that the corresponding millimeter wave radar is in a high-temperature and high-humidity state, the total duration of the corresponding millimeter wave radar in the high-temperature and high-humidity state in the historical stage is obtained and marked as a high-temperature and high-humidity condition value;

[0066] The vibration amplitude and vibration frequency of the corresponding millimeter wave radar are collected; if the vibration amplitude or vibration frequency of the corresponding millimeter wave radar exceeds the corresponding preset threshold value, it is judged that the corresponding millimeter wave radar is in an abnormal vibration state, the total duration of the corresponding millimeter wave radar in the abnormal vibration state in the historical stage is obtained and marked as a mechanical abnormal vibration condition value; and the number of times that the single duration of the corresponding millimeter wave radar in the high-temperature and high-humidity state or the single duration of the corresponding millimeter wave radar in the abnormal vibration state in the historical stage exceeds the corresponding preset duration threshold value is obtained and marked as a risk storage frequency;

[0067] The radar running value, the high-temperature and high-humidity condition value, the mechanical abnormal vibration condition value and the risk storage frequency are weighted and summed to obtain the radar monitoring and evaluation value of the corresponding millimeter wave radar; that is, the radar running value, the high-temperature and high-humidity condition value, the mechanical abnormal vibration condition value and the risk storage frequency are respectively assigned corresponding preset weight coefficients, and the radar running value, the high-temperature and high-humidity condition value, the mechanical abnormal vibration condition value and the risk storage frequency are respectively multiplied by the corresponding preset weight coefficients, and the sum of the four product results is marked as the radar monitoring and evaluation value; and the greater the value of the radar monitoring and evaluation value, the worse the quality status of the corresponding millimeter wave radar in general.

[0068] Embodiment four: as shown, Figure 3 The difference between this embodiment and embodiment one, embodiment two and embodiment three is that the intelligent driving auxiliary control method based on millimeter wave radar provided by the present application comprises the following steps:

[0069] Step one, using multiple vehicle-mounted millimeter wave radar sensors for target detection;

[0070] Step two, based on millimeter wave radar detection information and vehicle-mounted camera monitoring data, multi-modal data fusion is carried out and the environment perception result is output;

[0071] Step three, based on the environment perception result, the corresponding auxiliary control strategy is formulated;

[0072] Step four, based on the auxiliary control decision, the corresponding operation is executed;

[0073] Step five, judge the safety of auxiliary control, when generating the auxiliary control risk signal, make the vehicle display warning module display and warn.

[0074] The working principle of the application is: in use, the millimeter wave radar detection module uses multiple vehicle-mounted millimeter wave radar sensors for environment detection, the data fusion output module performs multi-modal data fusion on the radar detection information and the monitoring data of the vehicle-mounted camera and generates an environment perception result, the driving decision generation module analyzes the environment perception result and adopts a deep learning algorithm to formulate a corresponding control strategy, the driving assistance control module executes the corresponding operation based on the auxiliary control decision, significantly improves the driving safety and the intelligent and automatic level of the vehicle, and the auxiliary control safety evaluation module is used for analysis to judge the safety of the auxiliary control, when the auxiliary control risk signal is generated, the user is reminded to pause driving and corresponding investigation and treatment measures are taken, and when the auxiliary control safety signal is generated, the running reliability evaluation module is used to analyze the cooperation status of all millimeter wave radars on the vehicle to judge the running reliability, when the reliability abnormal signal is generated, the user is reminded to drive carefully and the millimeter wave radars of the vehicle are checked and repaired in time, further improving the driving safety and reducing the supervision difficulty of the vehicle.

[0075] The preferred embodiments of the application disclosed above are only used to help explain the application, and the determination of the threshold value in the technical solution is based on the data mean obtained under a large number of data dimension training. The preferred embodiments do not describe all the details, nor limit the application to the specific embodiments. Obviously, according to the content of the specification, many modifications and changes can be made. The specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the application, so that those skilled in the art can well understand and utilize the application. The application is limited by the claims and their entire scope and equivalents.

Claims

1. An intelligent driving assistance control system based on millimeter-wave radar, characterized in that, It includes a millimeter-wave radar detection module, a data fusion output module, a driving decision generation module, a driving assistance control module, an auxiliary control safety assessment module, and an in-vehicle display and warning module; The millimeter-wave radar detection module uses multiple vehicle-mounted millimeter-wave radar sensors for target detection, and the data fusion output module performs multimodal data fusion of millimeter-wave radar detection information and vehicle-mounted camera monitoring data to generate environmental perception results. The driving decision generation module uses deep learning algorithms to analyze the environmental perception results to identify different types of obstacles and assess collision risks, and formulates corresponding auxiliary control strategies accordingly. The driving assistance control module executes corresponding operations based on the auxiliary control decisions. The auxiliary control safety assessment module analyzes the data to determine the safety of the auxiliary control, and generates an auxiliary control safety signal or an auxiliary control risk signal accordingly. The auxiliary control safety signal or auxiliary control risk signal is then sent to the vehicle display and warning module. The specific analysis process of the auxiliary control security assessment module includes: The system collects the generation time of the corresponding auxiliary control strategy and marks it as the first characteristic time, and the time when the driving assistance control module performs the corresponding operation and marks it as the second characteristic time. The system calculates the delay duration by performing a time difference calculation between the second characteristic time and the first characteristic time. The system compares the delay duration with the corresponding preset delay duration threshold. If the delay duration exceeds the corresponding preset delay duration threshold, the corresponding delay duration is marked as a dangerous duration. The number of dangerous times per unit time is obtained and the ratio of it to the number of delayed times is calculated to obtain the dangerous time occupancy value. The dangerous time occupancy value is compared with the preset dangerous time occupancy threshold. If the dangerous time occupancy value exceeds the preset dangerous time occupancy threshold, an auxiliary control risk signal is generated. If the dangerous time duration does not exceed the preset dangerous time duration threshold, the excess value of the dangerous time duration compared with the corresponding preset delay duration threshold is marked as the time over monitoring value. The average value of all time over monitoring values ​​within a unit time is calculated to obtain the time over performance value, and the time over monitoring value with the largest value within a unit time is marked as the time over amplitude value. The auxiliary control effectiveness value is calculated by weighting and summing the dangerous time position value, the time over performance value, and the time over amplitude value. The auxiliary control effectiveness value is then compared with the preset auxiliary control effectiveness threshold. If the auxiliary control effectiveness value exceeds the preset auxiliary control effectiveness threshold, an auxiliary control risk signal is generated; if the auxiliary control effectiveness value does not exceed the preset auxiliary control effectiveness threshold, an auxiliary control safety signal is generated. The auxiliary control safety assessment module communicates with the operation reliability assessment module. The auxiliary control safety assessment module sends the auxiliary control safety signal to the operation reliability assessment module. When the operation reliability assessment module receives the auxiliary control safety signal, it analyzes the coordination status of all millimeter-wave radars on the vehicle to determine the operation reliability, and sends the reliability qualified signal or reliability abnormal signal to the vehicle display and warning module. The specific analysis process of the reliability assessment module is as follows: The radar monitoring and evaluation values ​​of all millimeter-wave radars are obtained. The radar monitoring and evaluation values ​​are compared with the preset radar monitoring and evaluation threshold. If the radar monitoring and evaluation value exceeds the preset radar monitoring and evaluation threshold, the corresponding millimeter-wave radar is marked as a non-preferred radar. If the radar monitoring and evaluation value does not exceed the preset radar monitoring and evaluation threshold, the current time is used as the end time and traces back to the beginning for a traceback period of set duration P1 to obtain all fault information of the corresponding millimeter-wave radar during vehicle operation within the traceback period. All faults of the corresponding millimeter-wave radar during vehicle operation are classified, and the occurrence of each type of fault is marked as the radar fault detection value. Each type of fault is pre-set to correspond to a set of preset detection influence weight values. The radar fault detection value of the corresponding type of fault is multiplied by the corresponding preset detection influence weight value to obtain the radar fault analysis value. The radar fault analysis values ​​of all types of faults of the corresponding millimeter-wave radar during the retrospective period are summed to obtain the radar fault decision value. The radar fault decision value is compared with the preset radar fault decision threshold. If the radar fault decision value exceeds the preset radar fault decision threshold, the corresponding millimeter-wave radar is marked as a non-optimal radar. If a non-optimal radar exists on the vehicle, a reliability anomaly signal is generated. If there is no non-optimal radar on the vehicle, several detection periods are set during the vehicle's operation within the traceability period. If a millimeter-wave radar malfunctions within the corresponding detection period, the corresponding detection period is marked as an exploration period. The number of exploration periods within the traceability period is obtained and the ratio is calculated with the total number of detection periods to obtain the exploration detection value. The exploration detection value is compared with the preset exploration detection threshold. If the exploration detection value exceeds the preset exploration detection threshold, a reliability anomaly signal is generated. If the exploration detection value does not exceed the preset exploration detection threshold, the radar quality assessment value is obtained by averaging the radar monitoring and evaluation values ​​of all millimeter-wave radars on the vehicle, and the radar anomaly assessment value is obtained by averaging the radar fault decision values ​​of all millimeter-wave radars on the vehicle. The reliability characteristic coefficient is obtained by weighted summation of the exploration detection value, the radar quality assessment value and the radar anomaly assessment value. The reliability characteristic coefficient is compared with a preset reliability characteristic coefficient threshold. If the reliability characteristic coefficient exceeds the preset reliability characteristic coefficient threshold, a reliability abnormality signal is generated; if the reliability characteristic coefficient does not exceed the preset reliability characteristic coefficient threshold, a reliability qualified signal is generated. The reliability assessment module communicates with the radar monitoring and evaluation module. The radar monitoring and evaluation module detects, evaluates and analyzes the quality status of all millimeter-wave radars on the vehicle one by one, and obtains the radar monitoring and evaluation value of the corresponding millimeter-wave radar. The radar monitoring and evaluation value of the corresponding millimeter-wave radar is then sent to the auxiliary control safety assessment module. The specific analysis process of the radar monitoring and evaluation module is as follows: The total operating time of the corresponding millimeter-wave radar in the historical period is obtained and marked as the radar operating value. The temperature of the corresponding millimeter-wave radar and the humidity of the environment are collected. If the temperature of the corresponding millimeter-wave radar or the humidity of the environment exceeds the corresponding preset threshold, it is determined that the corresponding millimeter-wave radar is in a high temperature and high humidity state. The total duration of the corresponding millimeter-wave radar in the high temperature and high humidity state in the historical period is obtained and marked as the high temperature and high humidity time value. The vibration amplitude and vibration frequency of the corresponding millimeter-wave radar are collected. If the vibration amplitude or vibration frequency of the corresponding millimeter-wave radar exceeds the corresponding preset threshold, it is determined that the corresponding millimeter-wave radar is in an abnormal vibration state. The total duration of the corresponding millimeter-wave radar in an abnormal vibration state in the historical period is obtained and marked as the mechanical abnormal vibration time value. Furthermore, the number of times the duration of a single instance of the millimeter-wave radar being in a high-temperature and high-humidity state or in a state of abnormal vibration exceeded the corresponding preset duration threshold was obtained in the historical period and marked as the risk frequency; the radar monitoring and evaluation value of the corresponding millimeter-wave radar was obtained by weighted summation of radar operating value, high-temperature and high-humidity condition value, mechanical vibration condition value and risk frequency.

2. The intelligent driving assistance control system based on millimeter-wave radar according to claim 1, characterized in that, The millimeter-wave radar detection module includes a forward-facing radar and corner radars. The forward-facing radar is installed in the vehicle emblem or front grille to detect obstacles in front of the vehicle. The corner radars are installed at the four corners of the vehicle to monitor blind spots to the sides and rear of the vehicle.

3. A control method for an intelligent driving assistance control system based on millimeter-wave radar as described in claim 2, characterized in that, Includes the following steps: Step 1: Target detection using multiple vehicle-mounted millimeter-wave radar sensors; Step 2: Output the environmental perception results; Step 3: Develop corresponding auxiliary control strategies; Step 4: Execute the corresponding operations based on the auxiliary control decisions; Step 5: Determine the safety of the auxiliary control.

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