WO2023178507A1

WO2023178507A1 - Assisted driving method and apparatus

Info

Publication number: WO2023178507A1
Application number: PCT/CN2022/082232
Authority: WO
Inventors: 尹福兰; 吴自贤; 余得水
Original assignee: 华为技术有限公司
Priority date: 2022-03-22
Filing date: 2022-03-22
Publication date: 2023-09-28

Abstract

An assisted driving method and apparatus, capable of being applied to intelligent vehicles or new-energy vehicles. The method comprises: obtaining rainfall information; obtaining a first traffic marking; obtaining a second traffic marking; determining, according to the rainfall information, a first weight value corresponding to the first traffic marking and a second weight value corresponding to the second traffic marking; and determining a third traffic marking according to the first traffic marking, the second traffic marking, the first weight value, and the second weight value. The influence of the rainfall information on the obtained traffic markings is taken into consideration, so that the improvement of the accuracy of the finally obtained traffic marking is facilitated, then the trouble of a driver not being able to clearly see the traffic markings in special weather is overcome, and the improvement of the safety of driving is facilitated.

Description

Assisted driving method and device

Technical field

The present application relates to the field of automotive technology, and in particular to an assisted driving method and device.

Background technique

With the development of society, the number of cars is gradually increasing, and people's demand for cars is getting higher and higher. In the process of driving a car, it is very important to ensure the safety of the driver. However, in special weather (such as heavy rain), the front window of the car may be blocked by rainwater, etc., causing the driver to be unable to see the traffic signs clearly. This will bring great challenges to safe driving and pose hidden risks to the driver's safety.

Therefore, there is an urgent need to provide an assisted driving method to improve driving safety in special weather conditions.

Contents of the invention

This application provides an assisted driving method and device in order to improve driving safety under special weather conditions.

In a first aspect, this application provides an assisted driving method, which includes: obtaining rainfall information; obtaining a first traffic sign line; obtaining a second traffic sign line; and determining a first weight value corresponding to the first traffic sign line based on the rainfall information. The second weight value corresponding to the second traffic sign line; the third traffic sign line is determined based on the first traffic sign line, the second traffic sign line, the first weight value and the second weight value.

Among them, the first traffic sign line and the second traffic sign line are fitting curves of traffic sign lines obtained based on different methods.

Based on the above technical solution, different methods are used to obtain the first traffic sign line and the second traffic sign line, and the impact of rainfall information on the method of obtaining the first traffic sign line and the second traffic sign line is considered, and the above-mentioned traffic sign line is determined based on the rainfall information. The weight value corresponding to the first traffic sign line and the second traffic sign line is further based on the above weight value, and the first traffic sign line and the second traffic sign line are merged to obtain a more accurate third traffic sign line. By considering the rainfall information The impact of different methods is beneficial to improving the accuracy of the final third traffic sign line, thereby alleviating the driver's trouble of being unable to see the traffic sign line clearly under special weather, thereby improving driving safety.

Optionally, the driving area can also be determined based on the above-mentioned third traffic marking line, where the driving area refers to an area where driving can be done safely, and can also be called a drivable area. It can be understood that by considering the impact of rainfall information on the method of obtaining the first traffic sign line and the second traffic sign line, it is beneficial to improve the accuracy of the finally obtained third traffic sign line. The more accurate the third traffic sign line is, the more accurate the third traffic sign line will be based on the third traffic sign line. The driving area determined by the three traffic marking lines will be more accurate. Therefore, the accuracy of the driving area will also be improved, which will help improve driving safety in special weather.

Combined with the first aspect, in some possible implementations of the first aspect, the above-mentioned obtaining of rainfall information includes: obtaining the output value of the rain sensor and the wiper speed information; determining the rainfall according to the output value of the rain sensor and the wiper speed information. grade.

The rainfall information is reflected through the rainfall level, and the current rainfall level is further determined based on the obtained output value of the rain sensor and wiper speed information to reflect the rainfall information. Since the output value of the rain sensor can reflect the size of the rain, the wiper speed information can reflect whether the wiper can remove the rain on the front window glass under full load operation. Therefore, taking the above two factors into consideration will help to reasonably determine The current rainfall information, such as rainfall level, can be obtained to make the weight value determined based on the rainfall level more accurate, thereby making the fused traffic signs more accurate. On the other hand, if the rain level is determined only by the output value of the sensor, there may be a situation where the wiper keeps working at full load enough to remove the rainwater from the front window glass in time. Therefore, the accuracy of the determined rain level is not high, and this application By combining the output value of the rain sensor and the wiper speed information to determine the rainfall level, the problem of low accuracy of rainfall levels caused by the above situation can be alleviated, which in turn helps to improve the accuracy of judgment of rainfall information, thereby meeting the needs of customers. need. On the other hand, determining the rainfall level can also be used to further determine whether the above scheme needs to be activated. For example, when the rainfall level reaches a preset value, the final traffic marking line is determined through the above scheme to ensure the safety of the driver.

In conjunction with the first aspect, in some possible implementations of the first aspect, the above-mentioned determination of the first weight value corresponding to the first traffic sign line and the second weight value corresponding to the second traffic sign line based on the rainfall information includes: according to The rainfall level determines the first weight value corresponding to the first traffic sign line and the second weight value corresponding to the second traffic sign line.

In the above technical solution, the rainfall level can be determined based on the output value of the rain sensor and the wiper speed information, and then the weight values corresponding to the first traffic marking line and the second traffic marking line are determined based on the rainfall level. The above rainfall level can be more Accurately reflect the current rainfall information, thereby making the determined weight value more accurate, which is conducive to improving the accuracy of the final traffic sign line and improving driving safety.

Combined with the first aspect, in some possible implementations of the first aspect, determining the rainfall level based on the output value of the rain sensor and wiper speed information includes: determining the current rainfall based on the output value of the rain sensor; The wiper speed information and the mapping relationship determine the rainfall level. The mapping relationship is used to indicate the correspondence between multiple rainfall ranges, multiple wiper speed ranges, and multiple rainfall levels.

In the above technical solution, the rainfall amount can be determined based on the output value of the rain sensor (such as the diameter of the raindrop, the number of raindrops, and the sensing area of the rain sensor, etc.), and then combined with the wiper speed, the rainfall level can be determined based on the pre-stored mapping relationship. In order to remind the driver when the rainfall level reaches the preset value, it can improve driving safety.

Combined with the first aspect, in some possible implementations of the first aspect, the first traffic sign line or the second traffic sign line is any of the following: road railings or curbs detected based on radar, and road railings or A fitting curve determined by the relative distance between the roadside and the traffic sign line; or a fitting curve determined based on the motion trajectory of the vehicle in front detected by radar and the relative distance between two adjacent traffic sign lines; or a fitting curve determined by the recognition camera A fitting curve determined by the traffic signs in the image; or a fitting curve determined based on the light trajectory of the vehicle in front collected by the camera, and the relative distance between two adjacent traffic signs; or based on the adjacent lanes collected by the camera The movement trajectory of the vehicle and the fitting curve determined by the relative distance between two adjacent traffic signs.

In the above technical solution, multiple methods of obtaining the first traffic sign line and the second traffic sign line are provided. The first traffic sign line and the second traffic sign line can be determined based on any two of the above methods, which improves flexibility. sex.

In conjunction with the first aspect, in some possible implementations of the first aspect, the above method further includes: determining the recommended vehicle speed based on the rainfall level.

Among them, the recommended vehicle speed refers to the vehicle speed recommended in the current driving environment. It is understandable that the recommended vehicle speed may be different under different rainfall levels. For example, the higher the rainfall level, the lower the recommended speed may be.

In the above technical solution, the recommended vehicle speed can also be determined based on the above-mentioned rainfall level, which is beneficial to ensuring that the vehicle speed is within a safe range. In addition, consider the impact of rainfall levels on vehicle speed. For example, when rainfall levels are higher, vehicle speeds may be lower, which is helpful to ensure the safety of drivers driving in different environments.

Combined with the first aspect, in some possible implementations of the first aspect, determining the recommended vehicle speed based on the rainfall level includes: determining a safe distance from the target vehicle based on the rainfall level, and the target vehicle is the vehicle in front or behind; The actual distance and safe distance of the target vehicle determine the recommended speed.

In the above technical solution, the safe distance between the vehicle and the target vehicle can be determined based on the rainfall level, that is, within what distance the vehicle is safe, and then the recommended vehicle speed can be determined based on the actual distance and safe distance from the target vehicle. , allowing the driver to drive according to the recommended speed and ensuring a safe distance from the vehicle in front or behind, which also ensures the driver's longitudinal safety while driving, which is conducive to improving driving safety.

Combined with the first aspect, in some possible implementations of the first aspect, determining a safe distance from the target vehicle based on the rainfall level includes: determining a road adhesion function based on the rainfall level; determining a safe distance from the target vehicle based on the road adhesion function. .

Among them, the road adhesion function is used to express the relationship between rainfall level and road adhesion. In other words, the road adhesion is different under different rainfall levels. For example, the higher the rainfall level, the smaller the road adhesion determined by the above-mentioned road adhesion function may be.

In the above technical solution, the road adhesion function is determined based on the rainfall level, and the safe distance from the target vehicle is further determined based on the road adhesion function. By considering the impact of the rainfall level on the road adhesion, it is beneficial to ensure the safety of the driver. For example, when the rainfall level is high, the road adhesion may be smaller, which is not conducive to vehicle braking, that is, the safety distance should be relatively larger, thereby improving driving safety.

Combined with the first aspect, in some possible implementations of the first aspect, the above method further includes: controlling a human machine interaction system (HMI) to display the third traffic marking line and/or the recommended vehicle speed.

In the above technical solution, the HMI can be controlled to display the third traffic marking line and/or the recommended vehicle speed. On the one hand, the driver can also determine the third traffic marking line in harsh environments, which is conducive to accurately determining the drivable area. . On the other hand, driving according to the above recommended speed will help ensure a safe distance from the vehicle in front or behind. Therefore, overall, it is beneficial to safe driving.

In conjunction with the first aspect, in some possible implementations of the first aspect, the above method further includes: determining whether to send a warning to the HMI based on the actual distance to the traffic sign line.

In the above technical solution, the actual distance between the vehicle and the traffic sign line is used to determine whether to send a warning to the HMI to remind the driver. One method is to determine whether to send a warning to the HMI through the actual distance between the vehicle and the traffic sign line and the vehicle speed. The duration between the current moment and the moment when the vehicle hits the traffic sign line, and if the duration is less than the preset time length, a warning is sent to the HMI, which is helpful to remind the driver that the vehicle is about to hit the traffic sign line, allowing the driver to make timely adjustments , ensuring that it travels within the drivable area, which is conducive to ensuring the safety of the driver. Another method is to send a warning to the HMI when the actual distance between the vehicle and the traffic sign line at the current moment is less than the preset distance, so that the driver can make timely adjustments to ensure that the vehicle is driving within the drivable area, which is conducive to ensuring that the driver safety.

In a second aspect, this application provides an auxiliary driving device, including a unit for implementing the method in the first aspect and any possible implementation of the first aspect. Each unit can implement corresponding functions by executing computer programs.

In a third aspect, the present application provides an assisted driving device, including a processor configured to execute the assisted driving method described in the first aspect and any possible implementation of the first aspect.

The apparatus may also include memory for storing instructions and data. The memory is coupled to the processor. When the processor executes instructions stored in the memory, the method described in the above first aspect and any possible implementation of the first aspect can be implemented.

The device may further include a communication interface for the device to communicate with other devices. For example, the communication interface may be a transceiver, a circuit, a bus, a module or other types of communication interfaces.

In the fourth aspect, this application provides a vehicle that can be used to implement the functions involved in the above-mentioned first aspect and any possible implementation of the first aspect, for example, for example, receiving or processing data involved in the above-mentioned method. and/or information.

Exemplarily, the vehicle includes the driving assistance device as described in the second aspect or the third aspect.

In a fifth aspect, the present application provides a chip system, which includes at least one processor for supporting the implementation of the functions involved in the above-mentioned first aspect and any possible implementation of the first aspect, for example, receiving or process the data and/or information involved in the above methods.

In a possible design, the chip system further includes a memory, the memory is used to store program instructions and data, and the memory is located within the processor or outside the processor.

The chip system can be composed of chips or include chips and other discrete devices.

In a sixth aspect, the present application provides a computer-readable storage medium, including a computer program, which, when run on a computer, causes the computer to implement the method in the first aspect and any possible implementation manner of the first aspect.

In a seventh aspect, the present application provides a computer program product. The computer program product includes: a computer program (which may also be called a code, or an instruction). When the computer program is run, it causes the computer to execute the first aspect and and any method in any possible implementation of the first aspect.

It should be understood that the second to seventh aspects of the present application correspond to the technical solution of the first aspect of the present application, and the beneficial effects achieved by each aspect and corresponding feasible implementations are similar, and will not be described again.

Description of the drawings

Figure 1 is a schematic diagram of a scenario applicable to the method provided by the embodiment of this application;

Figure 2 is a schematic system structure diagram of the assisted driving system provided by an embodiment of the present application;

Figure 3 is a schematic flow chart of the assisted driving method provided by the embodiment of the present application;

Figure 4 is a schematic diagram of multiple methods for obtaining lane lines provided by embodiments of the present application;

Figure 5 is a schematic diagram of information displayed on the vehicle-machine interface provided by the embodiment of the present application;

Figure 6 is a schematic block diagram of an auxiliary driving device provided by an embodiment of the present application;

Figure 7 is another schematic block diagram of the driving assistance device provided by an embodiment of the present application.

Detailed ways

The technical solutions in this application will be described below with reference to the accompanying drawings.

In order to clearly describe the technical solutions of the embodiments of the present application, the following description is first made.

First, in the embodiment of this application, "at least one item (item)" refers to one item (item) or multiple items (item). "And/or" describes the association of associated objects, indicating that there can be three relationships, for example, A and/or B, which can mean: A exists alone, A and B exist simultaneously, and B exists alone, where A, B can be singular or plural. The character "/" generally indicates that the related objects are in an "or" relationship, but it does not exclude the situation that the related objects are in an "and" relationship. The specific meaning can be understood based on the context.

Second, in the embodiments of this application, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or product that includes a series of steps or units. Apparatus are not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such processes, methods, products or devices.

In order to facilitate understanding of the assisted driving method provided by the embodiment of the present application, the application scenarios of the assisted driving method provided by the embodiment of the present application will be described below. It can be understood that the application scenarios described in the embodiments of this application are to more clearly illustrate the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application.

Figure 1 is a schematic diagram of a scenario applicable to the method provided by the embodiment of this application. As shown in Figure 1, multiple vehicles are driving on the road, for example, vehicle 110, vehicle 120, and vehicle 130. During the driving process of the vehicles, the driver needs to see the lane lines clearly, and then determine the drivable area of his vehicle. , such as the distance between your own vehicle and the vehicle in front, whether it crosses the lane line to affect the safety of vehicles in adjacent lanes, etc. Taking vehicle 110 as an example, during the driving process of vehicle 110, the driver needs to determine the lane line in order to drive safely in the lane. In addition, the driver also needs to ensure the distance from the vehicle 120 in front and the vehicle 130 in the adjacent lane to ensure driving safety.

The road in Figure 1 only shows lane lines, which should not limit the embodiment of the present application in any way. In actual roads, traffic marking lines such as diversion lines and turn marking lines that guide traffic may also be included. Drivers also need to see the above-mentioned various traffic marking lines clearly while driving.

Only three vehicles are shown in Figure 1, but with the development of society, the number of vehicles gradually increases on actual roads. Therefore, it is becoming more and more important to ensure the safety of the driver during vehicle driving.

In good weather, drivers can clearly see the above-mentioned traffic signs and determine the drivable area. However, in special weather (such as heavy rain), the front window of the car may be blocked by rainwater, etc., causing the driver to be unable to see the traffic signs clearly, and it is difficult for the driver to determine the drivable area, which will bring safety problems to the driver. Great challenge.

In order to solve the above problems, this application provides an assisted driving method, which uses the weight value determined based on the rainfall information to fuse the traffic marking lines obtained by different methods to obtain the final traffic marking line. Since the impact of rainfall information on obtaining traffic sign lines through various methods is taken into account, the final traffic sign lines are more accurate, which in turn helps improve driver safety.

The technical solutions of the present application and the technical solutions of the present application will be described in detail below with reference to the accompanying drawings.

In the embodiment shown below, traffic markings are described in detail using lane lines as an example, but this should not limit the scope of application of the method provided in this application. Based on the same method, other traffic marking lines can also be determined.

The method provided by the embodiments of this application can be applied not only to manually driven vehicles, but also to intelligently driven vehicles. Among them, intelligent driving vehicles refer to vehicles that use autonomous driving technology. Currently, in the field of intelligent driving, the classification standard given by the International Society of Automotive Engineers (SAE), SAE J3016, is widely used to classify intelligent driving. According to SAE's classification, autonomous driving technology is divided into six levels from low to high, L0 to L5. L0 is the lowest automation level, while L5 represents fully autonomous driving (that is, no driver intervention is required under all conditions). SAE’s naming for levels L0 to L2 is “driver support features”, and its naming for levels L3 to L5 is “automated driving features”. For the specific division method of each level, please refer to the existing technology, which will not be described again here.

FIG. 2 is a schematic system structure diagram of an assisted driving system provided by an embodiment of the present application. The assisted driving system 200 suitable for the method provided by the embodiment of the present application will be described in detail below with reference to FIG. 2 .

As shown in Figure 2, the assisted driving system 200 includes: an assisted driving device 210, a camera 220, a body control module (BCM) 230, a rain sensor 240, a radar 250, a braking system 260, and an HMI 270. The camera 220, BCM 230, rain sensor 240, radar 250, braking system 260, and HMI 270 are all connected to the auxiliary driving device 210 and can communicate with the auxiliary driving device 210. The functions of each part in the above-mentioned assisted driving system 200 will be described in detail below.

The auxiliary driving device 210 may be used to obtain rainfall information; obtain the first traffic sign line; obtain the second traffic sign line; and determine the first weight value corresponding to the first traffic sign line and the second weight value corresponding to the second traffic sign line based on the rainfall information. Weight value; determine the third traffic sign line based on the first traffic sign line, the second traffic sign line, the first weight value and the second weight value.

The camera 220 can be used to capture images or videos, and is one of the signal input sources for road and obstacle recognition in the assisted driving system 200 . For example, the camera 220 can output video data in original format to reflect various environments, obstacles, etc. on the road while the vehicle is driving. For another example, the camera 220 can capture images of traffic markings such as lane lines, etc., to facilitate recognition of lane lines.

BCM 230 can be used to calculate and output the current working status of the wiper (such as whether the wiper is on or off), wiper speed, wiper position, etc. In some cases, for example, the rain sensor is deployed on the BCM 230, and the BCM 230 can also be used to calculate and output the working status of the rain sensor, etc.

The rain sensor 240 can be used to calculate and output the current rain status (such as whether it is raining), the original rainfall signal, etc., where the original rainfall signal can be the voltage signal of the rain sensor, or the current raindrop density distribution converted from the voltage signal. Raindrop size etc.

The radar 250 can be used to output original point cloud data so that the assisted driving device 210 can calculate the fitting curve of the lane line. The radar 250 is one of the signal input sources for road and obstacle recognition in the assisted driving system 200 . The radar 250 may be a millimeter wave radar, a lidar, etc., and the embodiment of the present application does not limit the type of the radar 250 .

The braking system 260 can be used to output the current vehicle speed and validity, lateral acceleration, longitudinal acceleration, original value and validity of four-wheel speed, vehicle yaw angle, heading angle, gas pedal, brake pedal and other information.

HMI 270 is an important human-computer interaction interface of the assisted driving system 200. It can be used to display the currently calculated weather status, lane line information, obstacle information, following distance and recommended vehicle speed, etc., so that the driver can obtain the above information in a timely manner. .

In this embodiment of the present application, the HMI 270 can display the above information through the interface, and can also broadcast the above information through voice to remind the driver. The specific method by which the driver obtains the above information in the embodiment of the present application is not limited. For example, vibration can also be used to remind the driver when the driver's speed exceeds the recommended speed.

In addition, the structure illustrated in the embodiment of the present application does not constitute any limitation on the assisted driving system 200. In other embodiments, the assisted driving system 200 may also include more or fewer components than shown in the figure, or a combination of certain components. some parts, or split some parts, or arrange different parts. The components illustrated may be implemented in hardware, software, or a combination of software and hardware. For example, the above-mentioned assisted driving devices and autonomous driving functions can be integrated into a domain controller, integrated into components such as cameras or radars, or deployed independently.

The functions of each part in the assisted driving system 200 described above are only examples. In other embodiments, each part may include more or less functions, which is not limited by the embodiments of the present application.

The assisted driving method provided by this application will be described in detail below with reference to embodiments. The embodiments shown below are described with the auxiliary driving device as the execution subject, but this should not constitute any limitation on the execution subject of the method. As long as the program recording the code of the method provided by the embodiment of the present application can be run, the method provided by the embodiment of the present application can be executed.

Figure 3 is a schematic flowchart of the assisted driving method 300 provided by the embodiment of the present application. The assisted driving method 300 shown in FIG. 3 may include steps 310 to 340. Each step in the method 300 is described in detail below.

In step 310, the assisted driving device acquires the first traffic sign line and the second traffic sign line.

The first traffic sign line and the second traffic sign line may be two fitting curves obtained through different methods. It can be understood that the auxiliary driving device can also obtain more fitting curves through more methods. That is, the auxiliary driving device can obtain multiple fitting curves through a variety of methods. Each method can obtain one. Fitting curve of traffic sign line. Among them, the fitting curves described in this article are the first traffic sign line, the second traffic sign line, the fourth traffic sign line, etc. For example, take the lane line as an example for the traffic marking line. Use method 1 to obtain the fitting curve 1 of the lane line, use method 2 to obtain the fitting curve 2 of the lane line, and use method 3 to obtain the fitting curve 3 of the lane line. You can get Due to the different methods used for the three fitting curves of the lane lines, the expressions of the three fitting curves may also be different.

It should be noted that the above-mentioned multiple fitting curves may be fitting curves for the same traffic sign line, or they may be fitting curves for multiple traffic sign lines, which is not limited in the embodiments of the present application. For example, taking lane lines as an example, for a certain vehicle, the shapes of the lane lines on the left and right sides of the vehicle can be the same. Therefore, the fitting curve of the lane lines on the left side of the vehicle can be obtained by using method 1. 1. Use method 2 to obtain the fitting curve 2 of the lane line on the right side of the vehicle to facilitate the fusion of fitting curve 1 and fitting curve 2.

In addition, the auxiliary driving device can obtain the first traffic sign line and the second traffic sign line at the same time, or can obtain them separately, which is not limited in the embodiment of the present application. For example, step 310 can be divided into the following steps: the auxiliary driving device obtains the first traffic sign line; the auxiliary driving device obtains the second traffic sign line.

For example, the auxiliary driving device can obtain the above-mentioned fitting curve through at least two of several possible methods described below. How to obtain the above-mentioned fitting curve will be described in detail below.

One possible method is that the assisted driving device determines the fitting curve based on the road railings or curbs detected by the radar and the relative distance between the road railings or curbs and the traffic signs. Specifically, since radar is sensitive to road railings, curbs, etc., the auxiliary driving device can perform cluster fitting on the point cloud data obtained by the radar to identify road railings, curbs, etc., and then combine the road railings or curbs with The relative distance between the curb and the traffic sign line, the number of lanes, and the width of the lane. By offsetting the road railings, the lane line can be determined, and then the fitting curve can be calculated based on the lane line. For example, based on multiple lane lines The corresponding fitting curve is obtained by fitting the points.

Another possible method is that the assisted driving device determines the fitting curve based on the motion trajectory of the vehicle in front detected by the radar and the relative distance between two adjacent traffic signs. For example, the auxiliary driving device can use the neural network model to determine the fitting curve of the lane line based on the motion trajectory of the vehicle in front obtained by the radar. It can be understood that the above-mentioned neural network model can be a neural network model trained through historical data. By inputting the data of the movement trajectory of the preceding vehicle into the above-trained neural network model, the fitting curve of the lane line can be obtained. For specific steps, please refer to known technologies and will not be described in detail here.

Another possible method is that the assisted driving device determines the fitting curve by identifying the traffic sign lines in the images collected by the camera. For example, the assisted driving device can identify the lane lines through the images collected by the camera, and calculate the corresponding fitting curve based on the lane lines.

Another possible method is that the auxiliary driving device determines the fitting curve based on the light trajectory of the vehicle in front collected by the camera and the relative distance between two adjacent traffic signs. For example, the camera can collect the light trajectory of the vehicle in front, and then the auxiliary driving device uses the neural network model to determine the fitting curve of the lane line based on the above light trajectory, and determines the lane where the vehicle is located based on the distance between two adjacent lane lines. of two lane lines.

Another possible method is that the assisted driving device determines the fitting curve based on the motion trajectories of vehicles in adjacent lanes collected by cameras and the relative distance between two adjacent traffic signs. For example, the auxiliary driving device can use the neural network model to determine the fitting curve of the lane line based on the motion trajectory of the vehicle in front obtained by the radar. For specific steps, please refer to known technologies.

For example, the first traffic sign line and the second traffic sign line can be obtained by any two of the above methods. For example, the first traffic sign line and the second traffic sign line can be obtained through two radar-based methods. For another example, the first traffic sign line and the second traffic sign line can be obtained through any two of the three camera-based methods. For another example, the first traffic sign line and the second traffic sign line can be obtained through any radar-based method and any camera-based method. That is to say, the embodiment of the present application can obtain the first traffic sign line and the second traffic sign line through different methods of one sensor, or can also obtain the above-mentioned first traffic sign line and the second traffic sign line through different methods of multiple sensors. line, the embodiment of the present application does not limit this. In addition, the embodiment of the present application does not limit the type of sensor. In addition to cameras and radars, traffic marking lines can also be obtained based on other types of sensors.

The above methods of obtaining fitting curves are only examples and should not constitute any limitation on the embodiments of the present application. For example, the assisted driving device can also offset the railings captured by the camera, obtain lane lines based on the width of the lane, and then obtain a fitting curve corresponding to the lane lines.

It should be noted that the auxiliary driving device can obtain the fitting curve of the traffic sign line through at least two of a variety of methods. Taking lane lines as an example, an example in which the assisted driving device uses the above five methods to obtain the fitting curve of the lane lines will be given below in conjunction with Figure 4. That is, the auxiliary driving device obtains five fitting curves.

Figure 4 is a schematic diagram of multiple methods for obtaining lane lines provided by embodiments of the present application. As shown in Figure 4, the recognition of lane lines includes: identifying lane lines through point cloud data obtained by radar, or identifying lane lines through image data obtained by cameras, where the image data includes pictures or video data.

The following describes the method of identifying lane lines using point cloud data obtained by radar and the method of identifying lane lines using image data obtained by cameras.

Two methods for identifying lane lines through point cloud data obtained by radar are as follows:

The radar sends the point cloud data it acquires to the auxiliary driving device. The auxiliary driving device determines the lane line based on the point cloud data acquired by the radar, and then determines the fitting curve of the lane line. One method is for the assisted driving device to cluster and identify lane lines based on the characteristics of the road edge and the relative distance between the road edge and the lane line, and further determine the fitting curve of the lane line, such as by selecting multiple points on the lane line. , to obtain the fitting curve of the lane line. Another method is to use the assisted driving device to fit lane lines based on the movement trajectory of the vehicle in front. Similarly, after the auxiliary driving device determines the lane line, it further determines the fitting curve of the lane line.

Three methods for identifying lane lines through image data acquired by cameras are as follows:

One method is for the assisted driving device to directly identify the lane lines in the image. Another method is to determine the lane line based on the light trajectory of the vehicle in front, and then determine the fitting curve of the lane line. Another method is that the assisted driving device determines the lane lines based on the motion trajectories of vehicles in adjacent lanes, and then determines the fitting curve.

For specific steps of the method shown in Figure 4, please refer to the above description and will not be described in detail here.

As can be seen from the above, some of the above methods are to obtain point cloud data through radar, and some are to obtain image data through cameras. Whether the data is obtained by radar or camera, the obtained data can be obtained before determining the fitting curve based on the obtained data. Preprocess the data and use the processed data to determine the fitting curve, thereby improving the accuracy of the determined fitting curve.

Optionally, preprocessing includes: converting the coordinates of the acquired data into a standard vector control system (VCS) coordinate system, that is, the vehicle coordinate system, where the coordinate origin is the center point of the bumper. It can be understood that the coordinate system of the original data obtained by sensors such as radar is generally the Cartesian coordinate system, polar coordinate system, etc. of the sensor itself. The coordinate systems of data obtained by different radars are not uniform. By combining the coordinate systems of the obtained original data, is the vehicle coordinate system, which is conducive to keeping the coordinates of the determined fitting curve uniform.

Further, preprocessing may also include: unifying the sampling periods of different radars or cameras. For example, the time stamps of the output parameters of different radars or cameras are unified, in other words, the timers set internally are time synchronized. For specific time synchronization steps, please refer to known technologies, which will not be described in detail here.

Further, preprocessing may also include filtering and noise reduction processing on the acquired data. For example, the image data acquired by the camera can be preprocessed through filtering, noise reduction, etc. to remove interfering information such as rain lines in the image, which will help improve the recognizability of the image.

In step 320, the driving assistance device obtains rainfall information.

The rainfall information is used to determine the weight value corresponding to each fitting curve, such as the first weight value corresponding to the first traffic sign line and the second weight value corresponding to the second traffic sign line.

One possible implementation is that the auxiliary driving device obtains the output value of the rain sensor and the wiper speed information, and determines the rain level based on the output value of the rain sensor and the wiper speed information.

Another possible implementation is for the assisted driving device to obtain rainfall information based on the Internet of Vehicles. For example, the auxiliary driving device obtains the current rainfall amount from the cloud and combines it with the wiper speed information to determine the current rainfall level. That is to say, the auxiliary driving device can obtain the amount of rainfall through the rain sensor, or it can also obtain the current amount of rainfall from the cloud.

The following takes the auxiliary driving device to determine the rain level based on the output value of the rain sensor and wiper speed information as an example to describe in detail the process of determining the rain level. The wiper speed information refers to the current wiper speed, hereafter referred to as the wiper speed. In other words, the auxiliary driving device can determine the rain level based on the output value of the rain sensor and the wiper speed.

The driver assistance device determines the rain level based on the output value of the rain sensor and the wiper speed. For example, the auxiliary driving device can determine the current rainfall based on the output value of the rain sensor, and then determine the rainfall level based on the rainfall, wiper speed, and mapping relationship. The above mapping relationship is used to indicate multiple rainfall ranges and multiple wiper speed ranges. Correspondence to multiple rainfall levels.

The method by which the auxiliary driving device calculates rainfall based on the output value of the rain sensor is first described in detail below.

The output value of the rain sensor includes the raindrop diameter, the number of raindrops, and the sensing area of the rain sensor. Assuming that the raindrops are all spherical, the precipitation volume per unit time is regarded as the rainfall per unit time, and the auxiliary driving device receives the above information from the rain sensor. After parameters, the rainfall is calculated based on the following formula:

Among them, i represents the rainfall amount per unit time (minutes), n represents the number of raindrops per unit time, d represents the diameter of the raindrops, and s represents the sensing area of the rain sensor.

After the auxiliary driving device calculates the rainfall, it determines the rainfall level by combining the obtained wiper speed and the pre-stored mapping relationship.

An example of the correspondence between multiple rainfall ranges, multiple wiper speed ranges, and multiple rain levels is given below.

Table 1

雨量等级e _i Rainfall level e _i	雨量范围rainfall range	雨刮速度范围Wiper speed range
11	[0,i ₁] [0,i ₁ ]	[0,60％][0,60%]
22	(i ₁,i ₂] (i ₁ ,i ₂ ]	(60％,80％](60%,80%]
33	(i ₂,i ₃] (i ₂ ,i ₃ ]	(80％,95％](80%,95%]
44	(i ₃,i ₄] (i ₃ ,i ₄ ]	(95％,100％](95%,100%]
55	(i ₄,i ₅] (i ₄ ,i ₅ ]	(95％,100％](95%,100%]

As shown in Table 1, the first column represents the rainfall level, the second column represents the rainfall range corresponding to different levels, and the third column represents the wiper speed range corresponding to different levels. Table 1 shows five rainfall levels, namely rainfall level 1 to level 5. Different rainfall levels correspond to different rainfall ranges and wiper speed ranges. For example, when the rainfall has been at (i ₁ , i ₂ ] and the wiper speed is at (60%, 80%] for a period of time, the auxiliary driving device can determine the rain level as 2. Wherein, the wiper speed Use pulse width modulation (PWM) duty cycle.

The threshold values of the wiper speed range and the classification of rain levels shown in Table 1 are only examples and should not constitute any limitation on the embodiments of the present application. For example, the rainfall level can be further subdivided into six levels, namely levels 1 to 6. In addition, the above classification of levels does not involve the situation when it is not raining. For example, the rainfall level when it is not raining can be determined as level 0.

The above mapping relationship is not limited to the form of a table. For example, it can also be in the form of other data structures, such as an array, a queue, or a stack. This application does not limit the specific form of the above mapping relationship.

It should be noted that, when the determined rainfall level is greater than or equal to the preset threshold, the auxiliary driving device can determine the third traffic marking line through the above auxiliary driving method, and then determine the driving area of the vehicle. In other words, when the rainfall level is less than the preset threshold, the driving area of the vehicle can be determined through known techniques. In addition, the auxiliary driving device can also send an alarm to the HMI to warn the driver when the determined rainfall level is greater than or equal to the preset threshold, thereby improving driving safety.

It should be noted that the embodiment of the present application does not limit the order of step 310 and step 320. For example, the assisted driving device may also perform step 320 first and then step 310.

In step 330, the assisted driving device determines the first weight value corresponding to the first traffic sign line and the second weight value corresponding to the second traffic sign line based on the rainfall information.

The following will take lane lines as an example to describe in detail the process of determining the weight value of the assisted driving device.

The first possible implementation method is that the auxiliary driving device determines the weight value corresponding to each fitting curve based on the output value of the rain sensor and the wiper speed. For example, the corresponding relationship between the weight value, the output value of the rain sensor and the wiper speed can be stored in advance, and the auxiliary driving device determines the weight value based on the obtained output value of the rain sensor and the wiper speed, such as the first traffic sign corresponding to the first traffic sign line. A weight value and a second weight value corresponding to the second traffic sign line.

The second possible implementation method is that the auxiliary driving device determines the rainfall level based on the output value of the rain sensor and the wiper speed, and then determines the weight value corresponding to each fitting curve based on the rainfall level. For example, multiple weight values corresponding to multiple fitting curves satisfy:

and

Among them, 1≤j≤J, J>1, J represents the total number of multiple fitting curves, j and J are both integers; m _j represents the weight value corresponding to the fitting curve j, e represents the rainfall level, and λ _j represents the simulated The probability influence coefficient of the fitting curve j is used to adjust the weight value corresponding to the fitting curve j, so that the sum of the multiple weight values corresponding to the multiple fitting curves is 1, k represents the sensor characteristic constant, α _j represents the fitting curve The confidence level of j, i represents the rainfall amount.

That is to say, after the auxiliary driving device determines the rainfall level, it can determine the first weight value corresponding to the first traffic sign line and the second weight value corresponding to the second traffic sign line through the above formula.

In step 340, the assisted driving device determines the third traffic sign line based on the first traffic sign line, the second traffic sign line, the first weight value and the second weight value.

After determining the weight value corresponding to each fitting curve based on the above method, the assisted driving device obtains the final traffic marking line based on each fitting curve in the multiple fitting curves and its corresponding weight value. For example, the assisted driving device determines the final third traffic sign line based on the first traffic sign line, the second traffic sign line, the first weight value and the second weight value. The third traffic sign line is the traffic sign line after the fusion of the above-mentioned first traffic sign line and the second traffic sign line. Compared with the first traffic sign line and the second traffic sign line, the third traffic sign line is more accurate and has Helps improve driving safety.

One possible implementation method is that the auxiliary driving device fuses at least two fitting curves in a weighted manner. For example, taking two methods to obtain two fitting curves, the unified expression of the fitting curve corresponding to the same lane line is: l _j =a _0j +a _1j x +a _2j x ² +a _3j x ³ , where l _j represents the fitting curve obtained by method j, a _0j to a _3j represent the coefficients of the fitting curve. The coefficients of the fitting curves obtained by different methods are different. The weight value corresponding to the fitting curve l _j is m _j , then the lane line after fusion is

For example, taking the use of 5 methods to obtain 5 fitting curves as an example, the unified expression of the fitting curve corresponding to the same lane line is: l _j =a _0j +a _1j x +a _2j x ² +a _3j x ³ , where l _j represents the fitting curve obtained by method j, a _0j to a _3j represent the coefficients of the fitting curve. The coefficients of the fitting curves obtained by different methods are different. The weight value corresponding to the fitting curve l _j is m _j , then the lane line after fusion is

Optionally, the above method further includes: the auxiliary driving device determines the driving area of the vehicle based on the above third traffic marking line.

Taking lane lines as an example, the auxiliary driving device can determine the lane lines on both sides of the vehicle based on the above method. Based on the above lane lines, the driving area of the vehicle can be further determined.

One possible implementation is that after the auxiliary driving device determines the lane lines on one side of the vehicle based on the above method, it determines the two sides of the lane where the vehicle is located based on the relative distance between the two lane lines that are pre-stored or obtained from the cloud. lane lines to further determine whether there is a target vehicle ahead. If so, obtain the distance between the own vehicle and the target vehicle, and then determine the vehicle's driving area. In other words, the vehicle's driving area includes the lane in which the vehicle is currently located, the distance to the vehicle in front, and the threat degree of adjacent vehicles to its own vehicle. Among them, the threat degree of the adjacent vehicle to the own vehicle can be characterized by, for example, the collision risk, and the collision risk can be calculated by the distance between the adjacent vehicle and the own vehicle. You can refer to the known technology, which will not be detailed here. narrate.

It can be understood that in the above process, it is necessary to determine whether there is a target vehicle ahead. For example, it can be determined whether there is a target vehicle ahead through a radar or a camera can be used to determine whether there is a target vehicle ahead.

In this embodiment of the present application, each method of identifying the target vehicle corresponds to a confidence threshold. When the confidence of identifying the target vehicle using multiple methods is greater than the above confidence threshold, it is determined that there is a target vehicle ahead. For example, if a target vehicle is identified through a camera, and the confidence of this method is greater than its corresponding confidence threshold; in addition, if a target vehicle is identified through a radar, and the confidence of this method is greater than its corresponding confidence threshold, then assist The driving device determines that there is indeed a target vehicle ahead.

After the auxiliary driving device determines the drivable area of the vehicle, it can further determine the recommended vehicle speed based on the rainfall level to improve driving safety.

Optionally, the above method further includes: the auxiliary driving device determines the recommended vehicle speed based on the rainfall level.

Here, the recommended vehicle speed may refer to the vehicle speed recommended in the current driving environment. It is understandable that the recommended vehicle speed may be different under different rainfall levels. For example, the higher the rainfall level, the lower the recommended speed may be.

Depending on the rainfall level, the recommended driving speed may also be different. For example, the higher the rainfall level, the lower the recommended vehicle speed, which is beneficial to driver safety.

One possible implementation is that the auxiliary driving device can determine the safe distance between the vehicle and the target vehicle based on the rainfall level. The target vehicle is the vehicle in front or behind, and determine the recommended vehicle speed based on the actual distance and the safe distance between the vehicle and the target vehicle. In other words, under different rainfall levels, the safe distance between the vehicle and the target vehicle is different. For example, the higher the rainfall level, the greater the safe distance between the vehicle and the target vehicle should be.

The process of the auxiliary driving device determining the safe distance between the vehicle and the target vehicle based on the rainfall level will be described in detail below.

The assisted driving device can determine the road adhesion function based on the rainfall level, and then determine the safe distance from the target vehicle based on the road adhesion function. For example, the rainfall level and road surface adhesion function satisfy the following formula:

Among them, f (μ _i ) represents the value of the road adhesion function under the current rainfall, μ _i5 represents the estimated value of the road adhesion factor when the rainfall is the largest, μ _i1 represents the estimated value of the road adhesion factor when the rainfall is the smallest, μ _i represents the estimated value of the road adhesion factor under the current rainfall The estimated value of the road adhesion factor, f(μ _i5 ) represents the predefined road adhesion function value when the rainfall is maximum, f(μ _i1 ) represents the predefined road adhesion function value when the rainfall is minimum, from the above formula, it can be obtained that the current rainfall The value of the road adhesion function.

After the auxiliary driving device calculates the road adhesion function value under the current rainfall based on the above formula, it further determines the safe distance from the target vehicle. For example, the safety distance can be determined by the following formula:

Among them, d _w represents the safe distance between the own vehicle and the target vehicle, v ₁ represents the relative speed of the target vehicle, t ₁ represents the system delay time, f (μ _i ) represents the road adhesion function under the current rainfall, and v ₂ represents the own vehicle’s Speed, a represents the maximum longitudinal acceleration relative to the target vehicle, and t ₂ represents the driver's reaction time.

Further, the auxiliary driving device establishes the objective function λ = dd _w based on the obtained actual distance between the own vehicle and the target vehicle, where d represents the actual distance between the own vehicle and the target vehicle. By targeting the objective function value to be greater than 0, That is, the actual distance is greater than the safe distance, and the value range of the own vehicle's speed v ₂ can be calculated, that is, the speed of the own vehicle should be within the above speed range.

When the actual distance between the own vehicle and the target vehicle is less than or equal to the safe distance, a warning can be sent through the HMI.

Optionally, the above method further includes: controlling the HMI to display the third traffic sign line and/or the recommended vehicle speed. For example, traffic signs and/or recommended vehicle speeds can be displayed through screen images, head-up displays (HUD), etc. It can also prompt the recommended vehicle speed through voice broadcast.

After the auxiliary driving device determines the third traffic sign line and the recommended vehicle speed, the HMI can be controlled to display the third traffic sign line and/or the recommended vehicle speed. When the method provided by the embodiment of the present application is applied to a self-driving vehicle, the above-mentioned traffic sign line and recommended vehicle speed can be sent to the controller, so that the vehicle drives according to the above-mentioned traffic sign line and recommended vehicle speed.

Among them, the HMI can display the above recommended vehicle speed through the interface, and can also remind the driver of the recommended vehicle speed through voice, which is not limited in the embodiment of the present application.

Figure 5 is a schematic diagram of information displayed on the vehicle-machine interface provided by the embodiment of the present application. As shown in Figure 5, the information displayed on the vehicle-machine interface includes the lane lines of the current lane, current weather, recommended vehicle speed, distance to the target vehicle, etc. Among them, the lane lines are curves. The above-mentioned lane lines can remind the driver of the lane type, such as straight roads and curves, so that the driver can know the intersection ahead in time when the lane cannot be clearly seen. The current weather is heavy rain, the recommended vehicle speed is less than 35 kilometers/hour (km/h), and drivers are reminded to drive carefully as the road is slippery in rainy days. In addition, the vehicle-machine interface also shows that the distance between the own vehicle and the vehicle in front is 50 meters (m), the distance from the left lane line is 1.5m, and the distance from the right lane line is 0.7m. The distance between the vehicle and the lane line is displayed. The distance helps the driver adjust the heading angle and control the steering wheel as needed. When the vehicle is close to a lane line on one side, the driver can also be warned by red lane lines.

The above information is displayed in the figure by taking an intuitive image as an example, which should not constitute any limitation on the embodiment of the present application. For example, in some other embodiments, the above information may also be displayed in the form of text, or a combination of text and images may be used, which is not limited in the embodiments of the present application.

Optionally, the above method further includes: determining whether to send a warning to the HMI based on the actual distance between the vehicle and the traffic sign line.

One implementation is that the auxiliary driving device determines a first duration based on the actual distance between the vehicle and the traffic sign line. The first duration is the duration between the current moment and the moment when the vehicle hits the traffic sign line; when the first duration is less than Send a warning to HMI for a preset time period.

It is understandable that in addition to ensuring the driver's longitudinal safety, it is also necessary to ensure the driver's lateral safety. In other words, one's own vehicle should keep a distance from the vehicles in the adjacent lane. to the lane lines to ensure driver safety.

For example, the assisted driving device may determine the first duration based on the distance between the vehicle and the lane line, and if the first duration is less than the preset duration, send a warning to the HMI. For example, taking the right lane line as an example, the assisted driving device can calculate how long it will take for the own vehicle to drive to the right based on the distance between the own vehicle and the right lane line, the lateral acceleration of the own vehicle, and the speed of the own vehicle. Lane lines, when the calculated duration is greater than the preset duration, send a warning to the HMI.

Another possible implementation is that after the auxiliary driving device determines the actual distance between the vehicle and the traffic sign line, for example, after determining the actual distance between the vehicle and the traffic sign line through radar, when the actual distance is greater than the preset distance, Send warning to HMI.

Based on the above technical solution, different methods are used to obtain the first traffic sign line and the second traffic sign line, and the impact of rainfall information on the method of obtaining the first traffic sign line and the second traffic sign line is considered, and each is determined based on the rainfall information. The weight values corresponding to the above-mentioned first traffic sign line and the second traffic sign line are used to obtain a more accurate third traffic sign line. By considering the impact of rainfall information on different methods, it is conducive to improving the final third traffic sign line. The accuracy can alleviate the driver's trouble of being unable to see the traffic signs clearly under special weather conditions, thus helping to improve driving safety.

On the other hand, by considering the impact of rainfall information on the method of obtaining the first traffic sign line and the second traffic sign line, it is beneficial to improve the accuracy of the final third traffic sign line. The more accurate the third traffic sign line is, the more accurate the third traffic sign line will be. The driving area determined by the third traffic marking line will be more accurate. Therefore, the accuracy of the driving area will also be improved, which will help improve driving safety in special weather.

The auxiliary driving device provided by the embodiment of the present application will be described in detail below with reference to FIGS. 6 and 7 .

FIG. 6 is a schematic block diagram of the driving assistance device 600 provided by an embodiment of the present application. As shown in FIG. 6 , the device 600 may include: an acquisition unit 610 and a processing unit 620 . Each unit in the device 600 can be used to implement the method described in the embodiment shown in FIG. 3 or FIG. 4 .

When the device 600 is used to implement the method described in the embodiment shown in Figure 3, the acquisition unit 610 can be used to acquire rainfall information; the acquisition unit 610 can also be used to acquire the first traffic marking line and the second traffic marking line; The processing unit 620 may be used to determine the first weight value corresponding to the first traffic sign line and the second weight value corresponding to the second traffic sign line according to the rainfall information; according to the first traffic sign line, the second traffic sign line, the first weight value value and the second weight value determine the third traffic marking line. For details, please refer to the detailed description in the method embodiments, which will not be described again here.

The specific process of each unit performing the above corresponding steps has been described in detail in the above method embodiments, and will not be described again for the sake of brevity.

The division of units in the embodiments of this application is schematic and is only a logical function division. In actual implementation, there may be other division methods. In addition, each functional unit in various embodiments of the present application may be integrated into one processor, may exist independently, or may have two or more units integrated into one unit. The above integrated units can be implemented in the form of hardware or software functional units.

FIG. 7 is another schematic block diagram of the driving assistance device 700 provided by an embodiment of the present application. The device 700 may be a chip system, or may be a device configured with a chip system to implement the driver detection function in the above method embodiment. In the embodiment of the present application, the chip system may be composed of chips, or may include chips and other discrete components.

As shown in FIG. 7 , the device 700 may include a processor 710 and a communication interface 720 . Among them, the communication interface 720 can be used to communicate with other devices through a transmission medium, so that the device used in the device 700 can communicate with other devices. The communication interface 720 may be, for example, a transceiver, an interface, a bus, a circuit, or a device capable of implementing transceiver functions. The processor 710 can use the communication interface 720 to input and output data, and is used to implement the method described in the corresponding embodiment of FIG. 3 or FIG. 4 . Specifically, the device 700 can be used to implement the functions of the auxiliary driving device in the above method embodiment.

For example, if the device 700 is used to implement the method described in the embodiment shown in Figure 3, the processor 710 can be used to obtain the first traffic sign line; obtain the second traffic sign line; and determine the third traffic sign line according to the rainfall information. A first weight value corresponding to a traffic sign line and a second weight value corresponding to a second traffic sign line; determining a third traffic sign based on the first traffic sign line, the second traffic sign line, the first weight value and the second weight value Wire. For details, please refer to the detailed description in the method embodiments, which will not be described again here.

Optionally, the apparatus 700 further includes at least one memory 730 for storing program instructions and/or data. Memory 730 and processor 710 are coupled. The coupling in the embodiment of this application is an indirect coupling or communication connection between devices, units or modules, which may be in electrical, mechanical or other forms, and is used for information interaction between devices, units or modules. Processor 710 may cooperate with memory 730. Processor 710 may execute program instructions stored in memory 730 . At least one of the at least one memory may be included in the processor.

The specific connection medium between the above-mentioned processor 710, communication interface 720 and memory 730 is not limited in the embodiment of the present application. In the embodiment of the present application, in Figure 7, the processor 710, the communication interface 720, and the memory 730 are connected through a bus 740. The bus 740 is represented by a thick line in FIG. 7 , and the connection methods between other components are only schematically illustrated and not limited thereto. The bus can be divided into address bus, data bus, control bus, etc. For ease of presentation, only one thick line is used in Figure 7, but it does not mean that there is only one bus or one type of bus.

The present application also provides a vehicle, which can be used to implement the method described in the method embodiment shown in Figure 3 or Figure 4. The vehicle may correspond to the auxiliary driving device shown in FIG. 6 or 7 , for example, may be the above-mentioned auxiliary driving device, or may include the above-mentioned auxiliary driving device.

This application also provides a computer program product. The computer program product includes: a computer program (which can also be called a code, or an instruction). When the computer program is run, it causes the computer to execute the implementation shown in Figure 3 or Figure 4 method described in the example.

This application also provides a computer-readable storage medium that stores a computer program (which may also be called a code, or an instruction). When the computer program is run, the computer is caused to execute the method described in the embodiment shown in FIG. 3 or FIG. 4 .

The processor in the embodiment of the present application may be an integrated circuit chip with signal processing capabilities. During the implementation process, each step of the above method embodiment can be completed through an integrated logic circuit of hardware in the processor or instructions in the form of software. The above-mentioned processor can be a general processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (field programmable gate array, FPGA), or other available processors. Programmed logic devices, discrete gate or transistor logic devices, discrete hardware components. Each method, step and logical block diagram disclosed in the embodiment of this application can be implemented or executed. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present application can be directly implemented by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software module can be located in random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, registers and other mature storage media in this field. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

The memory in the embodiment of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, non-volatile memory can be read-only memory (ROM), programmable ROM (PROM), erasable programmable read-only memory (erasable PROM, EPROM), electrically removable memory. Erase electrically programmable read-only memory (EPROM, EEPROM) or flash memory. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of illustration, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (synchronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (double data rate SDRAM, DDR SDRAM), enhanced synchronous dynamic random access memory (enhanced SDRAM, ESDRAM), synchronous link dynamic random access memory (synchlink DRAM, SLDRAM) ) and direct memory bus random access memory (direct rambus RAM, DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

The terms "unit", "module", etc. used in this specification may be used to refer to computer-related entities, hardware, firmware, a combination of hardware and software, software, or software in execution.

Those of ordinary skill in the art will appreciate that the various illustrative logical blocks and steps described in connection with the embodiments disclosed herein can be implemented as electronic hardware, or a combination of computer software and electronic hardware. accomplish. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each specific application, but such implementations should not be considered beyond the scope of this application. In the several embodiments provided in this application, it should be understood that the disclosed devices, equipment and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or can be integrated into another system, or some features can be ignored, or not implemented. On the other hand, the coupling or direct coupling or communication connection between each other shown or discussed may be through some interfaces, and the indirect coupling or communication connection of the devices or units may be in electrical, mechanical or other forms.

The units described as discrete components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application can be integrated into one processing unit, each unit can exist physically alone, or two or more units can be integrated into one unit.

In the above embodiments, the functions of each functional unit may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions (programs). When the computer program instructions (program) are loaded and executed on a computer, the processes or functions described in accordance with the embodiments of the present application are generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, e.g., the computer instructions may be transferred from a website, computer, server, or data center Transmission to another website, computer, server or data center through wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more available media integrated. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., digital video discs (DVD)), or semiconductor media (e.g., solid state disks (SSD) )wait.

If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the existing technology or the part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned storage media include: U disk, mobile hard disk, ROM, RAM, magnetic disk or optical disk and other media that can store program codes.

The above are only specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any person familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application. should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

An assisted driving method, characterized by including:

Get rainfall information;

Get the first traffic sign line;

Get the second traffic sign line;

Determine the first weight value corresponding to the first traffic sign line and the second weight value corresponding to the second traffic sign line according to the rainfall information;

A third traffic sign line is determined based on the first traffic sign line, the second traffic sign line, the first weight value and the second weight value.
The method of claim 1, wherein obtaining rainfall information includes:

Obtain the output value of the rain sensor and wiper speed information;

The rainfall level is determined based on the output value of the rain sensor and the wiper speed information.
The method of claim 2, wherein determining the first weight value corresponding to the first traffic sign line and the second weight value corresponding to the second traffic sign line based on the rainfall information includes: :

The first weight value corresponding to the first traffic sign line and the second weight value corresponding to the second traffic sign line are determined according to the rainfall level.
The method of claim 2 or 3, wherein determining the rainfall level based on the output value of the rain sensor and the wiper speed information includes:

Determine the current rainfall based on the output value of the rain sensor;

The rainfall level is determined according to the rainfall amount, the wiper speed information, and a mapping relationship. The mapping relationship is used to indicate the corresponding relationship between multiple rainfall ranges, multiple wiper speed ranges, and multiple rainfall levels.
The method according to any one of claims 2 to 4, characterized in that the first traffic sign line or the second traffic sign line is any one of the following:

A fitting curve determined based on the road railing or curb detected by the radar, and the relative distance between the road railing or curb and the traffic marking line;

A fitting curve determined based on the motion trajectory of the vehicle in front detected by the radar and the relative distance between two adjacent traffic signs;

The fitting curve determined by identifying the traffic sign lines in the images collected by the camera;

A fitting curve determined based on the light trajectory of the vehicle in front collected by the camera and the relative distance between two adjacent traffic signs; or

The fitting curve is determined based on the movement trajectories of vehicles in adjacent lanes collected by cameras and the relative distance between two adjacent traffic signs.
The method according to any one of claims 2 to 5, characterized in that the method further includes:

A recommended vehicle speed is determined based on the rainfall level.
The method of claim 6, wherein determining the recommended vehicle speed based on the rainfall level includes:

Determine a safe distance from the target vehicle based on the rainfall level, and the target vehicle is the vehicle in front or behind;

The recommended vehicle speed is determined based on the actual distance to the target vehicle and the safe distance.
The method of claim 7, wherein determining a safe distance from the target vehicle based on the rainfall level includes:

determining a road adhesion function based on the rainfall level;

A safe distance from the target vehicle is determined based on the road surface adhesion function.
The method according to any one of claims 6 to 8, characterized in that the method further includes:

Control the human-computer interaction system HMI to display the third traffic sign line and/or the recommended vehicle speed.
The method of claim 9, further comprising:

Based on the actual distance from the traffic sign line, it is determined whether to send a warning to the HMI.
An auxiliary driving device, characterized by including:

Acquisition unit, used to obtain rainfall information;

The acquisition unit is also used to acquire the first traffic marking line and the second traffic marking line;

A processing unit configured to determine a first weight value corresponding to the first traffic sign line and a second weight value corresponding to the second traffic sign line based on the rainfall information;

The processing unit is further configured to determine a third traffic sign line based on the first traffic sign line, the second traffic sign line, the first weight value and the second weight value.
The device according to claim 11, wherein the acquisition unit is specifically configured to acquire the output value of the rain sensor and the wiper speed information; and determine the rainfall level according to the output value of the rain sensor and the wiper speed information. .
The device according to claim 12, wherein the processing unit is specifically configured to determine a first weight value corresponding to the first traffic sign line and a third weight value corresponding to the second traffic sign line according to the rainfall level. Two weight values.
The device according to claim 12 or 13, characterized in that the acquisition unit is specifically used to:

Determine the current rainfall based on the output value of the rain sensor;

The rainfall level is determined according to the rainfall amount, the wiper speed information, and a mapping relationship. The mapping relationship is used to indicate the corresponding relationship between multiple rainfall ranges, multiple wiper speed ranges, and multiple rainfall levels.
The device according to any one of claims 12 to 14, characterized in that the first traffic sign line or the second traffic sign line is any one of the following:

A fitting curve determined based on the road railing or curb detected by the radar, and the relative distance between the road railing or curb and the traffic marking line;

A fitting curve determined based on the motion trajectory of the vehicle in front detected by the radar and the relative distance between two adjacent traffic signs;

The fitting curve determined by identifying the traffic sign lines in the images collected by the camera;

The fitting curve is determined based on the light trajectory of the vehicle in front collected by the camera and the relative distance between two adjacent traffic signs;

The fitting curve is determined based on the movement trajectories of vehicles in adjacent lanes collected by cameras and the relative distance between two adjacent traffic signs.
The device according to any one of claims 12 to 15, wherein the processing unit is further configured to determine a recommended vehicle speed based on the rainfall level.
The device of claim 16, wherein the processing unit is specifically configured to:

Determine a safe distance from the target vehicle based on the rainfall level, and the target vehicle is the vehicle in front or behind;

The recommended vehicle speed is determined based on the actual distance to the target vehicle and the safe distance.
The device according to claim 17, wherein the processing unit is specifically configured to:

determining a road adhesion function based on the rainfall level;

A safe distance from the target vehicle is determined based on the road surface adhesion function.
The device according to any one of claims 16 to 18, characterized in that the device further includes: a control unit configured to control the human-computer interaction system HMI to display the third traffic sign line and/or the recommendation vehicle speed.
The device of claim 19, wherein the processing unit is further configured to determine whether to send a warning to the HMI based on the actual distance to the traffic sign line.
An auxiliary driving device, characterized by including a memory and a processor; wherein,

The memory is used to store program code;

The processor is configured to call the program code to implement the method according to any one of claims 1 to 10.
A vehicle, characterized by including the driving assistance device according to any one of claims 11 to 21.
A computer-readable storage medium, characterized in that computer-executable instructions are stored in the computer-readable storage medium, and when the computer-executable instructions are executed by a processor, they are used to implement any one of claims 1 to 10. method described.
A computer program product, characterized by comprising a computer program that implements the method according to any one of claims 1 to 10 when executed by a processor.