Vehicle control method, device, equipment and storage medium on flooded road

Abstract

The present invention belongs to the field of vehicle control technology, and discloses a vehicle control method, device, equipment and storage medium for a flooded road surface. The method includes: acquiring environmental perception information; determining water accumulation perception information and environmental perception information according to the environmental perception information; generating obstacle impact parameters according to the water accumulation perception information and environmental perception information; planning a driving trajectory based on the environmental perception information and obstacle impact parameters; and completing vehicle control according to the driving trajectory. Through the above-mentioned method, the water accumulation information in the image is perceived, and the driving trajectory is planned based on the perception of water accumulation, thereby avoiding vehicle failure caused by direct wading of the vehicle and improving the safety of vehicle control.

Description

Technical Field

[0001] The present invention relates to the field of vehicle control technology, and in particular to a vehicle control method, device, equipment and storage medium on a flooded road surface. Background Art

[0002] The rapid development of artificial intelligence (AI) technology has provided strong support for intelligent driving. Through technologies such as deep learning and machine learning, vehicles can continuously learn and optimize their driving behaviors to better adapt to various complex environments. Obstacle avoidance is crucial for intelligent driving vehicles. It refers to the ability of the vehicle to automatically identify and avoid various obstacles during driving. This ability is of great significance for ensuring driving safety, improving the intelligent driving experience, and reducing the risk of accidents. At present, intelligent driving-related obstacle avoidance technologies are more targeted at protruding objects on the ground with strong regularity, such as cones, water barriers, and guardrails. When water accumulates on the road, people generally choose to wade directly, which reduces the life of the vehicle.

[0003] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0004] The main purpose of the present invention is to provide a vehicle control method, device, equipment and storage medium on a flooded road, aiming to solve the technical problem of low safety of flooded roads faced by the prior art.

[0005] To achieve the above object, the present invention provides a vehicle control method on a flooded road, the method comprising the following steps:

[0006] Obtain environmental perception information;

[0007] Determine water accumulation perception information and environmental perception information according to the environmental perception information;

[0008] generating obstacle impact parameters according to the water accumulation perception information and the environment perception information;

[0009] Planning a driving trajectory based on the environmental perception information and obstacle impact parameters;

[0010] Vehicle control is completed according to the driving trajectory.

[0011] Optionally, generating obstacle impact parameters according to the water accumulation perception information and the environment perception information includes:

[0012] determining a water accumulation contour according to the water accumulation sensing information;

[0013] Determine the position of the protruding obstacle according to the environmental perception information;

[0014] Obstacle impact parameters are generated according to the water accumulation contour and the position of the protruding obstacle.

[0015] Optionally, determining a water accumulation contour according to the water accumulation perception information includes:

[0016] Get the current vehicle's driving information;

[0017] Determine the water depth distribution information according to the water accumulation perception information;

[0018] determining a water depth threshold according to the driving information;

[0019] The waterlogging contour is determined according to the waterlogging depth distribution information and the waterlogging depth threshold.

[0020] Optionally, determining a water depth threshold according to the driving information includes:

[0021] determining the current vehicle speed and suspension system operating parameters according to the driving information;

[0022] The water depth threshold is determined according to the current vehicle speed and the suspension system operating parameters.

[0023] Optionally, determining a water accumulation contour according to the water accumulation perception information includes:

[0024] Determine the water accumulation contour and water quality information of the water accumulation according to the water accumulation perception information;

[0025] Obstacle impact parameters are generated according to the ponding contour, ponding water quality information and the position of the protruding obstacle.

[0026] Optionally, generating obstacle impact parameters according to the ponding contour, ponding water quality information, and the position of the protruding obstacle includes:

[0027] Determining the credibility of water accumulation detection according to the water quality information of the water accumulation;

[0028] Adjusting the water accumulation contour according to the water accumulation detection credibility to obtain an adjusted water accumulation contour;

[0029] Obstacle impact parameters are generated according to the adjusted water accumulation contour.

[0030] Optionally, planning a driving trajectory based on the environmental perception information and obstacle impact parameters includes:

[0031] Performing environmental modeling according to the environmental perception information and obstacle impact parameters to obtain an environmental element network;

[0032] The driving trajectory is planned according to the preset path planning strategy and the environmental element network.

[0033] In addition, to achieve the above-mentioned purpose, the present invention also provides a vehicle control device for a flooded road surface, the vehicle control device for a flooded road surface comprising:

[0034] An acquisition module is used to acquire environmental perception information;

[0035] A processing module, used to determine water accumulation perception information and environmental perception information according to the environmental perception information;

[0036] The processing module is used to generate obstacle impact parameters according to the water accumulation perception information and the environment perception information;

[0037] The processing module is used to plan a driving trajectory based on the environmental perception information and obstacle impact parameters;

[0038] A control module is used to complete vehicle control according to the driving trajectory.

[0039] In addition, to achieve the above-mentioned purpose, the present invention also proposes a vehicle control device for a flooded road surface, the vehicle control device for a flooded road surface comprising: a memory, a processor, and a vehicle control program for a flooded road surface stored in the memory and executable on the processor, the vehicle control program for a flooded road surface being configured to implement the steps of the vehicle control method for a flooded road surface as described above.

[0040] In addition, to achieve the above-mentioned purpose, the present invention also proposes a storage medium, on which a vehicle control program for a flooded road surface is stored. When the vehicle control program for a flooded road surface is executed by a processor, the steps of the vehicle control method for a flooded road surface as described above are implemented.

[0041] The present invention obtains environmental perception information; determines water accumulation perception information and environmental perception information according to the environmental perception information; generates obstacle impact parameters according to the water accumulation perception information and environmental perception information; plans a driving trajectory based on the environmental perception information and obstacle impact parameters; and completes vehicle control according to the driving trajectory. Through the above-mentioned method, the water accumulation information in the image is perceived, and the driving trajectory is planned based on the perception of water accumulation, thereby avoiding vehicle failure caused by direct wading of the vehicle and improving the safety of vehicle control. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a flow chart of a first embodiment of a vehicle control method on a flooded road according to the present invention;

[0043] Figure 2 A schematic diagram of obstacle avoidance in accordance with an embodiment of a vehicle control method on a flooded road according to the present invention;

[0044] Figure 3A schematic diagram of trajectory update of an embodiment of a vehicle control method on a flooded road according to the present invention;

[0045] Figure 4 A schematic flow chart of a second embodiment of a vehicle control method on a flooded road according to the present invention;

[0046] Figure 5 It is a structural block diagram of a first embodiment of a vehicle control device for a flooded road according to the present invention;

[0047] Figure 6 It is a structural schematic diagram of a vehicle control device for a flooded road in a hardware operating environment involved in an embodiment of the present invention.

[0048] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0049] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0050] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0051] The main solution of the embodiment of the present application is: the vehicle-mounted terminal obtains environmental perception information; determines water accumulation perception information and environmental perception information based on the environmental perception information; generates obstacle impact parameters based on the water accumulation perception information and environmental perception information; plans a driving trajectory based on the environmental perception information and obstacle impact parameters; and completes vehicle control according to the driving trajectory.

[0052] In this embodiment, for the convenience of description, the following description is made by taking identification of the vehicle-mounted terminal as the execution subject.

[0053] Thanks to existing technologies such as deep learning and machine learning, vehicles can continuously learn and optimize their driving behaviors to better adapt to various complex environments. Obstacle avoidance is crucial for smart driving vehicles. It refers to the ability of the vehicle to automatically identify and avoid various obstacles during driving. This ability is of great significance for ensuring driving safety, improving the smart driving experience, and reducing the risk of accidents. However, the current smart driving-related obstacle avoidance technology is more targeted at protruding objects on the ground with strong regularity, such as cones, water barriers, and guardrails. When water accumulates on the road, people generally choose to wade directly, which reduces the life of the vehicle.

[0054] The present application provides a solution that enables the perception of water accumulation information in an image. By perceiving the water accumulation and planning the driving trajectory based on this information, vehicle failure caused by direct wading of the vehicle is avoided, thereby improving the safety of vehicle control.

[0055] It should be noted that the execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a vehicle-mounted terminal, etc. The following takes the vehicle-mounted terminal as an example to illustrate this embodiment and the following embodiments.

[0056] Based on this, the embodiment of the present application provides a vehicle control method on a flooded road, referring to Figure 1 , Figure 1 This is a flow chart of a first embodiment of a vehicle control method on a flooded road surface of the present application.

[0057] In this embodiment, the vehicle control method on a flooded road comprises the following steps:

[0058] Step S10: Acquire environmental perception information.

[0059] It should be noted that this embodiment is applied to the automatic driving or assisted driving scenario under the condition of wading water. Since the current intelligent driving related obstacle avoidance technology is more for the ground protruding objects with strong regularity such as cone barrels, water barriers, guardrails, etc., the recognition and processing capabilities for irregular and inconspicuous protruding obstacles such as road water accumulation are still insufficient. Therefore, this scheme proposes a method, device and related equipment for calculating and generating trajectory planning for avoiding waterlogged roads based on the vehicle's front-view camera and radar recognition and detection of key edge points of waterlogged roads. The image collected by the camera is processed by an image recognition algorithm to extract the characteristic information of the road waterlogging area, such as the area of ​​waterlogging, boundary shape and preliminary position, etc. The data obtained by the radar sensor is preprocessed, feature extracted and parameter calculated by the radar signal processing algorithm to obtain information such as the position of the waterlogged road ahead and the shape of key points. Combined with the recognition results of the camera and radar, the road waterlogging area is accurately identified and located through a fusion algorithm. The two complement each other to improve the accuracy and reliability of recognition. When the system confirms that there is water on the road ahead, it generates a corresponding deceleration and obstacle avoidance trajectory based on information such as the water area and key point locations. Of course, the obstacle avoidance trajectory will also take into account environmental conditions, such as lane line type and whether there are other protruding obstacles. The schematic diagram of intelligent driving deceleration and avoidance of water on the road is shown in Figure 3.

[0060] It should be noted that environmental perception information refers to the images of the scene collected by the on-board image acquisition device or other sensors, such as: lane images in the front direction, road images, images of other vehicles, pedestrian images, lidar information, millimeter-wave radar information, and obstacle images, etc.

[0061] Step S20: Determine water accumulation perception information and environmental perception information according to the environmental perception information.

[0062] It is understandable that when the camera captures an image of water on the road, it will perform image analysis to identify the waterlogged area. At the same time, combined with radar detection technology, this technology is based on the vehicle's millimeter-wave radar sending electromagnetic waves to the road surface, and then receiving and analyzing the reflected signals. Due to its special physical properties, the waterlogged road surface will produce strong reflections on the radar electromagnetic waves. By receiving and analyzing these reflected waves, the radar system can determine whether there is water on the road surface and estimate the relevant parameters of the waterlogging. Finally, the fusion technology of cameras and radars can be used to achieve all-round and multi-angle accurate perception of road waterlogging, and further generate deceleration and obstacle avoidance paths based on road waterlogging perception information and environmental perception information (lane line type, lane edge, protruding obstacles, etc.).

[0063] Furthermore, real-time road recognition can identify road conditions, including road surface status and environmental characteristics, in real time through the vehicle's front-view camera machine vision and edge analysis technology. Furthermore, when the camera captures an image of water on the road, the system will perform image analysis to identify the location and scope of the waterlogged area.

[0064] Among them, waterlogging-related information can also be obtained through the vehicle-equipped millimeter-wave radar, which transmits electromagnetic waves to the road surface and receives the signals reflected from the road surface. The waterlogged road surface has a smooth surface and a high moisture content, which results in strong reflection of radar electromagnetic waves. By analyzing the reflected signal, the radar system can determine whether there is water on the road surface and estimate the depth and range of the water.

[0065] It should be noted that through the fusion of camera and radar data, all-round and multi-angle road water perception information is provided. In addition to water accumulation information, environmental conditions such as lane line type, lane edge, and protruding obstacles can also be considered. Finally, based on the perceived road water and environmental conditions, the system generates a deceleration and obstacle avoidance path to help the driver or the autonomous driving system safely avoid the waterlogged area and ensure driving safety. It combines the visual recognition of the camera and the physical detection of the radar, using their respective advantages to improve the accurate perception of road water. Through real-time data analysis and path planning, it can effectively help drivers avoid the dangers of flooded sections and improve driving safety and comfort.

[0066] Step S30: Generate obstacle impact parameters according to the water accumulation perception information and the environment perception information.

[0067] It is understandable that obstacle influencing parameters may include: influencing factors, obstacle weight values, obstacle position / volume information and other parameters, where influencing factors, for example: comprehensive consideration of waterlogged areas, lane characteristics and possible obstacles, all of which will affect the vehicle's driving trajectory, and the system will evaluate each influencing factor. The obstacle weight is to assign appropriate weights to each influencing factor according to different situations and urgency, so that the system can respond correctly and generate reasonable path planning. Based on the evaluated influencing parameters, the vehicle's speed, direction or choice of different driving routes can be adjusted to ensure safe avoidance of waterlogged areas and other obstacles, while minimizing driving interruptions or discomfort.

[0068] Step S40: planning a driving trajectory based on the environmental perception information and obstacle impact parameters.

[0069] It is understandable that this embodiment reasonably calculates and generates a deceleration obstacle avoidance trajectory based on environmental perception, and is embodied in the form of algorithms such as penalty functions and obstacle avoidance function functions. Combining the impact of the vehicle speed and the weight of the penalty function in the objective function on obstacle avoidance, the following form of obstacle function function is selected:

[0070]

[0071] In the formula, S obs is the weight coefficient, v i =v x 2 +v y 2 ,(x i ,y i ) is the position coordinate of the obstacle point in the vehicle body coordinate system, (x0, y0) is the coordinate of the center of mass of the vehicle, and ε is a small positive number to prevent the denominator from being zero.

[0072] It should be noted that driving trajectory planning mainly relies on the model for calculation. The control goal in the trajectory planning layer is to minimize the deviation from the global reference path and achieve obstacle avoidance. Obstacle avoidance is achieved in the form of a penalty function. The specific form of the model predictive controller of the trajectory replanning layer is as follows:

[0073]

[0074] Us min ≤U t ≤U max In the formula, J obs,i is the obstacle avoidance function at sampling time i.

[0075] It is necessary to process the local reference path planned by the trajectory replanning algorithm to achieve smooth docking between the planning layer and the control layer. Curve fitting is the main way to process discrete points. Here we choose a 5th-order polynomial as the fitting curve, which is as follows:

[0076] Y=a0t 5 +a1t 4 +a2t 3 +a3t 2 +a4t+a5

[0077]

[0078] In the formula, a p =[a0, a1, a2, a3, a4, a5], b p =[b0, b1, b2, b3, b4, b5] are the parameters to be determined.

[0079] Specifically, for trajectory planning in a dynamic environment, the system can generate scattered points based on the current position of the vehicle and the target position. These scattered points may be determined based on real-time environmental perception to ensure that the path can avoid dynamic obstacles or adapt to real-time changing environmental conditions. The penalty function is used to avoid obstacles to obtain a set of scattered points of a feasible path, and then the final driving trajectory is obtained through curve fitting.

[0080] In some embodiments, environment modeling is performed based on the environment perception information and obstacle impact parameters to obtain an environment element network; and a driving trajectory is planned based on a preset path planning strategy and the environment element network.

[0081] It should be noted that the goal of environmental modeling is to construct an environmental element network based on environmental perception information and obstacle impact parameters. The environmental network is a real-time scenario model that includes information about various obstacles, water accumulation, road information, and environmental information. The penalty function determines which obstacles and roads should be avoided, and the preset path planning strategy determines how the vehicle chooses its route in the traversable area.

[0082] Step S50: completing vehicle control according to the driving trajectory.

[0083] It should be noted that once the global path and local path are generated by the path planning algorithm, the vehicle needs to follow these paths. Specifically, trajectory tracking is performed first. The trajectory tracking process is as follows Figure 3 As shown in the figure, the vehicle needs to compare its current position and direction with the planned path to determine which part of the path it is in. Based on the path information and environmental perception data, the vehicle accelerates, brakes, steers, and other operations through the control system to navigate the vehicle safely along the path.

[0084] This embodiment obtains environmental perception information; determines water accumulation perception information and environmental perception information based on the environmental perception information; generates obstacle impact parameters based on the water accumulation perception information and environmental perception information; plans a driving trajectory based on the environmental perception information and obstacle impact parameters; and completes vehicle control based on the driving trajectory. Through the above-mentioned method, the water accumulation information in the image is perceived, and the driving trajectory is planned based on the perception of water accumulation, which avoids vehicle failure caused by direct wading of the vehicle and improves the safety of vehicle control.

[0085] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 4 , step S30, the vehicle control method on a flooded road further includes:

[0086] Step S31: determining a water accumulation contour according to the water accumulation perception information.

[0087] It should be noted that, according to the specific determination process, for example: the millimeter-wave radar can analyze the reflected signal of the accumulated water and identify the location and possible depth of the accumulated water by analyzing the signal reflected by the road surface. Based on the image information or radar recognition of the water surface features, the boundary and shape of the accumulated water area are determined according to the intensity and pattern of the radar reflected signal or the image recognition algorithm. Then, the data detected by different sensors are fused, such as fusing the data of the camera and radar, and the advantages of both are comprehensively considered to improve the detection precision and accuracy of the accumulated water area. Finally, the contour is drawn, and the contour map of the accumulated water area is generated according to the information obtained from the analysis, marking the boundary and possible diffusion range of the accumulated water.

[0088] In some embodiments, driving information of the current vehicle is obtained; water accumulation depth distribution information is determined based on the water accumulation perception information; a water accumulation depth threshold is determined based on the driving information; and a water accumulation contour is determined based on the water accumulation depth distribution information and the water accumulation depth threshold.

[0089] It is understandable that the specific information on the distribution of water depth can be: after using sensors such as millimeter wave radar to detect water on the road and obtain real-time data on the depth of water, the collected water depth data is analyzed and processed, and data processing algorithms such as filters and data smoothing can be used to eliminate noise and abnormal data, so as to obtain more accurate water depth distribution information. A water depth threshold is set based on the characteristics and design limitations of the vehicle, as well as driving safety considerations. This threshold can be a fixed value, or it can be dynamically adjusted according to vehicle speed, road conditions, etc. Only water areas greater than this water depth threshold are determined as water contours.

[0090] In some embodiments, the current vehicle speed and suspension system operating parameters are determined based on the driving information; and the water depth threshold is determined based on the current vehicle speed and suspension system operating parameters.

[0091] It should be noted that when wading, a higher speed may increase the speed and pressure of water entering the bottom of the vehicle, which will increase the risk of damage to mechanical and electronic components. A lower speed is more conducive to reducing the influx of water and slowing down the impact during wading. And a higher speed may make the vehicle waves higher and increase the possibility of water entering the bottom of the vehicle. Therefore, the higher the speed, the shallower the water depth threshold should be set.

[0092] Similarly, the suspension directly determines the state of the vehicle chassis, and the state of the suspension system is crucial to the wading performance. In particular, a higher ground clearance can improve the ability to pass through water, so the higher the suspension system lifts the chassis, the deeper the water depth threshold can be set.

[0093] In some embodiments, the water accumulation contour and water quality information are determined based on the water accumulation perception information; and obstacle impact parameters are generated based on the water accumulation contour, water quality information and the position of the protruding obstacle.

[0094] Understandably, water quality may affect the system's ability to accurately assess the depth and bottom of a waterway, and water with low transparency may obscure obstacles or uneven bottoms, increasing the risk of accidents. Therefore, information on ponding water quality can be incorporated to adjust the obstacle impact parameters.

[0095] In some embodiments, the water accumulation detection credibility is determined based on the water quality information; the water accumulation contour is adjusted based on the water accumulation detection credibility to obtain an adjusted water accumulation contour; and obstacle impact parameters are generated based on the adjusted water accumulation contour.

[0096] It should be noted that the credibility of water accumulation detection is determined based on the water quality information. When the water is turbid and has low transmittance, the depth may not be accurately determined, and the situation of the underwater ground is also unclear. Therefore, there is a certain risk. The credibility of water accumulation detection can be used to set a weight for the water accumulation part to comprehensively consider and adjust the water accumulation contour to ensure driving safety, and then generate obstacle impact parameters based on the adjusted water accumulation contour.

[0097] Step S32: Determine the position of the protruding obstacle according to the environmental perception information.

[0098] It should be noted that object detection and recognition can use computer vision technology to process and analyze camera and radar data to identify possible obstacles. Based on image analysis or radar reflection data, obstacles in the surrounding environment are separated from the background. And the distance, direction and speed information provided by the sensor are used to determine the exact position of the obstacle relative to the vehicle. After obtaining the target and position, obstacles can also be classified according to sensor data and preset models, such as pedestrians on the sidewalk, vehicles on the road or other objects as prominent obstacles.

[0099] Step S33: Generate obstacle impact parameters according to the water accumulation contour and the position of the protruding obstacle.

[0100] It should be noted that the types of obstacles and the spatial positions of obstacles can be determined based on the water accumulation contour and the positions of the protruding obstacles, thereby constructing obstacle impact parameters.

[0101] This embodiment determines the water accumulation contour according to the water accumulation perception information; determines the position of the protruding obstacle according to the environmental perception information; and generates obstacle impact parameters according to the water accumulation contour and the protruding obstacle position. Through the above content, a detailed analysis of the water accumulation situation is achieved, and the integration of water accumulation and obstacles improves the accuracy and decision-making efficiency of vehicle path planning.

[0102] In addition, an embodiment of the present invention further proposes a storage medium on which a vehicle control program for a flooded road surface is stored. When the vehicle control program for a flooded road surface is executed by a processor, the steps of the vehicle control method for a flooded road surface as described above are implemented.

[0103] Reference Figure 5 , Figure 5 It is a structural block diagram of the first embodiment of the vehicle control device for flooded road surface of the present invention.

[0104] like Figure 5 As shown, the vehicle control device for a flooded road surface provided in an embodiment of the present invention includes:

[0105] An acquisition module 10 is used to acquire environmental perception information;

[0106] A processing module 20, configured to determine water accumulation perception information and environmental perception information according to the environmental perception information;

[0107] The processing module 20 is used to generate obstacle impact parameters according to the water accumulation perception information and the environment perception information;

[0108] The processing module 20 is used to plan a driving trajectory based on the environmental perception information and obstacle impact parameters;

[0109] The control module 30 is used to complete vehicle control according to the driving trajectory.

[0110] The vehicle control device for a flooded road provided by the present application adopts the vehicle control method for a flooded road in the above-mentioned embodiment, and can solve the technical problem of vehicle control for a flooded road. Compared with the prior art, the beneficial effects of the vehicle control device for a flooded road provided by the present application are the same as the beneficial effects of the vehicle control method for a flooded road provided by the above-mentioned embodiment, and the other technical features of the vehicle control device for a flooded road are the same as the features disclosed in the above-mentioned embodiment method, which will not be repeated here.

[0111] It should be understood that the above is only an example and does not constitute any limitation on the technical solution of the present invention. In specific applications, technicians in this field can make settings as needed, and the present invention does not limit this.

[0112] In this embodiment, the acquisition module 10 acquires environmental perception information; the processing module 20 determines water accumulation perception information and environmental perception information based on the environmental perception information; the processing module 20 generates obstacle impact parameters based on the water accumulation perception information and environmental perception information; the processing module 20 plans the driving trajectory based on the environmental perception information and obstacle impact parameters; and the control module 30 completes vehicle control based on the driving trajectory. Through the above-mentioned method, the water accumulation information in the image is perceived, and the driving trajectory is planned based on the perception of water accumulation and the information, which avoids vehicle failure caused by direct wading of the vehicle and improves the safety of vehicle control.

[0113] In some embodiments, the processing module 20 is used to determine the water accumulation contour according to the water accumulation perception information;

[0114] Determine the position of the protruding obstacle according to the environmental perception information;

[0115] Obstacle impact parameters are generated according to the water accumulation contour and the position of the protruding obstacle.

[0116] In some embodiments, the processing module 20 is used to obtain the driving information of the current vehicle;

[0117] Determine the water depth distribution information according to the water accumulation perception information;

[0118] determining a water depth threshold according to the driving information;

[0119] The waterlogging contour is determined according to the waterlogging depth distribution information and the waterlogging depth threshold.

[0120] In some embodiments, the processing module 20 is used to determine the current vehicle speed and suspension system operating parameters according to the driving information;

[0121] The water depth threshold is determined according to the current vehicle speed and the suspension system operating parameters.

[0122] In some embodiments, the processing module 20 is used to determine the water accumulation contour and water quality information of the water accumulation according to the water accumulation perception information;

[0123] Obstacle impact parameters are generated according to the ponding contour, ponding water quality information and the position of the protruding obstacle.

[0124] In some embodiments, the processing module 20 is used to determine the reliability of water accumulation detection according to the water quality information of the water accumulation;

[0125] Adjusting the water accumulation contour according to the water accumulation detection credibility to obtain an adjusted water accumulation contour;

[0126] Obstacle impact parameters are generated according to the adjusted water accumulation contour.

[0127] In some embodiments, the processing module 20 is used to perform environment modeling according to the environment perception information and obstacle impact parameters to obtain an environment element network;

[0128] The driving trajectory is planned according to the preset path planning strategy and the environmental element network.

[0129] The present application provides a vehicle control device for a flooded road surface, the vehicle control device for a flooded road surface comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the vehicle control method for a flooded road surface in the above-mentioned embodiment one.

[0130] Reference below Figure 6 , which shows a schematic diagram of the structure of a vehicle control device for a flooded road surface suitable for implementing an embodiment of the present application. The vehicle control device for a flooded road surface in the embodiment of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 6 The vehicle control device for a flooded road shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0131] like Figure 6As shown, the vehicle control device for flooded road surface may include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. Various programs and data required for the operation of the vehicle control device for flooded road surface are also stored in RAM1004. The processing device 1001, ROM1002, and RAM1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the vehicle control device for the flooded road surface to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows the vehicle control device for the flooded road surface with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have instead.

[0132] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0133] The vehicle control device for a flooded road provided by the present application adopts the vehicle control method for a flooded road in the above embodiment, and can solve the technical problem of vehicle control for a flooded road. Compared with the prior art, the beneficial effects of the vehicle control device for a flooded road provided by the present application are the same as the beneficial effects of the vehicle control method for a flooded road provided by the above embodiment, and the other technical features of the vehicle control device for a flooded road are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0134] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0135] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0136] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, the computer-readable program instructions being used to execute the vehicle control method on a flooded road surface in the above-mentioned embodiment.

[0137] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0138] The computer-readable storage medium may be included in the vehicle control device for flooded road surfaces; or may exist independently without being assembled into the vehicle control device for flooded road surfaces.

[0139] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the vehicle control device on the flooded road, the vehicle control device on the flooded road: obtains environmental perception information; determines water accumulation perception information and environmental perception information based on the environmental perception information; generates obstacle impact parameters based on the water accumulation perception information and environmental perception information; plans a driving trajectory based on the environmental perception information and obstacle impact parameters; and completes vehicle control according to the driving trajectory.

[0140] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0141] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0142] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0143] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned vehicle control method for a flooded road surface, and can solve the technical problem of vehicle control for a flooded road surface. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the vehicle control method for a flooded road surface provided by the above-mentioned embodiment, and will not be elaborated here.

[0144] The present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the vehicle control method on a flooded road as described above.

[0145] The computer program product provided by this application can solve the technical problem of vehicle control on flooded roads. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the vehicle control method on flooded roads provided by the above embodiments, which will not be repeated here.

[0146] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A vehicle control method on a flooded road, characterized in that: The vehicle control method on a flooded road comprises: Obtain environmental perception information; Determining water accumulation perception information and environmental condition perception information according to the environmental perception information, wherein the environmental condition perception information includes lane line type, lane edge, and protruding obstacles; generating obstacle impact parameters according to the water accumulation perception information and the environmental condition perception information; Planning a driving trajectory based on the environmental condition perception information and obstacle impact parameters; completing vehicle control according to the driving trajectory; The generating obstacle impact parameters according to the water accumulation perception information and the environmental condition perception information includes: determining a water accumulation contour according to the water accumulation sensing information; Determine the position of the protruding obstacle based on the environmental condition perception information; Generate obstacle influence parameters according to the water accumulation contour and the protruding obstacle position, wherein the obstacle influence parameters include influence factors, obstacle weight values, and obstacle position / volume information, and the influence factors include water accumulation area influence factors, lane feature influence factors, and obstacle influence factors; The determining of the water accumulation contour according to the water accumulation perception information includes: Get the current vehicle's driving information; Determine the water depth distribution information according to the water accumulation perception information; determining a water depth threshold according to the driving information; A water accumulation contour is determined according to the water accumulation depth distribution information and a water accumulation depth threshold, wherein a water accumulation area greater than the water accumulation depth threshold is determined as the water accumulation contour.

2. The method according to claim 1, characterized in that The step of determining a water depth threshold according to the driving information includes: determining the current vehicle speed and suspension system operating parameters according to the driving information; The water depth threshold is determined according to the current vehicle speed and the suspension system operating parameters.

3. The method according to claim 1, characterized in that The determining of the water accumulation contour according to the water accumulation perception information includes: Determine the water accumulation contour and water quality information of the water accumulation according to the water accumulation perception information; Obstacle impact parameters are generated according to the ponding contour, ponding water quality information and the position of the protruding obstacle.

4. The method according to claim 3, characterized in that The generating of obstacle impact parameters according to the ponding contour, ponding water quality information and the position of the protruding obstacle includes: Determining the credibility of water accumulation detection according to the water quality information of the water accumulation; Adjusting the water accumulation contour according to the water accumulation detection credibility to obtain an adjusted water accumulation contour; Obstacle impact parameters are generated according to the adjusted water accumulation contour.

5. The method according to claim 1, characterized in that The planning of the driving trajectory based on the environmental condition perception information and the obstacle impact parameter includes: Performing environmental modeling based on the environmental condition perception information and obstacle impact parameters to obtain an environmental element network; The driving trajectory is planned according to the preset path planning strategy and the environmental element network.

6. A vehicle control device for a flooded road, characterized in that: The vehicle control device for a flooded road surface comprises: An acquisition module is used to acquire environmental perception information; A processing module, configured to determine water accumulation perception information and environmental condition perception information according to the environmental perception information, wherein the environmental condition perception information includes lane line type, lane edge, and protruding obstacles; The processing module is used to generate obstacle impact parameters according to the water accumulation perception information and the environmental condition perception information; The processing module is used to plan a driving trajectory based on the environmental condition perception information and obstacle impact parameters; A control module, used to complete vehicle control according to the driving trajectory; The processing module is used to determine the water accumulation contour according to the water accumulation perception information; determine the position of the protruding obstacle according to the environmental condition perception information; generate obstacle influence parameters according to the water accumulation contour and the protruding obstacle position, the obstacle influence parameters include influencing factors, obstacle weight values ​​and obstacle position / volume information, and the influencing factors include water accumulation area influencing factors, lane feature influencing factors and obstacle influencing factors; obtain the driving information of the current vehicle; determine the water accumulation depth distribution information according to the water accumulation perception information; determine the water accumulation depth threshold according to the driving information; determine the water accumulation contour according to the water accumulation depth distribution information and the water accumulation depth threshold, wherein the water accumulation area greater than the water accumulation depth threshold is determined to be the water accumulation contour.

7. A vehicle control device for a flooded road, characterized in that: The device includes: a memory, a processor, and a vehicle control program for a flooded road surface stored in the memory and executable on the processor, wherein the vehicle control program for a flooded road surface is configured to implement the steps of a vehicle control method for a flooded road surface as described in any one of claims 1 to 5.

8. A storage medium, characterized in that: The storage medium stores a vehicle control program for a flooded road surface, and when the vehicle control program for a flooded road surface is executed by a processor, the steps of the vehicle control method for a flooded road surface according to any one of claims 1 to 5 are implemented.

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