Carrier control method and apparatus, electronic device, and storage medium

Abstract

The application provides a carrier control method and device, electronic equipment and storage medium. The driving environment of the carrier is detected by using a sensor to determine a detection result. Then, a target driving scene and corresponding target control parameters are determined according to the detection result. Finally, the carrier is controlled to safely drive in the target driving scene according to the target control parameters. The technical problem that the mobility carrier for the elderly or the disabled cannot intelligently identify the driving scene and automatically perform driving assistance according to the driving scene is solved, and the technical effect of improving the use experience and safety of the mobility carrier, such as the electric wheelchair, for the elderly or the disabled is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of automatic control, and in particular, to a carrier control method and device, an electronic device, and a storage medium. BACKGROUND

[0002] With the increase of the aging population, the demand for mobility carriers for the elderly or the disabled, such as electric folding wheelchairs, is also increasing, and the requirements are also increasing.

[0003] Since the existing mobility carriers such as electric wheelchairs have a control system that simply responds to control instructions of an operating lever or an operating button to perform basic operations such as traveling and braking, but for complex driving environments such as turning in an elevator and driving on a bumpy road, the user's driving level is required to solve various problems in the driving process, or additional assistance is required for human intervention.

[0004] This results in the technical problem that the user of the mobility carrier cannot independently cope with complex driving environments, resulting in a poor user experience of the mobility carrier. SUMMARY

[0005] The present application provides a carrier control method, device, electronic device, and storage medium to solve the technical problem that the existing mobility carriers for the elderly or the disabled cannot intelligently identify the driving scene and automatically assist driving according to the driving scene.

[0006] In a first aspect, the present application provides a carrier control method, comprising:

[0007] detecting a driving environment of a carrier using a sensor to determine a detection result;

[0008] determining a target driving scene and a corresponding target control parameter according to the detection result;

[0009] controlling the carrier to safely drive in the target driving scene according to the target control parameter.

[0010] In a possible design, the detection result includes an obstacle distance, and the determination of the target driving scene and the corresponding target control parameter according to the detection result comprises:

[0011] determining an obstacle category according to the obstacle distance;

[0012] determining the target driving scene according to the obstacle category;

[0013] determining an obstacle avoidance control parameter according to the obstacle distance and the target driving scene using a preset obstacle avoidance model, wherein the target control parameter includes the obstacle avoidance control parameter.

[0014] Optionally, the target driving scene includes: a normal driving scene, a road surface unevenness scene, and a narrow space scene.

[0015] In a possible design, the sensor includes: a first ground sensor and a second ground sensor, the first ground sensor and the second ground sensor are configured to detect a slant distance from the sensor to the road surface, and correspondingly, the obstacle distance includes a first slant distance and a second slant distance, the first slant distance is greater than the second slant distance, and the determining the obstacle category according to the obstacle distance includes:

[0016] If the fluctuation amplitudes of the first slant distance and the second slant distance are less than a preset fluctuation threshold, the obstacle category is determined as no obstacle, and correspondingly, the target driving scene is a normal driving scene.

[0017] Optionally, the determining the obstacle category according to the obstacle distance includes:

[0018] If a first fluctuation amplitude of the first slant distance is greater than or equal to the preset fluctuation threshold, and a second fluctuation amplitude of the second slant distance is less than the preset fluctuation threshold, the obstacle category is determined as a pit or a bump, and correspondingly, the road surface unevenness scene is a pit or a bump road surface.

[0019] In a possible design, the determining the obstacle category according to the obstacle distance includes:

[0020] If a difference between an average change rate of the first slant distance and an average change rate of the second slant distance is less than a preset change rate difference, the obstacle category is determined as a gentle slope, and correspondingly, the road surface unevenness scene is a gentle slope road surface.

[0021] If the difference between the average change rate of the first slant distance and the average change rate of the second slant distance is greater than or equal to the preset change rate difference, the obstacle category is determined as a slope uneven obstacle, and correspondingly, the road surface unevenness scene is a slope uneven road surface.

[0022] If the difference between the average change rate of the first slant distance and the average change rate of the second slant distance is greater than or equal to the preset change rate difference, the obstacle category is determined as a slope uneven obstacle, and correspondingly, the road surface unevenness scene is a slope uneven road surface.

[0023] Optionally, the sensor includes a gyroscope, the detection result includes a slope, and the determining the obstacle category according to the obstacle distance includes:

[0024] If the difference between the average change rate of the first slant distance and the average change rate of the second slant distance is less than a preset change rate difference, and the slope is less than a preset slope threshold, it is determined that the obstacle type is a downhill gentle slope, and the corresponding road uneven scene is a downhill gentle slope road surface

[0025] If the difference between the average change rate of the first slant distance and the average change rate of the second slant distance is greater than or equal to a preset change rate difference, and the slope is less than a preset slope threshold, it is determined that the obstacle type is a downhill uneven obstacle, and the corresponding road uneven scene is a downhill uneven road surface.

[0026] Optionally, the detection result includes a vehicle speed, and the determination of the obstacle avoidance control parameter according to the obstacle distance and the target driving scene by using a preset obstacle avoidance model includes:

[0027] The determination of a preset safe speed according to the target driving scene and the obstacle distance by using a preset obstacle avoidance model;

[0028] The determination of a brake control instruction according to the preset safe speed, so that the vehicle speed is reduced to below the preset safe speed, and the obstacle avoidance control parameter includes the brake control instruction.

[0029] In a possible design, when the first slant distance is greater than a first preset threshold, and the second slant distance is less than a second preset threshold, the obstacle is a pit.

[0030] In a possible design, the determination of the obstacle category according to the obstacle distance further includes:

[0031] If the difference between the fixed angle of the first ground sensor and / or the second ground sensor and the slope is less than a preset angle threshold, it is determined that the obstacle category is a second gentle slope in a downhill gentle slope road surface.

[0032] Correspondingly, the determination of the obstacle avoidance control parameter includes the determination that the operating state parameter of the current vehicle is unchanged.

[0033] If the difference between the fixed angle of the first ground sensor and / or the second ground sensor and the slope is greater than or equal to a preset angle threshold, it is determined that the obstacle category is a pit in a downhill gentle slope road surface.

[0034] Correspondingly, the determination of the obstacle avoidance control parameter includes the determination of a brake control instruction, so that the vehicle speed is less than or equal to a preset safe threshold.

[0035] In a possible design, the sensor includes a side sensor, the obstacle distance includes a lateral distance, and the determining the obstacle category according to the obstacle distance includes: if the lateral distance is less than a narrow space threshold, determining that the obstacle category is a non-crossable obstacle, and the corresponding target driving scenario is the narrow space scenario.

[0036] In a possible design, the determining the obstacle avoidance control parameter according to the obstacle distance and the target driving scenario by using the preset obstacle avoidance model includes:

[0037] The determining that the vehicle can make a U-turn by using the preset obstacle avoidance model according to the lateral distance, the vehicle width and a U-turn threshold includes:

[0038] The obstacle avoidance control parameter includes an automatic U-turn control parameter.

[0039] In a possible design, the determining that the vehicle can make a U-turn by using the preset obstacle avoidance model according to the lateral distance, the vehicle width and a U-turn threshold includes:

[0040] If the sum of the lateral distance and the vehicle width is greater than or equal to the U-turn threshold, it is determined that the vehicle can make a U-turn.

[0041] In a possible design, the sensor further includes a front-back sensor, the obstacle distance includes a front distance and a back distance, and the determining that the vehicle can make a U-turn further includes:

[0042] Determining a size relationship between the lateral distance and a direct U-turn threshold.

[0043] If the lateral distance is greater than or equal to the direct U-turn threshold, determining a back distance adjustment value according to the front distance and the back distance.

[0044] Correspondingly, the obstacle avoidance control parameter includes the back distance adjustment value.

[0045] Optionally, after the determining the size relationship between the lateral distance and the direct U-turn threshold, the method further includes:

[0046] If the lateral distance is less than the direct U-turn threshold, adjusting the back distance of the vehicle according to the back distance adjustment value.

[0047] Determining a lateral distance adjustment parameter according to the lateral distance by using the obstacle avoidance model.

[0048] Correspondingly, the lateral distance is adjusted by the vehicle according to the lateral distance adjustment parameter in a preset adjustment mode, so that the lateral distance is greater than or equal to the direct-turn threshold.

[0049] In a possible design, the preset adjustment mode includes:

[0050] The vehicle is controlled to rotate the rotation angle in the lateral distance adjustment parameter;

[0051] The vehicle is controlled to reverse rotation by the rotation angle;

[0052] The rearward distance adjustment value is determined again according to the forward distance and the rearward distance.

[0053] Correspondingly, the rearward distance of the vehicle is controlled to reach a preset rearward reserved value according to the rearward distance adjustment value.

[0054] In a possible design, the sensor includes at least a distance sensor covering the front, rear, left and right directions of the vehicle, and the target driving scene further includes an obstacle avoidance scene, and the obstacle avoidance control parameter is determined according to the obstacle distance and the target driving scene by using a preset obstacle avoidance model, including:

[0055] If the detection result of the distance sensor is less than a gear down distance, the speed control gear of the vehicle is determined, and the obstacle avoidance control parameter includes the speed control gear;

[0056] If the detection result is less than a sensitivity control distance, the speed or direction control instruction input by the user is reduced by a preset proportion to obtain a corresponding control value;

[0057] The gear down distance is greater than or equal to the sensitivity control distance.

[0058] In a possible design, the speed or direction control instruction input by the user is reduced by a preset proportion to obtain a corresponding control value, including:

[0059] The control value of the control rocker is multiplied by a preset attenuation coefficient.

[0060] Optionally, before the driving environment of the vehicle is detected by the sensor to obtain a detection result, the method further includes:

[0061] In response to a preset mode start instruction input by the user, the gear of the vehicle is set to a preset gear corresponding to the preset mode;

[0062] Correspondingly, the target control parameter is a product of an original control parameter obtained according to a preset control model and a correction coefficient, and the correction coefficient corresponds to the preset mode.

[0063] In a possible design, the preset mode includes a novice mode and an emergency mode, the correction coefficient corresponding to the novice mode is less than 1, and the correction coefficient corresponding to the emergency mode is greater than 1.

[0064] In a second aspect, the present application provides a carrier control device, including:

[0065] a detection module configured to detect a driving environment of the carrier by using a sensor, to determine a detection result;

[0066] a processing module configured to determine a target driving scenario and a corresponding target control parameter according to the detection result;

[0067] a control module configured to control the carrier to safely drive in the target driving scenario according to the target control parameter.

[0068] In a possible design, the detection result includes an obstacle distance, and the processing module, configured to determine a target driving scenario and a corresponding target control parameter according to the detection result, includes:

[0069] the processing module is configured to determine an obstacle category according to the obstacle distance;

[0070] the processing module is further configured to determine the target driving scenario according to the obstacle category;

[0071] the processing module is further configured to determine an obstacle avoidance control parameter according to the obstacle distance and the target driving scenario by using a preset obstacle avoidance model, and the target control parameter includes the obstacle avoidance control parameter.

[0072] Optionally, the target driving scenario includes a normal driving scenario, a road surface unevenness scenario, and a narrow space scenario.

[0073] In a possible design, the sensor includes a first ground sensor and a second ground sensor, the first ground sensor and the second ground sensor are configured to detect an oblique line distance from the sensor to a road surface, correspondingly, the obstacle distance includes a first oblique line distance and a second oblique line distance, the first oblique line distance is greater than the second oblique line distance, and the processing module is further configured to determine an obstacle category according to the obstacle distance, including:

[0074] the processing module is further configured to determine that the obstacle category is no obstacle and the target driving scenario is a normal driving scenario if a fluctuation amplitude of the first oblique line distance and the second oblique line distance is less than a preset fluctuation threshold.

[0075] Optionally, the processing module, configured to determine an obstacle category according to the obstacle distance, includes:

[0076] If the first fluctuation amplitude of the first slant distance is greater than or equal to the preset fluctuation threshold, and the second fluctuation amplitude of the second slant distance is less than the preset fluctuation threshold, it is determined that the obstacle category is a pit or a bump, and the corresponding road unevenness scene is a pit or a bump road.

[0077] In a possible design, the determining of the obstacle category according to the obstacle distance includes:

[0078] If the difference between the average change rate of the first slant distance and the average change rate of the second slant distance is less than a preset change rate difference, it is determined that the obstacle category is a gentle slope, and the corresponding road unevenness scene is a gentle slope road.

[0079] If the difference between the average change rate of the first slant distance and the average change rate of the second slant distance is greater than or equal to the preset change rate difference, it is determined that the obstacle category is a slope uneven obstacle, and the corresponding road unevenness scene is a slope uneven road.

[0080] Optionally, the sensor includes a gyroscope, and the detection result includes a slope, and the processing module is further configured to determine the obstacle category according to the obstacle distance, including:

[0081] The processing module is further configured to, if the difference between the average change rate of the first slant distance and the average change rate of the second slant distance is less than a preset change rate difference, and the slope is less than a preset slope threshold, determine that the obstacle type is a downhill gentle slope, and the corresponding road unevenness scene is a downhill gentle slope road.

[0082] If the difference between the average change rate of the first slant distance and the average change rate of the second slant distance is greater than or equal to a preset change rate difference, and the slope is less than a preset slope threshold, it is determined that the obstacle type is a downhill uneven obstacle, and the corresponding road unevenness scene is a downhill uneven road.

[0083] Optionally, the detection result includes a vehicle speed, and the processing module is further configured to determine an obstacle avoidance control parameter according to the obstacle distance and the target driving scene by using a preset obstacle avoidance model, including:

[0084] The processing module is further configured to determine a preset safe speed according to the target driving scene and the obstacle distance by using a preset obstacle avoidance model.

[0085] The processing module is further configured to determine a brake control instruction according to the preset safe speed, so as to make the vehicle speed drop below the preset safe speed, and the obstacle avoidance control parameter includes the brake control instruction.

[0086] In a possible design, when the first slant distance is greater than a first preset threshold and the second slant distance is less than a second preset threshold, the obstacle is a pit.

[0087] In a possible design, the processing module is further configured to determine an obstacle category according to the obstacle distance, and the processing module includes:

[0088] If a difference between the fixed angle of the first ground sensor and / or the second ground sensor and the slope is less than a preset angle threshold, the obstacle category is determined to be a second gentle slope in a downhill gentle slope road surface.

[0089] Correspondingly, the processing module is configured to determine an obstacle avoidance control parameter, including: determining that a running state parameter of the vehicle is unchanged.

[0090] If the difference between the fixed angle of the first ground sensor and / or the second ground sensor and the slope is greater than or equal to the preset angle threshold, the obstacle category is determined to be a pit in a downhill gentle slope road surface.

[0091] Correspondingly, the processing module is configured to determine the obstacle avoidance control parameter, including: determining a brake control instruction, so that the speed of the vehicle is less than or equal to a preset safety threshold.

[0092] In a possible design, the sensor includes a side sensor, and the obstacle distance includes a lateral distance. The processing module is configured to determine an obstacle category according to the obstacle distance, including: if the lateral distance is less than a narrow space threshold, the obstacle category is determined to be an insurmountable obstacle, and correspondingly, the target driving scene is the narrow space scene.

[0093] In a possible design, the processing module is further configured to determine an obstacle avoidance control parameter according to the obstacle distance and the target driving scene by using a preset obstacle avoidance model, including:

[0094] The processing module is further configured to determine, by using the preset obstacle avoidance model, that the vehicle can make a U-turn according to the lateral distance, a vehicle width and a U-turn threshold, and then

[0095] The processing module is further configured to determine an automatic U-turn control parameter by using the preset obstacle avoidance model, and the obstacle avoidance control parameter includes the automatic U-turn control parameter.

[0096] In a possible design, the processing module is further configured to determine, by using the preset obstacle avoidance model, that the vehicle can make a U-turn according to the lateral distance, a vehicle width and a U-turn threshold, including:

[0097] determining that the vehicle can make the turn if the sum of the lateral distance and the vehicle width is greater than or equal to the turn threshold.

[0098] In a possible design, the sensor further includes a front-rear sensor, the obstacle distance includes a front distance and a rear distance, and the processing module is further configured to determine, after determining that the vehicle can make the turn, that:

[0099] The processing module is further configured to determine a size relationship between the lateral distance and a direct-turn threshold.

[0100] The processing module is further configured to determine, if the lateral distance is greater than or equal to the direct-turn threshold, a rear distance adjustment value according to the front distance and the rear distance.

[0101] Correspondingly, the obstacle avoidance control parameter includes the rear distance adjustment value.

[0102] Optionally, the processing module is further configured to, after determining the size relationship between the lateral distance and the direct-turn threshold, determine:

[0103] if the lateral distance is less than the direct-turn threshold, adjust the rear distance of the vehicle according to the rear distance adjustment value.

[0104] The processing module is further configured to determine, by using the obstacle avoidance model, a lateral distance adjustment parameter according to the lateral distance.

[0105] Correspondingly, the control module is configured to control the vehicle to adjust the lateral distance in a preset adjustment manner according to the lateral distance adjustment parameter, so that the lateral distance is greater than or equal to the direct-turn threshold.

[0106] In a possible design, the preset adjustment manner includes:

[0107] The control module is further configured to control the vehicle to rotate the lateral distance by a rotation angle in the lateral distance adjustment parameter.

[0108] The control module is further configured to control the vehicle to rotate in a reverse direction by the rotation angle.

[0109] The processing module is further configured to determine, again, a rear distance adjustment value according to the front distance and the rear distance.

[0110] Correspondingly, the control module is further configured to control the rear distance of the vehicle to reach a preset rear reserved value according to the rear distance adjustment value.

[0111] In a possible design, the sensors include distance sensors covering at least four directions (front, back, left, and right) of the vehicle, and the target driving scenario further includes an obstacle avoidance scenario, and the processing module is further configured to determine an obstacle avoidance control parameter according to the obstacle distance and the target driving scenario by using a preset obstacle avoidance model, including:

[0112] The processing module is further configured to determine a speed control gear of the vehicle if the detection result of the distance sensor is less than the downshift distance, and the obstacle avoidance control parameter includes the speed control gear.

[0113] The processing module is further configured to reduce a speed or direction control instruction input by a user by a preset proportion to obtain a corresponding control value if the detection result is less than the sensitivity control distance.

[0114] The downshift distance is greater than or equal to the sensitivity control distance.

[0115] In a possible design, the processing module is further configured to reduce a speed or direction control instruction input by a user by a preset proportion to obtain a corresponding control value, including:

[0116] Multiplying a control value of a control joystick by a preset attenuation coefficient.

[0117] Optionally, before the step of detecting a driving environment of the vehicle by using the sensors to obtain a detection result, the method further includes:

[0118] The processing module is further configured to set a gear of the vehicle to a preset gear corresponding to a preset mode in response to a preset mode starting instruction input by a user.

[0119] Correspondingly, the target control parameter is a product of an original control parameter obtained according to a preset control model and a correction coefficient, and the correction coefficient corresponds to the preset mode.

[0120] In a possible design, the preset mode includes a novice mode and an emergency mode, the correction coefficient corresponding to the novice mode is less than 1, and the correction coefficient corresponding to the emergency mode is greater than 1.

[0121] In a third aspect, the present application provides an electronic device, including:

[0122] A memory configured to store program instructions.

[0123] A processor configured to invoke and execute the program instructions in the memory, and execute any one of the possible vehicle control methods provided in the first aspect.

[0124] In a fourth aspect, the present application provides a storage medium, wherein the readable storage medium stores a computer program, and the computer program is used to execute any possible vehicle control method provided in the first aspect.

[0125] The present application provides a vehicle control method and device, electronic equipment and storage medium. The vehicle control method comprises the following steps: detecting a driving environment of a vehicle by using a sensor, determining a detection result, determining a target driving scene and a corresponding target control parameter according to the detection result, and controlling the vehicle to drive safely in the target driving scene according to the target control parameter. The technical problem that the existing vehicle for the elderly or the disabled cannot intelligently identify a driving scene and automatically perform driving assistance according to the driving scene is solved, and the technical effects of improving the use experience and safety of the vehicle for the elderly or the disabled, such as an electric wheelchair, are achieved. BRIEF DESCRIPTION OF DRAWINGS

[0126] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0127] Figure 1 A vehicle use scene schematic diagram is provided for the present application;

[0128] Figure 2 A flowchart of a vehicle control method is provided for the present application;

[0129] Figure 3 A flowchart of a second vehicle control method is provided for the present application;

[0130] Figures 4A-4B An application scene schematic diagram of the vehicle control method provided by the embodiment of the present application when driving on a potholed road is provided;

[0131] Figure 5 A flowchart of a third vehicle control method is provided for the present application;

[0132] Figure 6 A flowchart of a fourth vehicle control method is provided for the present application;

[0133] Figure 7 A flowchart of a fifth vehicle control method is provided for the present application;

[0134] Figure 8 A structural schematic diagram of a vehicle control device is provided for the present application;

[0135] Figure 9A structural schematic diagram of an electronic device is provided in the present application. DETAILED DESCRIPTION

[0136] In order to make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work, including but not limited to combinations of the embodiments, fall within the scope of protection of the present application.

[0137] The terms "first", "second", "third", "fourth" and the like (if any) in the description, claims, and drawings of the present application are used to distinguish similar objects, and do not necessarily indicate a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to the process, method, product or device.

[0138] With the universal occurrence of population aging, the proportion of the elderly in the social population gradually increases. Due to the contradiction between the travel needs of the elderly and physiological aging, the demand for a walking aid such as an electric wheelchair is generated. Similarly, for some disabled people with physiological barriers, the vehicle is also an indispensable tool for their independent life.

[0139] However, the existing walking aid such as the electric wheelchair only has simple control of the motor in the electric wheelchair, and for more complex driving scenes such as potholed road surface, long slope road surface, narrow space (such as elevator room, supermarket escalator) and the like, the vehicle user himself has to rely on his own operation or the assistance of a nanny or caregiver, which seriously affects the use experience of the vehicle user.

[0140] Therefore, how to make the vehicle control intelligent, automatically recognize the complex driving scene, and automatically assist the control according to the characteristics of each driving scene, has become a technical problem to be solved urgently.

[0141] The vehicle control method provided by the present application will be described in detail below in combination with the drawings to solve the above technical problems.

[0142] Figure 1 A schematic diagram of a carrier usage scenario is provided for the present application. As shown, the carrier is an electric folding wheelchair 100, and a sensor 101 is installed on the electric folding wheelchair 100. When a user drives the electric folding wheelchair 100 to travel in various complex environments, such as uneven road surface scenarios and narrow space scenarios. Moreover, each scenario can be further divided into various sub-scenarios, such as ramp scenarios and pothole scenarios. The carrier control method provided by the present application enables the carrier to automatically identify various target driving scenarios and provide intelligent driving assistance to the user. Figure 1

[0143] The carrier control method provided by the present application will be described in detail below.

[0144] Figure 2 A flowchart of a carrier control method provided by the present application is shown in FIG. 1. As shown, the carrier control method provided by the present application includes the following specific steps: Figure 2

[0145] S201, detecting the driving environment of the carrier using a sensor to determine a detection result.

[0146] In this step, the installation method of the sensor includes being installed on the carrier, and / or being worn on the user, and uploading the detected environmental data, i.e., the detection result, to the carrier control system through wireless transmission. The sensor includes a radar, an infrared probe, a gyroscope, a camera, a laser range finder, etc.

[0147] In this embodiment, the carrier includes an electric wheelchair, an electric folding wheelchair, an electric scooter, etc.

[0148] S202, determining a target driving scenario and corresponding target control parameters according to the detection result.

[0149] In this embodiment, the detection result includes an obstacle distance, which is the measured distance between the sensor and the obstacle. The obstacle includes a fence, a pothole, a protrusion, a ramp, a staircase, a wall, etc.

[0150] The specific steps include:

[0151] determining an obstacle category according to the obstacle distance;

[0152] determining a target driving scenario according to the obstacle category;

[0153] determining an obstacle avoidance control parameter according to the obstacle distance and the target driving scenario using a preset obstacle avoidance model.

[0154] In this embodiment, the target control parameter includes an obstacle avoidance control parameter.

[0155] ​​It should be noted that the target driving scene includes: a normal driving scene, a road surface uneven scene, and a narrow space scene.

[0156] It should also be noted that the obstacle distance measured by the sensor can be a vertical distance or an inclined distance. For example, when a pit is measured by using an infrared probe or a laser range finder, the obstacle distance is the distance of the inclined line from the sensor to the ground.

[0157] S203, controlling the vehicle to safely drive in the target driving scene according to the target control parameter.

[0158] In this step, the control system controls a series of execution devices on the vehicle according to the generated target control parameter, such as the output power of the motor, the response speed of the rocker, the maximum speed of the vehicle, automatic braking, voice prompts, etc., so that the vehicle can automatically and intelligently assist the user to drive, and avoid some safety hazards that the user cannot easily find, such as stairs, pits, convex speed bumps, etc.

[0159] The embodiment of the present application provides a vehicle control method, which detects the driving environment of the vehicle by using a sensor, determines a detection result, then determines a target driving scene and corresponding target control parameters according to the detection result, and finally controls the vehicle to safely drive in the target driving scene according to the target control parameters. The technical problem that the walking aid vehicle for the elderly or the disabled cannot intelligently identify the driving scene and automatically assist driving according to the driving scene is solved, and the technical effect of improving the use experience and safety of the walking aid vehicle such as the electric wheelchair for the elderly or the disabled is achieved.

[0160] In order to better understand the application of the vehicle control method of the present application in different driving scenes, the above target driving scene will be described in more detail in combination with specific embodiments.

[0161] Figure 3 The flowchart of the second vehicle control method provided by the present application is shown in FIG. 2. As shown in the figure, the specific steps of the method include: Figure 3

[0162] S301, detecting the driving environment of the vehicle by using a sensor to determine a detection result, the detection result including an obstacle distance.

[0163] In this embodiment, the sensor includes a first ground sensor and a second ground sensor, and the first ground sensor and the second ground sensor are used to detect the inclined distance from the sensor to the road surface.

[0164] The detection result includes an obstacle distance, the obstacle distance including a first inclined distance and a second inclined distance, and the first inclined distance being greater than the second inclined distance. ​

[0165] Figures 4A-4B This is a schematic diagram illustrating an application scenario of the vehicle control method provided in this application when driving on a bumpy road surface. Figure 4A As shown, a first sensor 401 and a second sensor 402 are installed on the handrail of the vehicle 400. The first sensor 401 and the second sensor 402 can be implemented using radar, infrared detectors, laser rangefinders, etc. The installation angles of the first sensor 401 and the second sensor 402 are different, resulting in different angles between the first oblique distance H1 and the second oblique distance H2 measured by them and the road surface, and consequently, different lengths of H1 and H2. Figure 4B As shown, H1 is greater than H2. It can be understood that in another possible case, H1 may also be less than or equal to H2, or the installation angle of the first sensor 401 and the second sensor 402 can be dynamically adjusted, and can automatically change the measurement angle according to different driving scenarios and the needs of judgment.

[0166] It should also be noted that the first sensor 401 and the second sensor 402 can also be installed at the same location on the carrier 400, such as on a handle. Furthermore, the first sensor 401 and the second sensor 402 can also be a sensor array composed of multiple sensors. Those skilled in the art can choose the installation location and number of sensors according to the actual situation, and this application does not impose any limitations.

[0167] S302. Determine the obstacle category based on the obstacle distance, and determine the target driving scenario based on the obstacle category.

[0168] In one possible implementation, if the fluctuation range of the first diagonal distance and the second diagonal distance is less than a preset fluctuation threshold, then the obstacle category is determined to be obstacle-free, and the corresponding target driving scenario is a normal driving scenario.

[0169] like Figure 4A As shown, as the vehicle 400 moves, the distances H1 and H2 of the first and second diagonal lines will fluctuate due to the uneven road surface. When the fluctuations are small, they are considered normal driving bumps, and the road surface is still within the flat range. In this case, a preset fluctuation threshold is set as the criterion for determining whether the road surface is flat. Those skilled in the art can choose the specific value of the preset fluctuation threshold according to the actual situation, which is not limited here.

[0170] In another possible implementation, if the first fluctuation amplitude of the first diagonal distance is greater than or equal to a preset fluctuation threshold, and the second fluctuation amplitude of the second diagonal distance is less than the preset fluctuation threshold, then the obstacle category is determined to be a pit or a bump, and the corresponding uneven road surface scenario is a pit or a bump road surface.

[0171] like Figure 4BAs shown, the detection range of the first sensor 401 is farther than that of the second sensor 402. However, the area of ​​a pit or protrusion is finite. Therefore, the first sensor 401 will first detect the change in the first diagonal distance H1, i.e., the first fluctuation amplitude exceeds the preset fluctuation threshold. However, the second sensor 402 will still detect a flat road surface, i.e., the second fluctuation amplitude of the second diagonal distance H2 is less than the preset fluctuation threshold. This effectively prevents misjudgment of pits or slopes. Existing technologies typically only use one sensor to detect the fluctuation of the diagonal distance ahead, or use sensors with the same tilt angle on both sides to detect the diagonal distance fluctuation to determine if there is a pit ahead. However, such setups can easily lead to misidentifying pits as slopes, or slopes as pits or protrusions, resulting in incorrect judgments when identifying whether there is a step below, potentially causing falls and affecting the user experience.

[0172] Furthermore, when the distance of the first diagonal line is greater than the first preset threshold and the distance of the second diagonal line is less than the second preset threshold, the obstacle is a pit.

[0173] In another possible implementation, if the difference between the average rate of change of the first diagonal distance and the average rate of change of the second diagonal distance is less than a preset rate of change difference, then the obstacle category is determined to be a gentle slope, and the corresponding uneven road surface scenario is a gentle slope road surface. If the difference between the average rate of change of the first diagonal distance and the average rate of change of the second diagonal distance is greater than or equal to the preset rate of change difference, then the obstacle category is determined to be an uneven slope obstacle, such as a pothole, bump, or step in the slope.

[0174] When the vehicle has entered the ramp surface, the ramp may still have undulations, meaning the slope value changes depending on the location, such as potholes or bumps, or steps. At this point, it is necessary to identify whether the ramp is gentle or uneven, such as with potholes, bumps, or steps. In this embodiment, since the first slope distance is greater than the second slope distance, if an uneven obstacle is encountered, the average rate of change of the first slope distance over a preset time period will change, causing the difference between the average rate of change of the first slope distance and the average rate of change of the second slope distance to increase. If this difference is greater than or equal to a preset difference, the control system determines that an uneven obstacle has been encountered.

[0175] It should be noted that a ramp can be either uphill or downhill.

[0176] Furthermore, the slope from a gyroscope can be used to assist in determining whether an obstacle is uphill or downhill. That is, the sensor includes a gyroscope, the detection result includes the slope, and determining the obstacle category based on the obstacle distance includes:

[0177] If the difference between the average rate of change of the first oblique line distance and the average rate of change of the second oblique line distance is less than a preset rate of change difference, and the slope is less than a preset slope threshold, then the obstacle type is determined to be a gentle downhill slope, and the corresponding uneven road surface scenario is a gentle downhill slope road surface.

[0178] If the difference between the average rate of change of the first oblique line distance and the average rate of change of the second oblique line distance is greater than or equal to a preset rate of change difference, and the slope is less than a preset slope threshold, then the obstacle type is determined to be a downhill uneven obstacle, and the corresponding road surface uneven scenario is a downhill uneven road surface.

[0179] Similarly, a gyroscope can be used to make similar determinations for uphill sections.

[0180] Furthermore, unevenness on the slope can also be further identified. If the difference between the fixed angle of the first ground sensor and / or the second ground sensor and the slope is less than a preset angle threshold, then the obstacle category is determined to be the second gentle slope in a downhill gentle slope road surface;

[0181] Correspondingly, determining the obstacle avoidance control parameters includes: determining that the current operating status parameters of the vehicle remain unchanged;

[0182] If the difference between the fixed angle of the first ground sensor and / or the second ground sensor and the slope is greater than or equal to a preset angle threshold, then the obstacle category is determined to be a pothole on a gentle downhill road surface.

[0183] Correspondingly, determining the obstacle avoidance control parameters includes: determining a braking control command to make the vehicle speed less than or equal to a preset safety threshold.

[0184] S303. Using a preset obstacle avoidance model, determine the obstacle avoidance control parameters based on the obstacle distance and the target driving scenario.

[0185] Specifically, this step includes:

[0186] Using a preset obstacle avoidance model, a preset safe speed is determined based on the target driving scenario and the distance to the obstacle;

[0187] The braking control command is determined based on a preset safe speed to reduce the vehicle speed to below the preset safe speed. The obstacle avoidance control parameters include the braking control command.

[0188] For example, in this embodiment, the target driving scenario is an uneven road surface scenario. If the uneven road surface scenario is a gentle slope scenario, the preset safe speed can be set to the minimum operating speed. If the uneven road surface scenario is an uneven slope scenario, or a scenario with potholes, bumps, or steps, the preset safe speed can be set to zero, that is, the vehicle can be controlled to stop automatically to prevent a fall accident.

[0189] S304. Control the vehicle to drive safely in the target driving scenario according to the target control parameters.

[0190] This step is similar in principle to S203. For specific explanations of terms and principles, please refer to S203. It will not be repeated here.

[0191] This application provides a vehicle control method that automatically identifies specific uneven road conditions, such as potholes, bumps, steps, and ramps, and then controls the vehicle to take corresponding safety driving control measures. This solves the technical problem that mobility vehicles for the elderly or disabled cannot intelligently recognize driving scenarios and automatically provide driving assistance based on those scenarios, thus improving the user experience and safety of mobility vehicles such as electric wheelchairs for the elderly or disabled.

[0192] The following is combined with Figure 5 An example is given to illustrate the intelligent control of a vehicle operating in a confined space.

[0193] Figure 5 This is a flowchart illustrating a third vehicle control method provided in an embodiment of this application. Figure 5 As shown, the specific steps of this method include:

[0194] S501. Utilize sensors to detect the vehicle's driving environment to determine the detection results, including obstacle distances.

[0195] In this embodiment, the sensor includes a side sensor, and the obstacle distance includes lateral distance. Lateral distance includes left-side distance and right-side distance, that is, the distance between the obstacle and the left and right sides of the vehicle.

[0196] In one possible design, side sensors are installed at the front left, rear left, front right, and rear right of the vehicle. These side sensors can be radar, infrared detectors, laser rangefinders, etc. Of course, those skilled in the art can choose the number and specific type of side sensors according to the actual situation, and this application does not limit this choice.

[0197] S502. Determine the obstacle category based on the obstacle distance.

[0198] In this embodiment, it specifically includes:

[0199] If the lateral distance is less than the confined space threshold, the obstacle is classified as an insurmountable obstacle.

[0200] S503. Determine the target driving scenario based on the type of obstacle.

[0201] In this embodiment, if the obstacle category is an insurmountable obstacle, then the target driving scenario is the confined space scenario.

[0202] S504. Using a preset obstacle avoidance model, determine whether the vehicle can turn around based on the side distance, vehicle width, and turn-around threshold.

[0203] In this embodiment, a scenario of turning around in an elevator shaft within a confined space is used as an example for illustration. Specifically, it includes:

[0204] If the sum of the lateral distance and the vehicle width is greater than or equal to the turn-around threshold, then the vehicle is determined to be able to turn around.

[0205] It should be noted that the above-mentioned method for determining whether a vehicle can turn around is at least one of the methods used in this application. Alternatively, a two-dimensional or three-dimensional turning model can be established based on the lateral distance and the geometric relationship between the vehicle and the turning distance, thereby analyzing the spatial conditions for turning around in the turning model and obtaining the turning threshold. Those skilled in the art can choose the method and conditions for determining whether a turning is permissible based on the actual situation; this application does not impose any limitations.

[0206] In one possible design, the sensors on the vehicle also include forward and backward sensors, and the obstacle distance includes both forward and backward distances. After determining that the vehicle can turn around, the process further includes:

[0207] Determine the relationship between the lateral distance and the threshold for direct U-turn;

[0208] If the lateral distance is greater than or equal to the threshold for direct U-turn, then the rearward distance adjustment value is determined based on the forward and backward distances; correspondingly, the obstacle avoidance control parameters include the rearward distance adjustment value.

[0209] The purpose of this step is to adjust the distance between the rear of the vehicle and obstacles such as elevator walls to a safe distance, such as 0.5m, after confirming that the vehicle can turn around directly.

[0210] If the lateral distance is less than the direct turn threshold, the vehicle's rearward distance is adjusted according to the rearward distance adjustment value; using the obstacle avoidance model, the lateral distance adjustment parameter is determined based on the lateral distance; correspondingly, the vehicle's rearward distance is controlled to reach a preset rearward reserve value according to the rearward distance adjustment value.

[0211] The purpose of this step is to determine when the vehicle cannot turn around directly. The reason for not being able to turn around may be that the distance between the left and right sides is uneven, with one side being narrower. Therefore, a position adjustment command can be issued to the vehicle so that the vehicle can change the distribution of the left and right distances with the elevator shaft wall, i.e., obstacles.

[0212] Specifically, for one implementation method of the preset adjustment method, the specific steps include:

[0213] Control the rotation angle in the lateral distance adjustment parameter to rotate the vehicle left or right;

[0214] Control the vehicle to rotate in the opposite direction by the rotation angle;

[0215] The backward distance adjustment value is determined again based on the forward distance and the backward distance;

[0216] Correspondingly, the rearward distance of the vehicle is controlled to reach a preset rearward reserve value according to the rearward distance adjustment value.

[0217] Specifically, by controlling the vehicle to rotate left or right and then back, repeating this cycle, the vehicle can be adjusted horizontally, with each rotation angle ranging from 30 to 45 degrees. This rotational movement allows for fine-tuning of the horizontal distance.

[0218] It should be noted that forward and backward sensors refer to sensors capable of detecting the front and rear of the vehicle, including sonar radar, infrared detectors, and laser rangefinders. The number of sensors used for detecting the front and rear can be selected by those skilled in the art based on the specific circumstances. In one possible design, rotatable sensors can also be installed on the vehicle to periodically detect the presence of obstacles in front of, behind, and around the vehicle.

[0219] Regarding the "determining the relationship between the lateral distance and the direct U-turn threshold", when the lateral distance includes both the left and right distances, one possible implementation is to select the minimum value between the left and right distances and compare it with the direct U-turn threshold.

[0220] S505. Determine the automatic turning control parameters using a preset obstacle avoidance model.

[0221] In this embodiment, the obstacle avoidance control parameters include automatic turn-around control parameters, and the target control parameters are obstacle avoidance control parameters.

[0222] It should be noted that the construction of the preset obstacle avoidance model can be obtained by those skilled in the art based on the actual situation and the specific external dimensions of the vehicle through experimental modeling and other methods. This application does not limit the specific implementation method of the preset ratio model.

[0223] S506. Control the vehicle to drive safely in the target driving scenario according to the target control parameters, including automatic U-turn control parameters.

[0224] In this step, after the control system calculates the automatic turning operation control mode, it can send the control command to the controller of the actuator, so that the vehicle can automatically turn around in narrow environments such as elevator shafts.

[0225] Understandably, if the analysis and calculation by the control system shows that automatic turning cannot be achieved, or if the vehicle still cannot meet the requirements for automatic turning after adjusting the left and right and / or front and rear distances of the vehicle, a prompt message will be issued to the user, including a voice prompt.

[0226] This application provides a vehicle control method that enables automatic turning of a vehicle in confined spaces such as elevator shafts. This solves the technical problem that mobility vehicles for the elderly or disabled cannot recognize confined space scenarios and automatically turn around, thus improving the user experience and safety of mobility vehicles such as electric wheelchairs for the elderly or disabled.

[0227] Figure 6 This is a flowchart illustrating the fourth vehicle control method provided in this application. Figure 6 As shown, the specific steps of this method include:

[0228] S601. Utilize sensors to detect the vehicle's driving environment to determine the detection results, including obstacle distances.

[0229] In this embodiment, the sensors include distance sensors covering at least four directions: front, rear, left, and right of the vehicle. The distance sensors can be radar, infrared detectors, laser rangefinders, etc.

[0230] S602. Determine the obstacle category based on the obstacle distance, and determine the target driving scenario based on the obstacle category.

[0231] In this embodiment, the target driving scenario includes an obstacle avoidance scenario.

[0232] For example, when a vehicle is traveling on an escalator or between supermarket display cases, the aisles are narrow and there may be obstacles such as pedestrians or goods. In this case, distance sensors can be used to determine whether there are obstacles around the vehicle, thereby identifying the obstacle avoidance scenario.

[0233] S603. If the distance sensor's detection result is less than the downshift distance, then determine the vehicle's speed control gear.

[0234] In this embodiment, the obstacle avoidance control parameters include speed control levels.

[0235] Specifically, when an obstacle is detected ahead, the control system can control the vehicle to downshift and reduce speed.

[0236] S604. If the detection result is less than the sensitivity control distance, the control value corresponding to the speed or direction control command input by the user shall be reduced by a preset ratio.

[0237] In this embodiment, it specifically includes:

[0238] Multiply the control value of the joystick by the preset attenuation coefficient.

[0239] In this embodiment, the vehicle is equipped with a control joystick. The user uses the joystick to control the vehicle's direction and speed. When obstacles are present around the vehicle, the control sensitivity of the joystick can be reduced by multiplying the control value by a preset attenuation coefficient. This improves the vehicle's driving safety and prevents collisions caused by user misoperation.

[0240] It should be noted that the downshift distance in S603-S604 is greater than or equal to the sensitivity control distance.

[0241] S605. Control the vehicle to drive safely in the target driving scenario according to the target control parameters, including: speed control gear and control parameters adjusted according to the target driving scenario.

[0242] In this step, the vehicle's speed is controlled and the sensitivity of user input commands, such as joystick input, is adjusted in the obstacle avoidance scenario to ensure the vehicle can drive safely in the obstacle avoidance scenario.

[0243] This application provides a vehicle control method. It utilizes sensors to detect the vehicle's driving environment, determines the detection results, then identifies the obstacle category based on obstacle distance, and finally determines the target driving scenario based on the obstacle category. Next, if the distance sensor's detection result is less than the downshift distance, the vehicle's speed control level is determined. If the detection result is less than the sensitivity control distance, the control value corresponding to the user-input speed or direction control command is reduced by a preset ratio. Finally, the vehicle is controlled to drive safely in the target driving scenario based on the target control parameters. This method solves the technical problem of obstacle avoidance in confined spaces for mobility vehicles used by the elderly or disabled, achieving the technical effect of improving the user experience and safety of mobility vehicles such as electric wheelchairs for the elderly or disabled.

[0244] Figure 7 This is a flowchart illustrating the fifth vehicle control method provided in this application. Figure 7 As shown, the specific steps of this method include:

[0245] S701, in response to a user-inputted preset mode start command, sets the vehicle's gear to the preset gear corresponding to the preset mode.

[0246] In this embodiment, the preset modes include: beginner mode and emergency mode.

[0247] In beginner mode, vehicle speed is limited to a minimum to allow users to safely attempt driving a vehicle for the first time.

[0248] Emergency mode allows users to set their vehicles to cruise at maximum speed when they need to handle urgent matters.

[0249] S702. Use sensors to detect the vehicle's driving environment in order to determine the detection results.

[0250] S703. Determine the target driving scenario and the corresponding target control parameters based on the detection results. The target control parameters are the product of the original control parameters obtained from the preset control model and the correction coefficient.

[0251] In this step, the correction coefficient corresponds to the preset mode. Specifically, when the preset modes include: beginner mode and emergency mode, the correction coefficient corresponding to the beginner mode is less than 1, and the correction coefficient corresponding to the emergency mode is greater than 1.

[0252] S704. Control the vehicle to drive safely in the target driving scenario according to the target control parameters.

[0253] For the detailed implementation principles and terminology explanations of steps S702-S703, please refer to [link / reference]. Figure 2 The vehicle control methods S201-S203 shown will not be described again here.

[0254] The vehicle control method provided in this application provides different control response speeds and different scene processing results for different preset modes, making the use of vehicles more flexible and diverse for users, and maximizing user convenience and versatility while ensuring user safety.

[0255] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as ROM, RAM, magnetic disk, or optical disk.

[0256] Figure 8 This is a schematic diagram of a positioning device provided in this application. The positioning device can be implemented through software, hardware, or a combination of both.

[0257] like Figure 8 As shown, the vehicle control device 800 includes:

[0258] The detection module 801 is used to detect the driving environment of the vehicle using sensors in order to determine the detection results;

[0259] Processing module 802 is used to determine the target driving scenario and the corresponding target control parameters based on the detection results;

[0260] The control module 803 is used to control the vehicle to drive safely in the target driving scenario according to the target control parameters.

[0261] In one possible design, the detection result includes obstacle distance, and the processing module 802 is used to determine the target driving scenario and corresponding target control parameters based on the detection result, including:

[0262] The processing module 802 is used to determine the obstacle category based on the obstacle distance;

[0263] The processing module 802 is further configured to determine the target driving scenario based on the obstacle category;

[0264] The processing module 802 is further configured to use a preset obstacle avoidance model to determine obstacle avoidance control parameters based on the obstacle distance and the target driving scenario, wherein the target control parameters include the obstacle avoidance control parameters.

[0265] Optionally, the target driving scenarios include: normal driving scenarios, uneven road surface scenarios, and confined space scenarios.

[0266] In one possible design, the sensor includes a first ground sensor and a second ground sensor, which are used to detect the diagonal distance from the sensor to the road surface. Correspondingly, the obstacle distance includes a first diagonal distance and a second diagonal distance, wherein the first diagonal distance is greater than the second diagonal distance. The processing module 802 is further used to determine the obstacle category based on the obstacle distance, including:

[0267] The processing module 802 is further configured to determine that the obstacle category is obstacle-free and the corresponding target driving scenario is a normal driving scenario if the fluctuation amplitude of the first diagonal distance and the second diagonal distance is less than a preset fluctuation threshold.

[0268] Optionally, the processing module 802 is further configured to determine the obstacle category based on the obstacle distance, including:

[0269] If the first fluctuation amplitude of the first diagonal distance is greater than or equal to the preset fluctuation threshold, and the second fluctuation amplitude of the second diagonal distance is less than the preset fluctuation threshold, then the obstacle category is determined to be a pit or a bump, and the corresponding uneven road surface scenario is a pit or a bump road surface.

[0270] In one possible design, determining the obstacle category based on the obstacle distance includes:

[0271] If the difference between the average rate of change of the first oblique line distance and the average rate of change of the second oblique line distance is less than a preset rate of change difference, then the obstacle category is determined to be a gentle slope, and the corresponding uneven road surface scenario is a gentle slope road surface.

[0272] If the difference between the average rate of change of the first diagonal distance and the average rate of change of the second diagonal distance is greater than or equal to the preset rate of change difference, then the obstacle category is determined to be an uneven ramp obstacle, and the corresponding uneven road surface scenario is an uneven ramp road surface.

[0273] Optionally, the sensor includes a gyroscope, the detection result includes slope, and the processing module 802 is further configured to determine the obstacle category based on the obstacle distance, including:

[0274] The processing module 802 is further configured to determine that the obstacle type is a gentle downhill slope and the corresponding uneven road surface scenario is a gentle downhill slope if the difference between the average change rate of the first oblique line distance and the average change rate of the second oblique line distance is less than a preset change rate difference and the slope is less than a preset slope threshold.

[0275] If the difference between the average rate of change of the first oblique line distance and the average rate of change of the second oblique line distance is greater than or equal to a preset rate of change difference, and the slope is less than a preset slope threshold, then the obstacle type is determined to be a downhill uneven obstacle, and the corresponding road surface uneven scenario is a downhill uneven road surface.

[0276] Optionally, the detection results include vehicle speed. The processing module 802 is further configured to determine obstacle avoidance control parameters based on the obstacle distance and the target driving scenario using a preset obstacle avoidance model, including:

[0277] The processing module 802 is further configured to determine a preset safe speed based on the target driving scenario and the distance to the obstacle using a preset obstacle avoidance model;

[0278] The processing module 802 is further configured to determine a braking control command based on the preset safe speed, so as to reduce the vehicle speed to below the preset safe speed, wherein the obstacle avoidance control parameters include the braking control command.

[0279] In one possible design, the obstacle is a pit when the distance of the first diagonal line is greater than a first preset threshold and the distance of the second diagonal line is less than a second preset threshold.

[0280] In one possible design, the processing module 802 is further configured to determine the obstacle category based on the obstacle distance, and also includes:

[0281] If the difference between the fixed angle of the first ground sensor and / or the second ground sensor and the slope is less than a preset angle threshold, then the obstacle category is determined to be the second gentle slope in a downhill gentle slope road surface.

[0282] Correspondingly, the processing module 802 is used to determine obstacle avoidance control parameters, including: determining that the current operating status parameters of the vehicle remain unchanged;

[0283] If the difference between the fixed angle of the first ground sensor and / or the second ground sensor and the slope is greater than or equal to a preset angle threshold, then the obstacle category is determined to be a pothole on a gentle downhill road surface.

[0284] Correspondingly, the processing module 802 is used to determine obstacle avoidance control parameters, including: determining braking control commands to make the vehicle speed less than or equal to a preset safety threshold.

[0285] In one possible design, the sensor includes a side sensor, the obstacle distance includes a lateral distance, and the processing module 802 is used to determine the obstacle category based on the obstacle distance, including: if the lateral distance is less than a confined space threshold, then the obstacle category is determined to be an insurmountable obstacle, and the corresponding target driving scenario is the confined space scenario.

[0286] In one possible design, the processing module 802 is further configured to determine obstacle avoidance control parameters based on the obstacle distance and the target driving scenario using a preset obstacle avoidance model, including:

[0287] The processing module 802 is further configured to utilize the preset obstacle avoidance model to determine whether the vehicle can turn around based on the lateral distance, vehicle width, and turnaround threshold; then,

[0288] The processing module 802 is further configured to determine automatic turning control parameters using the preset obstacle avoidance model, wherein the obstacle avoidance control parameters include the automatic turning control parameters.

[0289] In one possible design, the processing module 802 is further configured to utilize the preset obstacle avoidance model to determine whether the vehicle can turn around based on the lateral distance, vehicle width, and turnaround threshold, including:

[0290] If the sum of the lateral distance and the vehicle width is greater than or equal to the turn-around threshold, then the vehicle is determined to be able to turn around.

[0291] In one possible design, the sensor further includes forward and backward sensors, the obstacle distance includes forward distance and backward distance, and the processing module 802, after determining that the vehicle can turn around, further includes:

[0292] The processing module 802 is also used to determine the relationship between the lateral distance and the direct turn threshold;

[0293] The processing module 802 is further configured to determine a rearward distance adjustment value based on the forward distance and the rearward distance if the lateral distance is greater than or equal to the direct turn threshold.

[0294] Correspondingly, the obstacle avoidance control parameters include the backward distance adjustment value.

[0295] Optionally, after determining the relationship between the lateral distance and the direct U-turn threshold, the processing module 802 further includes:

[0296] If the lateral distance is less than the direct turn threshold, then the rearward distance of the vehicle is adjusted according to the rearward distance adjustment value;

[0297] The processing module 802 is further configured to use the obstacle avoidance model to determine the lateral distance adjustment parameters based on the lateral distance;

[0298] Correspondingly, the vehicle is controlled to adjust the lateral distance according to the lateral distance adjustment parameter in a preset adjustment method so that the lateral distance is greater than or equal to the direct turn threshold.

[0299] In one possible design, the preset adjustment method includes:

[0300] The control module 803 is also used to control the rotation angle in the lateral distance adjustment parameter for the vehicle to rotate left or right;

[0301] The control module 803 is also used to control the vehicle to rotate in the opposite direction by the rotation angle;

[0302] The processing module 802 is further configured to determine the backward distance adjustment value again based on the forward distance and the backward distance;

[0303] Correspondingly, the control module 803 is also used to control the rearward distance of the vehicle to reach a preset rearward reserved value according to the rearward distance adjustment value.

[0304] In one possible design, the sensors include distance sensors covering at least four directions: front, rear, left, and right of the vehicle. The target driving scenario also includes an obstacle avoidance scenario. The processing module 802 is further configured to determine obstacle avoidance control parameters based on the obstacle distance and the target driving scenario using a preset obstacle avoidance model, including:

[0305] The processing module 802 is further configured to determine the speed control gear of the vehicle if the detection result of the distance sensor is less than the downshift distance, and the obstacle avoidance control parameters include the speed control gear.

[0306] The processing module 802 is also used to reduce the corresponding control value of the user-input speed or direction control command by a preset ratio if the detection result is less than the sensitivity control distance.

[0307] The downshift distance is greater than or equal to the sensitivity control distance.

[0308] In one possible design, the processing module 802 is further configured to reduce the speed or direction control command input by the user by a preset ratio to the corresponding control value, including:

[0309] Multiply the control value of the joystick by the preset attenuation coefficient.

[0310] Optionally, before using sensors to detect the vehicle's driving environment to determine the detection result, the method further includes:

[0311] The processing module 802 is also configured to respond to a user-input preset mode start command and set the gear of the vehicle to a preset gear corresponding to the preset mode.

[0312] Correspondingly, the target control parameter is the product of the original control parameter obtained according to the preset control model and the correction coefficient, and the correction coefficient corresponds to the preset mode.

[0313] In one possible design, the preset modes include: a beginner mode and an emergency mode, wherein the correction coefficient for the beginner mode is less than 1, and the correction coefficient for the emergency mode is greater than 1.

[0314] It is worth noting that, Figure 8 The vehicle control device provided in the illustrated embodiment can execute the method provided in any of the above method embodiments. Its specific implementation principle, technical features, explanation of technical terms and technical effects are similar, and will not be repeated here.

[0315] Figure 9 This is a schematic diagram of the structure of an electronic device provided in this application. Figure 9 As shown, the electronic device 900 may include at least one processor 901 and a memory 902. Figure 9 The example shown is an electronic device using a processor.

[0316] The memory 902 is used to store programs. Specifically, the program may include program code, which includes computer operation instructions.

[0317] The memory 902 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0318] The processor 901 is used to execute computer execution instructions stored in the memory 902 to implement the methods described in the above embodiments.

[0319] The processor 901 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0320] Optionally, the memory 902 can be either standalone or integrated with the processor 901. When the memory 902 is a device independent of the processor 901, the electronic device 700 may further include:

[0321] Bus 903 is used to connect the processor 901 and the memory 902. The bus can be an industry standard architecture (ISA) bus, a peripheral component (PCI) bus, or an extended industry standard architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc., but this does not mean there is only one bus or one type of bus.

[0322] Optionally, in a specific implementation, if the memory 902 and the processor 901 are integrated on a single chip, the memory 902 and the processor 901 can communicate through an internal interface.

[0323] This application also provides a computer-readable storage medium, which may include various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk. Specifically, the computer-readable storage medium stores program instructions, which are used in the vehicle control methods described in the above embodiments.

[0324] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A vehicle control method, characterized in that, include: Sensors are used to detect the vehicle's driving environment in order to determine the detection results; The target driving scenario and corresponding target control parameters are determined based on the detection results. The vehicle is controlled to drive safely in the target driving scenario according to the target control parameters; The detection results include obstacle distance, and determining the target driving scenario and corresponding target control parameters based on the detection results includes: The obstacle category is determined based on the obstacle distance; The target driving scenario is determined based on the obstacle category; Using a preset obstacle avoidance model, obstacle avoidance control parameters are determined based on the obstacle distance and the target driving scenario, wherein the target control parameters include the obstacle avoidance control parameters; The target driving scenarios include: confined space scenarios; The sensor includes a side sensor, and the obstacle distance includes lateral distance; Determining the obstacle category based on the obstacle distance includes: If the lateral distance is less than the confined space threshold, then the obstacle category is determined to be an insurmountable obstacle, and the corresponding target driving scenario is the confined space scenario. The sensors include distance sensors covering at least four directions: front, rear, left, and right of the vehicle. The target driving scenario also includes an obstacle avoidance scenario. The step of determining obstacle avoidance control parameters using a preset obstacle avoidance model, based on the obstacle distance and the target driving scenario, includes: If the detection result of the distance sensor is less than the downshift distance, then the speed control gear of the vehicle is determined, and the obstacle avoidance control parameters include the speed control gear; If the detection result is less than the sensitivity control distance, the control value corresponding to the user-input speed or direction control command is reduced by a preset ratio; the downshift distance is greater than or equal to the sensitivity control distance.

2. The vehicle control method according to claim 1, characterized in that, The step of determining obstacle avoidance control parameters using a preset obstacle avoidance model based on the obstacle distance and the target driving scenario includes: Using the preset obstacle avoidance model, based on the lateral distance, vehicle width, and turnaround threshold, it is determined that the vehicle can turn around; then, Using the preset obstacle avoidance model, automatic U-turn control parameters are determined, including the automatic U-turn control parameters.

3. The vehicle control method according to claim 2, characterized in that, The step of determining whether a vehicle can turn around using the preset obstacle avoidance model, based on the lateral distance, vehicle width, and turnaround threshold, includes: If the sum of the lateral distance and the vehicle width is greater than or equal to the turn-around threshold, then the vehicle is determined to be able to turn around.

4. The vehicle control method according to claim 3, characterized in that, The sensor also includes forward and backward sensors, the obstacle distance includes forward distance and backward distance, and after determining that the vehicle can turn around, the process further includes: Determine the relationship between the lateral distance and the threshold for direct U-turn; If the lateral distance is greater than or equal to the direct turn threshold, then the rearward distance adjustment value is determined based on the forward distance and the rearward distance; Correspondingly, the obstacle avoidance control parameters include the backward distance adjustment value.

5. The vehicle control method according to claim 4, characterized in that, After determining the relationship between the lateral distance and the direct U-turn threshold, the method further includes: If the lateral distance is less than the direct turn threshold, then the rearward distance of the vehicle is adjusted according to the rearward distance adjustment value; Using the obstacle avoidance model, determine the lateral distance adjustment parameters based on the lateral distance; Correspondingly, the vehicle is controlled to adjust the lateral distance according to the lateral distance adjustment parameter in a preset adjustment method so that the lateral distance is greater than or equal to the direct turn threshold.

6. The vehicle control method according to claim 5, characterized in that, The preset adjustment methods include: Control the rotation angle in the lateral distance adjustment parameter to rotate the vehicle left or right; Control the vehicle to rotate in the opposite direction by the rotation angle; The backward distance adjustment value is determined again based on the forward distance and the backward distance; Correspondingly, the rearward distance of the vehicle is controlled to reach a preset rearward reserve value according to the rearward distance adjustment value.

7. The vehicle control method according to claim 1, characterized in that, The control value corresponding to the user-input speed or direction control command reduced according to a preset ratio includes: Multiply the control value of the joystick by the preset attenuation coefficient.

8. The vehicle control method according to claim 1, characterized in that, Before using sensors to detect the vehicle's driving environment to determine the detection results, the method further includes: In response to a user-inputted preset mode start command, the vehicle's gear position is set to a preset gear position corresponding to the preset mode; Correspondingly, the target control parameter is the product of the original control parameter obtained according to the preset control model and the correction coefficient, and the correction coefficient corresponds to the preset mode.

9. The vehicle control method according to claim 8, characterized in that, The preset modes include: beginner mode and emergency mode. The correction coefficient for beginner mode is less than 1, and the correction coefficient for emergency mode is greater than 1.

10. A vehicle control device, characterized in that, include: The detection module is used to detect the vehicle's driving environment using sensors in order to determine the detection results; The processing module is used to determine the target driving scenario and the corresponding target control parameters based on the detection results; The target driving scenarios include: confined space scenarios; The control module is used to control the vehicle to drive safely in the target driving scenario according to the target control parameters; The detection results include obstacle distance. The processing module is used to determine the target driving scenario and corresponding target control parameters based on the detection results, including: The processing module is used to determine the obstacle category based on the obstacle distance; the obstacle distance includes lateral distance. The processing module is further configured to determine the target driving scenario based on the obstacle category; The processing module is further configured to use a preset obstacle avoidance model to determine obstacle avoidance control parameters based on the obstacle distance and the target driving scenario, wherein the target control parameters include the obstacle avoidance control parameters; The processing module is specifically used for: If the lateral distance is less than the confined space threshold, then the obstacle category is determined to be an insurmountable obstacle, and the corresponding target driving scenario is the confined space scenario. The sensors include distance sensors covering at least four directions: front, rear, left, and right of the vehicle. The target driving scenario also includes an obstacle avoidance scenario. The processing module is further configured to determine obstacle avoidance control parameters based on the obstacle distance and the target driving scenario using a preset obstacle avoidance model, including: The processing module is further configured to determine the speed control gear of the vehicle if the detection result of the distance sensor is less than the downshift distance, and the obstacle avoidance control parameters include the speed control gear. The processing module is further configured to reduce the control value corresponding to the user-input speed or direction control command by a preset ratio if the detection result is less than the sensitivity control distance; the downshift distance is greater than or equal to the sensitivity control distance.

11. An electronic device, characterized in that, include: processor; as well as, Memory for storing the executable instructions of the processor; The processor is configured to execute a vehicle control method according to any one of claims 1 to 9 by executing the executable instructions.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the vehicle control method according to any one of claims 1 to 9.

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