Vehicle driver assistance methods, devices, electronic equipment and storage media

Abstract

This application relates to the field of intelligent driving technology, and particularly to a vehicle assisted driving method, device, electronic device, and storage medium. The method includes: acquiring perception information of the current vehicle to determine the optimal driving route; generating at least one warning zone based on the optimal driving route; acquiring the actual distance between the nearest warning zone to the current vehicle within the at least one warning zone; and then matching the optimal assisted driving strategy to control the current vehicle. This solves the problem that when driving on complex lane routes, the vehicle may fail to change lanes in time due to the user ignoring navigation voice prompts, thus deviating from the originally planned route. By employing deep learning technology, the system intelligently judges the vehicle's driving conditions and surrounding environment, and reminds the user to change lanes in time when the vehicle shows a tendency to deviate, thereby avoiding deviation from the driving route.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent driving, in particular to an auxiliary driving method and device of a vehicle, an electronic device and a storage medium. BACKGROUND

[0002] With the large-scale popularization of vehicles, a certain degree of safety hazard is brought to the load of the traffic road, especially for the characteristics of the relatively closed section of the highway driving scene and the easy commercialization landing, the vehicle needs a related driving assistance system to assist the driver to drive safely when driving on the highway section, so as to ensure that the driver avoids the problem of feeling tired and boring due to long-term driving.

[0003] In the related art, when facing the area of the complex lane line of the highway branch, ramp, etc., the vehicle mostly starts the lane keeping auxiliary driving system, so as to start the automatic driving function after the long-term driving of the driver.

[0004] However, the vehicle starting the lane keeping auxiliary driving system can only drive along the current lane, and cannot automatically change lanes and drive into the route planned by navigation. If the driver is not familiar with the road condition, drives too fast, is not concentrated, or drives tiredly, etc., the driver is easy to ignore the prompt voice of navigation, and cannot change lanes in time at the branch road, so as to deviate from the originally planned route of navigation, which needs to be solved urgently. SUMMARY

[0005] The present application provides an auxiliary driving method and device of a vehicle, an electronic device and a storage medium, to solve the problem that the vehicle deviates from the originally planned route of navigation due to the user ignoring the navigation voice when the vehicle drives on the complex lane line.

[0006] The first aspect embodiment of the present application provides an auxiliary driving of a vehicle, including the following steps:

[0007] Obtaining the perception information of the current vehicle, wherein the perception information includes the destination of the current vehicle;

[0008] Determining the best driving route of the current vehicle according to the destination, generating at least one to-be-warned area according to the best driving route, and obtaining the actual distance between the to-be-warned area closest to the current vehicle in the at least one to-be-warned area; and

[0009] Matching the best auxiliary driving strategy of the current vehicle according to the actual distance, and controlling the current vehicle according to the best auxiliary driving strategy.

[0010] According to one embodiment of the present application, the matching of the best auxiliary driving strategy of the current vehicle according to the actual distance comprises:

[0011] if the actual distance is less than a first preset distance, the optimal auxiliary driving strategy is to issue a first early warning instruction;

[0012] if the actual distance is less than a second preset distance, it is determined whether the current vehicle meets a preset off-route condition, and when the preset off-route condition is met, the optimal auxiliary driving strategy is to issue a second early warning instruction, wherein the second preset distance is less than the first preset distance;

[0013] if the actual distance is less than a third preset distance, it is determined whether the current vehicle meets the preset off-route condition, and when the preset off-route condition is met, the optimal auxiliary driving strategy is to issue a third early warning instruction, wherein the third preset distance is less than the second preset distance;

[0014] if the actual distance is less than a fourth preset distance, the optimal auxiliary driving strategy is to issue a fourth early warning instruction, wherein the fourth preset distance is less than the third preset distance.

[0015] According to an embodiment of the present application, the determination of whether the current vehicle meets a preset off-route condition comprises:

[0016] acquiring a lane position, a steering wheel torque and a current speed of the current vehicle;

[0017] quantifying the lane position, the steering wheel torque and the current speed of the current vehicle;

[0018] based on a preset weighting strategy and a normalization strategy, performing weighting processing and normalization processing on the quantified lane position, the steering wheel torque and the current speed of the current vehicle to obtain a weighting result, and when the weighting result is greater than a preset threshold, determining that the current vehicle meets the preset off-route condition.

[0019] According to an embodiment of the present application, the control of the current vehicle according to the optimal auxiliary driving strategy comprises:

[0020] when the early warning instruction is a first early warning instruction, an early warning information is broadcasted through a preset acoustic device;

[0021] when the early warning instruction is a second early warning instruction, the early warning information is broadcasted again through the preset acoustic device, and a steering wheel of the current vehicle is controlled to start an early warning vibration mode, a deceleration request is sent to an EPS (Electronic-Power-Steering), a torque reduction request is sent to a power control system through the EPS, and the current vehicle is controlled to perform a lane change or exit an early warning operation;

[0022] When the early warning instruction is a third early warning instruction, the preset acoustic device is used to play the early warning information again, and the steering wheel of the current vehicle is controlled to start the early warning vibration mode, a deceleration request is sent to the EPS, a torque reduction request is sent to the power control system through the EPS, and then the EPS is used to apply a lateral torque to the steering wheel, so that the current vehicle is controlled to change lanes or exit the early warning operation.

[0023] When the early warning instruction is a fourth early warning instruction, the driving route of the current vehicle is re-planned.

[0024] According to an embodiment of the present application, at least one early warning area is generated according to the optimal driving route, comprising:

[0025] Based on the GPS (Global Positioning System), the route branch and / or ramp in the optimal driving route are obtained.

[0026] At least one early warning area is generated according to the route branch and / or the ramp.

[0027] According to the auxiliary driving method of the vehicle, the perception information of the current vehicle is obtained to determine the optimal driving route of the current vehicle, at least one early warning area is generated according to the optimal driving route, the actual distance between the closest early warning area in the at least one early warning area to the current vehicle is obtained, and then the optimal auxiliary driving strategy of the current vehicle is matched to control the current vehicle. Thus, the problem that the vehicle deviates from the originally planned route due to the user's neglect of the navigation voice when the vehicle drives on a complex road is solved. By using the deep learning technology, the user is reminded to change lanes in time when the vehicle has a deviation tendency according to the driving condition and the surrounding environment, so as to avoid the deviation of the driving route.

[0028] The second aspect embodiment of the present application provides an auxiliary driving device of a vehicle, comprising:

[0029] The acquisition module is configured to acquire perception information of a current vehicle, wherein the perception information comprises a destination of the current vehicle.

[0030] The generation module is configured to determine an optimal driving route of the current vehicle according to the destination, generate at least one early warning area according to the optimal driving route, and obtain an actual distance between a closest early warning area in the at least one early warning area to the current vehicle.

[0031] The matching module is configured to match an optimal auxiliary driving strategy of the current vehicle according to the actual distance, and control the current vehicle according to the optimal auxiliary driving strategy.

[0032] According to an embodiment of the present application, the matching module is specifically configured to:

[0033] If the actual distance is less than a first preset distance, the optimal auxiliary driving strategy is to issue a first warning instruction.

[0034] If the actual distance is less than a second preset distance, it is determined whether the current vehicle satisfies a preset off-route condition, and when the preset off-route condition is satisfied, the optimal auxiliary driving strategy is to issue a second warning instruction, wherein the second preset distance is less than the first preset distance.

[0035] If the actual distance is less than a third preset distance, it is determined whether the current vehicle satisfies the preset off-route condition, and when the preset off-route condition is satisfied, the optimal auxiliary driving strategy is to issue a third warning instruction, wherein the third preset distance is less than the second preset distance.

[0036] If the actual distance is less than a fourth preset distance, the optimal auxiliary driving strategy is to issue a fourth warning instruction, wherein the fourth preset distance is less than the third preset distance.

[0037] According to an embodiment of the present application, the matching module is specifically configured to:

[0038] Obtain a lane position, a steering wheel torque and a current speed of the current vehicle;

[0039] Quantize the lane position, the steering wheel torque and the current speed of the current vehicle;

[0040] Based on a preset weighting strategy and a normalization strategy, the lane position, the steering wheel torque and the current speed of the current vehicle after quantization are weighted and normalized to obtain a weighting result, and when the weighting result is greater than a preset threshold, it is determined that the current vehicle satisfies the preset off-route condition.

[0041] According to an embodiment of the present application, the matching module is specifically configured to:

[0042] When the warning instruction is a first warning instruction, a preset acoustic device is used to broadcast warning information.

[0043] When the early warning instruction is the second early warning instruction, the preset acoustic device is used to play the early warning information again, and the steering wheel of the current vehicle is controlled to start the early warning vibration mode, a deceleration request is sent to the EPS, a torque reduction request is sent to the power control system through the EPS, and the current vehicle is controlled to change lanes or exit the early warning operation;

[0044] When the early warning instruction is the third early warning instruction, after the preset acoustic device is used to play the early warning information again, the steering wheel of the current vehicle is controlled to start the early warning vibration mode, a deceleration request is sent to the EPS, a torque reduction request is sent to the power control system through the EPS, and the EPS is used to apply a lateral torque to the steering wheel, so that the current vehicle is controlled to change lanes or exit the early warning operation.

[0045] When the early warning instruction is the fourth early warning instruction, the driving route of the current vehicle is re-planned.

[0046] According to an embodiment of the present application, the generation module is specifically configured to:

[0047] Based on a global positioning system (GPS), a route branch and / or a ramp in the optimal driving route are acquired.

[0048] At least one early warning area is generated according to the route branch and / or the ramp.

[0049] The auxiliary driving device of the vehicle according to the embodiment of the present application acquires the perception information of the current vehicle to determine the optimal driving route of the current vehicle, generates at least one early warning area according to the optimal driving route, acquires the actual distance between the closest early warning area in the at least one early warning area and the current vehicle, and then matches the optimal auxiliary driving strategy of the current vehicle to control the current vehicle. Thus, the problem that the vehicle deviates from the originally planned route due to the user's neglect of the navigation voice when the vehicle drives on a complex road is solved. By using the deep learning technology, the user is reminded to change lanes in time when the vehicle has a deviation tendency according to the driving condition and the surrounding environment, so as to avoid the deviation of the driving route.

[0050] The third aspect embodiment of the present application provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the program to implement the auxiliary driving method of the vehicle as described in the above embodiments.

[0051] The fourth aspect embodiment of the present application provides a computer readable storage medium having a computer program stored thereon. The program is executed by a processor to implement the auxiliary driving method of the vehicle as described in the above embodiments.

[0052] Additional aspects and advantages of the present application will be partially apparent and partially described in the following description. BRIEF DESCRIPTION OF DRAWINGS

[0053] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the following description, taken in conjunction with the accompanying drawings, in which:

[0054] Figure 1 A structural schematic diagram according to an embodiment of the present application;

[0055] Figure 2 A flowchart of an auxiliary driving method of a vehicle according to an embodiment of the present application;

[0056] Figure 3 A flowchart of an implementation according to an embodiment of the present application;

[0057] Figure 4 A block schematic diagram of an auxiliary driving device of a vehicle according to an embodiment of the present application.

[0058] Figure 5 A structural schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0059] Embodiments of the present application are described in detail below with reference to the accompanying drawings, in which examples of embodiments are shown, wherein the same or similar notations represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by reference to the accompanying drawings are exemplary and are intended to explain the present application, and cannot be understood as limiting the present application.

[0060] The auxiliary driving method, device, electronic device and storage medium of a vehicle according to the embodiments of the present application are described below with reference to the accompanying drawings. In view of the problem that the vehicle is easy to deviate from the originally planned route of the navigation due to the user's neglect of the navigation voice when the vehicle is driving on a complex road route, the present application provides an auxiliary driving method of a vehicle, in which the perception information of the current vehicle is obtained to determine the optimal driving route of the current vehicle, and at least one to-be-warned area is generated according to the optimal driving route, and the actual distance between the to-be-warned area closest to the current vehicle in the at least one to-be-warned area is obtained, and then the optimal auxiliary driving strategy of the current vehicle is matched to control the current vehicle. Thus, the problem that the vehicle is easy to deviate from the originally planned route of the navigation due to the user's neglect of the navigation voice when the vehicle is driving on a complex road route is solved, and by using the deep learning technology, the user is reminded to change lanes in time when the vehicle has a deviation trend according to the driving condition and the surrounding environment, so as to avoid the deviation of the driving route.

[0061] Specifically, before introducing the embodiments of the present application, first introduce the system modules involved in the embodiments of the present application, such as Figure 1 As shown in the figure, respectively, are information acquisition module, navigation module, route deviation module and early warning module.

[0062] Among them, the information acquisition module is used to perceive the driving state and the surrounding environment of the vehicle, and provides GPS information and camera information for the navigation module; the navigation module is used to obtain vehicle information according to the destination input by the driver, plan the best driving route, and at the same time, the module is also used to locate the branch and calculate the distance between the waiting early warning area and the vehicle; the route deviation module is used to intelligently judge whether the vehicle has a deviation trend according to the driving condition of the vehicle by using deep learning technology; the early warning module is used to execute the corresponding early warning strategy according to the instruction, remind the driver to drive into the corresponding lane in time, and avoid driving route deviation.

[0063] Specifically, Figure 2 A flowchart of a vehicle auxiliary driving method provided by the embodiments of the present application.

[0064] As shown in the figure, Figure 2 The vehicle auxiliary driving method comprises the following steps:

[0065] In step S201, the perception information of the current vehicle is obtained, wherein the perception information includes the destination of the current vehicle.

[0066] Specifically, as shown in the figure, Figure 3 When the vehicle of the embodiments of the present application drives on the highway, it first needs to obtain the perception information of the current vehicle through the information acquisition module, including the position information of the current vehicle collected by GPS, the destination position information input by the driver, the lane line information detected by the camera, the speed information and the steering wheel torque information.

[0067] In step S202, the best driving route of the current vehicle is determined according to the destination, and at least one to be warned area is generated according to the best driving route, and the actual distance between the closest to-be-warned area in the at least one to-be-warned area and the current vehicle is obtained.

[0068] Further, in some embodiments, generating at least one to-be-warned area according to the best driving route comprises: based on the global positioning system GPS, obtaining the route branch and / or ramp in the best driving route; generating at least one to-be-warned area according to the route branch and / or ramp.

[0069] Specifically, in the embodiments of the present application, after the information acquisition module acquires the perception information of the current vehicle, the navigation module determines the optimal driving route of the current vehicle according to the acquired destination, and the GPS generates at least one to-be-warned area in the area needing warning such as the route branch and / or ramp in the optimal driving route, and calculates the actual distance between the current vehicle and the closest to-be-warned area in the at least one to-be-warned area in the optimal driving route, and the driver can autonomously select whether to turn on the lane keeping function according to the planning of the route, the familiarity and the driving state, so as to keep the vehicle driving in the lane line.

[0070] In step S203, the optimal auxiliary driving strategy of the current vehicle is matched according to the actual distance, and the current vehicle is controlled according to the optimal auxiliary driving strategy.

[0071] Further, in some embodiments, the optimal auxiliary driving strategy of the current vehicle is matched according to the actual distance, including: if the actual distance is less than a first preset distance, the optimal auxiliary driving strategy is to issue a first warning instruction; if the actual distance is less than a second preset distance, it is judged whether the current vehicle satisfies a preset off-route condition, and when the preset off-route condition is satisfied, the optimal auxiliary driving strategy is to issue a second warning instruction, wherein the second preset distance is less than the first preset distance; if the actual distance is less than a third preset distance, it is judged whether the current vehicle satisfies the preset off-route condition, and when the preset off-route condition is satisfied, the optimal auxiliary driving strategy is to issue a third warning instruction, wherein the third preset distance is less than the second preset distance; and if the actual distance is less than a fourth preset distance, the optimal auxiliary driving strategy is to issue a fourth warning instruction, wherein the fourth preset distance is less than the third preset distance.

[0072] Further, in some embodiments, it is judged whether the current vehicle satisfies the preset off-route condition, including: acquiring the lane position, steering wheel torque and current speed of the current vehicle; quantizing the lane position, steering wheel torque and current speed of the current vehicle; based on a preset weighting strategy and a normalization strategy, the quantized lane position, steering wheel torque and current speed of the current vehicle are weighted and normalized to obtain a weighting result, and when the weighting result is greater than a preset threshold, it is determined that the current vehicle satisfies the preset off-route condition.

[0073] The preset threshold, the first preset distance, the second preset distance, the third preset distance and the fourth preset distance can be a threshold value set by a person skilled in the art according to actual driving needs, or a threshold value obtained by computer simulation, which is not limited here.

[0074] Specifically, in the embodiment of the present application, after the actual distance between the closest to-be-warned region to the current vehicle in the at least one to-be-warned region is obtained, the best auxiliary driving strategy of the current vehicle is matched according to the actual distance.

[0075] Specifically, if the actual distance is less than the first preset distance, the best auxiliary driving strategy is to issue a first warning instruction to the driver, otherwise, the vehicle continues normal driving, for example, if the first preset distance is 2 kilometers and the actual distance is 1.5 kilometers, the first warning instruction is issued to the driver, and if the actual distance is 2.5 kilometers, the vehicle continues normal driving.

[0076] Further, if the actual distance is less than the second preset distance, it is determined whether the current vehicle satisfies a preset off-course condition, and when the current vehicle satisfies the preset off-course condition, the best auxiliary driving strategy is to issue a second warning instruction, for example, if the actual distance is 700 meters and the second preset distance is 1 kilometer, and when the current vehicle satisfies the preset off-course condition, the second warning instruction is issued to the driver, wherein the second preset distance is less than the first preset distance.

[0077] Specifically, in the embodiment of the present application, the off-course condition is detected by the vehicle system through an information acquisition module to detect the lane position, steering wheel torque and driving speed of the current vehicle, and the driving conditions are quantified, and based on a preset weighting strategy and a normalization strategy, the lane position, steering wheel torque and driving speed of the current vehicle are processed to obtain a weighted result, and when the weighted result is greater than a preset threshold, it is determined that the current vehicle satisfies the preset off-course condition. The weighting coefficient is intelligently determined by a deep learning model, and can be learned and optimized according to the driving habits of the driver, for example, if the weighted output result is greater than 1, it is determined that the current vehicle satisfies the preset off-course condition and has a tendency to deviate from the course, and the second warning instruction is sent to the driver.

[0078] For example, if the best planned road direction of the embodiment of the present application is the right front, the highway lane is three lanes, and the current vehicle is in the fast lane with a speed of 100 kilometers / hour, at this time the system executes the lane keeping function and the steering wheel has no right turning tendency, the driving conditions of the current vehicle are quantitatively processed, and after weighting and normalization processing, if the deep learning model outputs a weighted result greater than 1, the second warning instruction is sent to the user.

[0079] Further, if the actual distance is less than a third preset distance, it is determined whether the current vehicle satisfies a preset off-route condition, and when the current vehicle satisfies the preset off-route condition, the optimal auxiliary driving strategy is to issue a third warning instruction. For example, if the actual distance is 300 meters, the third preset distance is 500 meters, and when the current vehicle satisfies the preset off-route condition, a third warning instruction is issued to the driver, wherein the third preset distance is less than the second preset distance. It should be noted that the off-route condition of the third preset distance and the calculation of the weighting coefficient are the same as the off-route condition of the second preset distance and the calculation of the weighting coefficient, and will not be described in detail here.

[0080] Further, if the actual distance is less than a fourth preset distance, it means that the driver has missed the highway branch, i.e., the actual distance between the current vehicle and the nearest warning area is negative, and the optimal auxiliary driving strategy needs to issue a fourth warning instruction to the driver, wherein the fourth preset distance is less than the third preset distance.

[0081] Further, in some embodiments, the current vehicle is controlled according to the optimal auxiliary driving strategy, including: when the warning instruction is the first warning instruction, the preset acoustic device is used to broadcast the warning information; when the warning instruction is the second warning instruction, the preset acoustic device is used to broadcast the warning information again and control the steering wheel of the current vehicle to start the warning vibration mode, at the same time, a speed reduction request is sent to the EPS, and a torque reduction request is sent to the power control system through the EPS, so as to control the current vehicle to change lanes or exit the warning operation; when the warning instruction is the third warning instruction, after the preset acoustic device broadcasts the warning information again and controls the steering wheel of the current vehicle to start the warning vibration mode, at the same time, a speed reduction request is sent to the EPS, and a torque reduction request is sent to the power control system through the EPS, a lateral torque is applied to the steering wheel through the EPS, so as to control the current vehicle to change lanes or exit the warning operation; when the warning instruction is the fourth warning instruction, the driving route of the current vehicle is re-planned.

[0082] Specifically, in the embodiment of the present application, after the optimal auxiliary driving strategy of the current vehicle is matched according to the actual distance, if the user receives the first warning instruction, the preset acoustic device, such as the vehicle-mounted voice system, is used to broadcast the warning information according to the planned optimal driving route, for example, "2 kilometers later, drive to the right front, and enter the auxiliary road" or "drive straight, go to XX direction"; if the user receives the second warning instruction, the voice system is used to broadcast the warning information again and control the steering wheel of the current vehicle to start the warning vibration mode, at the same time, a deceleration request is sent to the EPS, and the EPS sends a torque reduction request to the power control system, so as to control the vehicle to decelerate and drive, facilitating the driver to change lanes or exit the warning operation; if the user receives the third warning instruction, the voice system is used to broadcast the warning information again and control the steering wheel of the current vehicle to start the warning vibration mode, at the same time, a deceleration request is sent to the EPS, and the EPS sends a torque reduction request to the power control system, and then the EPS applies a lateral torque to the steering wheel, so as to control the current vehicle to change lanes or exit the warning operation; if the user receives the fourth warning instruction, at this time, the vehicle has deviated from the originally planned route by the navigation module, so the navigation module re-plans the driving route of the current vehicle according to the destination and the current vehicle information.

[0083] Further, if the vehicle auxiliary driving system of the embodiment of the present application receives an exit instruction, the auxiliary driving device is exited and closed, at this time, the vehicle driving is handed over to the driver. It should be noted that the exit instruction is a fixed operation action, for example, the driver can cancel the warning process through voice or select another route provided by the navigation module through screen operation to meet the driving needs of the driver.

[0084] According to the auxiliary driving method of the vehicle of the embodiment of the present application, the perception information of the current vehicle is acquired to determine the optimal driving route of the current vehicle, at least one to-be-warned area is generated according to the optimal driving route, the actual distance between the to-be-warned area closest to the current vehicle in the at least one to-be-warned area is acquired, and then the optimal auxiliary driving strategy of the current vehicle is matched to control the current vehicle. Thus, the problem that the vehicle deviates from the originally planned route by the navigation when the vehicle drives on a complex road and the user ignores the navigation voice is solved, and the user is reminded to change lanes in time when the vehicle has a deviation trend through the deep learning technology according to the driving condition of the vehicle and the surrounding environment, so as to avoid the deviation of the driving route.

[0085] Secondly, the auxiliary driving device of the vehicle according to the embodiment of the present application is described with reference to the accompanying drawings.

[0086] Figure 4 is a block schematic diagram of the auxiliary driving device of the vehicle of the embodiment of the present application.

[0087] As Figure 4 shown, the auxiliary driving device 10 of the vehicle includes an acquisition module 100, a generation module 200 and a matching module 300.

[0088] The acquisition module 100 is configured to acquire perception information of the current vehicle, wherein the perception information includes a destination of the current vehicle.

[0089] The generation module 200 is configured to determine a best driving route of the current vehicle according to the destination, generate at least one to-be-warned area according to the best driving route, and acquire an actual distance between the at least one to-be-warned area and a to-be-warned area closest to the current vehicle.

[0090] The matching module 300 is configured to match a best auxiliary driving strategy of the current vehicle according to the actual distance, and control the current vehicle according to the best auxiliary driving strategy.

[0091] Further, in some embodiments, the matching module 300 is specifically configured to:

[0092] if the actual distance is less than a first preset distance, the best auxiliary driving strategy is to issue a first warning instruction;

[0093] if the actual distance is less than a second preset distance, it is determined whether the current vehicle meets a preset off-route condition, and when the preset off-route condition is met, the best auxiliary driving strategy is to issue a second warning instruction, wherein the second preset distance is less than the first preset distance;

[0094] if the actual distance is less than a third preset distance, it is determined whether the current vehicle meets a preset off-route condition, and when the preset off-route condition is met, the best auxiliary driving strategy is to issue a third warning instruction, wherein the third preset distance is less than the second preset distance;

[0095] if the actual distance is less than a fourth preset distance, the best auxiliary driving strategy is to issue a fourth warning instruction, wherein the fourth preset distance is less than the third preset distance.

[0096] Further, in some embodiments, the matching module 300 is specifically configured to:

[0097] acquire a lane position, a steering wheel torque and a current speed of the current vehicle;

[0098] quantize the lane position, the steering wheel torque and the current speed of the current vehicle;

[0099] The quantified lane position, steering wheel torque and current vehicle speed are weighted and normalized based on a preset weighting strategy and normalization strategy to obtain a weighting result, and when the weighting result is greater than a preset threshold, it is determined that the current vehicle meets the preset off-route condition.

[0100] Further, in some embodiments, the matching module 300 is specifically configured to:

[0101] When the early warning instruction is the first early warning instruction, the early warning information is broadcast through the preset acoustic device;

[0102] When the early warning instruction is the second early warning instruction, the early warning information is broadcast again through the preset acoustic device, and the steering wheel of the current vehicle is controlled to start the early warning vibration mode, while sending a deceleration request to the EPS, and sending a torque reduction request to the power control system through the EPS, to control the current vehicle to change lanes or exit the early warning operation;

[0103] When the early warning instruction is the third early warning instruction, the early warning information is broadcast again through the preset acoustic device, and the steering wheel of the current vehicle is controlled to start the early warning vibration mode, while sending a deceleration request to the EPS, and sending a torque reduction request to the power control system through the EPS, and then applying a lateral torque to the steering wheel through the EPS to control the current vehicle to change lanes or exit the early warning operation;

[0104] When the early warning instruction is the fourth early warning instruction, the driving route of the current vehicle is re-planned.

[0105] Further, in some embodiments, the generating module 200 is specifically configured to:

[0106] Based on the global positioning system GPS, the route branch and / or ramp in the optimal driving route are obtained;

[0107] At least one early warning area is generated according to the route branch and / or ramp.

[0108] The auxiliary driving device of the vehicle according to the embodiments of the present application obtains the perception information of the current vehicle to determine the optimal driving route of the current vehicle, and generates at least one early warning area according to the optimal driving route, and obtains the actual distance between the closest early warning area in the at least one early warning area to the current vehicle, and then matches the optimal auxiliary driving strategy of the current vehicle to control the current vehicle. Thus, the problem that the vehicle cannot change lanes in time and deviate from the originally planned route of the navigation due to the user's neglect of the navigation voice when the vehicle drives on a complex road is solved, and by using deep learning technology, the user is reminded to change lanes in time when the vehicle has a deviation tendency according to the driving condition of the vehicle and the surrounding environment, so as to avoid deviation of the driving route.

[0109] Figure 5A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include:

[0110] The memory 501, the processor 502, and the computer program stored on the memory 501 and capable of running on the processor 502.

[0111] When the processor 502 executes the program, it implements the vehicle assisted driving method provided in the above embodiments.

[0112] Furthermore, electronic devices also include:

[0113] Communication interface 503 is used for communication between memory 501 and processor 502.

[0114] The memory 501 is used to store computer programs that can run on the processor 502.

[0115] The memory 501 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0116] If the memory 501, processor 502, and communication interface 503 are implemented independently, then the communication interface 503, memory 501, and processor 502 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 5 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0117] Optionally, in a specific implementation, if the memory 501, processor 502, and communication interface 503 are integrated on a single chip, then the memory 501, processor 502, and communication interface 503 can communicate with each other through an internal interface.

[0118] Processor 502 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.

[0119] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described vehicle assisted driving method.

[0120] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0121] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0122] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0123] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0124] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0125] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by a program instructing related hardware, and the program can be stored in a computer-readable storage medium. When executed, the program includes one or a combination of the steps of the method embodiments.

[0126] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0127] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. An assisted driving method of a vehicle, characterized by, The method comprises the following steps: obtaining perception information of a current vehicle, wherein the perception information comprises a destination of the current vehicle; determining an optimal driving route of the current vehicle according to the destination, generating at least one pre-warning area according to the optimal driving route, and obtaining an actual distance between the at least one pre-warning area closest to the current vehicle; and matching an optimal auxiliary driving strategy of the current vehicle according to the actual distance, and controlling the current vehicle according to the optimal auxiliary driving strategy; wherein the matching of the optimal auxiliary driving strategy of the current vehicle according to the actual distance comprises: if the actual distance is less than a first preset distance, the optimal auxiliary driving strategy is to issue a first pre-warning instruction; if the actual distance is less than a second preset distance, it is determined whether the current vehicle meets a preset off-route condition, and when the preset off-route condition is met, the optimal auxiliary driving strategy is to issue a second pre-warning instruction, wherein the second preset distance is less than the first preset distance; if the actual distance is less than a third preset distance, it is determined whether the current vehicle meets the preset off-route condition, and when the preset off-route condition is met, the optimal auxiliary driving strategy is to issue a third pre-warning instruction, wherein the third preset distance is less than the second preset distance; and if the actual distance is less than a fourth preset distance, the optimal auxiliary driving strategy is to issue a fourth pre-warning instruction, wherein the fourth preset distance is less than the third preset distance; the determination of whether the current vehicle meets the preset off-route condition comprises: obtaining a lane position, a steering wheel torque and a current speed of the current vehicle; quantizing the lane position, the steering wheel torque and the current speed of the current vehicle; performing weighting processing and normalization processing on the quantized lane position, steering wheel torque and current speed of the current vehicle based on a preset weighting strategy and normalization strategy to obtain a weighting result, and determining that the current vehicle meets the preset off-route condition when the weighting result is greater than a preset threshold; and in the weighting processing, a weighting coefficient is intelligently determined by a deep learning model, and the deep learning model is simultaneously optimized according to the driving habits of a driver. The control of the current vehicle according to the optimal auxiliary driving strategy comprises: when the pre-warning instruction is a first pre-warning instruction, playing pre-warning information through a preset acoustic device; when the pre-warning instruction is a second pre-warning instruction, playing the pre-warning information again through the preset acoustic device and controlling a steering wheel of the current vehicle to start a pre-warning vibration mode, simultaneously sending a deceleration request to an electronic power steering system (EPS) and sending a torque reduction request to a power control system through the EPS to control the current vehicle to change lanes or exit the pre-warning operation; when the pre-warning instruction is a third pre-warning instruction, after playing the pre-warning information again through the preset acoustic device and controlling the steering wheel of the current vehicle to start the pre-warning vibration mode, simultaneously sending the deceleration request to the EPS and sending the torque reduction request to the power control system through the EPS, applying a lateral torque to the steering wheel through the EPS to control the current vehicle to change lanes or exit the pre-warning operation; and when the pre-warning instruction is a fourth pre-warning instruction, re-planning a driving route of the current vehicle.

2. The method of claim 1, wherein, Generating at least one pre-warning area according to the optimal driving route comprises: Obtaining a route branch and / or a ramp in the optimal driving route based on a global positioning system (GPS); Generating at least one pre-warning area according to the route branch and / or the ramp.

3. An assist driving device of a vehicle, characterized by Comprise: An acquisition module configured to acquire perception information of a current vehicle, wherein the perception information comprises a destination of the current vehicle; A generation module configured to determine an optimal driving route of the current vehicle according to the destination, generate at least one pre-warning area according to the optimal driving route, and acquire an actual distance between the at least one pre-warning area and a closest pre-warning area to the current vehicle; and A matching module configured to match an optimal auxiliary driving strategy of the current vehicle according to the actual distance, and control the current vehicle according to the optimal auxiliary driving strategy; The matching module is specifically configured to: if the actual distance is less than a first preset distance, the optimal auxiliary driving strategy is to issue a first pre-warning instruction; if the actual distance is less than a second preset distance, it is determined whether the current vehicle meets a preset off-route condition, and when the preset off-route condition is met, the optimal auxiliary driving strategy is to issue a second pre-warning instruction, wherein the second preset distance is less than the first preset distance; if the actual distance is less than a third preset distance, it is determined whether the current vehicle meets the preset off-route condition, and when the preset off-route condition is met, the optimal auxiliary driving strategy is to issue a third pre-warning instruction, wherein the third preset distance is less than the second preset distance; and if the actual distance is less than a fourth preset distance, the optimal auxiliary driving strategy is to issue a fourth pre-warning instruction, wherein the fourth preset distance is less than the third preset distance. The matching module is specifically configured to: acquire a lane position of the current vehicle, a steering wheel torque, and a current vehicle speed; quantize the lane position of the current vehicle, the steering wheel torque, and the current vehicle speed; perform weighting processing and normalization processing on the quantized lane position of the current vehicle, the steering wheel torque, and the current vehicle speed based on a preset weighting strategy and a normalization strategy, to obtain a weighting result; and determine that the current vehicle satisfies the preset off-route condition when the weighting result is greater than a preset threshold. The matching module is specifically configured to: when the early warning instruction is a first early warning instruction, play early warning information through a preset acoustic device; when the early warning instruction is a second early warning instruction, play the early warning information again through the preset acoustic device and control a steering wheel of the current vehicle to start an early warning vibration mode, simultaneously send a deceleration request to an EPS, and send a torque reduction request to a power control system through the EPS to control the current vehicle to perform a lane change or exit an early warning operation; when the early warning instruction is a third early warning instruction, play the early warning information again through the preset acoustic device and control the steering wheel of the current vehicle to start the early warning vibration mode, simultaneously send the deceleration request to the EPS, and send the torque reduction request to the power control system through the EPS, then apply a lateral torque to the steering wheel through the EPS to control the current vehicle to perform the lane change or exit the early warning operation; and when the early warning instruction is a fourth early warning instruction, re-plan a driving route of the current vehicle.

4. An electronic device, comprising: Comprise: A memory, a processor, and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the auxiliary driving method of the vehicle according to any one of claims 1-2.

5. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the auxiliary driving method of the vehicle according to any one of claims 1-2.

Images