Driving strategy determination method and device, equipment, storage medium and program product

Abstract

The invention relates to a driving strategy determination method and device, equipment, a storage medium and a program product, and relates to the technical field of vehicle safety. The method is applied to a vehicle and comprises the following steps: acquiring a current reaction capability parameter of a user driving the vehicle and an adaptive capability parameter of the user to a target scene; and processing the current response capability parameter and the adaptive capability parameter to obtain a target driving capability level of the user. Based on the target driving ability level and the target scene, a first driving strategy is determined from multiple driving strategies, one driving strategy in the multiple driving strategies corresponds to one driving ability level and one driving scene, and the driving strategies are used for reflecting the protection degree in the driving process; the driving ability level is in negative correlation with the protection degree reflected by the driving strategy. Therefore, the safety of the vehicle in the running process can be improved.

Description

Technical Field

[0001] This application relates to the field of automotive safety technology, specifically to a method, apparatus, device, storage medium, and program product for determining a driving strategy. Background Technology

[0002] With the acceleration of urbanization and the increase in vehicle ownership, users are using vehicles more frequently in their daily lives, making road traffic issues a hot topic in modern society. Driving, as an indispensable part of road traffic, affects the safety of every road user.

[0003] Driving scenarios typically refer to the various situations and environments a vehicle encounters while driving on the road. For example, a low-speed driving scenario where a vehicle slowly accelerates from a standstill at a traffic light or parking lot exit; a medium-speed driving scenario where a vehicle travels at a moderate speed on a city ring road or main road; and a high-speed driving scenario where a vehicle is overtaking on a highway or expressway.

[0004] However, due to factors such as users' relaxed vigilance during driving, unstable vehicle performance, unpredictable environmental changes, and frequent pedestrian and non-motorized vehicle activity, driving faces safety risks and cannot provide sufficient safety support during vehicle operation. Therefore, how to improve vehicle safety during driving has become an urgent technical problem to be solved. Summary of the Invention

[0005] This application provides a method, apparatus, device, storage medium, and program product for determining a driving strategy, to at least solve the technical problem of how to improve safety in low-speed driving conditions in related technologies. The technical solution of this application is as follows:

[0006] According to a first aspect of this application, a method for determining a driving strategy is provided, applied to a vehicle, comprising: acquiring current reaction capability parameters of a user driving the vehicle and user adaptability parameters to a target scenario; processing the current reaction capability parameters and adaptability parameters to obtain the user's target driving capability level; and determining a first driving strategy from multiple driving strategies based on the target driving capability level and the target scenario, wherein each driving strategy corresponds to a driving capability level and a driving scenario, and the driving strategy is used to reflect the degree of protection during driving, with the driving capability level being negatively correlated with the degree of protection reflected by the driving strategy.

[0007] Based on the aforementioned technical means, the current facial and behavioral information of the user driving the vehicle, as well as historical driving information in the target scenario, are collected. This information is then used to obtain reaction ability parameters and adaptation ability parameters through reaction ability prediction models and adaptation ability prediction models, respectively. These parameters are then processed to determine the user's target driving ability level. Different driving strategies are selected for different driving ability levels and different scenarios, with a negative correlation between the driving ability level and the degree of protection reflected by the driving strategy. Since the driving scenarios vary, and different users have different driving abilities in different scenarios, by individually statistically evaluating and assessing the driving ability of each user, and by incorporating the number of consecutive driving days and changes in vehicle type within the driving cycle into the evaluation, in addition to considering the pass rate of the driving scenario, a more comprehensive assessment of the user's driving ability can be achieved. Furthermore, determining targeted driving strategies based on driving ability for different driving scenarios increases the flexibility of protection measures. Through reasonable driving protection, different driving protection measures can be implemented for users with different driving abilities, enhancing driving comfort and increasing the sense of security for novice users, thereby improving vehicle safety during driving.

[0008] In one possible implementation, the method of "determining a first driving strategy from multiple driving strategies based on a target driving ability level and a target scenario" includes: determining multiple second driving strategies corresponding to the target scenario from multiple driving strategies based on the target scenario; and determining the first driving strategy from multiple second driving strategies based on the target driving ability level.

[0009] Based on the aforementioned technical means, users can select a suitable driving strategy from multiple driving strategies according to the target scenario and their target driving ability, further improving the adaptability of the driving strategy during the driving process. Starting safety is ensured by adding vehicle start-up protection in starting scenarios. Low-speed driving protection by employing acceleration limits in driving scenarios prevents users from accidentally pressing the pedal at close range, leading to continued sudden acceleration and potentially causing dangerous driving due to insufficient reaction time. This increases the flexibility of protective measures, thereby improving driving safety.

[0010] In one possible implementation, the driving ability level includes at least one of the following: a first level, a second level, and a third level, wherein the driving ability corresponding to the third level is greater than the driving ability corresponding to the second level, and the driving ability corresponding to the second level is greater than the driving ability corresponding to the first level. When the target scenario is a starting scenario, the second driving strategy includes: a starting type check strategy and / or a vehicle status check strategy. The method described above for "determining a first driving strategy from the second driving strategy based on the target driving ability level" includes: if the target driving ability level is a first level or a second level, then determining that the first driving strategy includes a starting type check strategy and a vehicle status check strategy. If the target driving ability level is a third level, then determining that the first driving strategy includes a vehicle status check strategy.

[0011] Based on the aforementioned technical means, when the target scenario is a starting scenario, a first driving strategy corresponding to the target driving ability level is determined from the second driving strategy based on different target driving ability levels. This can improve the targeting and efficiency of protection measures in the starting scenario, thereby enhancing the overall safety level of the vehicle during operation.

[0012] In one possible implementation, the method further includes: generating a check result indicating whether a problem exists in the vehicle during a start-up scenario. If the check result indicates a problem in the vehicle during a start-up scenario and the target driving ability level is Level 1, then in response to a start-up operation on the vehicle, a start-up event is not executed. If the check result indicates a problem in the vehicle during a start-up scenario and the target driving ability level is Level 1, then upon receiving an unlock command, in response to a start-up operation on the vehicle, a start-up event is executed. If the check result indicates a problem in the vehicle during a start-up scenario and the target driving ability level is Level 2 or Level 3, then in response to a start-up operation on the vehicle, a start-up event is executed.

[0013] Based on the aforementioned technical means, when the target scenario is a start-up scenario, the vehicle, based on the inspection results and driving ability level, will not execute a start-up event if the inspection results indicate a problem in the start-up scenario and the target driving ability level is Level 1. Instead, it will execute the start-up event upon receiving an unlock command. Conversely, it will execute the start-up event if the inspection results indicate a problem in the start-up scenario and the target driving ability level is Level 2 or Level 3. This allows for different start-up measures to be taken for different driving strategies, resulting in more comprehensive start-up protection and improved vehicle safety during the start-up process.

[0014] In one possible implementation, when the target scenario is a driving scenario, the second driving strategy includes: if the target distance between the vehicle and the adjacent vehicle is less than or equal to a first distance threshold, then setting the vehicle's acceleration to be less than an acceleration threshold. If the target distance is less than or equal to a second distance threshold, then engaging the brake pads to tighten the brake discs. The first distance threshold is greater than the second distance threshold, and both the first and second distance thresholds are negatively correlated with the driving ability level, while the acceleration threshold is positively correlated with the driving ability level.

[0015] Based on the aforementioned technical means, when the target scenario is a driving scenario, a first driving strategy corresponding to the target driving ability level is determined from the second driving strategy based on different target driving ability levels. This can improve the flexibility of protective measures in driving scenarios, reduce the stress on users during driving, and adapt to each user's driving ability to ensure safe driving.

[0016] In one possible implementation, the method for "obtaining the user's current reaction ability parameters and the user's adaptability parameters to the target scenario" includes: obtaining the user's current facial information and current behavior information, as well as historical driving information in the target scenario; inputting the current facial information and current behavior information into a reaction ability prediction model to obtain current reaction ability parameters; and inputting the historical driving information into an adaptability prediction model to obtain adaptability parameters.

[0017] Based on the aforementioned technical methods, the user's current facial and behavioral information, as well as historical driving information in the target scenario, are acquired through vehicle sensing devices. The acquired data is then classified and processed to obtain reaction capability parameters and adaptability parameters. This can prepare for future driving ability level assessments.

[0018] According to a second aspect provided in this application, a driving strategy determination device is provided, applied to a vehicle, the device comprising: an acquisition module and a processing module.

[0019] The acquisition module acquires the current reaction ability parameters and the user's adaptability parameters to the target scenario. The processing module processes these parameters to obtain the user's target driving ability level. Furthermore, based on the target driving ability level and the target scenario, the processing module determines a first driving strategy from multiple driving strategies. Each driving strategy corresponds to a driving ability level and a driving scenario, reflecting the degree of protection during driving. The driving ability level is negatively correlated with the degree of protection reflected by the driving strategy.

[0020] In one possible implementation, the processing module is specifically configured to determine a second driving strategy corresponding to the target scenario from a plurality of driving strategies. The processing module is also configured to determine a first driving strategy from the second driving strategy based on a target driving ability level.

[0021] In one possible implementation, the driving ability level includes at least one of the following: a first level, a second level, and a third level, wherein the driving ability corresponding to the third level is greater than the driving ability corresponding to the second level, and the driving ability corresponding to the second level is greater than the driving ability corresponding to the first level. When the target scenario is a starting scenario, the second driving strategy includes: a starting type check strategy and / or a vehicle status check strategy. The processing module is further configured to determine that the first driving strategy includes the starting type check strategy and the vehicle status check strategy if the target driving ability level is the first level or the second level. The processing module is further configured to determine that the first driving strategy includes the vehicle status check strategy if the target driving ability level is the third level.

[0022] In one possible implementation, the processing module is specifically configured to generate a check result indicating whether a problem exists in the vehicle during a start-up scenario. The processing module is further configured to, if the check result indicates a problem in the vehicle during a start-up scenario and the target driving ability level is Level 1, then, in response to a start-up operation on the vehicle, not execute a start-up event. The processing module is further configured to, if the check result indicates a problem in the vehicle during a start-up scenario and the target driving ability level is Level 1, then, upon receiving an unlock command, execute a start-up event in response to a start-up operation on the vehicle. The processing module is further configured to, if the check result indicates a problem in the vehicle during a start-up scenario and the target driving ability level is Level 2 or Level 3, then, in response to a start-up operation on the vehicle, execute a start-up event.

[0023] In one possible implementation, when the target scenario is a driving scenario, the second driving strategy includes: if the target distance between the vehicle and the adjacent vehicle is less than or equal to a first distance threshold, then setting the vehicle's acceleration to be less than an acceleration threshold; if the target distance is less than or equal to a second distance threshold, then executing a braking event. The first distance threshold is greater than the second distance threshold, and both the first and second distance thresholds are negatively correlated with the driving ability level, while the acceleration threshold is positively correlated with the driving ability level.

[0024] In one possible implementation, the acquisition module is specifically used to acquire the user's current facial information and current behavior information, as well as historical driving information in the target scenario. The processing module is further used to input the current facial information and current behavior information into the reaction ability prediction model to obtain current reaction ability parameters. The processing module is also used to input the historical driving information into the adaptive ability prediction model to obtain adaptive ability parameters.

[0025] According to a third aspect provided in this application, a vehicle is provided, comprising: a processor; and a memory for storing processor-executable instructions. The processor is configured to execute instructions to implement the method of any of the possible embodiments of the first aspect described above.

[0026] According to a fourth aspect provided in this application, a computer-readable storage medium is provided that, when the instructions in the computer-readable storage medium are executed by a processor of a vehicle, enables the vehicle to perform the method of any possible implementation of the first aspect described above.

[0027] According to the fifth aspect provided in this application, a computer program product is provided, the computer program product including computer instructions that, when executed on a vehicle, cause the vehicle to perform the method of any possible implementation of the first aspect described above.

[0028] Therefore, the above-mentioned technical features of this application have the following beneficial effects:

[0029] (1) By collecting the current facial and behavioral information of the user driving the vehicle, as well as historical driving information in the target scenario, and using the reaction ability prediction model and the adaptation ability prediction model to obtain reaction ability parameters and adaptation ability parameters respectively, the user's target driving ability level is obtained by processing the reaction ability parameters and adaptation ability parameters. Different driving strategies are selected for different driving ability levels and different scenarios, and the degree of protection reflected by the driving ability level and the driving strategy is negatively correlated. Since the driving scenarios in which the vehicle is located are different, and the driving abilities of different users in different driving scenarios are also different, by separately statistically evaluating the driving ability of each user, and in addition to considering the driving pass rate of the driving scenario, incorporating the number of consecutive driving days and changes in the type of vehicle driven in the driving cycle into the evaluation, the user's driving ability can be more comprehensively evaluated. Furthermore, based on the driving ability, targeted driving strategies can be determined for different driving scenarios, which can increase the flexibility of protection measures. Through reasonable driving protection, different driving protection can be provided for users with different driving abilities, which can enhance driving comfort and increase the sense of security of novice users, thereby improving the safety of the vehicle during driving.

[0030] (2) Based on the target scenario and driving ability, users can select a suitable driving strategy from multiple driving strategies, which can further improve the adaptability of the driving strategy during the driving process. Starting safety is ensured by adding vehicle start-up protection in the starting scenario. Low-speed driving protection with acceleration limits in the driving scenario prevents users from accidentally pressing the pedal at close range, leading to continued sudden acceleration and untimely reaction causing dangerous driving. This increases the flexibility of the protection measures, thereby improving driving safety.

[0031] (3) When the target scenario is a starting scenario, a first driving strategy corresponding to the target driving ability level is determined from the second driving strategy based on different target driving ability levels. This can improve the pertinence and efficiency of protection measures in the starting scenario, thereby improving the overall safety level of the vehicle during driving.

[0032] (4) When the target scenario is a starting scenario, the vehicle, based on the inspection results and driving ability level, will not execute a starting event if the inspection results indicate a problem in the starting scenario and the target driving ability level is Level 1. Instead, it will execute the starting event upon receiving an unlock command. Conversely, it will execute a starting event if the inspection results indicate a problem in the starting scenario and the target driving ability level is Level 2 or Level 3. This allows for different starting measures to be taken for different driving strategies, resulting in more comprehensive starting protection and improved vehicle safety during the starting process.

[0033] (5) When the target scenario is a driving scenario, a first driving strategy corresponding to the target driving ability level is determined from the second driving strategy based on different target driving ability levels. This can improve the flexibility of protection measures in driving scenarios, reduce the stress on users during driving, and adapt to each user's driving ability to ensure safe driving.

[0034] (6) The system acquires the user's current facial and behavioral information, as well as historical driving information in the target scenario, through vehicle sensing devices. The acquired data is then classified and processed to obtain reaction capability parameters and adaptability parameters. This can prepare for future driving ability level assessments.

[0035] It should be noted that the technical effects of any of the implementation methods in aspects two through five can be found in the technical effects of the corresponding implementation methods in aspect one, and will not be repeated here.

[0036] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0037] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application, and do not constitute an undue limitation of this application.

[0038] Figure 1 This is a schematic diagram of the structure of a vehicle according to an exemplary embodiment;

[0039] Figure 2 This is a flowchart illustrating a method for determining a driving strategy according to an exemplary embodiment;

[0040] Figure 3 This is a flowchart illustrating another method for determining a driving strategy according to an exemplary embodiment;

[0041] Figure 4 This is a flowchart illustrating another method for determining a driving strategy according to an exemplary embodiment;

[0042] Figure 5 This is a flowchart illustrating another method for determining a driving strategy according to an exemplary embodiment;

[0043] Figure 6 This is a schematic diagram illustrating an example of a vehicle starting from a lateral position according to an exemplary embodiment;

[0044] Figure 7 This is a schematic diagram illustrating an example of facial information recognition according to an exemplary embodiment;

[0045] Figure 8 This is an example diagram illustrating the determination of a driving ability level according to an exemplary embodiment;

[0046] Figure 9 This is a block diagram illustrating a driving strategy determination device according to an exemplary embodiment;

[0047] Figure 10 This is a block diagram illustrating an electronic device according to an exemplary embodiment. Detailed Implementation

[0048] To enable those skilled in the art to better understand the technical solutions of this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0049] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0050] Before providing a detailed description of the method for determining the driving strategy according to the embodiments of this application, the implementation environment and application scenarios of the embodiments of this application will be introduced first.

[0051] With the increase in car ownership, road safety issues are becoming increasingly prominent. Many families own one or more cars, but not everyone drives them regularly, and some even alternate between electric and gasoline vehicles. Different users have different driving abilities, and novice drivers, elderly drivers, or those with limited driving skills may face higher safety risks, especially at low speeds.

[0052] Currently, a collision avoidance system for electric vehicles can be used to achieve collision avoidance during vehicle driving. This system includes: a vehicle speed detection device; a vehicle distance detection device; a wheel motor braking device installed on the host vehicle, the wheel motor braking device including wheel brake motors, which applies braking force to the wheels upon receiving an emergency braking signal to provide regenerative braking to the host vehicle; and a vehicle controller, which determines the collision time based on the host vehicle speed, the speed of the vehicle ahead, and the first relative distance when the host vehicle speed exceeds a predetermined speed and the first relative distance is less than a predetermined distance, and sends an emergency braking signal to the wheel motor braking device when the collision time is less than a predetermined time. Alternatively, an autonomous driving capability detection method can be used to acquire multiple first driving data points of the target vehicle performing autonomous driving based on the target driving system in the target scenario; based on the first values ​​corresponding to each driving information included in the multiple first driving data points, a first quantization value corresponding to each driving information is determined; multiple second driving data points of the target vehicle performing autonomous driving based on the initial driving system in the target scenario are acquired; based on the second values ​​corresponding to each driving information included in the multiple second driving data points, a second quantization value corresponding to each driving information is determined; based on the first quantization value and the second quantization value corresponding to each driving information, the autonomous driving capability of the target driving system in the target scenario is detected, and the detection result is obtained.

[0053] While the aforementioned technical solutions can determine the collision distance and initiate braking by using vehicle speed when employing predicted distance as the safety protection distance, and can also determine driving ability by combining scene driving information with the user's initial state, they do not provide driving protection for users with different driving abilities. Furthermore, the assessment of driving ability does not consider the user's physiological state and driving cycle. Therefore, they cannot provide a more comprehensive evaluation of the user's ability to take corresponding protective measures with greater adaptability, and ultimately cannot better provide driving safety.

[0054] In conclusion, improving vehicle safety during operation is a pressing technical problem that needs to be addressed.

[0055] To address the aforementioned problems, this application provides a method for determining a driving strategy. This involves acquiring the current reaction ability parameters and the user's adaptability parameters to a target scenario. The current reaction ability parameters and adaptability parameters are processed to obtain the user's target driving ability level. Based on the target driving ability level and the target scenario, a first driving strategy is determined from multiple driving strategies. Each driving strategy corresponds to a driving ability level and a driving scenario. The driving strategy reflects the degree of protection during driving, and the driving ability level is negatively correlated with the degree of protection reflected by the driving strategy. This allows for corresponding protective measures to be taken for users with different driving abilities when facing different driving scenarios during vehicle operation, improving driving safety and increasing the flexibility of protective measures, thereby preventing accidents.

[0056] The implementation environment of the embodiments of this application is described below.

[0057] Figure 1 This is a schematic diagram illustrating the structure of a vehicle according to an exemplary embodiment, such as... Figure 1 As shown, the vehicle includes: a driving ability assessment module 101, a braking protection module 102, and a safety inspection module 103.

[0058] The driving ability assessment module 101 is used to assess the user's driving ability and obtain the user's driving ability level, which reflects the user's driving ability. The driving ability assessment module 101 may include a user detection module 104 and a user data recording module 105. The user detection module 104 is used to acquire user information about the vehicle and historical driving information of the target scenario; for example, user information may include the user's facial information, behavioral information, etc. The user data recording module 105 is used to store the information collected by the user detection module 104. Furthermore, the driving ability assessment module 101 can send the user's driving ability level to the braking protection module 102 and the safety check module 103.

[0059] The braking protection module 102 is used to monitor and control the vehicle's braking system. For example, during low-speed emergency braking, the braking protection module mainly adjusts the safety distance and acceleration limit, detecting the safe protection distance to avoid a collision. Furthermore, the braking protection module 102 can also receive the driving ability level sent by the driving ability assessment module 101. Additionally, the braking protection module 102 can control the vehicle's braking system based on the driving ability level to perform braking operations. The braking protection module 102 may include a safety distance calculation module 106 and a braking module 107. The safety distance calculation module 106 is used to calculate the safe distance to adjacent vehicles. For example, the safety distance calculation module 106 can receive the driving ability level sent by the driving ability assessment module 101 and determine the safe distance to adjacent vehicles based on the driving ability level. The braking module 107 is used to receive the safe distance to adjacent vehicles reflected by the safety distance calculation module 106 and control the vehicle's braking effect to adjust braking safety.

[0060] The safety check module 103 receives parameters from the user detection module 104 regarding the user's current reaction ability and adaptability to the target scenario, as well as the driving ability level sent by the driving ability assessment module 101. Based on this data, it performs a comprehensive safety assessment of the vehicle's status. Furthermore, the safety check module 103 can select whether to provide voice prompts and the scope of the check. The safety check module 103 may include a start-up safety check 108 and a vehicle body safety check 109. The start-up safety check 108 checks user behavior, such as seatbelt checks, door checks, gear shift checks, and start-up turn signal checks. The vehicle body safety check 109 checks the vehicle's status, such as tire pressure checks and engine status checks.

[0061] For ease of understanding, the method for determining the driving strategy provided in this application will be described in detail below with reference to the accompanying drawings. Figure 2 This is a flowchart illustrating a method for determining a driving strategy according to an exemplary embodiment, such as... Figure 2 As shown, the method includes the following steps:

[0062] S201. Obtain the current reaction capability parameters of the user driving the vehicle and the user's adaptability parameters to the target scenario.

[0063] Among them, the current reaction capability parameter reflects the user's current reaction capability, and the target scenario adaptability parameter reflects the user's adaptability to the target scenario.

[0064] It should be noted that the representation of the current reaction capability parameter and the adaptability parameter in this application embodiment is not limited. For example, the current reaction capability parameter can be high, medium, or low. Or, the current reaction capability parameter can be L1, L2, or L3. Or, the current reaction capability parameter can be a, b, or c. Similarly, the description of the adaptability parameter can refer to the description of the current reaction capability parameter. The following description uses the current reaction capability parameter of high, medium, or low as an example to illustrate the embodiments of this application.

[0065] One possible implementation involves the vehicle storing multiple preset user adaptability parameters for different scenarios. The system acquires the user's identity information, road environment information, and the vehicle's current speed. Based on the road environment information, the target scenario is determined. Based on the user's identity information and the target scenario, the user's adaptability parameters for that scenario are then determined.

[0066] Optionally, the target scenario can be determined based on the vehicle's speed; for example, the target scenario could be a low-speed driving scenario. The vehicle's current speed can be obtained. If the current speed is less than a preset speed threshold, the target scenario is determined to be a low-speed driving scenario.

[0067] For example, the target scenario could be a starting scenario. Alternatively, the target scenario could be a driving scenario, such as a meeting scenario or a parking scenario.

[0068] S202. Process the current reaction capability parameters and adaptability parameters to obtain the user's target driving capability level.

[0069] Among them, the driving ability level is used to reflect the user's driving ability. There are multiple driving ability levels, and the driving ability level is positively correlated with driving ability.

[0070] In other words, the higher the driving ability level, the stronger the user's driving ability. The lower the driving ability level, the weaker the user's driving ability.

[0071] In one possible design, the driving ability level can be at least one of the following: Level 1, Level 2, and Level 3. Level 3 is higher than Level 2, and Level 2 is higher than Level 1. Specifically, the driving ability corresponding to Level 3 is greater than the driving ability corresponding to Level 2, and the driving ability corresponding to Level 2 is greater than the driving ability corresponding to Level 1.

[0072] As one possible approach, vehicles can use driving ability assessment algorithms to process reaction and adaptation parameters to obtain a driving ability level.

[0073] It should be noted that the embodiments of this application do not limit the driving ability assessment algorithm. For example, the driving ability assessment algorithm can be a weighted summation method. Furthermore, the driving ability assessment algorithm can also be a decision tree, neural network, or other machine learning algorithms.

[0074] For example, as shown in Table 1, it illustrates the relationship between driving ability level and current reaction ability parameters and adaptability parameters.

[0075] Table 1

[0076]

[0077] In other words, when both the current reaction ability parameter and the adaptation ability parameter are low, the driving ability level is L1 (i.e., Level 1). When the current reaction ability parameter is low and the adaptation ability parameter is medium, the driving ability level is L2 (i.e., Level 2). When the current reaction ability parameter is medium and the adaptation ability parameter is high, the driving ability level is L3 (i.e., Level 3). When the current reaction ability parameter is high and the adaptation ability parameter is low-high, the driving ability level is L3 (i.e., Level 3). Level 2 is higher than Level 1, and Level 3 is higher than Level 2. For other cases in Table 1, please refer to the above explanation of the examples in Table 1; they will not be repeated here.

[0078] S203. Based on the target driving ability level and target scenario, determine the first driving strategy from multiple driving strategies.

[0079] Among the multiple driving strategies, each driving strategy corresponds to a driving ability level and a driving scenario.

[0080] For example, multiple driving strategies include driving strategy 1 to driving strategy 4, driving ability levels include first level and second level, and driving scenarios include scenario a and scenario b. Specifically, when the driving ability level is first level and the scenario is scenario a, the corresponding driving strategy is driving strategy 1. When the driving ability level is second level and the scenario is scenario a, the corresponding driving strategy is driving strategy 2. When the driving ability level is first level and the scenario is scenario b, the corresponding driving strategy is driving strategy 3. When the driving ability level is second level and the scenario is scenario b, the corresponding driving strategy is driving strategy 4.

[0081] In this embodiment of the application, the driving strategy is used to reflect the degree of protection during the driving process, and the driving ability level is negatively correlated with the degree of protection reflected by the driving strategy.

[0082] In other words, the higher the driving ability level, the lower the level of protection reflected by the driving strategy. Conversely, the lower the driving ability level, the higher the level of protection reflected by the driving strategy.

[0083] The technical solution provided by the above embodiments brings at least the following beneficial effects: By collecting the current facial information and current behavioral information of the user driving the vehicle, as well as historical driving information in the target scenario, and then using the reaction ability prediction model and the adaptation ability prediction model to obtain reaction ability parameters and adaptation ability parameters respectively, the user's target driving ability level is obtained by processing the reaction ability parameters and adaptation ability parameters. Different driving strategies are selected for different driving ability levels and different scenarios, and the degree of protection reflected by the driving ability level and the driving strategy is negatively correlated. Since the driving scenarios in which the vehicle is located are different, and the driving abilities of different users in different driving scenarios are also different, by separately statistically evaluating and assessing the driving ability of each user, and by incorporating the number of consecutive driving days and changes in the type of vehicle driven in the driving cycle into the evaluation in addition to considering the driving scenario pass rate, the user's driving ability can be more comprehensively assessed. Furthermore, based on driving ability, targeted driving strategies can be determined for different driving scenarios, which can increase the flexibility of protection measures. Through reasonable driving protection, different driving protection can be provided for users with different driving abilities, which can enhance driving comfort and increase the sense of security for novice users, thereby improving the safety of the vehicle during driving.

[0084] In some embodiments, where multiple second driving strategies exist corresponding to a target scenario, in order to comprehensively consider and selectively choose a first driving strategy based on the target driving ability among the multiple second driving strategies, then as follows: Figure 3 As shown, determining the first driving strategy from multiple driving strategies based on the target driving ability level and target scenario (i.e., S203) may include the following steps:

[0085] S301. Based on the target scenario, determine the second driving strategy corresponding to the target scenario from multiple driving strategies.

[0086] In one possible design, the target scenario can be a starting scenario. When the scenario is a starting scenario, the second driving strategy includes: a starting type check strategy and / or a vehicle status check strategy.

[0087] In other words, the second driving strategy can be either a start-up type check strategy, a vehicle status check strategy, or a start-up type check strategy and a vehicle status check strategy.

[0088] The starting type check strategy may include at least one of the following: seat belt check, door check, and starting turn signal check. The vehicle condition check strategy may include at least one of the following: tire pressure check and engine condition check.

[0089] In another possible design, the target scenario can be a driving scenario. In the case of a driving scenario, the second driving strategy includes: if the target distance between the vehicle and the adjacent vehicle is less than or equal to a first distance threshold, then setting the vehicle's acceleration to less than an acceleration threshold; if the target distance is less than or equal to a second distance threshold, then executing a braking event, where the first distance threshold is greater than the second distance threshold.

[0090] It should be noted that the vehicle is equipped with internal and external sensing modules, which can determine the distance to nearby vehicles. If the target distance is less than the safe distance, the braking module is triggered to perform a braking event.

[0091] It should be noted that the embodiments of this application do not limit the first distance threshold and the second distance threshold. For example, the first distance threshold can be 1 meter (m) and the second distance threshold can be 40 centimeters (cm). Alternatively, the first distance threshold can be 0.5m and the second distance threshold can be 20cm. Or, the first distance threshold can be 0.3m and the second distance threshold can be 10cm.

[0092] For example, suppose the first distance threshold is 1m, the second distance threshold is 40cm, and the acceleration threshold is 1.5 meters per second squared (m / s²). 2 If the target distance is 50cm, then the target distance is less than the first distance threshold, and the vehicle's acceleration is set to be less than 1.5m / s². 2 If the target distance is 30cm, then the target distance is less than the second distance threshold, and a braking event is executed.

[0093] S302. Based on the target driving ability level, determine the first driving strategy from the second driving strategy.

[0094] Different driving ability levels correspond to different second driving strategies, while the first driving strategy is a driving strategy that matches the target driving ability level.

[0095] In one possible design, if the second driving strategy includes a start-up type check strategy and / or a vehicle status check strategy, and the target driving ability level is level one or level two, then the first driving strategy is determined to include a start-up type check strategy and a vehicle status check strategy.

[0096] For example, if the driving ability level is L1 (i.e., Level 1) or L2 (i.e., Level 2), a start-up safety check and a vehicle condition check are performed.

[0097] If the target driving ability level is Level 3, then the first driving strategy is determined to include a vehicle status check strategy.

[0098] In other words, when the target driving ability level is level three, the vehicle only needs to execute the vehicle status check strategy and does not need to execute the start type check strategy.

[0099] For example, if the driving ability level is L3 (i.e., the third level), a vehicle condition check is performed.

[0100] Understandably, when the target scenario is a starting scenario, a first driving strategy corresponding to the target driving ability level is determined from the second driving strategy based on different target driving ability levels. This can improve the targeting and efficiency of protection measures in the starting scenario, thereby improving the overall safety level of the vehicle during operation.

[0101] In one possible design, when the target scenario is a driving scenario, the second first distance threshold and the second distance threshold are negatively correlated with the driving ability level, while the acceleration threshold is positively correlated with the driving ability level.

[0102] As one possible implementation, if the target driving ability level is Level 1, then the first distance threshold in the target driving strategy is determined as the first safe distance, the second distance threshold as the second safe distance, and the acceleration threshold as the first acceleration. The first safe distance is greater than the second safe distance.

[0103] If the target driving ability level is Level 2, then the first distance threshold in the target driving strategy is determined as the third safe distance, the second distance threshold as the fourth safe distance, and the acceleration threshold as the second acceleration. Specifically, the third safe distance is greater than the fourth safe distance, the first safe distance is greater than the third safe distance, the second safe distance is greater than the fourth safe distance, and the first acceleration is less than the second acceleration.

[0104] If the target driving ability level is level three, then the first distance threshold in the target driving strategy is determined to be the fifth safe distance, the second distance threshold to be the sixth safe distance, and the acceleration threshold to be the third acceleration. Specifically, the fifth safe distance is greater than the sixth safe distance, the third safe distance is greater than the fifth safe distance, the fourth safe distance is greater than the sixth safe distance, and the second acceleration is less than the third acceleration.

[0105] It should be noted that the fifth safety distance can be 0. That is, when the target driving ability level is level three, no first distance threshold is set. Furthermore, when the target driving ability level is level three, the third acceleration can be a relatively large value, such as 100 m / s². 2 Alternatively, no acceleration threshold may be set.

[0106] For example, the driving ability level is L1, the first safe distance is set to 1m, the second safe distance is set to 40cm, and the first acceleration is set to 1.5m / s². 2 The driving ability level is L2, with the third safe distance set at 0.5m, the fourth safe distance at 20cm, and the second acceleration at 2m / s². 2 The driving ability level is L3, with no first safe distance, a fifth safe distance of 10cm, and no acceleration limit. L2 is greater than L1, and L3 is greater than L2; that is, the second level is higher than the first, and the third level is higher than the second. Therefore, the smaller the first and second safe distances, the greater the acceleration limit, and the higher the driving ability level.

[0107] Understandably, when the target scenario is a driving scenario, a first driving strategy corresponding to the target driving ability level is determined from the second driving strategy based on different target driving ability levels. This can improve the flexibility of protective measures in driving scenarios, reduce the stress on users during driving, and adapt to each user's driving ability to ensure safe driving.

[0108] Based on the above solutions, it is clear that users can select the appropriate driving strategy from multiple options based on the target scenario and their target driving ability, further improving the adaptability of the driving strategy during driving. Starting safety is ensured by adding vehicle start-up protection in starting scenarios. Low-speed driving protection with acceleration limits in driving scenarios prevents users from accidentally pressing the pedal at close range, leading to sudden acceleration and potentially dangerous driving due to insufficient reaction time. This increases the flexibility of protective measures, thereby improving driving safety.

[0109] In some embodiments, when the target scenario is a starting scenario, the vehicle may take different starting operations depending on the driving level.

[0110] In this embodiment, when the target scenario is a start-up scenario, the vehicle can execute a first driving strategy corresponding to the start-up scenario and generate a check result. The check result indicates whether there are any problems with the vehicle in the start-up scenario. The check result includes: the result of a start-up safety check and / or the result of a vehicle body status check. Then, based on the check result and the target driving level, a start-up event can be executed.

[0111] As one possible implementation, if the inspection result indicates a problem with the vehicle in the start-up scenario, and the target driving ability level is Level 1, then in response to the vehicle start-up operation, the start-up event is not executed. If the inspection result indicates a problem with the vehicle in the start-up scenario, and the target driving ability level is Level 1, then upon receiving an unlock command, in response to the vehicle start-up operation, the start-up event is executed. The unlock command is used to trigger the release of the parking function.

[0112] It should be noted that if the inspection results indicate a problem with the vehicle during the start-up scenario, the vehicle can maintain its parking function. Even if the user initiates a start-up operation, the vehicle will not execute the start-up event. If the vehicle receives an unlock operation from the user, it can release the parking function. Thus, after receiving a start-up operation from the user, the vehicle can execute the start-up event.

[0113] For example, an unlock button is deployed in the vehicle. It can receive user input to the unlock button and generate an unlock command.

[0114] As one possible implementation, if the inspection results indicate that the vehicle has a problem in the start-up scenario and the target driving capability level is level two or three, then in response to the start-up operation of the vehicle, a start-up event is executed.

[0115] In other words, if the target driving ability level is level two or three, the user does not need to perform an unlocking operation; the user can directly perform a starting operation to trigger the vehicle to start.

[0116] Optionally, if the inspection results indicate a problem with the vehicle in a start-up scenario, and the target driving ability level is Level 1 or Level 2, a voice prompt message is issued to indicate a problem with the start-up safety check and / or vehicle condition. If the inspection results indicate a problem with the vehicle in a start-up scenario, and the target driving ability level is Level 3, a prompt message is displayed on the instrument panel to indicate a problem with the vehicle condition.

[0117] For example, such as Figure 4 As shown, when problems arise in the starting scenario, different measures are taken depending on the current user's driving ability level. When the target driving ability level is Level 1, the vehicle does not execute the starting event; it can only execute the starting event after receiving an unlock command. When the target driving ability level is Level 2 or Level 3, the vehicle can ignore the problems in the starting scenario and execute the starting event.

[0118] Understandably, when the target scenario is a start-up scenario, the vehicle, based on the inspection results and driving ability level, will not execute a start-up event if the inspection results indicate a problem in the start-up scenario and the target driving ability level is Level 1. Instead, it will execute the start-up event upon receiving an unlock command. Conversely, it will execute the start-up event if the inspection results indicate a problem in the start-up scenario and the target driving ability level is Level 2 or Level 3. This allows for different start-up measures to be taken for different driving strategies, resulting in more comprehensive start-up protection and improved vehicle safety during the start-up process.

[0119] In some embodiments, the current reaction capability parameters and the user's adaptability parameters to the target scenario can be determined using relevant and historical information about the user. For example... Figure 5 As shown, obtaining the user's current reaction ability parameters and the user's adaptability parameters to the target scenario (i.e., S201) may include the following steps:

[0120] S501. Obtain the user's current facial information and current behavior information, as well as historical driving information in the target scenario.

[0121] The current facial information includes at least one of the following: eye features, expression features, pupil features, etc. The current behavioral information includes at least one of the following: the user's driving behavior and road environment information. The historical driving information for the target scenario includes at least one of the following: number of consecutive driving days, changes in vehicle type, and the number of times the user has successfully passed through the current scenario.

[0122] For example, the vehicle is equipped with in-vehicle and out-of-vehicle sensing devices to obtain the user's current facial information and current behavior information.

[0123] The vehicle stores historical information, including driving data from different preset users in various scenarios. The vehicle can then use this historical information to determine the user's driving history for a target scenario.

[0124] S502. Input the current facial information and current behavioral information into the reaction ability prediction model to obtain the current reaction ability parameters.

[0125] Among them, the reaction capacity prediction model is used to obtain reaction capacity parameters.

[0126] For example, the vehicle is equipped with in-vehicle computing devices inside and outside the vehicle. The current facial information and current behavior information are input into the reaction ability prediction model through the in-vehicle computing devices to obtain reaction ability parameters.

[0127] It should be noted that the embodiments of this application do not limit the reaction ability prediction model. For example, the reaction ability prediction model can be obtained based on decision trees, neural networks, etc., in machine learning algorithms. As another example, the adaptability prediction model can also be obtained by training a linear regression model.

[0128] S503. Input historical driving information into the adaptive capability prediction model to obtain adaptive capability parameters.

[0129] Among them, the adaptability prediction model is used to obtain adaptability parameters.

[0130] For example, the vehicle is equipped with in-vehicle and out-of-vehicle computing devices. Historical driving information is input into the adaptive capability prediction model through the in-vehicle computing devices to obtain adaptive capability parameters.

[0131] It should be noted that the embodiments of this application do not limit the vehicle's internal and external sensing devices and the vehicle-mounted computing devices. For example, the vehicle's internal and external sensing modules may include cameras, LiDAR, and millimeter-wave radar. As another example, the vehicle-mounted computing device may be an onboard computing unit.

[0132] It should be noted that the embodiments of this application do not limit the adaptive ability prediction model. For example, the adaptive ability prediction model can be obtained based on decision trees, neural networks, etc., in machine learning algorithms. As another example, the adaptive ability prediction model can also be trained using a linear regression model.

[0133] For example, such as Figure 6 As shown, in a driving scenario involving a vehicle starting from a lateral position, vehicle 601 is the vehicle waiting to start, vehicle 602 is a neighboring vehicle of vehicle 601, and vehicle 603 is a vehicle traveling at low speed on the road. First, vehicle 601 can recognize the user's face through a sensing device, then perform camera correction, and then extract facial features through a convolutional neural network to obtain the user's personal information, as well as eye and expression features as the user's current facial information (e.g., ...). Figure 7 (As shown). Secondly, vehicle 601 can obtain driving behavior and road environment as the user's current behavior information through sensing devices. Vehicle 601 inputs the current facial information and current behavior information into the reaction ability prediction model through the vehicle's computer to obtain the current reaction ability parameters. Then, based on statistical data such as the number of times the current user has started and passed vehicles in the lateral direction, the number of days driving that vehicle, and whether the type of vehicle has changed during long-term driving, it uses historical driving information for the target scenario. Vehicle 601 inputs the historical driving information into the adaptive ability prediction model through the vehicle's computer to obtain adaptive ability parameters.

[0134] The following section describes the process of determining the level based on these two parameters using specific examples. For instance, as shown below... Figure 8As shown, current behavioral information includes driving behavior and road environment. Driving behavior information includes at least one of the following: steering wheel operation, accelerator pedal operation, and brake pedal operation. Inputting current facial information and current behavioral information into the reaction ability prediction model yields reaction ability parameters. Continuous driving days include driving duration distribution and longest driving time. Inputting continuous driving days, changes in vehicle type, and the number of times the user successfully traversed the current scenario into the reaction ability prediction model yields adaptation parameters. The target driving ability level can be obtained using both reaction ability parameters and adaptation parameters.

[0135] Understandably, vehicle sensing devices acquire the user's current facial and behavioral information, as well as historical driving information in the target scenario. This data is then categorized to obtain reaction and adaptability parameters. This process can prepare for future driving ability level assessments.

[0136] The foregoing mainly describes the solutions provided by the embodiments of this application from a methodological perspective. To achieve the above functions, the driving strategy determination device or equipment includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0137] This application embodiment can, based on the above method, exemplarily divide the driving strategy determination device or equipment into functional modules. For example, the driving strategy determination device or equipment may include functional modules corresponding to each functional division, or two or more functions may be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. It should be noted that the module division in this application embodiment is illustrative and only represents one logical functional division; in actual implementation, there may be other division methods.

[0138] Figure 9 This is a block diagram illustrating a driving strategy determination device according to an exemplary embodiment. The driving strategy determination device is applied to a vehicle for performing... Figure 2 , Figure 3 or Figure 5 The method shown. The driving strategy determination device 900 includes: an acquisition module 901 and a processing module 902.

[0139] The acquisition module 901 is used to acquire the current reaction ability parameters and the user's adaptability parameters to the target scenario of the driving vehicle. The processing module 902 is used to process the current reaction ability parameters and adaptability parameters to obtain the user's target driving ability level. The processing module 902 is also used to determine a first driving strategy from multiple driving strategies based on the target driving ability level and the target scenario. Each driving strategy corresponds to a driving ability level and a driving scenario. The driving strategy reflects the degree of protection during the driving process, and the driving ability level is negatively correlated with the degree of protection reflected by the driving strategy.

[0140] In one possible implementation, the processing module 902 is specifically configured to determine a second driving strategy corresponding to the target scenario from multiple driving strategies based on the target scenario. The processing module 902 is also configured to determine a first driving strategy from the second driving strategy based on the target driving ability level.

[0141] In one possible implementation, the driving ability level includes at least one of the following: a first level, a second level, and a third level, wherein the driving ability corresponding to the third level is greater than the driving ability corresponding to the second level, and the driving ability corresponding to the second level is greater than the driving ability corresponding to the first level. When the target scenario is a starting scenario, the second driving strategy includes: a starting type check strategy and / or a vehicle status check strategy. The processing module 902 is specifically configured to determine that the first driving strategy includes the starting type check strategy and the vehicle status check strategy if the target driving ability level is the first level or the second level. The processing module 902 is further configured to determine that the first driving strategy includes the vehicle status check strategy if the target driving ability level is the third level.

[0142] In one possible implementation, processing module 902 is specifically configured to generate a check result indicating whether a problem exists in the vehicle during a start-up scenario. Processing module 902 is further configured to, if the check result indicates a problem in the vehicle during a start-up scenario and the target driving ability level is Level 1, not execute a start-up event in response to a start-up operation on the vehicle. Processing module 902 is further configured to, if the check result indicates a problem in the vehicle during a start-up scenario and the target driving ability level is Level 1, execute a start-up event in response to a start-up operation on the vehicle upon receiving an unlock command. Processing module 902 is further configured to, if the check result indicates a problem in the vehicle during a start-up scenario and the target driving ability level is Level 2 or Level 3, execute a start-up event in response to a start-up operation on the vehicle.

[0143] In one possible implementation, when the target scenario is a driving scenario, the second driving strategy includes: if the target distance between the vehicle and the adjacent vehicle is less than or equal to a first distance threshold, then setting the vehicle's acceleration to be less than an acceleration threshold; if the target distance is less than or equal to a second distance threshold, then executing a braking event. The first distance threshold is greater than the second distance threshold, and both the first and second distance thresholds are negatively correlated with the driving ability level, while the acceleration threshold is positively correlated with the driving ability level.

[0144] In one possible implementation, the acquisition module 901 is specifically used to acquire the user's current facial information and current behavior information, as well as historical driving information in the target scenario. The processing module 902 is further used to input the current facial information and current behavior information into the reaction ability prediction model to obtain current reaction ability parameters. The processing module 902 is also used to input the historical driving information into the adaptive ability prediction model to obtain adaptive ability parameters.

[0145] Regarding the apparatus in the above embodiments, the specific manner in which each unit performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0146] Figure 10 This is a block diagram illustrating an electronic device according to an exemplary embodiment. Figure 10 As shown, the electronic device 1000 includes, but is not limited to, a processor 1001 and a memory 1002.

[0147] The memory 1002 described above is used to store the executable instructions of the processor 1001. It is understood that the processor 1001 is configured to execute instructions to implement the driving strategy determination method in the above embodiments.

[0148] It should be noted that those skilled in the art will understand that Figure 10 The electronic device structure shown does not constitute a limitation on the electronic device; the electronic device may include, but is not limited to, other electronic devices. Figure 10 This may indicate more or fewer components, or combinations of certain components, or different component arrangements.

[0149] The processor 1001 is the control center of the electronic device. It connects various parts of the electronic device via various interfaces and lines. By running or executing software programs and / or modules stored in the memory 1002, and by calling data stored in the memory 1002, it performs various functions and processes data, thereby providing overall monitoring of the electronic device. The processor 1001 may include one or more processing units. Optionally, the processor 1001 may integrate an application processor and a modem processor. The application processor mainly handles the operating system, user interface, and applications, while the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 1001.

[0150] The memory 1002 can be used to store software programs and various data. The memory 1002 may mainly include a program storage area and a data storage area, wherein the program storage area may store the operating system, application programs (such as processing units) required by at least one functional module, etc. In addition, the memory 1002 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0151] In an exemplary embodiment, a computer-readable storage medium including instructions is also provided, such as a memory 1002 including instructions, which can be executed by a processor 1001 of an electronic device 1000 to implement the method for determining the driving strategy in the above embodiments.

[0152] In actual implementation, Figure 9 The functions of the acquisition module 901 and the processing module 902 can both be provided by Figure 10 The processor 1001 calls the computer program stored in the memory 1002 to implement the process. The specific execution process can be found in the description of the driving strategy determination method section of the previous embodiment, and will not be repeated here.

[0153] Optionally, the computer-readable storage medium may be a non-transitory computer-readable storage medium, such as a read-only memory (ROM), a random access memory (RAM), a CD-ROM, magnetic tape, a floppy disk, and an optical data storage device.

[0154] In an exemplary embodiment, this application also provides a computer program product including one or more instructions, which can be executed by a processor of an electronic device to complete the method for determining the driving strategy in the above embodiments.

[0155] It should be noted that when one or more instructions in the computer-readable storage medium or computer program product are executed by the processor of an electronic device, they implement the various processes of the above-described method for determining the driving strategy and achieve the same technical effect as the above-described method for determining the driving strategy. To avoid repetition, these will not be repeated here.

[0156] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0157] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another apparatus, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0158] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units; that is, it can be located in one place or distributed in multiple different locations. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0159] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0160] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, essentially, or the parts that contribute to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0161] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for determining a driving strategy, characterized in that, Applied to vehicles, the method includes: Obtain the current reaction ability parameters of the user driving the vehicle and the user's adaptability parameters to the target scenario; The current reaction capability parameter and the adaptation capability parameter are processed to obtain the user's target driving capability level; Based on the target driving ability level and the target scenario, a first driving strategy is determined from multiple driving strategies. Each driving strategy corresponds to a driving ability level and a driving scenario. The driving strategy is used to reflect the degree of protection during the driving process, and the driving ability level is negatively correlated with the degree of protection reflected by the driving strategy.

2. The method according to claim 1, characterized in that, The step of determining a first driving strategy from multiple driving strategies based on the target driving ability level and the target scenario includes: Based on the target scenario, a second driving strategy corresponding to the target scenario is determined from the plurality of driving strategies; Based on the target driving ability level, the first driving strategy is determined from the second driving strategy.

3. The method according to claim 2, characterized in that, When the target scenario is a driving scenario, the second driving strategy includes: if the target distance between the vehicle and the adjacent vehicle is less than or equal to a first distance threshold, then setting the acceleration of the vehicle to be less than an acceleration threshold; if the target distance is less than or equal to a second distance threshold, then executing a braking event, wherein the first distance threshold is greater than the second distance threshold. The first distance threshold and the second distance threshold are negatively correlated with the driving ability level, while the acceleration threshold is positively correlated with the driving ability level.

4. The method according to claim 2 or 3, characterized in that, The driving ability level includes at least one of the following: a first level, a second level, and a third level, wherein the driving ability corresponding to the third level is greater than the driving ability corresponding to the second level, and the driving ability corresponding to the second level is greater than the driving ability corresponding to the first level. When the target scenario is a starting scenario, the second driving strategy includes: a starting type check strategy and / or a vehicle status check strategy; Determining the first driving strategy from the second driving strategy based on the target driving ability level includes: If the target driving ability level is the first level or the second level, then the first driving strategy is determined to include a start-up type check strategy and a vehicle status check strategy. If the target driving ability level is the third level, then the first driving strategy is determined to include a vehicle status check strategy.

5. The method according to claim 4, characterized in that, The method further includes: Generate inspection results, which are used to indicate whether the vehicle has a problem in the starting scenario; If the inspection result indicates that the vehicle has a problem in the starting scenario, and the target driving ability level is the first level, then in response to the starting operation of the vehicle, the starting event is not executed; If the inspection result indicates that the vehicle has a problem in the starting scenario, and the target driving ability level is the first level, then upon receiving an unlock command, in response to the starting operation of the vehicle, a starting event is executed; If the inspection result indicates that the vehicle has a problem in the starting scenario, and the target driving ability level is the second level or the third level, then in response to the starting operation of the vehicle, a starting event is executed.

6. The method according to any one of claims 1-3, characterized in that, The acquisition of the user's current reaction ability parameters and the user's adaptability parameters to the target scenario includes: Obtain the user's current facial information and current behavior information, as well as historical driving information in the target scene; The current facial information and the current behavioral information are input into the reaction ability prediction model to obtain the current reaction ability parameters; The historical driving information is input into the adaptive capability prediction model to obtain the adaptive capability parameters.

7. A device for determining a driving strategy, characterized in that, Applied to vehicles, the device includes: The acquisition module is used to acquire the current reaction ability parameters of the user driving the vehicle and the user's adaptability parameters to the target scenario; The processing module is used to process the current reaction capability parameters and the adaptation capability parameters to obtain the user's target driving capability level; The processing module is further configured to determine a first driving strategy from multiple driving strategies based on the target driving ability level and the target scenario. Each driving strategy corresponds to a driving ability level and a driving scenario. The driving strategy is used to reflect the degree of protection during the driving process, and the driving ability level is negatively correlated with the degree of protection reflected by the driving strategy.

8. An electronic device, characterized in that, include: processor; A memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, When the computer-executable instructions stored in the computer-readable storage medium are executed by the processor of the electronic device, the electronic device is capable of performing the method as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, The computer program product includes computer program instructions that, when executed, implement the method as described in any one of claims 1 to 6.

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