Methods for generating driving and riding behavior habit tables, intelligent driving control methods and systems

Abstract

This invention provides a method for generating a driving and riding behavior habit table, an intelligent driving control method, and a system. The method for generating the driving and riding behavior habit table includes the following steps: acquiring the current vehicle's usage status data based on the completion of each driving trip; classifying multiple usage status data according to each group of drivers and passengers to obtain at least one driving parameter group and a corresponding non-driving parameter group for each group; establishing a temporary driving and riding behavior mapping table based on the mapping relationship between each group of drivers and passengers, the driving parameter group, and the non-driving parameter group; generating a blank driving and riding behavior habit table, which contains the same parameter columns as the temporary driving and riding behavior mapping table; and updating the driving and riding behavior habit table using data from the temporary driving and riding behavior mapping table based on preset conditions. This invention can improve vehicle usage efficiency, protect user data privacy, and enhance user driving safety.

Description

Technical Field

[0001] This invention relates to the field of intelligent driving, and more specifically, to a method for generating a driving behavior habit table, an intelligent driving control method, and a system. Background Technology

[0002] With the continuous development of automotive technology, future vehicles will evolve towards digitalization, intelligence, and personalization. As automotive technology advances and becomes more widespread, and basic vehicle performance, safety, and comfort are met, users also desire easier access to and use of their preferred personalized features. Currently, the ability to automatically adjust driving parameters and onboard equipment based on the combination of all occupants is not yet fully developed.

[0003] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of the present invention, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0004] In view of this, the present invention provides a method for generating a driving behavior habit table, an intelligent driving control method, and a system to at least solve the above-mentioned problems.

[0005] One aspect of the present invention provides a method for generating a driving and riding behavior habit table, comprising the following steps:

[0006] Based on the completion of each driving trip of the current vehicle, the current vehicle usage status data is obtained. The usage status data includes the personal information, driving information and non-driving information of all drivers and passengers in each driving trip.

[0007] The multiple usage status data are categorized according to each driver and passenger group to obtain at least one driving parameter group and a non-driving parameter group corresponding to each driving parameter group.

[0008] A temporary driving behavior mapping table is established based on the mapping relationship between each of the driver / passenger groups, the driving parameter groups, and the non-driving parameter groups;

[0009] Generate a blank driving behavior habit table, wherein the driving behavior habit table contains the same parameter columns as the temporary driving behavior mapping table; and

[0010] Based on meeting preset conditions, the driving behavior habit table is updated using data from the temporary driving behavior mapping table.

[0011] In some embodiments, updating the driving behavior habit table using data from the temporary driving behavior mapping table based on meeting preset conditions includes the following steps:

[0012] If the number of identical usage status data exceeds a preset value, the data in the temporary driving behavior mapping table with the same group of drivers and passengers will be compared with the data in the driving behavior habit table.

[0013] When the comparison result meets the first preset condition, the existing data in the driving behavior habit table is updated using the usage status data in the temporary driving behavior mapping table; and

[0014] When the comparison result meets the second preset condition, the usage status data in the temporary driving behavior mapping table is used to add new data to the driving behavior habit table.

[0015] In some embodiments, the first preset condition is that the starting location, starting time, and arrival location in the driving information of the temporary driving behavior mapping table are exactly the same as the parameters in a certain driving parameter group in the driving behavior habit table within a preset range.

[0016] In some embodiments, the second preset condition is that the starting location, starting time, and arrival location in the driving information of the temporary driving behavior mapping table are different from at least one of the parameters of any driving parameter group in the driving behavior habit table within a preset range.

[0017] In some embodiments, obtaining the current vehicle usage status data based on the completion of each driving trip of the current vehicle includes the following steps:

[0018] Based on the completion of each driving trip of the current vehicle, a request is sent to whether to save the usage status data of this driving trip, in order to confirm whether this driving trip is used to generate the driving behavior habit table;

[0019] Based on the confirmation information received from the driver / passenger in the driver's seat, the usage status data of this driving trip is saved to the current vehicle's storage module;

[0020] The usage status data is obtained from the storage module of the current vehicle.

[0021] In some embodiments,

[0022] The personal information of the drivers and passengers includes identity information;

[0023] The driving information includes at least the starting point, starting time, arrival point, arrival time, driving route, parking location, vehicle speed, and engine speed for each driving trip of the current vehicle;

[0024] The non-driving information includes at least the window settings, air conditioning settings, lighting settings, music settings, and radio settings for each driving trip of the current vehicle.

[0025] In some embodiments, each driving parameter group corresponds to a driving task, and the driving task includes at least: going to work, leaving get off work, going to school, leaving school, and going on a trip.

[0026] In some embodiments, the temporary driving behavior mapping table further includes a count flag to indicate the number of each identical driving task;

[0027] If the value of the number of times the driving task is less than a preset value within a preset time period, the usage status data corresponding to the driving task will be deleted from the temporary driving behavior mapping table.

[0028] In some embodiments, the usage status data, the temporary driving behavior mapping table, and the driving behavior habit table are encrypted and stored in the current vehicle's memory.

[0029] In some embodiments, the identity information of the driver or passenger is obtained by at least one or more of the following methods: fingerprint lock recognition, camera photo recognition, or iris recognition.

[0030] Another aspect of the present invention provides an intelligent driving control method, comprising the following steps:

[0031] Generating a driving and riding behavior habit table specifically includes: acquiring the current vehicle's usage status data based on the completion of each driving trip, the usage status data including personal information, driving information, and non-driving information of all drivers and passengers in each driving trip; classifying multiple usage status data according to each driver and passenger group to obtain at least one driving parameter group and a corresponding non-driving parameter group for each driver and passenger group; establishing a temporary driving and riding behavior mapping table based on the mapping relationship between each driver and passenger group, the driving parameter group, and the non-driving parameter group; generating a blank driving and riding behavior habit table, the driving and riding behavior habit table containing the same parameter columns as the temporary driving and riding behavior mapping table; and updating the driving and riding behavior habit table using data from the temporary driving and riding behavior mapping table based on meeting preset conditions.

[0032] The system detects the identity information and driving information of each driver and passenger in the current driving trip, matches them with the driver and passenger groups and driving parameter groups in the driving behavior habit table, and updates the current vehicle usage status based on the driving parameter groups and non-driving parameter groups that meet the matching conditions.

[0033] In some embodiments, detecting the identity information and driving information of each driver / passenger in the current driving trip, matching them with the driver / passenger group and driving parameter group in the driving behavior habit table, and updating the current vehicle usage status based on the driving parameter group and non-driving parameter group that meet the matching conditions includes the following steps:

[0034] Detect the identity information and driving information of each of the drivers and passengers in the current driving trip, wherein the driving information includes at least the starting point, starting time, and arrival point;

[0035] Match the above information with the driver / passenger group and driving parameter group in the driving behavior habit table;

[0036] When the matching conditions are met, a request is sent to determine whether to update the current vehicle usage status based on the driving behavior habit table.

[0037] Based on the confirmation information received from the driver / passenger located in the driver's seat, the usage status data is obtained from the driving / passenger behavior habit table; and

[0038] The current vehicle usage status is updated based on the driving parameter group and the non-driving parameter group that meet the matching conditions.

[0039] In some embodiments, after the current vehicle travels to the destination according to the driving behavior habit table, it parks at the parking location in the driving behavior habit table.

[0040] In some embodiments, the intelligent driving control method further includes the following steps:

[0041] When a preset abnormal situation is detected during the execution of the driving trip, an abnormality alert message is sent to all the drivers and passengers.

[0042] If no feedback is received from any of the drivers or passengers within a preset time, the abnormality alert message is sent to the emergency contact person in the driver's or passenger's personal information.

[0043] In some embodiments, the intelligent driving control method further includes the following steps:

[0044] The delay time of the current driving trip is obtained based on the driving information and the average time of the driving path progress in the corresponding usage status data.

[0045] Collect and sort the latency times of other vehicles traveling on the same route, and allocate higher access privileges to vehicles with higher latency times; and

[0046] Based on the level of permission parameters, plan the overtaking route for the vehicle with the largest delay among several vehicles traveling on the same road.

[0047] Another aspect of the present invention provides an intelligent driving control system for implementing the above-described intelligent driving control method, comprising:

[0048] The habit generation module generates a driving and riding behavior habit table, specifically including: acquiring the current vehicle's usage status data based on the completion of each driving trip, the usage status data including personal information, driving information, and non-driving information of all drivers and passengers in each driving trip; classifying multiple usage status data according to each driver and passenger group to obtain at least one driving parameter group and a corresponding non-driving parameter group for each driver and passenger group; establishing a temporary driving and riding behavior mapping table based on the mapping relationship between each driver and passenger group, the driving parameter group, and the non-driving parameter group; generating a blank driving and riding behavior habit table, the driving and riding behavior habit table containing the same parameter columns as the temporary driving and riding behavior mapping table; and updating the driving and riding behavior habit table using data from the temporary driving and riding behavior mapping table based on meeting preset conditions.

[0049] The driving execution module detects the identity information and driving information of each driver and passenger in the current driving trip, matches them with the driver and passenger groups and driving parameter groups in the driving behavior habit table, and updates the current vehicle usage status based on the driving parameter groups and non-driving parameter groups that meet the matching conditions.

[0050] The beneficial effects of this invention compared to the prior art include at least the following:

[0051] The driving behavior habit table generation method, intelligent driving control method, and system of the present invention generate and maintain a driving behavior habit table to understand the current driving habits of vehicle users and the personalized settings of in-vehicle equipment, avoiding repeated settings during each driving trip and improving the user's vehicle usage efficiency; at the same time, the above driving information is encrypted and stored to protect the user's data privacy; and preventive plans are also formulated for unexpected situations during driving to improve the user's driving safety.

[0052] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Attached Figure Description

[0053] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention. It is obvious that the drawings described below are merely some embodiments of the invention, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0054] Methods for generating driving and riding behavior habit tables, intelligent driving control methods and systems

[0055] Figure 1 A flowchart illustrating a method for generating a driving behavior habit table according to the present invention is shown;

[0056] Figure 2 Show Figure 1 A flowchart of the sub-steps of step S110;

[0057] Figure 3 Show Figure 1 A flowchart of the sub-steps of step S150;

[0058] Figure 4 A flowchart of an intelligent driving control method according to the present invention is shown;

[0059] Figure 5 Show Figure 4 A flowchart of the sub-steps of step S220;

[0060] Figure 6 Show Figure 4 A flowchart of a subsequent step in the intelligent driving control method;

[0061] Figure 7 Show Figure 4 A flowchart of another subsequent step in the intelligent driving control method;

[0062] Figure 8 A schematic diagram of a module of an intelligent driving control system according to the present invention is shown;

[0063] Figure 9 This diagram illustrates the structure of an intelligent driving control device according to the present invention.

[0064] Figure 10 A schematic diagram of the structure of a computer-readable storage medium according to the present invention is shown. Detailed Implementation

[0065] To make the advantages, spirit, and features of the present invention easier and clearer to understand, detailed descriptions and discussions will follow with reference to specific embodiments and the accompanying drawings. It is important to note that these specific embodiments are merely representative examples of the present invention, and the specific methods, apparatuses, conditions, materials, etc., exemplified are not intended to limit the present invention or the corresponding specific embodiments. Furthermore, the devices in the figures are only used to illustrate their relative positions and are not drawn to scale; this is to be stated beforehand.

[0066] In the description of this specification, references to terms such as "one specific embodiment," "another specific embodiment," or "partial specific embodiment," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment is included in at least one embodiment of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments.

[0067] In various embodiments of the invention, the expression "or" includes any or all combinations of the words listed simultaneously. For example, the expression "A or B" may include A, may include B, or may include both A and B. Furthermore, the indefinite articles "a," "an," and "an" preceding the means or elements of the invention are not restrictive in terms of the number of means or elements (i.e., the number of times they appear). Therefore, "a" should be interpreted as including one or at least one, and singular means or elements also include plural forms, unless the quantity clearly refers to the singular form.

[0068] Through meticulous and in-depth research, the inventors in this case have provided a solution to the problems existing in the prior art. Figure 1 A flowchart illustrating a method for generating a driving behavior habit table according to the present invention is shown. Figure 4 A flowchart of an intelligent driving control method according to the present invention is shown. Figure 8 This diagram illustrates a module schematic of an intelligent driving control system according to the present invention. (For example...) Figure 1 , 4As shown in Figure 8, this invention discloses a method for generating a driving and riding behavior habit table, an intelligent driving control method, and a system. The method for generating the driving and riding behavior habit table includes the following steps: S110, acquiring the current vehicle's usage status data based on the completion of each driving trip, including personal information, driving information, and non-driving information of all drivers and passengers in each driving trip; S120, classifying multiple usage status data according to each driver and passenger group to obtain at least one driving parameter group and a corresponding non-driving parameter group for each driver and passenger group; S130, establishing a temporary driving and riding behavior mapping table based on the mapping relationship between each driver and passenger group, driving parameter group, and non-driving parameter group; S140, generating a blank driving and riding behavior habit table, which contains the same parameter columns as the temporary driving and riding behavior mapping table; and S150, updating the driving and riding behavior habit table using data from the temporary driving and riding behavior mapping table based on met preset conditions. The driving behavior habit table generation method, intelligent driving control method, and system of the present invention generate and maintain a driving behavior habit table to understand the current driving habits of vehicle users and the personalized settings of in-vehicle equipment, avoiding repeated settings during each driving trip and improving the user's vehicle usage efficiency; at the same time, the above driving information is encrypted and stored to protect the user's data privacy; and preventive plans are also formulated for unexpected situations during driving to improve the user's driving safety.

[0069] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0070] like Figure 1 As shown, one aspect of the present invention provides a method for generating a driving behavior habit table, comprising the following steps:

[0071] S110. Based on the completion of each driving trip of the current vehicle, obtain the current vehicle usage status data, which includes the personal information, driving information and non-driving information of all drivers and passengers in each driving trip;

[0072] S120. Classify multiple usage status data according to each driver and passenger group to obtain at least one driving parameter group and a non-driving parameter group corresponding to each driving parameter group.

[0073] S130. Establish a temporary driving behavior mapping table based on the mapping relationship between each driver / passenger group, driving parameter group, and non-driving parameter group.

[0074] S140. Generate a blank driving behavior habit table, which contains the same parameter columns as the temporary driving behavior mapping table; and

[0075] S150. Based on meeting preset conditions, update the driving behavior habit table using data from the temporary driving behavior mapping table.

[0076] It is worth noting that S110 to S150 are merely step numbers, used for ease of reference and to avoid word repetition, rather than restricting the order of implementation of the steps in this method. In other embodiments, the order of the above steps in this method can also be interchanged, and this is not a limitation. Subsequent step numbers in this invention all have the same meaning, and repeated details will not be elaborated upon.

[0077] Figure 2 Show Figure 1 A flowchart of the sub-steps of step S110. In some embodiments, such as Figure 2 As shown, step S110 includes the following steps:

[0078] S111. Based on the completion of each driving trip of the current vehicle, send a request to whether to save the usage status data of this driving trip, in order to confirm whether this driving trip is used to generate a driving behavior habit table;

[0079] S112. Based on the confirmation information received from the driver or passenger in the driver's seat, save the usage status data of this driving trip to the current vehicle's storage module.

[0080] S113. Obtain usage status data from the current vehicle's storage module.

[0081] In steps S111 to S113, to generate a user's driving behavior habit table, the vehicle records usage status data for each completed trip. However, users do not necessarily want their vehicle usage data to be used to analyze their driving habits every time, such as occasional use like long-distance inter-provincial road trips, or private use that they do not want others to know. Therefore, each time the vehicle wants to save the user's usage status data for a particular trip, it needs the user's consent. Only after the user's consent can the vehicle save the data. The user's consent to save the aforementioned usage status data means that the user wants to use this data to generate a driving behavior habit table. Subsequent times when the vehicle accesses the aforementioned usage status data, the user's permission is not required again. The vehicle usage status data for each trip includes three parts: personal information of all passengers, driving information, and non-driving information.

[0082] The personal information of drivers and passengers includes identity information used to uniquely identify each individual. It's important to note that drivers and passengers include not only the driver but also the individuals who ride in the vehicle during the trip. Different combinations of drivers and passengers may correspond to different vehicle uses, making the analysis of driving and passenger behavior habits crucial. Obtaining the identity information of drivers and passengers can be achieved using at least one or more of the following methods in combination: fingerprint lock recognition, camera image recognition, or iris recognition. Specifically, fingerprint lock recognition or iris recognition can be used to identify the driver, while the identities of passengers can be identified by taking photos taken by one or more cameras installed inside the vehicle.

[0083] Driving information refers to information directly related to vehicle movement during each trip, including at least the origin, start time, destination, arrival time, route, parking location, vehicle speed, and engine speed. Location-related data can be obtained through any one or more GNSS (Global Navigation Satellite System) positioning systems. GNSS includes the US GPS (Global Positioning System), Russia's GLONASS, Europe's Galileo, and China's BeiDou Navigation Satellite System. Vehicle speed and engine speed can be directly recorded from the data displayed on the car's dashboard.

[0084] Non-driving information refers to the personalized configuration of the in-vehicle environment for each trip, including at least the window settings, air conditioning settings, lighting settings, music settings, and radio settings for each driving trip. This data can also be captured by the vehicle's system.

[0085] In some embodiments, each driving parameter group corresponds to a driving task. Specifically, each group of drivers and passengers can correspond to multiple driving parameter groups, meaning the same drivers and passengers use the car for different purposes, i.e., multiple driving tasks. Driving tasks include at least: going to work, going home, going to school, going home, and traveling. For example, in the cases of parents taking their child to school and parents taking their child on a trip, the drivers and passengers are the same, but their driving parameter groups are different, i.e., the starting location, starting time, and arrival location are different. Therefore, they are judged as different driving tasks, and naturally correspond to different non-driving information.

[0086] The following examples illustrate that different drivers and passengers have different preferences for vehicle personalization features. For instance, young people may enjoy spirited driving and adjust more driving parameters, preferring dynamic music and lower air conditioning temperatures. Older adults may prefer gentle driving, adjusting driving parameters less and liking soothing music, turning off the air conditioning, opening windows for ventilation, and adjusting the seat back for massage and lumbar support. When there are infants or other passengers resting in the car, gentle driving is needed, requiring fewer adjustments to driving parameters, and personalization features such as turning off music and ambient lighting, turning on the air purifier, and activating active noise cancellation are preferred. Based on these examples, it can be seen that different drivers and passengers can have different non-driving information, i.e., different personalization settings, for the same driving task.

[0087] The following examples illustrate that the same driver and passengers may have relatively fixed driving modes and personalized configuration needs for specific trips during specific time periods. For instance, when commuting to work, drivers and passengers are usually in a hurry, so the vehicle speed and engine speed are relatively high. Upon arrival at the parking spot, the car automatically parks, and uplifting music plays throughout the journey. When leaving get off work, traffic jams are common, and drivers and passengers are often irritable. During maneuvers such as following other vehicles and changing lanes, the driver assistance system can intervene, while soothing music plays and the seat massage function is activated. On weekend family trips, because there are children, the vehicle needs to be driven smoothly, and the speed and engine speed should not be too high. Upon arrival at the parking spot, the car automatically parks, and upbeat music or children's songs can be played, with the sunroof slightly opened for ventilation. When taking children to training classes, because there are children, the vehicle needs to be driven smoothly, and upon arrival at the parking spot, the car automatically parks, and cartoons can be played. Based on the above, it can be seen that the same driver and passengers can correspond to multiple driving parameter groups, i.e., multiple driving tasks. The same driving task usually has the same non-driving information, i.e., the same personalized configuration, but it can also have multiple personalized configurations.

[0088] In some embodiments, in step S130, the temporary driving behavior mapping table further includes a frequency flag to indicate the number of times each identical driving task occurs. When the frequency flag value of a driving task is less than a preset value within a preset time period, the usage status data corresponding to the driving task is deleted from the temporary driving behavior mapping table. The magnitude of the frequency flag value over a period of time is mainly used to characterize the frequency of occurrence of the driving task. Even if drivers and passengers agree to include some low-frequency vehicle usage status data in the data source for driving behavior habit analysis, it is still unsuitable as analysis data due to its low frequency of occurrence. Therefore, a frequency flag is added to the temporary driving behavior mapping table to exclude these low-frequency driving behaviors and add high-frequency driving behaviors to the driving behavior habit table.

[0089] Figure 3 Show Figure 1 A flowchart of the sub-steps of step S150. In some embodiments, such as Figure 3As shown, step S150 includes the following sub-steps:

[0090] S151. Based on the fact that the number of identical usage status data exceeds a preset value, compare the data in the temporary driving behavior mapping table with the driving behavior habit table for the same group of drivers and passengers.

[0091] S152. When the comparison result meets the first preset condition, the existing data in the driving behavior habit table is updated using the usage status data in the temporary driving behavior mapping table; and

[0092] S153. When the comparison result meets the second preset condition, the usage status data in the temporary driving behavior mapping table is used to add new data to the driving behavior habit table.

[0093] The purpose of step S150 is to generate and maintain a driving behavior habit table using data from a temporary driving behavior mapping table under certain conditions. Specifically, it requires data from the temporary driving behavior mapping table where the number of identical driving behaviors has reached a certain requirement; only then can it be considered a habit. There are at least two ways to generate and maintain this table: the first is to modify the corresponding data in the driving behavior habit table using data from the temporary driving behavior mapping table; the second is to add data from the temporary driving behavior mapping table to the driving behavior habit table. The first method requires meeting a first preset condition, and the second method requires meeting a second preset condition. In both cases, the data being compared must be data from the same group of drivers / passengers.

[0094] In some embodiments, the first preset condition is that the starting location, starting time, and arrival location in the driving information of the temporary driving behavior mapping table are exactly the same as the aforementioned parameters in a certain driving parameter group in the driving behavior habit table within a preset range. The purpose of the first preset condition is to identify the same driving task. The fact that the starting location, starting time, and arrival location are all the same generally indicates the same task. For example, if the driver and passenger group consists of three people (parents and child), the starting location is always home, the starting time is always between 7:00 AM and 7:20 AM, and the arrival location is always school, then it can be determined that the task is taking the child to school. After determining that it is the same driving task, it can be found that other data in the temporary driving behavior mapping table are different from the corresponding data in the driving behavior habit table, indicating that the user's driving habits have changed, and therefore the driving behavior habit table needs to be updated. It is worth noting that the starting location, starting time, and arrival location are all within a range. Due to errors in the positioning data and slight differences in the starting time, setting it to a range is sufficient; they do not need to be exactly the same. Of course, the first preset condition is not limited to the above; arrival time, driving route, and parking location data can also be added for more accurate judgment.

[0095] In some embodiments, the second preset condition is that the starting location, starting time, and arrival location in the driving information of the temporary driving behavior mapping table are at least one different from the aforementioned parameters of any driving parameter group in the driving behavior habit table within a preset range. The purpose of the second preset condition is to identify different driving tasks. The starting location, starting time, and arrival location can roughly distinguish different driving tasks. For example, parents taking their children to school and parents taking their children on a weekend trip both have the same group of drivers and passengers, and the starting location and starting time may be the same, but the arrival locations are different, thus they can be identified as different tasks. After determining that they are different driving tasks, it can be found that the user has formed a new driving habit, so this new driving habit needs to be added to the driving behavior habit table. It is worth noting that the starting location, starting time, and arrival location are also within a range. Of course, the second preset condition is not limited to the above; arrival time, driving route, and parking location data can also be added for more accurate judgment.

[0096] In other embodiments, when the number of identical usage status data in the temporary driving behavior mapping table exceeds a preset value, and none of these data belongs to the same driver / passenger group as any item in the driving behavior habit table, the aforementioned usage status data is directly added to the driving behavior habit table. This occurs when a new driver / passenger group has emerged, for example, the vehicle was originally used by a family of three but is now used by three generations (five people), or it may be used by a single user after marriage for two people. The emergence of a new driver / passenger group forms a new habit, therefore it also needs to be added to the driving behavior habit table.

[0097] In some embodiments, state data, temporary driving behavior mapping tables, and driving behavior habit tables are encrypted and stored in the current vehicle's memory. All of the above data involves user privacy, is stored and processed locally within the vehicle, is not transmitted externally, and is stored in encrypted form to ensure user privacy.

[0098] The method for generating a driving and riding behavior habit table of the present invention generates and maintains a driving and riding behavior habit table to understand the current driving habits of vehicle users and the personalized settings of in-vehicle equipment, avoiding repeated settings during each driving and riding, thereby improving the user's efficiency in using the vehicle; at the same time, all the above driving and riding information is encrypted and stored to protect the user's data privacy.

[0099] Based on the same inventive concept, such as Figure 4 As shown, another aspect of the present invention provides an intelligent driving control method, comprising the following steps:

[0100] S210. Generate a driving and riding behavior habit table, specifically including: based on the completion of each driving trip of the current vehicle, obtain the current vehicle usage status data, which includes the personal information, driving information, and non-driving information of all drivers and passengers in each driving trip; classify multiple usage status data according to each driver and passenger group to obtain at least one driving parameter group and a corresponding non-driving parameter group for each driver and passenger group; establish a temporary driving and riding behavior mapping table according to the mapping relationship between each driver and passenger group, driving parameter group, and non-driving parameter group; generate a blank driving and riding behavior habit table, which contains the same parameter columns as the temporary driving and riding behavior mapping table; and update the driving and riding behavior habit table using the data in the temporary driving and riding behavior mapping table based on the conditions met.

[0101] S220: Detect the identity information and driving information of each driver and passenger in the current driving trip, match them with the driver and passenger groups and driving parameter groups in the driving behavior habit table, and update the current vehicle usage status based on the driving parameter groups and non-driving parameter groups that meet the matching conditions.

[0102] For step S210, which uses the method described above for generating the driving and riding behavior habit table, please refer to the above content for details.

[0103] Figure 5 Show Figure 4 A flowchart of the sub-steps of step S220. (e.g.) Figure 5 As shown, in some embodiments, step S220 includes the following sub-steps:

[0104] S221. Detect the identity information and driving information of each driver and passenger in the current driving trip, wherein the driving information includes at least the starting point, starting time and destination;

[0105] S222. Match the above information with the driver and passenger group and driving parameter group in the driving behavior habit table;

[0106] S223. When the matching conditions are met, send a request to whether to update the current vehicle usage status based on the driving behavior habit table;

[0107] S224. Based on receiving confirmation information from the driver / passenger in the driver's seat, obtain usage status data from the driving / passenger behavior habit table; and

[0108] S225. Update the current vehicle usage status based on the driving parameter group and non-driving parameter group that meet the matching conditions.

[0109] In step S211, the identity information and starting and ending points of each driver / passenger's driving information are used as criteria to identify the same driving task for the same group of drivers / passengers. In step S213, even if the same driving task is detected, the vehicle does not automatically use this habit; user consent is required. This step is necessary because the vehicle's prediction may be incorrect, the user may have generated a completely new driving task, or the user may simply wish to drive autonomously without assistance. In step S214, only after user consent can assisted driving be performed according to the driving / passenger behavior habit table.

[0110] In some embodiments, after the vehicle travels to its destination according to a driving behavior habit table, it parks at the parking location specified in the table. Parking is very difficult for many drivers with limited experience. This invention allows for the automatic parking of vehicles by setting parking locations at the corresponding destinations, thereby further improving vehicle efficiency and reducing driving difficulty.

[0111] Figure 6 Show Figure 4 A flowchart of a subsequent step in the intelligent driving control method. In some embodiments, such as Figure 6 As shown, the above-mentioned intelligent driving control method may further include the following steps:

[0112] S230. When a preset abnormal situation is detected during the execution of a driving trip, an abnormality reminder message is sent to all drivers and passengers.

[0113] S240. If no feedback is received from any driver or passenger within a preset time, send an abnormality alert to the emergency contact person in the driver's or passenger's personal information.

[0114] Regarding step S230, unexpected events are inevitable during driving. In such cases, the vehicle needs to develop a preventative plan and notify the user. For example, in extreme situations such as traffic jams, icy roads, or heavy fog, the vehicle can replan the driving route and adjust vehicle parameters based on acceleration, temperature, humidity, and light sensors, such as playing music, closing windows, turning on fog lights, and raising the temperature. This alert information will then be sent to all passengers. Regarding step S240, if all passengers do not respond, a more serious situation may have occurred, or even if the user has been in an accident and is unable to respond. In this case, an alert can be sent to emergency contacts, or even the police can be called, to ensure user safety. Furthermore, if the user lives in a mountainous area, at a high latitude, or during winter, where these specific climatic conditions are frequent, the preventative plan can be added to the driving behavior habit log for future responses.

[0115] Figure 7 Show Figure 4A flowchart of another subsequent step in the intelligent driving control method. In some embodiments, such as Figure 7 As shown, the above-mentioned intelligent driving control method may further include the following steps:

[0116] S250. Based on the average time of the driving path progress in the current driving information and the corresponding usage status data, obtain the delay time of the current driving trip;

[0117] S260 collects and sorts the delay times of other vehicles traveling on the same route, allocating higher passage permission parameters to vehicles with higher delay times; and

[0118] S270. Based on the level of the permission parameters, plan the overtaking route for the vehicle with the largest delay among several vehicles traveling on the same road.

[0119] This embodiment primarily addresses the coordination problem of multiple vehicles on the same driving path. In step S250, when multiple vehicles using the intelligent driving control method of this invention appear on the same driving path at the same time, some drivers may be in a hurry, while others may be driving at a leisurely pace. If neither driver is aware of the other's situation, unsafe overtaking behavior may occur. To avoid this situation, this embodiment proposes a solution. In step S250, a method for determining if a vehicle is in a rush is provided. This involves estimating the time required for the current driving task based on past driving data, and simultaneously estimating the arrival time based on the start time of the current driving task. The estimated arrival time is compared with the latest historical arrival time. If the estimated arrival time is later, it is determined that the vehicle may be late, and a delay time is calculated. Furthermore, this delay time is updated in real time, specifically by comparing the average progress time of the driving path with the already traveled path of the current driving task to generate the current delay time in real time. In step S260, the current vehicle sorts other vehicles traveling on the same road by their delay times to determine which vehicle is in a greater hurry, thus assessing the overtaking potential of surrounding vehicles. In step S270, the vehicle with the longer delay time, i.e., the one in a greater hurry and with a higher chance of overtaking, is given priority to reduce the possibility of accidents.

[0120] The intelligent driving control method of the present invention generates and maintains a driving behavior habit table to understand the current driving habits of vehicle users and the personalized settings of in-vehicle equipment, avoiding repeated settings during each driving trip and improving the user's vehicle usage efficiency; at the same time, all the above driving information is encrypted and stored to protect the user's data privacy; and it also formulates prevention plans for unexpected situations during driving to improve the user's driving safety.

[0121] Based on the same inventive concept, such as Figure 8As shown, another aspect of the present invention provides an intelligent driving control system 50 for implementing the above-described intelligent driving control method, specifically including:

[0122] The habit generation module 51 generates a driving and riding behavior habit table, specifically including: acquiring the current vehicle's usage status data based on the completion of each driving trip, including personal information, driving information, and non-driving information of all drivers and passengers in each driving trip; classifying multiple usage status data according to each driver and passenger group to obtain at least one driving parameter group and a corresponding non-driving parameter group for each driver and passenger group; establishing a temporary driving and riding behavior mapping table based on the mapping relationship between each driver and passenger group, driving parameter group, and non-driving parameter group; generating a blank driving and riding behavior habit table, which contains the same parameter columns as the temporary driving and riding behavior mapping table; and updating the driving and riding behavior habit table using data from the temporary driving and riding behavior mapping table based on meeting preset conditions.

[0123] The driving execution module 52 detects the identity information and driving information of each driver and passenger in the current driving trip, matches them with the driver and passenger groups and driving parameter groups in the driving behavior habit table, and updates the current vehicle usage status based on the driving parameter group and non-driving parameter group that meet the matching conditions.

[0124] In some embodiments, the driving execution module 52 is configured to: detect the identity information and driving information of each occupant in the current driving trip, wherein the driving information includes at least the start location, start time, and arrival location; match the above information with occupant groups and driving parameter groups in a driving behavior habit table; when the matching conditions are met, send a request to whether to update the current vehicle usage status based on the driving behavior habit table; obtain usage status data from the driving behavior habit table based on the confirmation information received from the occupant in the driver's seat; and update the current vehicle usage status according to the driving parameter group and non-driving parameter group that meet the matching conditions.

[0125] In some embodiments, the intelligent driving control system 50 is configured to further include: an anomaly alert module 53, which sends an anomaly alert message to all drivers and passengers when a preset anomaly is detected during the execution of the driving trip; and sends an anomaly alert message to the emergency contact person in the personal information of the drivers and passengers if no feedback is received from any driver or passenger within a preset time.

[0126] In some embodiments, the intelligent driving control system 50 is configured to further include: a multi-vehicle coordination module 54, which obtains the delay time of the current driving trip based on the average time of the driving path progress in the current driving information and the corresponding usage status data; collects and sorts the delay times of other vehicles traveling on the same road, and assigns higher passage permission parameters to vehicles with higher delay times; and plans overtaking paths for vehicles with higher delay times among several vehicles traveling on the same road according to the level of permission parameters.

[0127] The intelligent driving control system of this invention generates and maintains a driving behavior habit table to understand the current vehicle user's driving habits and the personalized settings of the in-vehicle equipment, avoiding repeated settings during each driving trip and improving the user's vehicle usage efficiency; at the same time, all the above driving information is encrypted and stored to protect the user's data privacy; and it also formulates prevention plans for unexpected situations during driving to improve the user's driving safety.

[0128] Figure 9 This diagram illustrates the structure of an intelligent driving control device according to the present invention. Based on the same inventive concept, such as… Figure 9 As shown, another aspect of the present invention provides an intelligent driving control device, comprising: a processor; and a memory storing executable instructions of the processor. The processor is configured to perform steps of an intelligent driving control method by executing the executable instructions.

[0129] Those skilled in the art will understand that various aspects of the present invention can be implemented as systems, methods, or program products. Therefore, various aspects of the present invention can be specifically implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or a combination of hardware and software aspects, collectively referred to herein as a "circuit," "module," or "platform."

[0130] The following reference Figure 9 To describe an electronic device 600 according to this embodiment of the present invention. Figure 9 The electronic device 600 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0131] like Figure 9 As shown, the electronic device 600 is presented in the form of a general-purpose computing device. The components of the electronic device 600 may include, but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including storage unit 620 and processing unit 610), a display unit 640, etc.

[0132] The storage unit stores program code, which can be executed by the processing unit 610 to perform the steps described in the above-described section on the electronic prescription transfer processing method according to various exemplary embodiments of the present invention. For example, the processing unit 610 can perform actions such as... Figure 4 The steps are shown in the figure.

[0133] Storage unit 620 may include a readable medium in the form of a volatile storage unit, such as random access memory (RAM) 6201 and / or cache memory 6202, and may further include a read-only memory (ROM) 6203.

[0134] Storage unit 620 may also include a program / utility 6204 having a set (at least one) program module 6205, such program module 6205 including but not limited to: operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0135] Bus 630 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0136] Electronic device 600 can also communicate with one or more external devices 700 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 600, and / or with any device that enables electronic device 600 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 650. Furthermore, electronic device 600 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 660. Network adapter 660 can communicate with other modules of electronic device 600 via bus 630. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms.

[0137] The intelligent driving control device of the present invention generates and maintains a driving behavior habit table to understand the current driving habits of vehicle users and the personalized settings of in-vehicle equipment, avoiding repeated settings during each driving trip and improving the user's vehicle usage efficiency; at the same time, all the above driving information is encrypted and stored to protect the user's data privacy; and it also formulates prevention plans for unexpected situations during driving to improve the user's driving safety.

[0138] Figure 10 This diagram illustrates the structure of a computer-readable storage medium according to the present invention. Based on the same inventive concept, such as… Figure 10 As shown, another aspect of the present invention also provides a computer-readable storage medium for storing a program that, when executed, implements the steps of an intelligent driving control method. In some possible embodiments, various aspects of the present invention can also be implemented as a program product comprising program code that, when run on a terminal device, causes the terminal device to perform the steps described in the above-described electronic prescription processing method section of this specification according to various exemplary embodiments of the present invention.

[0139] like Figure 10 As shown, a program product 800 for implementing the above-described method according to an embodiment of the present invention is described. This product may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, the readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0140] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0141] Computer-readable storage media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable storage medium may also be any readable medium other than a readable storage medium that can transmit, propagate, or transfer a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0142] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0143] The computer-readable storage medium of the present invention generates and maintains a driving behavior habit table to understand the current vehicle user's driving habits and the personalized settings of the in-vehicle equipment, avoiding repeated settings during each driving trip and thus improving the user's vehicle usage efficiency; at the same time, all the above driving information is stored in encrypted form to protect the user's data privacy; and it also develops prevention plans for unexpected situations during driving, improving the user's driving safety.

[0144] In summary, the method for generating a driving behavior habit table, as well as the intelligent driving control method, system, device, and storage medium of the present invention, by generating and maintaining a driving behavior habit table, can grasp the current driving habits of vehicle users and the personalized settings of in-vehicle devices, avoiding repeated settings during each driving trip, thereby improving the user's vehicle usage efficiency; at the same time, all the above driving information is encrypted and stored to protect the user's data privacy; and preventive plans are also formulated for unexpected situations during driving, improving the user's driving safety.

[0145] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A method of generating a driving behavior habit table, characterized by, The method comprises the following steps: obtaining usage state data of the current vehicle based on completion of each driving trip of the current vehicle, the usage state data comprising personal information, driving information and non-driving information of all passengers in each driving trip; classifying a plurality of pieces of the usage state data according to each passenger group to obtain at least one driving parameter group of each passenger group and a non-driving parameter group corresponding to each driving parameter group; establishing a temporary driving behavior mapping table according to a mapping relationship between each passenger group, the driving parameter group and the non-driving parameter group; generating a blank driving behavior habit table, the driving behavior habit table having the same parameter columns as the temporary driving behavior mapping table; and updating the driving behavior habit table using data in the temporary driving behavior mapping table based on a preset condition, the updating of the driving behavior habit table using data in the temporary driving behavior mapping table based on the preset condition comprising the following steps: comparing the data in the temporary driving behavior mapping table and the driving behavior habit table having the same passenger group based on the number of the same usage state data exceeding a preset value; when the comparison result meets a first preset condition, updating existing data in the driving behavior habit table using the usage state data in the temporary driving behavior mapping table; and when the comparison result meets a second preset condition, adding new data in the driving behavior habit table using the usage state data in the temporary driving behavior mapping table. The first preset condition is that the starting location, starting time and arrival location in the driving information of the temporary driving behavior mapping table are completely the same as the above parameters in a certain driving parameter group in the driving behavior habit table within a preset range.

2. The method of claim 1, wherein The second preset condition is that the starting location, starting time and arrival location in the driving information of the temporary driving behavior mapping table are different from the above parameters of any driving parameter group in the driving behavior habit table within a preset range.

3. The method of claim 1, wherein The obtaining of the usage state data of the current vehicle based on completion of each driving trip of the current vehicle comprises the following steps:

4. The method of claim 1, wherein sending a request for saving the usage state data of the current driving trip to confirm whether the current driving trip is used to generate the driving behavior habit table based on completion of each driving trip of the current vehicle; saving the usage state data of the current driving trip to a storage module of the current vehicle based on receiving confirmation information of the passenger in the driver seat; obtaining the usage state data from the storage module of the current vehicle.

5. The method for generating a driving behavior habit table according to claim 1, wherein the personal information of the passenger comprises identity information; and the driving information at least comprises starting location, starting time, arrival location, arrival time, driving path, parking location, vehicle speed and engine speed of each driving trip of the current vehicle. ​ ​ ​ The non-driving information at least includes window settings, air conditioning settings, light settings, music settings and radio settings of the current vehicle for each driving trip.

6. The method of claim 1, wherein Each driving parameter group corresponds to a driving task, and the driving task at least includes going to work, leaving work, going to school, leaving school and going on a trip.

7. The method of claim 6, wherein The temporary driving behavior mapping table further includes a number flag bit, which is used to represent the number of each same driving task. When the number flag bit value of the driving task is less than a preset value within a preset time, the use state data corresponding to the driving task is deleted from the temporary driving behavior mapping table.

8. The method of claim 1, wherein The use state data, the temporary driving behavior mapping table and the driving behavior habit table are stored in the memory of the current vehicle in an encrypted manner.

9. The method of claim 1, wherein The identity information of the driver is obtained by at least one or a combination of the following modes: fingerprint lock recognition, camera shooting recognition or iris recognition.

10. An intelligent driving control method, characterized by, The method comprises the following steps: A driving behavior habit table is generated, specifically including: obtaining use state data of the current vehicle based on completion of each driving trip of the current vehicle, the use state data including personal information, driving information and non-driving information of all drivers in each driving trip; classifying a plurality of use state data according to each driver group to obtain at least one driving parameter group of each driver group and a non-driving parameter group corresponding to each driving parameter group; establishing a temporary driving behavior mapping table according to the mapping relationship between each driver group, the driving parameter group and the non-driving parameter group; generating a blank driving behavior habit table, the driving behavior habit table having the same parameter column as the temporary driving behavior mapping table; and updating the driving behavior habit table using data in the temporary driving behavior mapping table based on a preset condition; the updating of the driving behavior habit table using data in the temporary driving behavior mapping table based on the preset condition comprises the following steps: comparing the data in the temporary driving behavior mapping table and the driving behavior habit table having the same driver group based on the number of the same use state data exceeding a preset value; updating the existing data of the driving behavior habit table using the use state data in the temporary driving behavior mapping table when the comparison result meets a first preset condition; and adding new data in the driving behavior habit table using the use state data in the temporary driving behavior mapping table when the comparison result meets a second preset condition; The identity information and driving information of each driver of the current driving trip are detected, and the driver group and the driving parameter group in the driving behavior habit table are matched, and the use state of the current vehicle is updated according to the driving parameter group and the non-driving parameter group meeting the matching condition. 11.The intelligent driving control method of claim 10, wherein, The identity information and driving information of each passenger in the current driving trip are detected and matched with the passenger group and driving parameter group in the driving habit table, and the use state of the current vehicle is updated according to the driving parameter group and the non-driving parameter group that meet the matching conditions, including the following steps: Detecting the identity information and driving information of each passenger in the current driving trip, wherein the driving information includes at least starting location, starting time and arrival location; Matching the above information with the passenger group and driving parameter group in the driving habit table; When the matching condition is met, send a request whether to update the use state of the current vehicle based on the driving habit table; Based on the confirmation information received from the driver seated in the driver's seat, obtain the use state data from the driving habit table; and Update the use state of the current vehicle according to the driving parameter group and the non-driving parameter group that meet the matching conditions. 12.The intelligent driving control method of claim 10, wherein, After the current vehicle drives to the arrival location according to the driving habit table, it is parked at the parking location in the driving habit table. 13.The intelligent driving control method of claim 10, wherein, Further comprising the following steps: When a preset abnormal condition is detected during the driving trip, send an abnormal reminder information to all the passengers; Based on the fact that no feedback information is received from any of the passengers within a preset time, send the abnormal reminder information to the emergency contact person in the personal information of the passenger. 14.The intelligent driving control method of claim 10, wherein, Further comprising the following steps: Based on the average time of the driving path progress in the driving information and the corresponding use state data, obtain the delay time of the current driving trip; Collect the delay time of other vehicles driving on the same road and sort them, and configure higher traffic permission parameters for vehicles with higher delay time; And According to the level of permission parameters, plan the overtaking path of vehicles with larger delay time among the vehicles driving on the same road.

15. An intelligent driving control system for implementing the intelligent driving control method according to any one of claims 10 to 14, characterized in that, It includes: The habit generation module generates a driving behavior habit table, specifically comprising: based on completion of each driving trip of the current vehicle, obtaining usage state data of the current vehicle, the usage state data including personal information, driving information and non-driving information of all passengers in each driving trip; classifying a plurality of the usage state data according to each passenger group to obtain at least one driving parameter group of each passenger group and a non-driving parameter group corresponding to each driving parameter group; establishing a temporary driving behavior mapping table according to the mapping relationship between each passenger group, the driving parameter group and the non-driving parameter group; generating a blank driving behavior habit table, the driving behavior habit table having the same parameter columns as the temporary driving behavior mapping table; and based on a predetermined condition, updating the driving behavior habit table using data in the temporary driving behavior mapping table; the updating the driving behavior habit table using data in the temporary driving behavior mapping table based on the predetermined condition comprises: comparing the temporary driving behavior mapping table having the same passenger group with data in the driving behavior habit table based on the number of the same usage state data exceeding a preset value; when the comparison result meets a first preset condition, updating existing data of the driving behavior habit table using the usage state data in the temporary driving behavior mapping table; and when the comparison result meets a second preset condition, adding new data in the driving behavior habit table using the usage state data in the temporary driving behavior mapping table; The driving execution module detects identity information and driving information of each passenger in the current driving trip, matches the passenger group and the driving parameter group in the driving behavior habit table, and updates the usage state of the current vehicle according to the driving parameter group and the non-driving parameter group meeting the matching condition.

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