CN115203536A - Method and device for recommending intelligent driving parameters based on driving scene - Google Patents
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Abstract
The invention discloses a method and a device for recommending intelligent driving parameters based on a driving scene, wherein the method comprises the following steps: identifying a driving scene of a current vehicle, wherein the driving scene is used for representing a driving purpose and a driving environment of a user; recommending intelligent driving parameters to the user based on the driving scene, wherein the intelligent driving parameters are obtained by calculating data recorded in the manual driving process of the user; the intelligent driving parameters are used in an intelligent driving mode of the vehicle. According to the intelligent driving method and the intelligent driving system, the driving psychological expectation of the user is collected in the manual driving process of the user to determine the intelligent driving parameters, and the intelligent driving parameters meeting the requirements of the user can be intelligently recommended to the user by identifying the driving scene of the vehicle, so that the riding experience in the intelligent driving process is more consistent with the riding preference experience of the user.
Description
Technical Field
The invention relates to the field of intelligent driving, in particular to a method and a device for recommending intelligent driving parameters based on a driving scene.
Background
The automotive industry is undergoing a revolution, starting to drive from manual to the field of automated driving intelligence. However, as a mass production product, the automatic driving is not only in the high-tech landing, but also needs to match with the psychological expectation of the user, and the intelligent driving style is recommended based on the scene, so that the automatic driving is a solution.
At present, products for customizing intelligent cabin control according to scenes exist in the industry, but the scenes are defined based on user information in a vehicle, are not defined according to the use purpose and environment of the vehicle, and do not meet the functional requirements of intelligent driving; scenes are based on user active selection, not recommendations; the parameters adapted according to the scene do not include the intelligent driving function parameters.
The prior art is therefore still subject to further development.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method and a device for recommending intelligent driving parameters based on a driving scene, which can recommend the driving parameters suitable for the driving scene according to the driving scene identification and the identification result.
According to a first aspect of the present invention, there is provided a method for recommending intelligent driving parameters based on driving scenarios, comprising:
identifying a driving scene of a current vehicle, wherein the driving scene is used for representing a driving purpose and a driving environment of a user;
recommending intelligent driving parameters to the user based on the driving scene, wherein the intelligent driving parameters are obtained by calculating data recorded in the manual driving process of the user;
the intelligent driving parameters are used in an intelligent driving mode of the vehicle.
In some embodiments, the identifying a driving scenario of a current vehicle comprises:
the driving expectation of the user is identified based on at least one of current time, navigation POI information, temperature, seat occupancy information, weather information, in-vehicle living object detection information, path images, user emotion and driving behavior parameters, and the driving scene of the current vehicle is matched according to the driving expectation.
In some embodiments, the data identifying the driving desire of the user consists of data and data thresholds associated with the driving desire among data recorded during manual driving by the user, and the data and data thresholds at least partially satisfy the activation requirements of the driving scenario.
In some embodiments, the recommending smart driving parameters to the user based on the driving scenario includes:
recommending a driving scene name to a user in a screen display mode, wherein the driving scene name is selected by the user and then the intelligent driving parameter is called; the intelligent driving parameters are used for restricting the driving behavior in the intelligent driving mode, and the intelligent driving parameters at least comprise: the system comprises a path planning constraint, a overtaking time constraint, a vehicle speed constraint, an acceleration and deceleration constraint, an overtaking constraint and a lane change constraint.
In some embodiments, the method further comprises: and when the running speed of the vehicle exceeds a threshold value and/or the vehicle is positioned on a common running road, starting driving scene recognition.
According to a second aspect of the present invention, there is provided an apparatus for recommending intelligent driving parameters based on driving scenarios, comprising:
the identification module is used for identifying a driving scene of a current vehicle, wherein the driving scene is used for representing the driving purpose and the driving environment of a user;
the recommending module is used for recommending intelligent driving parameters to the user based on the driving scene, and the intelligent driving parameters are obtained by calculating data recorded in the manual driving process of the user;
a driving module to use the intelligent driving parameters in an intelligent driving mode of the vehicle.
According to a third aspect of the present invention, there is provided a method of intelligent driving parameter acquisition, comprising:
acquiring data recorded in the manual driving process of a user;
if part of the data triggers a screening threshold, screening the part of the data;
and calculating the partial data to obtain intelligent driving parameters, and defining driving scene names or binding the driving scene names according to the positions or paths in the data.
In some embodiments, the calculating the partial data to derive the smart driving parameter includes:
and calculating the partial data to obtain the quantile or median of the partial data, and taking the quantile or median of the partial data as the intelligent driving parameter.
In some embodiments, the smart driving parameters include at least: the system comprises a path planning constraint, a overtaking time constraint, a vehicle speed constraint, an acceleration and deceleration constraint, an overtaking constraint and a lane change constraint.
In some embodiments, the acquiring data recorded during manual driving of the user includes:
the method comprises the steps of identifying a driving scene of a current vehicle, and taking data of user manual driving in a plurality of same driving scenes as samples, wherein the samples are data recorded in the process of the user manual driving.
According to a fourth aspect of the present invention, there is provided an apparatus for intelligent driving parameter acquisition, comprising:
the recording module is used for acquiring data recorded in the manual driving process of the user;
the screening module is used for screening partial data in the data if the screening threshold value is triggered by partial data in the data;
and the acquisition module is used for calculating the partial data to obtain intelligent driving parameters, and defining driving scene names or binding the driving scene names according to the positions or paths in the data.
According to a fifth aspect of the present invention there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a computer, performs the method of any of the first or third aspects of the present invention.
According to the technical scheme provided by the invention, the driving psychological expectation of the user is collected in the manual driving process of the user to determine the intelligent driving parameters, and the intelligent driving parameters meeting the requirements of the user can be intelligently recommended to the user by identifying the driving scene of the vehicle, so that the riding experience in the intelligent driving process is more in line with the riding preference experience of the user.
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Fig. 1 is a schematic flow chart of an intelligent driving parameter obtaining method according to an embodiment of the present invention;
FIG. 2 is a schematic block diagram of an intelligent driving parameter obtaining apparatus according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart of a method for recommending intelligent driving parameters based on a driving scenario according to an embodiment of the present invention;
fig. 4 is a schematic block diagram of an apparatus for recommending intelligent driving parameters based on a driving scenario according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
An intelligent driving vehicle includes a sensor system having a plurality of sensors that detect information about the environment in which the vehicle is traveling. The vehicle and its associated controller use the detected information to detect outside information or information of the vehicle itself or information of the user inside the vehicle. The smart vehicle may manage any data related to the user's trip or route through the location module. The user may log in and specify the start location and destination of the trip via the user interface. The location module communicates with other components of the intelligent drive vehicle, such as maps and route information, to obtain trip related data. In some embodiments, the location module may obtain real-time traffic information from a traffic information system or server as the vehicle moves along the route.
The intelligent vehicle includes a data collection module for driving the statistical information. Such as accelerator, brake, steering at different points in time) and the like, and the vehicle's response to speed, acceleration or deceleration, direction, and the like. For example, the driving command may be determined from sensor data provided by a sensor system (e.g., a steering sensor, a throttle sensor, a brake sensor, etc.). The driving statistics may also include routing information, such as the most frequently selected routes by the user, family, work, personal points of interest, etc., provided by the location module or server, for example. For a particular object (e.g., another vehicle in a cross-route) and metadata describing the object (e.g., speed, direction, steering angle), it is decided how the encountered object operates (e.g., exceeds, yields, stops, passes).
Based on the driving statistics and/or user-specific information, a control system of the vehicle may invoke one or more machine learning models or algorithms (e.g., deep learning architectures such as deep neural networks, convolutional deep neural networks, deep belief networks, and/or recurrent neural networks) to continuously determine or learn one or more user driving behaviors of the user for one or more predetermined driving scenarios, from which the user's driving preferences may be analyzed. The vehicle-mounted camera system can also analyze the emotion, state and other information of the user, and the control system can be trained better by utilizing the emotion, state and other information. Of course, the intelligent control module of the vehicle is not limited to the above.
Referring to fig. 1, the method for obtaining intelligent driving parameters provided by the present invention includes:
step 110: and acquiring data recorded in the manual driving process of the user.
Step 120: and if part of the data triggers a screening threshold, screening the part of the data.
Step 130: and calculating the partial data to obtain intelligent driving parameters, and defining driving scene names or binding the driving scene names according to the positions or paths in the data.
When a user manually drives a vehicle, the system can actively collect data in the driving process, and exemplary data comprises time, navigation POI (point of interest), vehicle speed, overtaking times, acceleration, steering angle, personal information of the user, images recorded by a driving recorder, images recorded by a vehicle-mounted camera, user conditions, road conditions (muddy roads or highways) and the like.
The collected data are various and cannot be easily classified, so that the recorded data can be screened, namely when some part of data in the data meet the minimum sample requirement of a driving scene, characteristic values are extracted from the part of data, and then calculation analysis is carried out to form intelligent driving parameters aiming at the specific driving scene.
In one embodiment, specific data for a driving scenario may be defined to activate data collection for that scenario. The method comprises the steps of identifying a driving scene of a current vehicle, and taking data of user manual driving in a plurality of same driving scenes as samples, wherein the samples are data recorded in the process of the user manual driving.
For example, the definition of a vacation scene is: POI (park, zoo, plantain, scenic spot) & temperature (> 5 ℃) near the time (weekend + legal holiday) & navigation destination point (within 1 km) & no raining & the back row seat occupied (back row seat load >10 kg) & live things are arranged. In the manual driving process of a user, firstly, a destination is selected, and whether interest points related to vacation exist at the destination or nearby the destination can be searched out through the destination selected by the user; if the information is satisfied, the user is possibly a vacation scene, and corresponding data can be recorded in the manual driving process of the user.
In yet another embodiment, the recorded data may be used to derive a corresponding driving scenario after analysis. For example, a user goes out and goes to a certain CBD office building in a downtown area at 8 points every day, the driving route is from a certain road to a certain road and experiences 5 traffic lights, and the driving scene of manual driving of the user can be judged to be in a working scene every day from Monday to Friday. For such a case, the recorded data may be analyzed first to obtain corresponding driving parameters, and then defined as the work scene.
In another scene, the driving scene can be identified through the acquired path and the image on the path in the manual driving process of the user. When the vehicle-mounted camera on the driving path acquires the street view, the server of the vehicle judges the current position and the current surrounding environment according to the street view, if the surrounding environment is a building, the building belongs to an office area and a residential area, the scene may be an on-duty scene or an off-duty scene, and if the surrounding environment is a flower sea, the scene may be a vacation scene. It will be appreciated that the acquisition of data may be recorded from the start of a manual drive by the user, and the recognition of the scene may be that after the destination is reached (particularly for driving behaviour without navigation). The data acquisition may be performed when the vehicle speed exceeds a threshold, for example a speed greater than 20km/h, or to initiate driving scenario recognition. If the route driven by the user is located on a common driving road, such as a certain road or a certain road to a certain road, the route is judged to be the route frequently driven by the user compared with historical data, driving scene recognition can be started, and data can be collected; or to train driving scene recognition based on the data.
When the intelligent driving parameters are obtained by calculating the partial data, the associated data or the knowledge graph and the like can be formed by utilizing one or more machine learning models or algorithm calculation. The driving parameters can be used for limiting intelligent driving and restraining driving behaviors so as to meet user habits. And as a calculation mode of the driving parameters, calculating quantiles or medias of the data or partial data, and taking the quantiles or medias of the partial data as the intelligent driving parameters. The partial data are calculated because the acquired data can contain information such as images and environments, but are not used for driving control of the vehicle, so that intelligent driving parameters can be obtained by calculating only partial data, and the data such as the images can be used as calculation basis for scene recognition.
In the manual driving process of a user, intelligent driving parameters obtained by automatic calculation of a vehicle comprise: the system comprises a path planning constraint, a overtaking time constraint, a vehicle speed constraint, an acceleration and deceleration constraint, an overtaking constraint and a lane change constraint. Of course, the smart driving is not limited to this, and may also include playing music type, air conditioning temperature, vehicle bluetooth control, parking location, radio frequency band, and the like. The psychological expectation of the user on the intelligent driving function in different states is met through the constraint control of the intelligent driving parameters on the intelligent driving mode. The experience in the intelligent driving process approaches the experience of manual driving of a user.
As an example of data calculation, the overspeed ratio can be calculated by the calculation formula:
wherein v is ref,p I is the overspeed ratio, i is the serial number, from 1 to n, n is the number, v i Is the vehicle speed, v, corresponding to the serial number i limit，i The vehicle speed limit corresponding to the serial number i.
For longitudinal acceleration and longitudinal deceleration, screening acceleration positive values in a starting stage (0-40 km/h) by the longitudinal acceleration, sequencing the acceleration positive values, and calculating a 95th quantile of the acceleration positive values; and screening the acceleration negative values of the braking stage (0-40 km/h) by the longitudinal deceleration, sequencing the absolute values of the acceleration negative values, and calculating the 95th quantile of the acceleration negative values. The 97th lateral acceleration and 97th lateral deceleration can be calculated in the same manner.
In one embodiment, the smart driving parameters include the following constraints:
wherein v is the speed of the vehicle, a is the longitudinal acceleration, jerk is the change rate of the longitudinal acceleration, s is the coordinate of the vehicle, s lead As coordinates of the front vehicle, v lead For the preceding vehicle speed, t r Time taken for decision-making action, d safe For longitudinal safety distance, s rear As a coordinate with the rear vehicle, v rear The rear vehicle speed.
The intelligent driving parameters are applied to an intelligent driving system and used for controlling a driving system, a braking system, a steering system and the like of a vehicle. The method includes the steps that data recorded in the manual driving process of a user are obtained; triggering a screening threshold according to partial data in the data, and screening the partial data in the data; calculating based on the partial data to obtain intelligent driving parameters; the intelligent driving parameters can be used for simulating manual driving of a user, so that the intelligent driving under different driving scenes and different states of the user meets the psychological expectation of the user.
Accordingly, the present invention further provides an apparatus for intelligently acquiring driving parameters based on the above, as shown in fig. 2, the apparatus includes:
the recording module 21 is used for acquiring data recorded in the manual driving process of the user;
the screening module 22 is configured to screen a part of the data if the part of the data triggers a screening threshold;
the obtaining module 23 is configured to calculate the partial data to obtain an intelligent driving parameter, and define a driving scene name or bind the driving scene name according to a position or a path in the data.
When enough data is obtained to meet the calculation result of the intelligent driving parameters, the intelligent driving mode of the vehicle can be constrained or optimized based on the intelligent driving parameters, and the driving experience requirements of the user in different scenes can be met. As shown in fig. 3, the present invention provides a method for recommending intelligent driving parameters based on driving scenarios, comprising:
step 310: identifying a driving scene of a current vehicle, wherein the driving scene is used for representing a driving purpose and a driving environment of a user;
step 320: recommending intelligent driving parameters to the user based on the driving scene, wherein the intelligent driving parameters are obtained by calculating data recorded in the manual driving process of the user;
step 330: the smart driving parameters are used in a smart driving mode of the vehicle.
The method and the system can identify the driving expectation of the user based on at least one of the current time, navigation POI information, temperature, seat occupancy information, weather information, in-vehicle living object detection information, path images (namely images shot on the road), user emotion and driving behavior parameters, and match the driving scene of the current vehicle according to the driving expectation. For example, rain is detected outside the vehicle, and the vehicle can directly enter a scene of rainy and snowy days. Of course, the scope of recognition is not limited to the above examples.
The driving purpose is a desired purpose of the user's driving, such as work, shopping, traveling, accompanying, etc. The driving environment comprises a traffic route, an environment outside the vehicle, an environment inside the vehicle, personnel inside the vehicle and the like where the vehicle is located. The driving objectives and the driving environment may be used to simulate the experience of a user driving manually as a driving expectation. The style of a driver is not invariable and can change along with the accumulation of driving experience and use scenes; even under the same road environment, the psychological expectation of the driver on the intelligent driving function is different under different states; the definition of the driving scenario may therefore be understood as a constraint on intelligent driving that biases it towards the state of the user's manual driving experience.
The data used for identifying the driving expectation of the user consists of data which are recorded in the manual driving process of the user and are related to the driving expectation and a data threshold; the description in the method for obtaining the intelligent driving parameters can be specifically referred to, and the driving expectation of the user can be understood as whether the user is inclined to continuously overtake, accelerate and decelerate, whether the navigation route needs to be fastest, and the like. In some application scenarios, the data and data thresholds used to determine the driving desires of the user at least partially satisfy the activation requirements of the driving scenario; for example, when the driving speed of the vehicle exceeds a threshold value and/or the vehicle is located on a common driving road, the driving scene recognition is started. After the scene recognition is started, the following data are recorded: vehicle information such as speed limit, traffic lights, speed, acceleration, steering lights, steering wheel turning angles and the like; the characteristic values of the data include: overspeed proportion, yellow light robbing times, overtaking lane change frequency and lane change duration.
When the intelligent driving parameters are recommended to the user, the driving scene names can be recommended to the user in a screen display mode through display, and the intelligent driving parameters are called after the driving scene names are selected by the user. In some embodiments, if the user agrees 5 consecutive choices for a scenario recommendation, the scenario recommendation still notifies the user through the meter display screen, but the user's opinion is no longer asked.
The intelligent driving parameters are used for restricting the driving behavior in the intelligent driving mode, and the intelligent driving parameters at least comprise: the system comprises a path planning constraint, a overtaking time constraint, a vehicle speed constraint, an acceleration and deceleration constraint, an overtaking constraint and a lane change constraint.
For example, the path planning constraint may select an elevated road, whether to change lane to overtake when the current vehicle is at a slow speed, the lane change duration is used to constrain selection of the lane change waiting time, and the lane change may be performed in combination with the constraint of acceleration and deceleration. As a constraint objective function for intelligent driving parameter calculation:
wherein, the first and the second end of the pipe are connected with each other,Cto optimize the objective, w v Is the speed error weight coefficient, v is the speed of the bicycle, v r Target vehicle speed, w a Is the acceleration error weight coefficient, a is the longitudinal acceleration, w jerk Is the jerk weight coefficient, jerk is the longitudinal acceleration rate, w s Is a distance error weight coefficient, eta is a zone bit of a distance target, s is a coordinate of the self-vehicle, s lead As coordinates of the preceding vehicle, v lead The speed of the preceding vehicle, delta t is the collision time, d stop The minimum distance when parking.
It can be understood from the above that, the driving scene can be divided into a plurality of scenes, such as several scenes of commuting, shopping, handling, vacation, accompanying, rainy and snowy days, and the like, the scenes of working on duty, working off duty, accompanying, shopping, vacation, rainy and snowy days and the like can be automatically identified, and the control parameters under the scenes are automatically used for control, so that the experience and satisfaction of users can be improved under an intelligent driving mode.
Correspondingly, as shown in fig. 4, the present invention further provides a device for recommending intelligent driving parameters based on driving scenarios, comprising:
the identification module 41 is used for identifying a driving scene of the current vehicle, wherein the driving scene is used for representing the driving purpose and the driving environment of a user;
a recommending module 42, configured to recommend an intelligent driving parameter to the user based on the driving scenario, where the intelligent driving parameter is obtained by calculating data recorded in a manual driving process of the user;
a driving module 43 for using the smart driving parameters in a smart driving mode of the vehicle.
Reference may be made to the detailed description of the embodiment shown in fig. 1 and 3 with respect to the apparatus.
The invention also provides a computer-readable storage medium on which a computer program is stored, the computer program, when executed by a processor, implementing the steps of the intelligent driving parameter acquisition method as described above; or steps of a method for recommending intelligent driving parameters based on a driving scenario.
It is to be understood that the computer-readable storage medium may include: any entity or device capable of carrying a computer program, recording medium, U disk, removable hard disk, magnetic disk, optical disk, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), and software distribution medium. The computer program includes computer program code. The computer program code may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable storage medium may include: any entity or device capable of carrying computer program code, recording medium, U.S. disk, removable hard disk, magnetic diskette, optical disk, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), and software distribution medium.
In some embodiments of the present invention, the apparatus may include a controller, and the controller is a single chip integrated with a processor, a memory, a communication module, and the like. The processor may refer to a processor included in the controller. The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The above examples are only intended to illustrate the technical solution of the present invention, and not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (12)
1. A method for recommending intelligent driving parameters based on driving scenes is characterized by comprising the following steps:
identifying a driving scene of a current vehicle, wherein the driving scene is used for representing a driving purpose and a driving environment of a user;
recommending intelligent driving parameters to the user based on the driving scene, wherein the intelligent driving parameters are obtained by calculating data recorded in the manual driving process of the user;
the intelligent driving parameters are used in an intelligent driving mode of the vehicle.
2. The method of claim 1, wherein the identifying the driving scenario of the current vehicle comprises:
the driving expectation of the user is identified based on at least one of current time, navigation POI information, temperature, seat occupancy information, weather information, in-vehicle living object detection information, path images, user emotion and driving behavior parameters, and the driving scene of the current vehicle is matched according to the driving expectation.
3. The method of claim 2, wherein the data identifying the driving desires of the user comprises data and data thresholds associated with the driving desires of the data recorded during manual driving by the user, and the data and data thresholds at least partially satisfy the activation requirements of the driving scenario.
4. The method of claim 1, wherein recommending smart driving parameters to a user based on a driving scenario comprises:
recommending a driving scene name to a user in a screen display mode, wherein the driving scene name is selected by the user and then the intelligent driving parameter is called; the intelligent driving parameters are used for restricting the driving behavior in the intelligent driving mode, and the intelligent driving parameters at least comprise: the system comprises a path planning constraint, a overtaking time constraint, a vehicle speed constraint, an acceleration and deceleration constraint, an overtaking constraint and a lane change constraint.
5. The method of claim 1, further comprising: and when the running speed of the vehicle exceeds a threshold value and/or the vehicle is positioned on a common running road, starting driving scene recognition.
6. An apparatus for recommending intelligent driving parameters based on driving scenarios, comprising:
the identification module is used for identifying a driving scene of a current vehicle, wherein the driving scene is used for representing the driving purpose and the driving environment of a user;
the recommending module is used for recommending intelligent driving parameters to the user based on the driving scene, and the intelligent driving parameters are obtained by calculating data recorded in the manual driving process of the user;
a driving module to use the intelligent driving parameters in an intelligent driving mode of the vehicle.
7. A method of intelligent driving parameter acquisition, comprising:
acquiring data recorded in the manual driving process of a user;
if a screening threshold value is triggered by part of the data, screening the part of the data;
and calculating the partial data to obtain intelligent driving parameters, and defining driving scene names or binding the driving scene names according to the positions or paths in the data.
8. The method of claim 7, wherein said calculating the portion of data to derive smart driving parameters comprises:
and calculating the partial data to obtain the quantile or median of the partial data, and taking the quantile or median of the partial data as the intelligent driving parameter.
9. The method of claim 7, wherein the smart driving parameters include at least: the system comprises a path planning constraint, a overtaking time constraint, a vehicle speed constraint, an acceleration and deceleration constraint, an overtaking constraint and a lane change constraint.
10. The method of claim 7, wherein the obtaining data recorded during manual driving by the user comprises:
the method comprises the steps of identifying a driving scene of a current vehicle, and taking data of user manual driving in a plurality of same driving scenes as samples, wherein the samples are data recorded in the process of the user manual driving.
11. An apparatus for intelligent driving parameter acquisition, comprising:
the recording module is used for acquiring data recorded in the manual driving process of the user;
the screening module is used for screening partial data in the data if the screening threshold value is triggered by the partial data in the data;
and the acquisition module is used for calculating the partial data to obtain intelligent driving parameters, and defining driving scene names or binding the driving scene names according to the positions or paths in the data.
12. A computer-readable storage medium, characterized in that a computer program is stored thereon, which computer program, when executed by a computer, performs the method of any one of claims 1 to 5 or claims 7 to 10.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115534981A (en) * | 2022-12-05 | 2022-12-30 | 广汽埃安新能源汽车股份有限公司 | Automatic driving mode adjusting method and device for vehicle |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115534981A (en) * | 2022-12-05 | 2022-12-30 | 广汽埃安新能源汽车股份有限公司 | Automatic driving mode adjusting method and device for vehicle |
| CN115534981B (en) * | 2022-12-05 | 2023-03-07 | 广汽埃安新能源汽车股份有限公司 | Automatic driving mode adjusting method and device for vehicle |
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