CN112389451A

CN112389451A - Method, device, medium, and vehicle for providing a personalized driving experience

Info

Publication number: CN112389451A
Application number: CN201910750445.4A
Authority: CN
Inventors: 陈勇; 陆芸
Original assignee: Volkswagen China Investment Co Ltd
Current assignee: Volkswagen China Investment Co Ltd
Priority date: 2019-08-14
Filing date: 2019-08-14
Publication date: 2021-02-23
Also published as: WO2021028533A1

Abstract

According to an example embodiment of the present disclosure, a method, device, medium, and vehicle for providing a personalized driving experience are provided. The method includes obtaining first driving behavior data of a first user collected from at least one vehicle, wherein the first driving behavior data includes user maneuver data collected by the first user during a maneuver of the at least one vehicle. The method further includes controlling the current vehicle to provide an adapted personalized driving experience to the first user based on the first driving behavior data of the first user. According to the embodiment of the disclosure, the driving behavior data of each user on each vehicle is collected, and then the auxiliary driving or automatic driving of the current vehicle is controlled according to each driving behavior data, so that the user feels like driving by himself, thereby improving the personalized driving experience of the user.

Description

Method, device, medium, and vehicle for providing a personalized driving experience

Technical Field

Embodiments of the present disclosure relate generally to the field of intelligent driving, and more particularly, to methods, devices, media, and vehicles for providing a personalized driving experience.

Background

With the rapid development of electronic technology and network technology, vehicles become more and more intelligent. Vehicle intellectualization is closely related to vehicle electronic technology, and intelligent vehicles can realize some functions such as live-action navigation, voice control, vehicle distance detection and the like. Along with the continuous development of the car networking technology, the intelligent vehicle can realize the communication processes of direct vehicle-road interaction, vehicle-vehicle interaction and the like. Therefore, vehicle intelligence is considered to be an innovative revolution and development of the existing vehicle electronic technology.

An automatic driving vehicle is also called an unmanned vehicle, and is an intelligent vehicle which realizes unmanned driving through a computer system. The automatic driving vehicle acquires real-time traffic conditions around the vehicle through a video camera, a radar sensor, a laser range finder and the like, and realizes accurate navigation control on the vehicle through a high-precision map and precise calculation. The automatic driving can be divided into the following stages according to the automation level: assisted driving, partially automated driving, highly automated driving, and fully automated driving, wherein during the assisted driving phase, some driving assistance functions, such as assisted braking, may be provided.

The design of the driving assistance functions (e.g. active safety systems) of current vehicles is based on the same hazard limit value to control whether the system triggers a warning or whether an active intervention is required. However, different driving individuals differ greatly in the definition of a hazard and the tolerance to the hazard. Based on the current development technical route, the products put into the market cannot meet the individual requirements of the users, and on the contrary, the users can stop using the products or functions because the systems are not smart enough, so that the due product efficiency cannot be achieved.

Disclosure of Invention

According to example embodiments of the present disclosure, a method, an apparatus, a device, a computer-readable storage medium, and a vehicle for providing a personalized driving experience capable of providing a personalized driving experience suitable for each user are provided.

In a first aspect of the present disclosure, a method for providing a personalized driving experience is provided. The method comprises the following steps: obtaining first driving behavior data of a first user collected from at least one vehicle, wherein the first driving behavior data comprises user maneuver data collected by the first user during a maneuver of the at least one vehicle; controlling the current vehicle to provide a personalized driving experience to the first user based on the first driving behavior data of the first user. In this way, the driving behavior data of each user on each vehicle is collected, and then the auxiliary driving or automatic driving of the current vehicle is controlled according to the respective driving behavior data, so that the user feels like driving by himself, thereby improving the personalized driving experience of the user.

In some embodiments, wherein controlling the current vehicle to provide the personalized driving experience to the first user comprises: determining a first driving habit of a first user based on first driving behavior data of the first user; and controlling the current vehicle to provide a personalized driving experience corresponding to the first driving habit to the first user. By analyzing the driving behavior data of each user, the driving habits of each user can be determined, thereby being beneficial to providing more accurate personalized driving experience.

In some embodiments, wherein the current vehicle is a different vehicle than the at least one vehicle and the current vehicle is of a higher autonomous driving class than the at least one vehicle, or the current vehicle and the at least one vehicle belong to the same autonomous driving class and the current vehicle has more assisted driving functions than the at least one vehicle, the method further comprises: user maneuver data of a first user during a maneuver of a current vehicle is collected. In this way, the driving behavior data of the user on the automatic driving vehicles with different grades or different functions can be collected, the data of the automatic driving vehicles with high grades or functions under more complex working conditions are continuously collected along with the improvement of the automatic driving grades or functions of the driving vehicles, and the driving behavior data and the driving habit data of the user are continuously improved, so that the driving behavior database of the user is enriched, and the personalized driving experience of the user is further improved.

In some embodiments, the method further comprises: determining a second driving habit of the second user based on second driving behavior data collected by the second user during driving of the vehicle, wherein the second driving habit differs from the first driving habit in at least one of: driving speed, following distance, acceleration control and brake control; and controlling the current vehicle to provide a personalized driving experience corresponding to the second driving habit to the second user. Thus, even if different users ride the same vehicle, the users can respectively obtain different driving experiences provided according to the respective historical driving habits, and the driving pleasure is improved.

In some embodiments, wherein obtaining first driving behavior data of the first user collected from the at least one vehicle comprises: verifying a first identity of a first user by biometric identification or account login in response to the first user entering a current vehicle; in response to the first identity being verified, determining a first identification of the first user; and obtaining first driving behavior data from a driving behavior server based on a first identification of the first user, wherein the driving behavior server stores driving behavior data of a plurality of users collected by an on-vehicle driving assistance system, and the on-vehicle driving assistance system includes an image acquisition device, a radar device, and a satellite positioning system. The user identity is verified in a biological characteristic recognition (such as fingerprint recognition, face recognition and the like), so that the user verification efficiency can be improved, and unnecessary login burden on the user is reduced. In addition, by storing a large amount of driving behavior data of users, a valuable driving behavior database and an ecological circle can be established, and meanwhile, the data uploading enthusiasm of each user can be stimulated by having an individual driving behavior data account.

In some embodiments, wherein obtaining first driving behavior data of the first user collected from the at least one vehicle comprises: obtaining first scene data collected by a first user during a maneuver of at least one vehicle in a first scene; and obtaining second context data collected by the first user during the maneuver of the at least one vehicle in a second context, wherein the first context and the second context are distinguished according to at least one of: weather conditions, road type, time period, and area type. In this way, finer-grained driving behavior data can be obtained, subsequent driving behavior analysis and automatic driving control are facilitated, and the driving experience of the user on the current vehicle is further improved.

In some embodiments, wherein controlling the current vehicle to provide the personalized driving experience corresponding to the first driving habit to the first user comprises: controlling a distance between a current vehicle and a preceding vehicle to be maintained at least a first distance in response to a first user riding the current vehicle in a first scene; and in response to the first user riding the current vehicle in a second scene, controlling the distance between the current vehicle and the front vehicle to be kept at least a second distance, wherein the first scene is a sunny scene and the second scene is a rainy scene, and the first distance is smaller than the second distance. In this way, the automatic driving function can be more humanized, and the driving experience of the user is further improved.

In some embodiments, wherein controlling the current vehicle to provide the personalized driving experience corresponding to the first driving habit to the first user comprises: determining an average speed at which a first user drives at least one vehicle on a highway; and controlling the automatic driving of the current vehicle on the expressway according to the average speed in response to the current vehicle traveling on the expressway. In this way, the automatic driving of the vehicle can better accord with the driving style and habit of the user, and the satisfaction degree of the user is improved.

In some embodiments, wherein controlling the current vehicle to provide the personalized driving experience corresponding to the first driving habit to the first user comprises: adjusting driving control of the current vehicle in response to receiving driving feedback from the first user; collecting driving environment data of a current vehicle within a predetermined time period before driving feedback; and modifying the autonomous driving algorithm based on the collected driving environment data. In this way, user feedback can be processed and predetermined mode parameters can be modified, making the autopilot or driveassist function more intelligent and accurate.

In some embodiments, wherein controlling the current vehicle to provide the personalized driving experience corresponding to the first driving habit to the first user comprises: in response to the current vehicle being an assisted driving vehicle or a partially autonomous vehicle, controlling at least one of the following functions of the current vehicle according to a first driving habit: adaptive cruise, lane keeping assist and automatic emergency braking. In this way, in a driving assistance scene, the driving experience of the user can be improved, thereby expanding the application range of the embodiment of the present disclosure.

In some embodiments, wherein controlling the current vehicle to provide the personalized driving experience corresponding to the first driving habit to the first user comprises: in response to the current vehicle being a fully autonomous vehicle, a full driving process of the current vehicle is controlled according to the first driving habit. In this way, the user can experience the feeling and fun of driving the vehicle during the fully automatic driving, and the user experience is improved.

In a second aspect of the present disclosure, an apparatus for providing a personalized driving experience is provided. The apparatus comprises: at least one processing unit, and at least one memory coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit, the instructions, when executed by the at least one processing unit, causing the apparatus to perform actions. The actions include: obtaining first driving behavior data of a first user collected from at least one vehicle, wherein the first driving behavior data comprises user maneuver data collected by the first user during a maneuver of the at least one vehicle; controlling the current vehicle to provide a personalized driving experience to the first user based on the first driving behavior data of the first user. In this way, the driving behavior data of each user on each vehicle is collected, and then the auxiliary driving or automatic driving of the current vehicle is controlled according to each driving behavior data, so that the user feels like driving by himself, thereby being capable of improving the personalized driving experience of the user.

In some embodiments, wherein the current vehicle is a different vehicle than the at least one vehicle and the current vehicle is of a higher autonomous driving rating than the at least one vehicle, or the current vehicle and the at least one vehicle belong to the same autonomous driving rating and the current vehicle has more assisted driving functions than the at least one vehicle, the acts further comprising: user maneuver data of a first user during a maneuver of a current vehicle is collected. In this way, the driving behavior data of the user on the automatic driving vehicles with different grades or different functions can be collected, the data of the automatic driving vehicles with high grades or functions under more complex working conditions are continuously collected along with the improvement of the automatic driving grades or functions of the driving vehicles, and the driving behavior data and the driving habit data of the user are continuously improved, so that the driving behavior database of the user is enriched, and the personalized driving experience of the user is further improved.

In some embodiments, the actions further comprise: determining a second driving habit of the second user based on second driving behavior data collected by the second user during driving of the vehicle, wherein the second driving habit differs from the first driving habit in at least one of: driving speed, following distance, acceleration control and brake control; and controlling the current vehicle to provide a personalized driving experience corresponding to the second driving habit to the second user. Thus, even if different users ride the same vehicle, the users can respectively obtain different driving experiences provided according to the driving habits of the users, and the driving pleasure is improved.

In some embodiments, wherein obtaining first driving behavior data of the first user collected from the at least one vehicle comprises: verifying a first identity of a first user by biometric identification or account login in response to the first user entering a current vehicle; in response to the first identity being verified, determining a first identification of the first user; and obtaining first driving behavior data from a driving behavior server based on a first identification of the first user, wherein the driving behavior server stores driving behavior data of a plurality of users collected by an on-vehicle driving assistance system, and the on-vehicle driving assistance system includes an image acquisition device, a radar device, and a satellite positioning system. The user identity is verified in a biological characteristic recognition (such as fingerprint recognition, face recognition and the like), so that the user verification efficiency can be improved, and unnecessary login burden on the user is reduced. In addition, by storing a large amount of driving behavior data of users, a valuable driving behavior database and an ecological circle can be established, and meanwhile, the account with the personal driving behavior data can stimulate the data uploading enthusiasm and enthusiasm of each user.

In some embodiments, wherein controlling the current vehicle to provide the personalized driving experience corresponding to the first driving habit to the first user comprises: determining an average speed at which a first user drives at least one vehicle on a highway; and controlling the automatic driving of the current vehicle on the expressway according to the average speed in response to the current vehicle traveling on the expressway. In this way, the automatic driving can be more in line with the driving style and habit of the user, and the satisfaction degree of the user is improved.

In a third aspect of the present disclosure, a computer readable storage medium is provided, having stored thereon a computer program which, when executed by a processor, implements the method according to the above first aspect. It should be appreciated that the computer readable storage medium according to the third aspect may be deployed in both a vehicle and a server, thereby increasing the flexibility of embodiments of the present disclosure.

In a fourth aspect of the present disclosure, a vehicle is provided comprising an apparatus for providing a personalized driving experience according to the above second aspect. In this way, the method and apparatus according to embodiments of the present disclosure can be deployed on a current vehicle, improving the driving experience of a user while driving or riding the current vehicle.

It should be understood that the statements herein set forth in this summary are not intended to limit the essential or critical features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.

Drawings

The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, like or similar reference characters designate like or similar elements, and wherein:

FIG. 1 illustrates an example environment for providing a personalized driving experience in accordance with an embodiment of the present disclosure;

FIG. 2 shows a flow diagram of a method for providing a personalized driving experience, according to an embodiment of the present disclosure;

FIG. 3 illustrates another example environment for providing a personalized driving experience in accordance with an embodiment of the disclosure;

FIG. 4 illustrates yet another example environment for providing a personalized driving experience in accordance with an embodiment of the present disclosure;

FIG. 5 shows a block diagram of an example architecture of an in-vehicle driving assistance system according to an embodiment of the present disclosure;

FIG. 6A shows a schematic diagram of providing a personalized driving experience in a sunny scene, according to an embodiment of the disclosure;

FIG. 6B shows a schematic diagram of providing a personalized driving experience in a rainy day scene according to an embodiment of the disclosure;

FIG. 7 shows a flow diagram of a method for processing driving feedback of a user according to an embodiment of the present disclosure; and

FIG. 8 illustrates a block diagram of a device capable of implementing various embodiments of the present disclosure.

Detailed Description

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are illustrated in the accompanying drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.

In describing embodiments of the present disclosure, the terms "include" and its derivatives should be interpreted as being inclusive, i.e., "including but not limited to. The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The term "some embodiments" should be understood as "at least some embodiments". The term "user" of the vehicle denotes a person using the vehicle, which may be a driver or a passenger of the vehicle. Other explicit and implicit definitions are also possible below.

As shown above, the driving assistance function or the automatic driving function of the vehicle on the market currently provides the same set of parameters, for example, for the braking assistance function, the braking assistance function assists the driver to brake when the vehicle distance is less than a certain distance, however, different people have different habits and preferences, for example, some people do not like emergency braking, and thus the user experience of the existing driving assistance function is not good and not personalized. An improvement to the conventional method is to select a corresponding driving mode (e.g., a normal mode, a sport mode) according to personal information (e.g., age, gender) of a person in the vehicle, however, on one hand, the driving modes provided are only a few and cannot meet different requirements of thousands of users, and thus the provided functions are not personalized, and on the other hand, the personal information cannot represent actual driving preferences of the person in the vehicle, for example, people of the same age may have different driving preferences, and thus, the improved method still cannot provide a truly personalized driving experience.

To this end, embodiments of the present disclosure propose a new approach to providing a personalized driving experience. According to the embodiment of the disclosure, the driving behavior data of each user on each vehicle is collected, and then the auxiliary driving or automatic driving of the current vehicle is controlled according to each driving behavior data, so that the user feels like driving by himself, and therefore the personalized driving experience of the user can be improved. It should be understood that the method according to embodiments of the present disclosure is not intended to change the user, but to change the control of the current vehicle so that the current vehicle is more adapted to the driving habits and style of the user. Some example implementations of the present disclosure will be described in detail below with reference to fig. 1-8.

Fig. 1 illustrates an example environment 100 for providing a personalized driving experience in accordance with an embodiment of the disclosure. As shown in fig. 1, during driving of vehicle 121 by user 111, driving behavior data 131 of user 111 may be collected and stored in driving behavior server 130. The stored driving behavior data 131 may provide a personalized experience for the user 111 when driving or riding in the current vehicle 122 in the future. In the example of fig. 1, vehicle 122 may be, for example, an autonomous vehicle, with user 111 sitting in the rear row of vehicle 122. In the conventional method, the automatic driving program of the vehicle 122 drives the vehicle 122 according to a predetermined uniform mode, or selects one of several limited modes (e.g., normal mode, sport mode), and the driving style provided by this method cannot meet the individual needs of various users. In contrast, the embodiment of the present disclosure guides the vehicle 122 to perform automatic driving according to the driving behavior data 131 when the user 111 drives the vehicle 121 by himself, so that the automatic driving of the vehicle 122 can be performed like the passenger 111 drives by himself, which greatly improves the driving experience of the user 111.

Driving behavior data 131 may be data gathered by user 111 during a period of time or at all times while driving vehicle 121, which may be sent to driving behavior server 130 for storage in real time, periodically, or consistently. In some embodiments, driving behavior data 131 may include, but is not limited to, throttle data, brake data, steering avoidance maneuver, etc., and driving behavior data 131 may also include external images, radar data, and satellite positioning data, etc., collected by various collection devices of vehicle 121.

Fig. 2 shows a flow diagram of a method 200 for providing a personalized driving experience according to an embodiment of the present disclosure. It should be appreciated that the method 200 according to embodiments of the present disclosure may be performed by a local device within the vehicle 122 described with reference to fig. 1, by the server 130 (the server 130 may include an autonomous driving model in addition to storing driving behavior data) or a device in the cloud, or partially locally at the vehicle 122 and partially at the server 130.

At block 202, first driving behavior data of a first user collected from at least one vehicle is obtained, wherein the first driving behavior data comprises user handling data collected by the first user during handling of the at least one vehicle, such as user driving data collected by the user 111 during handling of the vehicle 111, or user handling data collected by the user 111 during handling of the unmanned vehicle 111. In some embodiments, driving behavior data for a user may be collected from a vehicle. Alternatively, the driving behavior data of a certain user may also be collected from a plurality of vehicles (e.g., a plurality of vehicles that the user has used).

For example, vehicle 122 described with reference to fig. 1 obtains driving behavior data 131 of user 111 collected from vehicle 121 from driving behavior server 130. If vehicle 122 is a driver-assisted vehicle or a partially driven vehicle, user 111 may be the driver of vehicle 122; if vehicle 122 is a highly autonomous vehicle or is fully autonomous, user 111 may be a passenger of vehicle 122, who may not even be seated in a driver's position (as shown in FIG. 1, user 111 is seated in the rear row of vehicle 122). In some embodiments, after vehicle 122 verifies the identity of user 111, its user identification (e.g., user account) is determined before obtaining the driving behavior data 131 of verified user 111 from server 130.

Optionally, at block 204, a first driving habit of the first user is determined based on the first driving behavior data of the first user. For example, vehicle 122 may immediately learn the driving habits and styles of user 111, and in determining driving habits, some noisy data and/or unreasonable and/or non-compliant data may be removed. It should be appreciated that any known or future developed driving behavior analysis method may be used in conjunction with embodiments of the present disclosure. In one example, vehicle 122 may learn that user 111's driving style is relatively smooth, driving at a relatively slow speed, dislikes rapid acceleration and frequent lane changes, and is relatively far from the vehicle. It should be appreciated that in some cases, the current vehicle may also be directly controlled to provide a personalized driving experience to the first user based on the first driving behavior data of the first user without determining the driving habits of the user.

At block 206, the current vehicle is controlled to provide a personalized driving experience to the first user. For example, a control device or computing device in vehicle 122 determines its driving habits from the driving behavior data 131 of user 111, and then drives vehicle 122 at a relatively smooth, slower speed, thereby satisfying the personalized experience of user 111. Conversely, if the vehicle 122 is driven at a faster speed, the user 111 may feel uncomfortable and be unaccustomed to. In some embodiments, the current vehicle that the user is currently driving or riding in may be a different vehicle than the at least one vehicle that collects driving behavior data. Alternatively, the current vehicle that the user is currently driving or riding in may also be the same vehicle as the at least one vehicle that collects the driving behavior data.

Therefore, according to the method 200 of the embodiment of the present disclosure, the respective driving habits of the respective users are determined by collecting the driving behavior data of the respective users on the respective vehicles, and then the assistant driving or the automatic driving of the current vehicle is controlled according to the respective driving habits, so that the users feel like driving themselves, thereby being capable of improving the personalized driving experience of the users.

In some embodiments, vehicle 122 may be a driver-assisted vehicle or a partially autonomous vehicle, and thus, the adaptive cruise, lane keeping assist, and/or automatic emergency braking functions, etc. of vehicle 122 may be controlled according to driving habits of user 111. In this way, in a driving assistance scene, the driving experience of the user can be improved, thereby expanding the application range of the embodiment of the present disclosure.

Alternatively, vehicle 122 may be a fully autonomous vehicle, and thus, the fully autonomous driving process of vehicle 122 may be controlled according to the driving habits of user 111. In this manner, during full autopilot, the autonomously driven vehicle 122 can still provide the user 111 with the same pleasure and enjoyment of driving by himself, enhancing the user experience. One example classification of an automatic driving level may include the following six levels: l0, no automation configuration, it is completely the driver himself driving the vehicle without any active safety configuration; l1, driver assistance, where the vehicle has certain functions to assist the driver in performing certain tasks of lateral or longitudinal vehicle movement (but not simultaneously performing the complex task of parallel overtaking), the driver still assumes most of the vehicle control capability; l2, advanced driving assistance, vehicles are capable of some ability to assist the driver in performing vehicle movement tasks including lateral and longitudinal (vehicles can autonomously perform certain complex tasks), but the driver needs to monitor the vehicle in real time to accomplish these tasks; l3, automatic driving under a specific scene, wherein when the vehicle is in dynamic driving, the automatic driving system can be used for the whole intervention of the vehicle to drive under the consent of a user, and the user can correct errors generated when the vehicle is in automatic driving at any time; l4, advanced automatic driving, all operations are realized by an automatic driving system when the vehicle runs, and in an execution scene, the vehicle has no unrealistic expression and completely does not need the operation intervention of a user; l5, the vehicle can reach the destination by automatic driving without user operation, whether in a specific execution scenario or not.

In some embodiments, where vehicle 122 is at a higher level of autonomous driving than vehicle 121. Alternatively, vehicle 122 belongs to the same autonomous driving class as vehicle 121, but vehicle 122 has more driving assistance functions than vehicle 121. User manipulation data of user 111 during manipulation of vehicle 121 may be collected. In this way, the driving behavior data of the user on the automatic driving vehicles with different grades or different functions can be collected, the data of the automatic driving vehicles with high grades or functions under more complex working conditions are continuously collected along with the improvement of the automatic driving grades or functions of the driving vehicles, and the driving behavior data and the driving habit data of the user are continuously improved, so that the driving behavior database of the user is enriched, and the personalized driving experience of the user is further improved.

Fig. 3 illustrates another example environment 300 for providing a personalized driving experience in accordance with an embodiment of the disclosure. In contrast to fig. 1, the driving behavior server 130 also stores driving behavior data 132 collected during the driving of the vehicle 123 by the further user 112. Then, when the user 112 is riding in the autonomous vehicle 122, the vehicle 122 obtains the driving behavior data 132 of the user 112 from the driving behavior server 130, and accordingly determines the driving habits of the user 112, which are faster, faster acceleration, faster braking, closer following, etc., unlike the user 111, and thus controls the unmanned vehicle 122 to travel at a faster speed. In this way, even if different users (e.g., user 111 in fig. 1, user 112 in fig. 3) ride the same vehicle (vehicle 122), they can respectively obtain different driving experiences provided according to respective driving habits, thereby satisfying the driving demands of different people.

In some embodiments, the vehicle 122 may verify the identity of the person in its vehicle by biometric identification and/or account login, etc., and obtain corresponding driving behavior data from the driving behavior server 130 only after the verification of identity is passed. The biometric identification may include fingerprint identification, face identification, voiceprint identification, and the like, wherein the fingerprint identification is verified by collecting a fingerprint of the user, the face identification is performed by acquiring a face image of the user in the vehicle through the vehicle-mounted camera, and the voiceprint identification is performed by collecting voice of the user in the vehicle through the vehicle-mounted microphone. The identity of the user is verified in a biological characteristic recognition mode, so that the user verification efficiency can be improved, and unnecessary login burden on the user is reduced. Alternatively, login may also be accomplished by the user entering an account number and password in a graphical user interface of the vehicle 122, thereby completing authentication of the user and acquisition of the user's historical driving behavior data.

Fig. 4 illustrates yet another example environment 400 for providing a personalized driving experience in accordance with an embodiment of the disclosure. Unlike the example of fig. 3 (in fig. 3 multiple users may share the same unmanned vehicle, e.g., a taxi), in the example of fig. 4, each user has their own current vehicle (e.g., vehicle 122 and vehicle 124 may be dedicated vehicles for user 111 and user 112, respectively), e.g., user 111 is riding his current vehicle 122, user 112 is riding his current vehicle 124, and by driving

behavior data

131 and 132,

vehicles

122 and 124 can be controlled to adapt to the driving habits of

users

111 and 112, respectively, to travel.

Fig. 5 shows a block diagram of an example architecture of an in-vehicle driving assistance system 500 according to an embodiment of the present disclosure. For example, the in-vehicle driving assistance system 500 may be an Advanced Driving Assistance System (ADAS), which may be deployed at the vehicle 121 shown with reference to fig. 1 for collecting driving behavior data of the user.

As shown in fig. 5, the in-vehicle driving assistance system 500 includes an image acquisition device 510 (such as a camera), a radar device 520 (such as a laser radar), a satellite positioning system 530 (such as a Global Positioning System (GPS)), a throttle sensor 540, a brake sensor 550, a steering sensor 560, an Electronic Control Unit (ECU)570, an actuator 580, and a communication module 590, wherein the actuator is configured to perform predetermined tasks according to processing of collected data by the ECU 570, and the tasks may include, but are not limited to, adaptive cruise, lane departure warning, lane keeping assist, pedestrian protection, automatic parking, electric vehicle warning, and the like. According to an embodiment of the present disclosure, the vehicle 121 may collect the driving behavior data 131 of the user 111 through its on-board driving assistance system 500 and transmit the driving behavior data 131 to the driving behavior server 130 for storage through the communication module 590.

The image capturing device 510 may include a front view camera that analyzes video content to provide Lane Departure Warning (LDW), automatic Lane Keeping Assist (LKA), high beam/low beam control, and Traffic Sign Recognition (TSR), and a rear view camera system that may help a driver to find objects or people behind the vehicle to back up and park smoothly in a parking spot while ensuring safety. The radar device 520 supports an adaptive cruise control, collision avoidance, and collision warning system, etc., with or without automatic steering and brake intervention functions. In a collision warning system, a radar chipset may detect and track targets, automatically adjust the speed of the vehicle and control the distance to the vehicle ahead according to the traffic conditions ahead, alert the driver in the event of a collision and initiate emergency braking intervention. The satellite positioning system 530 is used to acquire and record position information of the vehicle. According to embodiments of the present disclosure, information collected by the image collection device 510, the radar device 520, and the satellite positioning system 530 may be stored as part of the driving behavior data.

The throttle sensor 540, the brake sensor 550, and the steering sensor 560 are used to collect a throttle position, a brake position, and a steering wheel position, respectively, of a user during driving of the vehicle, which may be stored as part of driving behavior data. In some embodiments, various driving behavior parameters may be stored in a predetermined fixed format, and data for each user is stored in association with their account. When a user needs to replace the vehicle or use a vehicle with a higher automatic driving grade, the new vehicle can immediately learn the driving habits and behaviors of the vehicle user and drive the vehicle according to individual preferences only by transferring the collected personalized driving behavior data to the newly used vehicle. Further, an in-vehicle driving assistance system 500 according to an embodiment of the present disclosure may also be deployed at the vehicle 122 shown in fig. 1, or a more advanced system than the in-vehicle driving assistance system 500 may be deployed.

Generally speaking, the driving behavior of the same driver in different scenes may be different, for example, it is common to open relatively slower in rainy days than in sunny days. In some embodiments, different scenes may be distinguished according to one or more of weather conditions, road types, time periods, and area types, and driving behavior data of the user is collected in the different scenes, so that finer-grained data collection is achieved, subsequent driving behavior analysis and automatic driving control are facilitated, and the driving experience of the user on the current vehicle is further improved. The scenes can be divided into sunny days, rainy days, snowy days and the like according to the weather conditions, the scenes can be divided into straight roads, turning guide-in, crossroads and the like according to the road types, the scenes can be divided into daytime, night, early morning, dusk and the like according to the time periods, and the scenes can be divided into cities, suburbs, villages and the like according to the region types.

Fig. 6A shows a schematic diagram of providing a personalized driving experience in a sunny scene 600, according to an embodiment of the disclosure. In a sunny scene 600, with the sun 610 high, visibility high, and the ground generally not slippery, the autopilot system may control the distance between the vehicle 122 and the preceding vehicle 620 to maintain at least a first distance 630. Fig. 6B shows a schematic diagram of providing a personalized driving experience in a rainy scene 650 according to an embodiment of the disclosure. In a rainy day scenario 650, where cloud 660 is raining, resulting in slippery road surfaces, the autonomous driving system may control the distance between vehicle 122 and preceding vehicle 620 to maintain at least a second distance 670. Since the following distance of the user 111 during driving is usually longer in rainy days than in sunny days, the vehicle distance 670 in rainy days may be larger than the vehicle distance 630 in sunny days when the vehicle 122 is driven automatically for the user 111 accordingly. In this way, the automatic driving function can be more humanized, and the driving experience of the user is further improved.

In some embodiments, an average speed of user 111 driving vehicle 121 on the highway may also be determined, and then autonomous driving of vehicle 122 on the highway may be controlled based on this average speed as autonomous vehicle 122 travels on the highway. In this way, the automatic driving can be more consistent with the driving speed of the user, and the satisfaction degree of the user is improved.

FIG. 7 shows a flowchart of a method 700 for processing driving feedback of a user according to an embodiment of the present disclosure. It should be understood that the method 700 depicted in fig. 7 may be performed after the method 200. At block 702, vehicle 122 is controlled to provide user 111 with a driving experience that conforms to his driving habits. At block 704, a determination is made as to whether driving feedback from user 111 is received within vehicle 122, e.g., user 111 may provide driving feedback via speech, such as the user saying "turn on slow". If no feedback is received from user 111, return to block 702 to continue controlling vehicle driving. If user feedback is received at 704, control of the currently riding vehicle 122 is adjusted at 706, e.g., such that the vehicle 122 slows down a little. Next, at block 708, driving environment data of the vehicle 122 is collected for a previous period of time fed back by the user 111, and at block 710, the autonomous driving algorithm is modified based on the driving environment data. In this way, user feedback can be processed and predetermined mode parameters can be modified, making the autopilot or driveassist function more intelligent and accurate. Further, algorithm iterations of the intelligent driving system may also be facilitated through user feedback, whereby the autonomous driving algorithm is automatically modified through user feedback.

Fig. 8 illustrates a schematic block diagram of an example device 800 that may be used to implement embodiments of the present disclosure. It should be understood that the device 800 may be included within the vehicle 122 described with reference to fig. 1 or as the server 130. As shown, device 800 includes a Central Processing Unit (CPU)801 that may perform various appropriate actions and processes in accordance with computer program instructions stored in a Read Only Memory (ROM)802 or loaded from a storage unit 808 into a Random Access Memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the device 800 can also be stored. The CPU 801, ROM 802, and RAM 803 are connected to each other via a bus 804. An input/output (I/O) interface 805 is also connected to bus 804.

A number of components in the device 800 are connected to the I/O interface 805, including: an input unit 806, such as a keyboard, a mouse, or the like; an output unit 807 such as various types of displays, speakers, and the like; a storage unit 808, such as a magnetic disk, optical disk, or the like; and a communication unit 809 such as a network card, modem, wireless communication transceiver, etc. The communication unit 809 allows the device 800 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.

The processing unit 801 performs the various methods and processes described above, such as the methods 200 and/or 700. For example, in some embodiments, the methods may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 808. In some embodiments, part or all of the computer program can be loaded and/or installed onto device 800 via ROM 802 and/or communications unit 809. When loaded into RAM 803 and executed by CPU 801, a computer program may perform one or more of the acts or steps of the methods described above. Alternatively, in other embodiments, CPU 801 may be configured to perform the method by any other suitable means (e.g., by way of firmware).

The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), System On Chip (SOCs), load programmable logic devices (CPLDs), and the like.

Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

Further, while acts or steps are depicted in a particular order, this should be understood as requiring that such acts or steps be performed in the particular order shown or in sequential order, or that all illustrated acts or steps be performed, to achieve desirable results. Under certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limitations on the scope of the disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented in multiple implementations separately or in any suitable subcombination.

Although embodiments of the disclosure have been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.

Claims

1. A method (200) for providing a personalized driving experience, comprising:

obtaining (202) first driving behavior data (131) of a first user (111) collected from at least one vehicle (121), the first driving behavior data (131) comprising user handling data collected by the first user (111) during handling of the at least one vehicle (121);

controlling (206) a current vehicle (121, 122) to provide a personalized driving experience to the first user (111) based on the first driving behavior data (131) of the first user (111).

2. The method (200) of claim 1, wherein controlling (206) a current vehicle (121, 122) to provide a personalized driving experience to the first user (111) comprises:

determining (204) a first driving habit of the first user (111) based on the first driving behavior data (131) of the first user (111); and

controlling (206) a current vehicle (121, 122) to provide a personalized driving experience corresponding to the first driving habit to the first user (111).

3. The method (200) according to claim 1, wherein the current vehicle (122) is a different vehicle than the at least one vehicle (121), and the current vehicle (122) is of a higher autonomous driving class than the at least one vehicle (121), or the current vehicle (122) belongs to the same autonomous driving class as the at least one vehicle (121) and the current vehicle (122) has more auxiliary driving functions than the at least one vehicle (121), the method further comprising:

user handling data of the first user (111) during handling of the current vehicle (122) is collected.

4. The method (200) of claim 2, further comprising:

determining a second driving habit of a second user (112) based on second driving behavior data (132) collected by the second user (112) during driving of one vehicle (121, 123), the second driving habit differing from the first driving habit in at least one of: driving speed, following distance, acceleration control and brake control; and

controlling the current vehicle (121, 122) to provide a personalized driving experience corresponding to the second driving habit to the second user (112).

5. The method (200) according to claim 1, wherein obtaining (202) first driving behavior data (131) of a first user (111) collected from at least one vehicle (121) comprises:

verifying a first identity of the first user (111) by biometric identification or account login in response to the first user (111) entering the current vehicle (121, 122);

determining a first identity of the first user (111) in response to the first identity being verified; and

-obtaining the first driving behavior data (131) from a driving behavior server (130) based on the first identification of the first user (111), the driving behavior server (130) storing driving behavior data (131, 132) of a plurality of users (111, 112) collected by an on-board driving assistance system (500), and the on-board driving assistance system (500) comprising an image acquisition device (510), a radar device (520) and a satellite positioning system (530).

6. The method (200) according to claim 2, wherein obtaining (202) first driving behavior data (131) of the first user (111) collected from at least one vehicle (121) comprises:

obtaining first context data collected by the first user (111) during the maneuver of the at least one vehicle (121) in a first context (600); and

obtaining second context data collected by the first user (111) during the maneuver of the at least one vehicle (121) in a second context (650), the first context (600) and the second context (650) being distinguished according to at least one of: weather conditions, road type, time period, and area type.

7. The method (200) of claim 6, wherein controlling (206) a current vehicle (121, 122) to provide a personalized driving experience corresponding to the first driving habit to the first user (111) comprises:

controlling a distance between the current vehicle (121, 122) and a preceding vehicle (620) to maintain at least a first distance (630) in response to the first user (111) riding the current vehicle (121, 122) in the first scene (600); and

-in response to the first user (111) riding the current vehicle (121, 122) in the second scenario (650), controlling a distance between the current vehicle (121, 122) and a preceding vehicle (620) to maintain at least a second distance (670), the first scenario (600) being a sunny scenario and the second scenario (650) being a rainy scenario, and the first distance (630) being smaller than the second distance (670).

8. The method (200) of claim 2, wherein controlling (206) a current vehicle (121, 122) to provide a personalized driving experience corresponding to the first driving habit to the first user (111) comprises:

-determining an average speed of said first user (111) driving said at least one vehicle (121) on a highway; and

controlling the automatic driving of the current vehicle (121, 122) on the highway according to the average speed in response to the current vehicle (121, 122) traveling on the highway.

9. The method (200) of claim 2, wherein controlling (206) a current vehicle (121, 122) to provide a personalized driving experience corresponding to the first driving habit to the first user (111) comprises:

in response to receiving (704) driving feedback from the first user (111), adjusting (706) driving control of the current vehicle (121, 122);

collecting (708) driving environment data of the current vehicle (121, 122) within a predetermined time period before the driving feedback; and

modifying (710) an autonomous driving algorithm based on the collected driving environment data.

10. The method (200) of claim 2, wherein controlling (206) a current vehicle (121, 122) to provide a personalized driving experience corresponding to the first driving habit to the first user (111) comprises:

in response to the current vehicle (121, 122) being an assisted driving vehicle or a partially autonomous vehicle, controlling at least one of the following functions of the current vehicle (121, 122) in accordance with the first driving habit: adaptive cruise, lane keeping assist and automatic emergency braking.

11. The method (200) of claim 2, wherein controlling (206) a current vehicle (121, 122) to provide a personalized driving experience corresponding to the first driving habit to the first user (111) comprises:

in response to a current vehicle (121, 122) being a fully autonomous vehicle, a fully autonomous driving process of the current vehicle (121, 122) is controlled in accordance with the first driving habit.

12. An apparatus (800) for providing a personalized driving experience, comprising:

at least one processing unit (801); and

at least one memory (802, 803), the at least one memory (802, 803) coupled to the at least one processing unit (801) and storing instructions for execution by the at least one processing unit (801), which when executed by the at least one processing unit (801) cause the apparatus (800) to perform acts comprising:

13. The apparatus (800) of claim 12, wherein controlling (206) a current vehicle (121, 122) to provide a personalized driving experience to the first user (111) comprises:

14. The apparatus (800) of claim 12, wherein the current vehicle (122) is a different vehicle than the at least one vehicle (121), and the current vehicle (122) is of a higher autonomous driving class than the at least one vehicle (121), or the current vehicle (122) is of the same autonomous driving class as the at least one vehicle (121) and the current vehicle (122) has more assisted driving functions than the at least one vehicle (121), the acts further comprising:

15. The apparatus (800) of claim 13, the acts further comprising:

16. The apparatus (800) of claim 12, wherein obtaining (202) first driving behavior data (131) of the first user (111) collected from the at least one vehicle (121) comprises:

17. The apparatus (800) of claim 13, wherein obtaining (202) first driving behavior data (131) of the first user (111) collected from the at least one vehicle (121) comprises:

18. The apparatus (800) of claim 17, wherein controlling (206) a current vehicle (121, 122) to provide a personalized driving experience corresponding to the first driving habit to the first user (111) comprises:

19. The apparatus (800) of claim 13, wherein controlling (206) a current vehicle (121, 122) to provide a personalized driving experience corresponding to the first driving habit to the first user (111) comprises:

20. The apparatus (800) of claim 13, wherein controlling (206) a current vehicle (121, 122) to provide a personalized driving experience corresponding to the first driving habit to the first user (111) comprises:

21. The apparatus (800) of claim 13, wherein controlling (206) a current vehicle (121, 122) to provide a personalized driving experience corresponding to the first driving habit to the first user (111) comprises:

22. The apparatus (800) of claim 13, wherein controlling (206) a current vehicle (121, 122) to provide a personalized driving experience corresponding to the first driving habit to the first user (111) comprises:

23. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method (200) according to any one of claims 1-11.

24. A vehicle (122, 124) comprising an apparatus (600) for providing a personalized driving experience according to any of claims 12-22.