CN112863244A

CN112863244A - Method and device for promoting safe driving of vehicle

Info

Publication number: CN112863244A
Application number: CN201911188008.4A
Authority: CN
Inventors: 陈勇
Original assignee: Volkswagen AG
Current assignee: Volkswagen AG
Priority date: 2019-11-28
Filing date: 2019-11-28
Publication date: 2021-05-28
Anticipated expiration: 2039-11-28
Also published as: CN112863244B; WO2021104833A1

Abstract

The invention relates to a method and a device for promoting safe driving of a vehicle, the method comprising: determining a current driving scene of a vehicle; obtaining at least one vehicle accident scenario from a database; judging whether the current driving scene of the vehicle is matched with the at least one vehicle accident scene; and automatically performing an action to avoid the vehicle entering the at least one vehicle accident scenario if the current driving scenario of the vehicle matches the at least one vehicle accident scenario.

Description

Method and device for promoting safe driving of vehicle

Technical Field

The present invention relates to a method and apparatus for facilitating safe driving of a vehicle.

Background

In the field of automatic driving of automobiles, safe driving of the automobile is an important consideration. Current autonomous vehicles travel on the road by mounting various sensors and controllers, and continuously optimize the autonomous driving algorithm by collecting safe driving data during the natural driving of the vehicle. The data collected by this method belong to safe driving data in normal or non-extreme situations. The safe driving data is used for training the intelligent vehicle to know what is a good safe driving mode, so that the intelligent vehicle only learns the driving mode under the non-accident condition. However, during actual driving, a bad situation, that is, an accident, often occurs. Since it is often very difficult and costly to collect driving data in extreme (e.g., accident) situations through the vehicle's own natural driving conditions, people are often unable to train current autonomous cars how to deal with the accident scenario based on the data in extreme situations.

Therefore, in order to promote safe driving of an autonomous vehicle, it is desirable to be able to make an autonomous driving system that teaches the vehicle in combination with safe driving data and vehicle accident data to know what is a safe driving style and what is a dangerous driving style, thereby improving the level of intelligent learning and efficiency of the vehicle.

Disclosure of Invention

This summary is provided to introduce a selection of concepts that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.

It is an object of the present invention to provide a method and apparatus for facilitating safe driving of a vehicle that at least partially overcomes the deficiencies of the prior art.

An embodiment of the present invention provides a method for facilitating safe driving of a vehicle, including: determining a current driving scene of a vehicle; obtaining at least one vehicle accident scenario from a database; judging whether the current driving scene of the vehicle is matched with the at least one vehicle accident scene; and automatically performing an action to avoid the vehicle entering the at least one vehicle accident scenario if the current driving scenario of the vehicle matches the at least one vehicle accident scenario.

Embodiments of the present invention also provide an apparatus for facilitating safe driving of a vehicle, including: the determining module is used for determining the current driving scene of the vehicle; an obtaining module for obtaining at least one vehicle accident scenario from a database; the judging module is used for judging whether the current driving scene of the vehicle is matched with the at least one vehicle accident scene; and the execution module is used for automatically executing actions to avoid the vehicle from entering the at least one vehicle accident scene if the current driving scene of the vehicle is matched with the at least one vehicle accident scene.

An apparatus for promoting safe driving of a vehicle according to an embodiment of the present invention includes: a processor; and a memory for storing executable instructions, wherein the executable instructions, when executed, cause the processor to perform the aforementioned method.

A machine-readable medium according to an embodiment of the invention has stored thereon executable instructions, which when executed, cause a machine to perform the aforementioned method.

A system for facilitating safe driving of a vehicle according to an embodiment of the present invention includes: a sensor for sensing running condition information of the vehicle and surrounding environment information of the vehicle; and a control device for performing the aforementioned method.

Wherein the system further includes an execution device for executing an operation on the vehicle based on an output of the control device.

As can be seen from the above description, the solution of the embodiment of the present invention performs punitive training for some erroneous or dangerous driving behaviors of the autonomous vehicle by using the training model based on the accident data in the natural driving data, so that the autonomous vehicle can avoid entering an accident scene in which an accident may occur.

It should be noted that one or more of the above aspects include the features described in detail below and particularly pointed out in the claims. The following description and the annexed drawings set forth in detail certain illustrative features of the one or more aspects. These features are indicative of but a few of the various ways in which the principles of various aspects may be employed and the present disclosure is intended to include all such aspects and their equivalents.

Drawings

The disclosed aspects will hereinafter be described in conjunction with the appended drawings, which are provided to illustrate, but not to limit, the disclosed aspects.

FIG. 1 illustrates an architectural diagram of a system for facilitating safe driving of a vehicle, in accordance with an embodiment of the present invention;

FIG. 2 illustrates a flow diagram of a method for facilitating safe driving of a vehicle, in accordance with an embodiment of the present invention;

FIG. 3 illustrates a flow diagram of a method for facilitating safe driving of a vehicle in accordance with another embodiment of the present invention;

FIG. 4 shows an exemplary diagram of a method for generating a vehicle accident scenario, in accordance with one embodiment of the present invention;

FIG. 5 shows a schematic view of an apparatus for facilitating safe driving of a vehicle according to an embodiment of the invention;

fig. 6 shows a schematic view of an apparatus for facilitating safe driving of a vehicle according to an embodiment of the present invention.

Detailed Description

The present disclosure will now be discussed with reference to various exemplary embodiments. It is to be understood that the discussion of these embodiments is merely intended to enable those skilled in the art to better understand and thereby practice the embodiments of the present disclosure, and does not teach any limitation as to the scope of the present disclosure.

Various embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

FIG. 1 illustrates an architectural diagram of a system 100 for facilitating safe driving of a vehicle, in accordance with an embodiment of the present invention. As shown in fig. 1, an exemplary system 100 for facilitating safe driving of a vehicle may include a sensor 102, a processor 104, a control device 106, a database 108, and an execution device 110.

The sensor 102 may include various types of sensors for sensing running condition information of the vehicle and surrounding environment information of the vehicle, for example, a speed sensor for detecting a speed and/or acceleration of the vehicle itself, a radar sensor for detecting a size, a distance, a moving speed, and the like of an object near the vehicle, a temperature sensor for detecting an engine temperature, an image sensor for capturing a surrounding environment of the vehicle, a brightness sensor, a sound sensor, and the like. For simplicity, only a few examples of sensors for use in a vehicle are listed here, and in practice there may be any available sensors suitable for use in a vehicle. The sensor 102 may communicate the detected data or information to the processor 104 and/or the control device 106.

The processor 104 may analyze the data detected by the sensor 102 to determine the current driving scenario of the vehicle. In some embodiments, the current driving scenario of the vehicle may be represented by means of a feature set, wherein the features in the feature set include, but are not limited to, at least one of: the information specific to the vehicle, the current vehicle speed, the current time, the place where the vehicle is located, the surrounding environment information, the basic information of the automatic driving system or the driver of the vehicle, and the like. In some examples, the intrinsic information of the vehicle includes, but is not limited to, model, brand, manufacturer, displacement, transmission, engine information, factory hours, total distance and time traveled, wear, drive style, etc.; basic information of the automatic driving system of the vehicle includes, but is not limited to, a development company of the system, a version of the system, software and hardware parameters of the system, and the like; basic information of the driver of the vehicle includes, but is not limited to, sex, age, driving age, physical condition, driving style (e.g., like driving fast, like driving slow, like merging and overtaking, etc.), and the like. In some examples, the ambient environment information includes, but is not limited to, ambient environment temperature, brightness, sound, weather, size of other objects in the surroundings, distance from the host vehicle, speed, minimum and maximum speed limits for the road segment, road conditions, road surface quality, and the like. By way of example, the current driving scenario of the vehicle can be represented by the following exemplary feature set F1: [ 8 o' clock, county road, rainy day, smooth road condition, poor road surface quality, highest speed limit of 100, vehicle speed of 100, other vehicles in front of 100 meters, other vehicles in back of 100 meters, vehicle type A, running for 10 years, tire aging, automatic driving system version 1 ]. It is to be understood that, for ease of illustration, only a few exemplary features are listed herein; in practice, the set of features representing the current driving scenario of the vehicle may include more, less, or different features than the examples described above.

The processor 104 provides the analyzed data to the control device 106 so that the control device 106 can compare the current driving scenario of the vehicle determined at the processor 104 with the vehicle accident scenario obtained from the database 108. Herein, a vehicle accident scenario may be represented by means of a feature set, wherein features in the feature set may include, but are not limited to, at least one of: the type, time, place, reason, surrounding environment, vehicle speed, vehicle damage condition, casualty condition, optional vehicle intrinsic information and the like of the accident occurrence. In some examples, the reasons for the occurrence of an accident include, but are not limited to: a vehicle speed exceeding or falling below a predetermined vehicle speed, a distance from a nearby vehicle or object falling below a predetermined distance, a steering wheel rotation angle exceeding or falling below a predetermined angle, a steering wheel rotation direction error, a braking force or degree exceeding or falling below a predetermined value, a vehicle malfunction, or the like; the inherent information of the vehicle includes but is not limited to the model, brand, manufacturer, displacement, transmission, engine information, factory time, total travel distance and time, loss condition, driving mode and the like of the vehicle; the surrounding environment includes, but is not limited to, the temperature, brightness, sound, weather, size of surrounding other objects, distance from the host vehicle, speed, minimum and maximum speed limits for the road section, road conditions, road surface quality, etc. of the surrounding environment at the time of the accident. By way of example, an exemplary vehicle accident scenario may be represented by the following feature set F': [ rear-end collision, 8 o' clock in the evening, county road, rainy day, smooth road condition, poor road surface quality, maximum speed limit of 100, vehicle speed of 120, exceeding the predetermined vehicle speed of 20%, vehicle type A, having run for 10 years, tire aging, automatic driving system version 1, serious damage to front bumper, and light injury to vehicle occupants ]. It is to be understood that, for ease of illustration, only a few exemplary features are listed herein; in practice, the set of features representing a vehicle accident scenario may include more, less, or different features than the examples described above.

In some embodiments, the control device 106 may match the current driving scene of the vehicle with the vehicle accident scene by means of feature comparison. If the two match or the degree of match reaches a threshold, the control device 106 may instruct the performance device 110 to automatically perform an action to avoid the vehicle entering an accident scenario. It is to be understood that any suitable matching or comparison method may be employed to perform the matching operation of the current driving scenario of the vehicle and the vehicle accident scenario.

In some examples, automatically performing the action may include adjusting, by an autonomous driving system of the vehicle, a current operating state of the vehicle, e.g., from a uniform speed travel operation of the vehicle to performing at least one action including: braking, stopping, turning, accelerating, decelerating, doubling, etc. In other examples, automatically performing the operation may include sending a prompt signal to a user of the vehicle, for example, a sound signal such as "accelerate and merge, current driving situation conforms to a rear-end accident scene", displaying a warning message on a screen of an in-vehicle display, projecting a warning message on a glass in front of the user, and the like. Herein, the user of the vehicle includes at least one of an automatic driving system of the vehicle or a human driver. In some alternative examples, the control device 106 may also provide an indication signal to other vehicles in the vicinity of the host vehicle to instruct users of the other vehicles to perform actions to avoid entering the accident scenario. In some examples, the indication signal may include a sound signal, a light signal, an image signal, and the like.

For example, when the features in the feature set of the vehicle current driving scenario F1 are matched with the corresponding features in the feature set F' of the vehicle accident scenario, the control device may determine that the features are matched with each other or that the matching degree reaches a threshold value, so that the control device may determine that the vehicle may enter a rear-end accident scenario, and instruct the execution device to adjust the current driving state of the vehicle, for example, to decelerate and/or turn to another lane. Alternatively, the control apparatus may also provide an indication signal to the rear vehicle, such as a voice signal, an image signal, or the like, indicating that the rear vehicle is decelerating. As another example, assuming that the current driving scenario F2 of the vehicle is [ 2 pm, highway, sunny day, smooth road condition, good road surface quality, highest speed limit 120, vehicle speed 100, no other object within 200 m around, vehicle type a, driven for 0.5 year, new tire, version 10 of the automatic driving system ], when the control device matches the current driving scenario F2 with the accident scenario F', it may be determined that the two do not match or the matching degree does not reach the threshold value, the control device does not instruct the execution device to adjust the current driving state of the vehicle, and optionally continues to obtain the new current driving scenario from the processor 104.

It should be understood that although the processor 104 is shown in fig. 1 as being separate from the control device 106, in some embodiments, the processor 104 may be incorporated into the control device 106. Furthermore, although database 108 is shown in fig. 1 as being included in system 100, in some examples, database 108 may also be located external to system 100 and may communicate data with system 100 via wired or wireless communication. In addition, the various components included in the system 100 may be connected in any manner, whether wirelessly or by wire.

FIG. 2 illustrates a flow diagram of a method 200 for facilitating safe driving of a vehicle, in accordance with one embodiment of the present invention. The method 200 shown in fig. 2 may be implemented by the system 100, for example.

As shown in FIG. 2, at block 202, a current driving scenario, for example, a current driving scenario of a vehicle in motion, is determined.

At block 204, a vehicle accident scenario is obtained from a database. In some examples, the database may be a local database disposed within the vehicle or an external database communicable with an autonomous driving system of the vehicle, a cloud database, or the like.

At block 206, a match between the current driving scenario of the vehicle and the vehicle accident scenario may be determined, such as a full match, a partial match, a threshold level of match, and so on.

At block 208, if the current driving scenario of the vehicle matches or matches the accident scenario or scenarios obtained from the database, or the degree of match reaches a threshold, an action is automatically performed to avoid the vehicle entering the vehicle accident scenario.

FIG. 3 shows a schematic diagram of a method 300 for facilitating safe driving of a vehicle, in accordance with another embodiment of the invention. The method 300 shown in fig. 3 may be implemented by the system 100, for example.

As shown in fig. 3, the method 300 may include, at block 302, sensing travel conditions and ambient environment information, which may be performed, for example, by the sensors 102 in the system 100.

At block 304, a current driving scenario may be determined, for example, from the driving conditions and ambient environment information sensed at 302. This may be performed, for example, by the processor 104 in the system 100.

At block 306, a vehicle accident scenario may be obtained from a database. In some examples, the vehicle accident scenario may be generated by training a model based on real accident data and pre-stored in a database. This may be performed, for example, by the control device 106 in the system 100.

At block 308, a determination may be made as to whether the current driving scenario of the vehicle determined at block 304 matches at least one of the vehicle accident scenarios obtained at block 306. If not, i.e., not matched or the degree of match is below a threshold, the system may optionally continue to determine the current driving scenario of the vehicle. If so, i.e., matches or the degree of match is above a threshold, the method may proceed to block 310 to automatically perform an action to avoid the vehicle entering a vehicle accident scenario.

Optionally, the method 300 may further include, at block 312, providing an indication signal to other vehicles in the vicinity of the vehicle to instruct users of the other vehicles to perform an action to avoid entering the vehicle accident scenario.

FIG. 4 shows an example process 400 for obtaining a vehicle accident scenario, in accordance with one embodiment of the present invention. For example, the process may be one example for the operations in block 204 in method 200 and block 306 in method 300. In this exemplary process, a vehicle accident scenario may be generated by training a model based on the collected real vehicle accident data.

At block 402, vehicle accident data may be collected. In some examples, the vehicle accident data is data about a real accident that has occurred. In this context, the vehicle accident data may be collected by a third party or a cloud server from one or more vehicle accidents that have occurred. By way of example, the third party may include at least one of: traffic authorities, insurance companies, tachograph data collection companies, and the like.

At block 404, the collected vehicle accident data is analyzed to classify the accident data into valid accident data and invalid accident data based at least on the cause of the accident. For example, an accident that is caused by the driver's operation and that is avoidable in the case of automatic driving may be generally regarded as an ineffective accident, such as an accident that the driver dozes off or looks at a cell phone, while an accident that is caused by the non-driver's operation and that is avoidable in the case of automatic driving may be generally regarded as an effective accident, such as an accident caused by a rear-vehicle collision.

For example, data relating to an accident that the vehicle has lost time to avoid due to other objects (e.g., pedestrians, other vehicles, animals, thrown objects, etc.) that suddenly appear in the vicinity of the vehicle while the vehicle is in normal driving may be considered valid accident data. Such accidents may not be completely avoided in case of either manual driving by a person or automatic driving of a vehicle by an automatic driving system. Therefore, by collecting the accident data, generating an accident scene based on the effective accident data through the training model, and providing the accident scene to the automatic driving system of the vehicle, the automatic driving system can enable the vehicle to avoid the accident in the subsequent driving process.

In other examples, for accidents caused by drivers dozing or inattention to the surrounding environment, a vehicle in an autonomous driving state may avoid such accidents. Thus, data relating to such incidents may be considered invalid incident data.

The above examples are merely exemplary and in practice the classification of accident data may be done in any suitable way known.

At block 406, valid incident data is extracted from the classified incident data.

At block 408, a vehicle accident scenario may be generated from the extracted valid accident data for comparison or matching with a current driving scenario during vehicle driving.

Optionally, the generated accident scenario may be updated as the collected vehicle accident data changes. In some instances, the valid accident data in the vehicle accident data collected from the most recent accident or accidents is also updated as the actual accident data may increase over time and the cause of the accident may change. For example, over time and after an autonomous driving system is trained using the techniques of the present invention, some valid accident data may be updated to invalid accident data. For example, an initial rear-end collision may be considered as a valid accident that is not caused by the driver's operation and is inevitable in the case of automatic driving; after the technology of the invention is adopted, the automatic driving system can automatically execute acceleration and/or merging actions when judging that the current driving scene of the vehicle is matched with an accident scene (for example, the distance between the front vehicle and the rear vehicle is less than 50 meters) so as to avoid rear-end accidents. Thus, such rear-end collisions may be updated to invalid accidents in the accident data collected after the techniques of the present invention are employed.

It will be appreciated by those skilled in the art that the above examples are merely exemplary, and in other embodiments, the vehicle accident data may be classified and the accident scenario generated therefrom in any other manner.

Fig. 5 shows a schematic view of an apparatus 500 for facilitating safe driving of a vehicle according to an embodiment of the present invention. The apparatus 500 shown in fig. 5 can be implemented by software, hardware or a combination of software and hardware.

As shown in fig. 5, the apparatus 500 may include a determination module 502, an obtaining module 504, a determination module 506, and an execution module 508.

The determination module 502 may be used to determine a current driving scenario of the vehicle.

The obtaining module 504 may be used to obtain at least one vehicle accident scenario from a database, wherein the at least one vehicle accident scenario is generated by training a model based on the collected vehicle accident data. In some examples, the vehicle accident data is classified into valid accident data and invalid accident data based at least on a cause of the accident occurrence, and wherein the at least one vehicle accident scenario is generated by training a model based on the valid accident data. In some implementations, the vehicle accident data is collected by a third party or by a cloud server from one or more vehicle accidents that have occurred. Herein, the vehicle accident scenario is represented by a set of features comprising at least one of the following features: the type, time, place, reason, surrounding environment, vehicle speed, vehicle damage condition, casualty condition, inherent information of the vehicle and the like of the accident occurrence.

The determining module 506 may be configured to determine whether the current driving scenario of the vehicle matches the at least one vehicle accident scenario.

The performing module 508 may be configured to automatically perform an action to avoid the vehicle entering the at least one vehicle accident scenario if the current driving scenario of the vehicle matches the at least one vehicle accident scenario, for example, the degree of matching reaches a threshold.

Further, the obtaining module 504 is further configured for: obtaining the updated at least one vehicle accident scenario. In some embodiments, the updated at least one vehicle accident scenario is generated further based on valid accident data in the updated vehicle accident data, and wherein the updated vehicle accident data is derived based on vehicle accident data collected by the third party or the cloud server from one or more newly occurring vehicle accidents.

Further, optionally, the apparatus 500 may further comprise a transmitting module for transmitting an indication signal to other vehicles in the vicinity of the vehicle, wherein the indication signal is for instructing users of the other vehicles to perform an action to avoid entering the at least one vehicle accident scenario.

Fig. 6 shows a schematic diagram of an apparatus 600 for facilitating safe driving of a vehicle according to an embodiment of the invention.

As shown in fig. 6, device 600 may include a processor 602 and a memory 604, where memory 604 is to store executable instructions that, when executed, cause processor 602 to perform method 200 shown in fig. 2 and/or method 300 shown in fig. 3.

Embodiments of the present invention also provide a machine-readable medium having stored thereon executable instructions that, when executed, cause a machine to perform the method 200 of fig. 2 and/or the method 300 of fig. 3.

It should be understood that all operations in the methods described above are exemplary only, and the present disclosure is not limited to any operations in the methods or the order of the operations, but rather should encompass all other equivalent variations under the same or similar concepts.

It should also be understood that all of the modules in the above described apparatus may be implemented in various ways. These modules may be implemented as hardware, software, or a combination thereof. In addition, any of these modules may be further divided functionally into sub-modules or combined together.

The processor has been described in connection with various apparatus and methods. These processors may be implemented using electronic hardware, computer software, or any combination thereof. Whether such processors are implemented as hardware or software depends upon the particular application and the overall design constraints imposed on the system. By way of example, the processor, any portion of the processor, or any combination of processors presented in this disclosure may be implemented as a microprocessor, microcontroller, Digital Signal Processor (DSP), Field Programmable Gate Array (FPGA), Programmable Logic Device (PLD), state machine, gated logic, discrete hardware circuits, and other suitable processing components configured to perform the various functions described in this disclosure. The functionality of a processor, any portion of a processor, or any combination of processors presented in this disclosure may be implemented as software executed by a microprocessor, microcontroller, DSP, or other suitable platform.

The above description is provided to enable any person skilled in the art to practice the various aspects described herein. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects. Thus, the claims are not intended to be limited to the aspects shown herein. All structural and functional equivalents to the elements of the various aspects described herein that are known or later come to be known to those of ordinary skill in the art are expressly incorporated herein by reference and are intended to be encompassed by the claims.

It will be understood by those skilled in the art that various modifications and changes may be made in the embodiments disclosed above without departing from the spirit of the invention, and these modifications and changes are intended to fall within the scope of the invention as defined in the appended claims.

Claims

1. A method for facilitating safe driving of a vehicle, comprising:

determining a current driving scene of a vehicle;

obtaining at least one vehicle accident scenario from a database;

judging whether the current driving scene of the vehicle is matched with the at least one vehicle accident scene; and

automatically performing an action to avoid the vehicle entering the at least one vehicle accident scenario if the current driving scenario of the vehicle matches the at least one vehicle accident scenario.

2. The method of claim 1, wherein the at least one vehicle accident scenario is generated by training a model based on collected vehicle accident data.

3. The method of claim 2, wherein the vehicle accident data is classified into valid accident data and invalid accident data based at least on a cause of an accident occurrence, and wherein the at least one vehicle accident scenario is generated by a training model based on the valid accident data.

4. The method of claim 2, wherein the vehicle accident data is collected by a third party or by a cloud server from one or more vehicle accidents that have occurred.

5. The method of claim 4, wherein obtaining the at least one vehicle accident scenario further comprises: obtaining an updated at least one vehicle accident scenario,

wherein the updated at least one vehicle accident scenario is generated further based on valid accident data in updated vehicle accident data, and wherein the updated vehicle accident data is derived based on vehicle accident data collected by the third party or the cloud server from one or more newly occurring vehicle accidents.

6. The method of claim 1, wherein the vehicle accident scenario is represented by a set comprising at least one of: the type, time, place, cause, surrounding environment, vehicle speed, vehicle damage condition, casualty condition and the inherent information of the vehicle.

7. The method of claim 1, further comprising:

transmitting an indication signal to other vehicles in the vicinity of the vehicle, wherein the indication signal is used to instruct users of the other vehicles to perform an action to avoid entering the at least one vehicle accident scenario.

8. The method of claim 1, wherein automatically performing an action comprises at least one of: adjusting the current operation of the vehicle, sending a prompt signal to a user of the vehicle.

9. An apparatus for facilitating safe driving of a vehicle, comprising:

the determining module is used for determining the current driving scene of the vehicle;

an obtaining module for obtaining at least one vehicle accident scenario from a database;

the judging module is used for judging whether the current driving scene of the vehicle is matched with the at least one vehicle accident scene; and

an execution module to automatically perform an action to avoid the vehicle entering the at least one vehicle accident scenario if the current driving scenario of the vehicle matches the at least one vehicle accident scenario.

10. The apparatus of claim 9, wherein the at least one vehicle accident scenario is generated by training a model based on collected vehicle accident data.

11. The apparatus of claim 10, wherein the vehicle accident data is classified into valid accident data and invalid accident data based at least on a cause of an accident occurrence, and wherein the at least one vehicle accident scenario is generated by a training model based on the valid accident data.

12. The apparatus of claim 10, wherein the vehicle accident data is collected by a third party or by a cloud server from one or more vehicle accidents that have occurred.

13. The apparatus of claim 12, wherein the obtaining module is further configured for: obtaining an updated at least one vehicle accident scenario,

14. The apparatus of claim 9, wherein the vehicle accident scenario is represented by a set comprising at least one of: the type, time, place, cause, surrounding environment, vehicle speed, vehicle damage condition, casualty condition and the inherent information of the vehicle.

15. The apparatus of claim 10, further comprising:

a sending module, configured to send an indication signal to another vehicle in the vicinity of the vehicle, where the indication signal is used to instruct a user of the other vehicle to perform an action to avoid entering the at least one vehicle accident scenario.

16. The apparatus of claim 10, wherein automatically performing an action comprises at least one of: adjusting the current operation of the vehicle, sending a prompt signal to a user of the vehicle.

17. An apparatus for facilitating safe driving of a vehicle, comprising:

a processor; and

a memory to store executable instructions, wherein the executable instructions, when executed, cause the processor to perform the method of claims 1-8.

18. A machine-readable medium having stored thereon executable instructions, wherein the executable instructions, when executed, cause a machine to perform the method of claims 1-8.

19. A system for facilitating safe driving of a vehicle, comprising:

a sensor for sensing running condition information of the vehicle and surrounding environment information of the vehicle;

control device for performing the method of claims 1-8.

20. The system of claim 19, further comprising:

an execution device for executing an operation on the vehicle based on an output of the control device.