Method and apparatus for generating information

1. A method for generating information, comprising:

acquiring first driving environment data of a target road segment;

comparing the first driving environment data with pre-stored second driving environment data of the target road segment, and determining a difference between the first driving environment data and the second driving environment data; and

generating, in response to determining the difference satisfying a preset condition, road abnormality information,

wherein the determining the difference between the first driving environment data and the second driving environment data includes:

in response to determining that the first driving environment data includes image data and the second driving environment data includes point cloud data, or in response to determining that the second driving environment data includes image data and the first driving environment data includes point cloud data:

converting the point cloud data into image data corresponding to the point cloud data; and

comparing the image data converted from the point cloud data with the image data included in the first or second driving environment data, to determine a difference between the image data converted from the point cloud data and the image data included in the first or second driving environment data, and determining the determined difference as the difference between the first driving environment data and the second driving environment data,

wherein before updating the second driving environment data, the method further comprises:

determining, in driving routes preset for autonomous driving vehicles, a driving route including the target road segment,

acquiring a vehicle identifier corresponding to the driving route including the target road segment; and

sending the road abnormality information to an autonomous driving vehicle indicated by the vehicle identifier, to instruct the autonomous driving vehicle indicated by the vehicle identifier to park into a nearest parking space.

2. The method according to claim 1 , wherein the generating, in response to determining the difference satisfying a preset condition, road abnormality information includes:

recognizing a type of an object corresponding to the difference; and

generating, in response to determining the type of the object matching at least one type in a preset type set, the road abnormality information, wherein the preset type set includes at least one of: a lane line type, a traffic sign type, a median strip type, or a building type.

3. The method according to claim 2 , wherein the generating, in response to determining the difference satisfying a preset condition, road abnormality information includes:

determining, in response to determining the type of the object matching the at least one type in the preset type set, a difference distance corresponding to the difference; and

generating, in response to determining the difference distance being greater than or equal to a preset threshold, the road abnormality information.

4. The method according to claim 1 , wherein the point cloud data is collected by radar detecting apparatus.

5. The method according to claim 1 , further comprising:

updating, in response to determining the difference satisfying the preset condition, the second driving environment data according to the first driving environment data.

6. The method according to claim 5 , further comprising:

generating, in response to a completion of the updating of the second driving environment data, an electronic map according to the updated second driving environment data; and

outputting the electronic map.

7. The method according to claim 1 , wherein the generating, in response to determining the difference satisfying a preset condition, road abnormality information includes:

in response to an object corresponding to the determined difference being of a lane line type, calculating a deviation distance of a lane line in the first driving environment data as compared with a corresponding lane line in the second driving environment data; and

in response to the deviation distance being greater than a preset threshold, generating the road abnormality information.

8. The method according to claim 1 , wherein the generating, in response to determining the difference satisfying a preset condition, comprises:

in response to an object corresponding to the determined difference being of a traffic sign type, calculating a deviation distance of a traffic sign in the first driving environment data as compared with a corresponding traffic sign in the second driving environment data; and

in response to the deviation distance being greater than a preset threshold, generating the road abnormality information.

9. The method according to claim 1 , wherein the first driving environment data is an image of an environment where a vehicle is located.

10. An apparatus for generating information, comprising:

at least one processor; and

a memory storing instructions, the instructions when executed by the at least one processor, causing the at least one processor to perform operations, the operations comprising:

acquiring first driving environment data of a target road segment;

comparing the first driving environment data with pre-stored second driving environment data of the target road segment, and determining a difference between the first driving environment data and the second driving environment data; and

generating, in response to determining the difference satisfying a preset condition, road abnormality information,

wherein the determining the difference between the first driving environment data and the second driving environment data includes:

in response to determining that the first driving environment data includes image data and the second driving environment data includes point cloud data, or in response to determining that the second driving environment data includes image data and the first driving environment data includes point cloud data:

converting the point cloud data into image data corresponding to the point cloud data; and

comparing the image data converted from the point cloud data with the image data included in the first or second driving environment data, to determine a difference between the image data converted from the point cloud data and the image data included in the first or second driving environment data, and determining the determined difference as the difference between the first driving environment data and the second driving environment data,

wherein before updating the second driving environment data, the operations further comprise:

determining, in driving routes preset for autonomous driving vehicles, a driving route including the target road segment,

acquiring a vehicle identifier corresponding to the driving route including the target road segment; and

sending the road abnormality information to an autonomous driving vehicle indicated by the vehicle identifier, to instruct the autonomous driving vehicle indicated by the vehicle identifier to park into a nearest parking space.

11. The apparatus according to claim 10 , wherein the generating, in response to determining the difference satisfying a preset condition, road abnormality information includes:

recognizing a type of an object corresponding to the difference; and

generating, in response to determining the type of the object matching at least one type in a preset type set, the road abnormality information, wherein the preset type set includes at least one of: a lane line type, a traffic sign type, a median strip type, or a building type.

12. The apparatus according to claim 11 , wherein the generating, in response to determining the difference satisfying a preset condition, road abnormality information includes:

determining, in response to determining the type of the object matching the at least one type in the preset type set, a difference distance corresponding to the difference; and

generating, in response to determining the difference distance being greater than or equal to a preset threshold, the road abnormality information.

13. The apparatus according to claim 10 , wherein the point cloud data is collected by radar detecting apparatus.

14. The apparatus according to claim 10 , the operations further comprising:

updating, in response to determining the difference satisfying the preset condition, the second driving environment data according to the first driving environment data.

15. The apparatus according to claim 14 , the operations further comprising:

generating, in response to a completion of the updating of the second driving environment data, an electronic map according to the updated second driving environment data; and

outputting the electronic map.

16. A non-transitory computer readable medium, storing a computer program, the computer program, when executed by a processor, causing the processor to perform operations, the operations comprising:

acquiring first driving environment data of a target road segment;

comparing the first driving environment data with pre-stored second driving environment data of the target road segment, and determining a difference between the first driving environment data and the second driving environment data; and

generating, in response to determining the difference satisfying a preset condition, road abnormality information,

wherein the determining the difference between the first driving environment data and the second driving environment data includes:

in response to determining that the first driving environment data includes image data and the second driving environment data includes point cloud data, or in response to determining that the second driving environment data includes image data and the first driving environment data includes point cloud data:

converting the point cloud data into image data corresponding to the point cloud data; and

comparing the image data converted from the point cloud data with the image data included in the first or second driving environment data, to determine a difference between the image data converted from the point cloud data and the image data included in the first or second driving environment data, and determining the determined difference as the difference between the first driving environment data and the second driving environment data,

wherein before updating the second driving environment data, the operations further comprise:

determining, in driving routes preset for autonomous driving vehicles, a driving route including the target road segment,

acquiring a vehicle identifier corresponding to the driving route including the target road segment; and

sending the road abnormality information to an autonomous driving vehicle indicated by the vehicle identifier, to instruct the autonomous driving vehicle indicated by the vehicle identifier to park into a nearest parking space.