AUTONOMOUS DRIVING ASSISTANCE METHOD, DRIVING DEVICE, ASSISTANCE DEVICE AND READABLE STORAGE MEDIUM
An autonomous driving assistance method, a driving device, an assistance device and a readable storage medium are provided by the present disclosure. The driving device processes collected current scene information by using a current autonomous driving model, and initiates an assistance driving request to an assistance device according to a processing result; receives and performs a driving instruction feedback by the assistance device, where the driving instruction is used to optimize the current autonomous driving model in conjunction with the current scene information, so as to perform a following autonomous driving task by using the optimized autonomous driving model. Therefore, a problem, that when performing an autonomous driving task, an existing deriving device fails to continue performing the autonomous driving task since a preset autonomous driving model cannot process scene information, can be solved, improving intelligence and applicability of the autonomous driving model.
1 . An autonomous driving assistance method, comprising:
processing collected current scene information by using a current autonomous driving model, and initiating an assistance driving request to an assistance device according to a processing result;
receiving and performing a driving instruction feedback by the assistance device, wherein the driving instruction is used to optimize the current autonomous driving model in conjunction with the current scene information, so as to perform a following autonomous driving task by using the optimized autonomous driving model.
2 . The autonomous driving assistance method according to claim 1 , wherein the autonomous driving model comprises a deep learning algorithm model;
the driving instruction is specifically used to generate a training sample in conjunction with the current scene information; training the deep learning algorithm model by using the training sample to obtain a trained deep learning algorithm model; wherein the trained deep learning algorithm model is the optimized autonomous driving model.
3 . The autonomous driving assistance method according to claim 1 , wherein the processing collected current scene information by using a current autonomous driving model, and initiating an assistance driving request to an assistance device according to a processing result comprises:
processing the collected current scene information by using the current autonomous driving model to obtain the processing result;
determining a confidence of the processing result;
initiating the assistance driving request to the assistance device, when the confidence is less than a preset threshold.
4 . The autonomous driving assistance method according to claim 3 , further comprising: when the confidence is greater than or equal to the preset threshold, performing an autonomous driving task according to the processing result.
5 . An autonomous driving assistance method, comprising:
receiving an assistance driving request initiated by a driving device, wherein the driving device processes collected current scene information by using a current autonomous driving model, and initiates the assistance driving request according to a processing result;
receiving a driving instruction triggered by a user, and transmitting the driving instruction to the driving device, so that the driving instruction is performed by the driving device; wherein the driving instruction is used to optimize the current autonomous driving model in conjunction with the current scene information, so as to perform a following autonomous driving task by using the optimized autonomous driving model.
6 . The autonomous driving assistance method according to claim 5 , wherein the driving request and the driving instruction are transmitted to the driving device through a wireless mobile network.
7 . The autonomous driving assistance method according to claim 5 , wherein the driving request and the driving instruction are transmitted to the driving device through near field communication technology.
8 . A driving device, comprising: a processor, and a computer readable medium for storing program codes, which, when executed by the processor, cause the processor to:
process collected current scene information by using a current autonomous driving model, and obtain a processing result;
initiate an assistance driving request to an assistance device according to the processing result; and further receive a driving instruction feedback by the assistance device, so that the driving instruction is performed by the driving device, wherein the driving instruction is used to optimize the current autonomous driving model in conjunction with the current scene information, so as to perform a following autonomous driving task by using the optimized autonomous driving model.
9 . The driving device according to claim 8 , wherein the autonomous driving model comprises a deep learning algorithm model; and
the driving instruction is specifically used to generate a training sample in conjunction with the current scene information; train the deep learning algorithm model by using the training sample to obtain a trained deep learning algorithm model; wherein the trained deep learning algorithm model is the optimized autonomous driving model.
10 . The driving device according to claim 8 , wherein, when the program codes cause the processor to process collected current scene information by using a current autonomous driving model, and obtain a processing result, the program codes further cause the processor to: determine a confidence of the processing result; when the confidence is less than a preset threshold, the program codes cause the processor to initiate the assistance driving request to the assistance device.
11 . The driving device according to claim 10 , wherein when the confidence is greater than or equal to the preset threshold, the driving device performs an autonomous driving task according to the processing result.
12 . An assistance device, comprising a memory, a processor connected to the memory, and a computer program stored on the memory and executable on the processor, wherein:
when executing the computer program, the processor executes the method according to claim 5 .
13 . A readable storage medium, comprising a program that, when being executed on a terminal, causes the terminal to implement the method according to claim 1 .
14 . A readable storage medium, comprising a program that, when being executed on a terminal, causes the terminal to implement the method according to claim 5 .