CN113147791A - Vehicle control method and device and automatic driving vehicle - Google Patents
Vehicle control method and device and automatic driving vehicle Download PDFInfo
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- CN113147791A CN113147791A CN202110513155.5A CN202110513155A CN113147791A CN 113147791 A CN113147791 A CN 113147791A CN 202110513155 A CN202110513155 A CN 202110513155A CN 113147791 A CN113147791 A CN 113147791A
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- 238000000034 method Methods 0.000 title claims abstract description 56
- 206010039203 Road traffic accident Diseases 0.000 claims abstract description 78
- 230000008569 process Effects 0.000 claims abstract description 20
- 230000003993 interaction Effects 0.000 claims description 21
- 238000012549 training Methods 0.000 claims description 12
- 238000010801 machine learning Methods 0.000 claims description 11
- 238000012545 processing Methods 0.000 claims description 7
- 238000003062 neural network model Methods 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 4
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W60/00—Drive control systems specially adapted for autonomous road vehicles
- B60W60/001—Planning or execution of driving tasks
- B60W60/0015—Planning or execution of driving tasks specially adapted for safety
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
- B60W40/04—Traffic conditions
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W2050/0001—Details of the control system
- B60W2050/0043—Signal treatments, identification of variables or parameters, parameter estimation or state estimation
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Abstract
The application discloses a control method and device of a vehicle and an automatic driving vehicle. Wherein, the method comprises the following steps: acquiring images of two sides of a road where a current vehicle is located in the process that the current vehicle runs according to an automatic driving mode; judging whether target traffic indication marks exist on two sides of the road or not according to the image, wherein the target traffic indication marks are used for indicating that traffic accidents easily occur on the current road section; if the target traffic indication mark exists, predicting the probability of traffic accidents on the current road section; adjusting the driving state of the current vehicle according to the probability of the traffic accident on the current road section, wherein the driving state comprises the following steps: the travel speed of the vehicle and the driving mode of the vehicle. The technical problems that traffic accidents may occur and the driving safety is poor when the automatic driving vehicle passes through the accident-prone road section are solved.
Description
Technical Field
The application relates to the field of automatic driving, in particular to a vehicle control method and device and an automatic driving vehicle.
Background
At present, the automatic driving technology is developed quickly, but many technical problems still exist and are not overcome, for example, the automatic driving vehicle may pass through some accident-prone sections during the driving process, if the automatic driving vehicle still drives according to the previously set driving parameters when passing through the accident-prone sections, the risk of occurrence of traffic accidents may be increased, and the driving safety is poor.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the application provides a vehicle control method and device and an automatic driving vehicle, and aims to at least solve the technical problems that when the automatic driving vehicle passes through a road section with multiple accidents, traffic accidents may happen, and the driving safety is poor.
According to an aspect of an embodiment of the present application, there is provided a control method of a vehicle, including: acquiring images of two sides of a road where a current vehicle is located in the process that the current vehicle runs according to an automatic driving mode; judging whether target traffic indication marks exist on two sides of the road or not according to the image, wherein the target traffic indication marks are used for indicating that traffic accidents easily occur on the current road section; if the target traffic indication mark exists, predicting the probability of traffic accidents on the current road section; adjusting the driving state of the current vehicle according to the probability of the traffic accident on the current road section, wherein the driving state comprises the following steps: the travel speed of the vehicle and the driving mode of the vehicle.
Optionally, judging whether target traffic indication marks exist on two sides of the road according to the image includes: judging whether a target traffic identification exists in the acquired image; if the target traffic identification exists in the image, determining that target traffic indication identifications exist on two sides of the road; and if the target traffic identification does not exist in the image, determining that the target traffic indication identification does not exist on the two sides of the road.
Optionally, predicting the probability of the traffic accident occurring on the current road segment includes: determining characteristic information of the current road section, wherein the characteristic information at least comprises the following components: position information of a current road section and image information of the current road section; and inputting the characteristic information of the current road section into the machine learning model for processing to obtain the probability of the traffic accident of the current road section.
Optionally, before inputting the feature information of the current road segment into the machine learning model for processing, the method further includes: obtaining a training data set, wherein the training data set comprises: the position information of the current road section, the image information of the current road section and the probability of traffic accidents occurring on the current road section; training the neural network model based on the training data set to generate a machine learning model.
Optionally, adjusting the driving state of the current vehicle according to the probability of the traffic accident occurring on the current road segment includes: if the probability of the traffic accident occurring on the current road section is higher than a preset threshold value, controlling the current vehicle to decelerate to pass through the current road section; or controlling the current vehicle to be switched from an automatic driving mode to a manual driving mode and pass through the current road section according to the manual driving mode; and if the probability of the traffic accident on the current road section is lower than a preset threshold value, controlling the current vehicle to pass through the current road section according to the current running speed.
According to another aspect of the embodiments of the present application, there is also provided a control method of a vehicle, including: displaying the collected images of the two sides of the road where the current vehicle is located in a human-computer interaction interface of the current vehicle in the process that the current vehicle runs according to the automatic driving mode; displaying target traffic indication marks on two sides of a current road on a human-computer interaction interface, wherein the target traffic indication marks are used for indicating that traffic accidents easily occur on the current road section; displaying the probability of traffic accidents on the current road section on a human-computer interaction interface; displaying reminding information on the human-computer interaction interface, wherein the reminding information is used for reminding whether to adjust the driving state of the vehicle, and the driving state comprises: the travel speed of the vehicle and the driving mode of the vehicle.
According to another aspect of the embodiments of the present application, there is also provided a control apparatus of a vehicle, including: the acquisition module is used for acquiring images of two sides of a road where the current vehicle is located in the process that the current vehicle runs according to the automatic driving mode; the judging module is used for judging whether target traffic indication marks exist on two sides of the road according to the image, wherein the target traffic indication marks are used for indicating that traffic accidents easily occur on the current road section; the prediction module is used for predicting the probability of traffic accidents on the current road section under the condition that the target traffic indication mark exists; the adjusting module is used for adjusting the driving state of the current vehicle according to the probability of the traffic accident on the current road section, wherein the driving state comprises the following steps: the travel speed of the vehicle and the driving mode of the vehicle.
According to another aspect of the embodiments of the present application, there is also provided an autonomous vehicle, including: the automatic driving system comprises image acquisition equipment and a controller, wherein the image acquisition equipment is used for acquiring images of two sides of a road where a current vehicle is located in the process that the current vehicle runs according to an automatic driving mode; the controller is communicated with the image acquisition equipment and is used for judging whether target traffic indication marks exist on two sides of the road according to the image, wherein the target traffic indication marks are used for indicating that traffic accidents easily occur on the current road section; under the condition that the target traffic indication mark exists, predicting the probability of traffic accidents on the current road section; adjusting the driving state of the current vehicle according to the probability of the traffic accident on the current road section, wherein the driving state comprises the following steps: the travel speed of the vehicle and the driving mode of the vehicle.
According to still another aspect of the embodiments of the present application, there is also provided a nonvolatile storage medium including a stored program, wherein the apparatus in which the nonvolatile storage medium is controlled when the program is executed performs the above control method of the vehicle.
According to still another aspect of the embodiments of the present application, there is also provided a processor for executing a program stored in a memory, wherein the program executes the above control method of the vehicle.
In the embodiment of the application, images of two sides of a road where a current vehicle is located are collected when the current vehicle runs according to an automatic driving mode; judging whether target traffic indication marks exist on two sides of the road or not according to the image, wherein the target traffic indication marks are used for indicating that traffic accidents easily occur on the current road section; if the target traffic indication mark exists, predicting the probability of traffic accidents on the current road section; adjusting the driving state of the current vehicle according to the probability of the traffic accident on the current road section, wherein the driving state comprises the following steps: the driving speed of the vehicle and the driving mode of the vehicle predict the probability of the traffic accident on the road section after the road section where the traffic accident is prone to occur is determined, and then the driving state of the vehicle is adjusted according to the predicted probability, so that the risk of the traffic accident occurring when the automatic driving vehicle passes through the road section where the accident is prone to occur is reduced, the technical effect of the driving safety of the automatic driving vehicle is improved, and the technical problems that the traffic accident may occur and the driving safety is poor when the automatic driving vehicle passes through the road section where the accident is prone to occur are solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a flow chart of a method of controlling a vehicle according to an embodiment of the present application;
FIG. 2 is a flow chart of another method of controlling a vehicle according to an embodiment of the present application;
fig. 3 is a block diagram of a control apparatus of a vehicle according to an embodiment of the present application;
fig. 4 is a block diagram of an autonomous vehicle according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
According to an embodiment of the present application, there is provided an embodiment of a control method for a vehicle, it should be noted that the steps shown in the flowchart of the drawings may be executed in a computer system such as a set of computer executable instructions, and that while a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in an order different from that here.
Fig. 1 is a flowchart of a control method of a vehicle according to an embodiment of the present application, as shown in fig. 1, the method including the steps of:
step S102, collecting images of two sides of a road where a current vehicle is located in the process that the current vehicle runs according to an automatic driving mode;
step S104, judging whether target traffic indication marks exist on two sides of the road according to the image, wherein the target traffic indication marks are used for indicating that traffic accidents easily occur on the current road section;
the target traffic indicator is referred to as an "accident-prone link sign".
Step S106, if the target traffic indication mark exists, predicting the probability of traffic accidents on the current road section;
step S108, adjusting the driving state of the current vehicle according to the probability of the traffic accident on the current road section, wherein the driving state comprises the following steps: the travel speed of the vehicle and the driving mode of the vehicle.
Through the steps, after the traffic accident easily-occurring road section is determined, the probability of the traffic accident occurring on the road section is predicted, and then the driving state of the vehicle is adjusted according to the predicted probability, so that the risk of the traffic accident occurring when the automatically-driven vehicle passes through the accident easily-occurring road section is reduced, and the technical effect of the driving safety of the automatically-driven vehicle is improved.
According to an optional embodiment of the present application, when step S104 is executed, it is determined whether a target traffic identifier exists in the acquired image; if the target traffic identification exists in the image, determining that target traffic indication identifications exist on two sides of the road; and if the target traffic identification does not exist in the image, determining that the target traffic indication identification does not exist on the two sides of the road.
In the step, the acquired images at two sides of the road are compared with the pre-stored accident-prone road section mark, so that whether the accident-prone road section mark exists in the acquired images at two sides of the road can be determined.
According to another optional embodiment of the application, the acquired images of the two sides of the road can be input into a machine learning model trained in advance for recognition, and whether the acquired images of the two sides of the road have accident-prone road section signs or not is determined. Through the method, whether the current driving road section of the vehicle is the accident-prone road section or not can be determined.
According to an alternative embodiment of the present application, step S106 is implemented by: determining characteristic information of the current road section, wherein the characteristic information at least comprises the following components: position information of a current road section and image information of the current road section; and inputting the characteristic information of the current road section into the machine learning model for processing to obtain the probability of the traffic accident of the current road section.
In some optional embodiments of the present application, before inputting the feature information of the current road segment into the machine learning model for processing, a training data set needs to be obtained, where the training data set includes: the position information of the current road section, the image information of the current road section and the probability of traffic accidents occurring on the current road section; training the neural network model based on the training data set to generate a machine learning model.
In the method, the probability of the accident of the road section where the vehicle is located is predicted by utilizing the machine learning model trained in advance, and the technical effect of accurately determining the probability of the traffic accident of the road section can be realized.
In some optional embodiments of the present application, step S108 is implemented by: if the probability of the traffic accident occurring on the current road section is higher than a preset threshold value, controlling the current vehicle to decelerate to pass through the current road section; or controlling the current vehicle to be switched from an automatic driving mode to a manual driving mode and pass through the current road section according to the manual driving mode; and if the probability of the traffic accident on the current road section is lower than a preset threshold value, controlling the current vehicle to pass through the current road section according to the current running speed.
In the step, the driving state of the current vehicle is adjusted according to the predicted probability of the traffic accident occurring on the current road section, and specifically, if the probability of the traffic accident occurring on the current road section is higher than a preset threshold value, the vehicle needs to be controlled to run at a reduced speed; or to switch the vehicle from an automatic driving mode to a manual driving mode. And if the probability of the accident occurring on the current road section is lower than the preset threshold value, keeping the current driving parameters of the vehicle to continue driving. By the method, the technical effect of improving the driving safety when the automatic driving vehicle passes through the road section with multiple accidents can be achieved.
Fig. 2 is a flowchart of another control method of a vehicle according to an embodiment of the present application, as shown in fig. 2, the method including:
step S202, in the process that the current vehicle runs according to the automatic driving mode, displaying the collected images of the two sides of the road where the current vehicle is located in a human-computer interaction interface of the current vehicle;
step S204, displaying target traffic indication marks on two sides of the current road on a human-computer interaction interface, wherein the target traffic indication marks are used for indicating that traffic accidents easily occur on the current road section;
step S206, displaying the probability of traffic accidents on the current road section on a human-computer interaction interface;
step S208, displaying reminding information on the human-computer interaction interface, wherein the reminding information is used for reminding whether to adjust the driving state of the vehicle, and the driving state comprises: the travel speed of the vehicle and the driving mode of the vehicle.
The vehicle control method provided in steps S202 to S208 can improve the human-computer interaction experience of the user.
It should be noted that, reference may be made to the description related to the embodiment shown in fig. 1 for a preferred implementation of the embodiment shown in fig. 2, and details are not described here again.
Fig. 3 is a block diagram of a control apparatus of a vehicle according to an embodiment of the present application, and as shown in fig. 3, the apparatus includes:
the acquisition module 30 is used for acquiring images of two sides of a road where the current vehicle is located in the process that the current vehicle runs according to the automatic driving mode;
the judging module 32 is configured to judge whether target traffic indication marks exist on two sides of a road according to the image, where the target traffic indication marks are used to indicate that a traffic accident is likely to occur in a current road section;
the prediction module 34 is configured to predict the probability of a traffic accident occurring on the current road segment under the condition that the target traffic indication identifier exists;
an adjusting module 36, configured to adjust a driving status of the current vehicle according to a probability of a traffic accident occurring on the current road segment, where the driving status includes: the travel speed of the vehicle and the driving mode of the vehicle.
It should be noted that, reference may be made to the description related to the embodiment shown in fig. 1 for a preferred implementation of the embodiment shown in fig. 3, and details are not described here again.
Fig. 4 is a block diagram of a structure of an autonomous vehicle according to an embodiment of the present application, which includes, as shown in fig. 4: an image acquisition device 40, and a controller 42, wherein,
the image acquisition equipment 40 is used for acquiring images of two sides of a road where the current vehicle is located in the process that the current vehicle runs according to the automatic driving mode;
the controller 42 is communicated with the image acquisition equipment 40 and is used for judging whether target traffic indication marks exist on two sides of the road according to the image, wherein the target traffic indication marks are used for indicating that traffic accidents easily occur on the current road section; under the condition that the target traffic indication mark exists, predicting the probability of traffic accidents on the current road section; adjusting the driving state of the current vehicle according to the probability of the traffic accident on the current road section, wherein the driving state comprises the following steps: the travel speed of the vehicle and the driving mode of the vehicle.
It should be noted that, reference may be made to the description related to the embodiment shown in fig. 1 for a preferred implementation of the embodiment shown in fig. 4, and details are not described here again.
The embodiment of the application also provides a nonvolatile storage medium, which comprises a stored program, wherein the device where the nonvolatile storage medium is located is controlled to execute the control method of the vehicle when the program runs.
The nonvolatile storage medium stores a program for executing the following functions: acquiring images of two sides of a road where a current vehicle is located in the process that the current vehicle runs according to an automatic driving mode; judging whether target traffic indication marks exist on two sides of the road or not according to the image, wherein the target traffic indication marks are used for indicating that traffic accidents easily occur on the current road section; if the target traffic indication mark exists, predicting the probability of traffic accidents on the current road section; adjusting the driving state of the current vehicle according to the probability of the traffic accident on the current road section, wherein the driving state comprises the following steps: the travel speed of the vehicle and the driving mode of the vehicle. Or
Displaying the collected images of the two sides of the road where the current vehicle is located in a human-computer interaction interface of the current vehicle in the process that the current vehicle runs according to the automatic driving mode; displaying target traffic indication marks on two sides of a current road on a human-computer interaction interface, wherein the target traffic indication marks are used for indicating that traffic accidents easily occur on the current road section; displaying the probability of traffic accidents on the current road section on a human-computer interaction interface; displaying reminding information on the human-computer interaction interface, wherein the reminding information is used for reminding whether to adjust the driving state of the vehicle, and the driving state comprises: the travel speed of the vehicle and the driving mode of the vehicle.
The embodiment of the application also provides a processor which is used for operating the program stored in the memory, wherein the program is used for executing the control method of the vehicle when running.
The processor is used for running a program for executing the following functions: acquiring images of two sides of a road where a current vehicle is located in the process that the current vehicle runs according to an automatic driving mode; judging whether target traffic indication marks exist on two sides of the road or not according to the image, wherein the target traffic indication marks are used for indicating that traffic accidents easily occur on the current road section; if the target traffic indication mark exists, predicting the probability of traffic accidents on the current road section; adjusting the driving state of the current vehicle according to the probability of the traffic accident on the current road section, wherein the driving state comprises the following steps: the travel speed of the vehicle and the driving mode of the vehicle. Or
Displaying the collected images of the two sides of the road where the current vehicle is located in a human-computer interaction interface of the current vehicle in the process that the current vehicle runs according to the automatic driving mode; displaying target traffic indication marks on two sides of a current road on a human-computer interaction interface, wherein the target traffic indication marks are used for indicating that traffic accidents easily occur on the current road section; displaying the probability of traffic accidents on the current road section on a human-computer interaction interface; displaying reminding information on the human-computer interaction interface, wherein the reminding information is used for reminding whether to adjust the driving state of the vehicle, and the driving state comprises: the travel speed of the vehicle and the driving mode of the vehicle.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present application, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present application and it should be noted that those skilled in the art can make several improvements and modifications without departing from the principle of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.
Claims (10)
1. A control method of a vehicle, characterized by comprising:
acquiring images of two sides of a road where a current vehicle is located in the process that the current vehicle runs according to an automatic driving mode;
judging whether target traffic indication marks exist on two sides of the road according to the image, wherein the target traffic indication marks are used for indicating that traffic accidents easily occur on the current road section;
if the target traffic indication mark exists, predicting the probability of traffic accidents occurring on the current road section;
adjusting the driving state of the current vehicle according to the probability of the traffic accident on the current road section, wherein the driving state comprises the following steps: a travel speed of the vehicle and a driving mode of the vehicle.
2. The method of claim 1, wherein determining whether target traffic indicators exist on both sides of the road according to the image comprises:
judging whether the target traffic identification exists in the acquired image or not;
if the target traffic identification exists in the image, determining that the target traffic indication identification exists on two sides of the road;
and if the target traffic identification does not exist in the image, determining that the target traffic indication identification does not exist on two sides of the road.
3. The method of claim 1, wherein predicting the probability of a traffic accident occurring for the current road segment comprises:
determining feature information of the current road segment, wherein the feature information at least comprises: the position information of the current road section and the image information of the current road section;
and inputting the characteristic information of the current road section into a machine learning model for processing to obtain the probability of the traffic accident of the current road section.
4. The method of claim 3, wherein before inputting the feature information of the current road segment into a machine learning model for processing, the method further comprises:
obtaining a training data set, wherein the training data set comprises: the position information of the current road section, the image information of the current road section and the probability of traffic accidents occurring on the current road section;
training a neural network model based on the training data set, generating the machine learning model.
5. The method of claim 1, wherein adjusting the driving status of the current vehicle according to the probability of the traffic accident occurring on the current road segment comprises:
if the probability of the traffic accident occurring on the current road section is higher than a preset threshold value, controlling the current vehicle to decelerate to pass through the current road section; or controlling the current vehicle to be switched from the automatic driving mode to a manual driving mode and to pass through the current road section according to the manual driving mode;
and if the probability of the traffic accident on the current road section is lower than the preset threshold value, controlling the current vehicle to pass through the current road section according to the current running speed.
6. A control method of a vehicle, characterized by comprising:
displaying collected images of two sides of a road where a current vehicle is located in a human-computer interaction interface of the current vehicle in the process that the current vehicle runs according to an automatic driving mode;
displaying target traffic indication marks on two sides of the current road on the human-computer interaction interface, wherein the target traffic indication marks are used for indicating that traffic accidents easily occur on the current road section;
displaying the probability of the traffic accident on the current road section on the human-computer interaction interface;
displaying reminding information on the human-computer interaction interface, wherein the reminding information is used for reminding whether to adjust the driving state of the vehicle, and the driving state comprises: a travel speed of the vehicle and a driving mode of the vehicle.
7. A control apparatus of a vehicle, characterized by comprising:
the system comprises an acquisition module, a display module and a control module, wherein the acquisition module is used for acquiring images of two sides of a road where a current vehicle is located in the process that the current vehicle runs according to an automatic driving mode;
the judging module is used for judging whether target traffic indication marks exist on two sides of the road according to the image, wherein the target traffic indication marks are used for indicating that traffic accidents easily occur on the current road section;
the prediction module is used for predicting the probability of the traffic accident of the current road section under the condition that the target traffic indication mark exists;
the adjusting module is used for adjusting the driving state of the current vehicle according to the probability of the traffic accident on the current road section, wherein the driving state comprises the following steps: a travel speed of the vehicle and a driving mode of the vehicle.
8. An autonomous vehicle, comprising: an image acquisition device and a controller, wherein,
the image acquisition equipment is used for acquiring images of two sides of a road where the current vehicle is located in the process that the current vehicle runs according to an automatic driving mode;
the controller is communicated with the image acquisition equipment and is used for judging whether target traffic indication marks exist on two sides of the road according to the image, wherein the target traffic indication marks are used for indicating that traffic accidents easily occur on the current road section; predicting the probability of the traffic accident of the current road section under the condition that the target traffic indication mark exists; adjusting the driving state of the current vehicle according to the probability of the traffic accident on the current road section, wherein the driving state comprises the following steps: a travel speed of the vehicle and a driving mode of the vehicle.
9. A nonvolatile storage medium characterized by comprising a stored program, wherein a device on which the nonvolatile storage medium is installed is controlled to execute the control method of the vehicle according to any one of claims 1 to 6 when the program is executed.
10. A processor for running a program stored in a memory, wherein the program when run performs a control method of a vehicle according to any one of claims 1 to 6.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115719325A (en) * | 2022-12-07 | 2023-02-28 | 钧捷科技（北京）有限公司 | Road condition image processing system based on unmanned driving |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115719325A (en) * | 2022-12-07 | 2023-02-28 | 钧捷科技（北京）有限公司 | Road condition image processing system based on unmanned driving |
| CN115719325B (en) * | 2022-12-07 | 2023-11-17 | 钧捷科技（北京）有限公司 | Unmanned road condition image processing system |
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