CN113085861A - Control method and device for automatic driving vehicle and automatic driving vehicle - Google Patents
Control method and device for automatic driving vehicle and automatic driving vehicle Download PDFInfo
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- CN113085861A CN113085861A CN202110331395.3A CN202110331395A CN113085861A CN 113085861 A CN113085861 A CN 113085861A CN 202110331395 A CN202110331395 A CN 202110331395A CN 113085861 A CN113085861 A CN 113085861A
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- 238000000034 method Methods 0.000 title claims abstract description 51
- 230000008569 process Effects 0.000 claims abstract description 20
- 238000010801 machine learning Methods 0.000 claims description 24
- 238000012549 training Methods 0.000 claims description 15
- 238000012545 processing Methods 0.000 claims description 9
- 230000006870 function Effects 0.000 claims description 3
- 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
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/18—Propelling the vehicle
- B60W30/18009—Propelling the vehicle related to particular drive situations
- B60W30/18159—Traversing an intersection
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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
- B60W2552/00—Input parameters relating to infrastructure
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Abstract
The application discloses a control method and device for an automatic driving vehicle and the automatic driving vehicle. Wherein, the method comprises the following steps: collecting images of the surrounding environment of the vehicle in the running process of the vehicle; determining position information of a first intersection existing on a driving path of the vehicle according to the image, wherein the first intersection is a position where the driving path intersects with other roads; judging whether a traffic signal lamp exists at the first intersection or not; and controlling the running state of the vehicle when the vehicle passes through the first intersection according to the judgment result. The application solves the technical problem of poor driving safety when the automatic driving vehicle passes through the intersection.
Description
Technical Field
The application relates to the field of automatic driving, in particular to a control method and device of an automatic driving vehicle and the automatic driving vehicle.
Background
In recent years, the automatic driving technology is developed rapidly, but many technical problems still exist and are not overcome, for example, when a vehicle runs on a straight road section, the road condition is detected in real time according to sensors such as a radar and a camera, and the driving safety is high. However, when passing through some crossroads, the passing vehicles and traffic lights exist, so that the road condition is complex and the driving safety is poor for the automatic driving vehicles.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the application provides a control method and device for an automatic driving vehicle and the automatic driving vehicle, so as to at least solve the technical problem of poor driving safety when the automatic driving vehicle passes through an intersection.
According to an aspect of an embodiment of the present application, there is provided a control method of an autonomous vehicle, including: collecting images of the surrounding environment of the vehicle in the running process of the vehicle; determining position information of a first intersection existing on a driving path of the vehicle according to the image, wherein the first intersection is a position where the driving path intersects with other roads; judging whether a traffic signal lamp exists at the first intersection or not; and controlling the running state of the vehicle when the vehicle passes through the first intersection according to the judgment result.
Optionally, determining the position information of the first intersection existing on the driving path of the vehicle according to the image includes: inputting the image into a first machine learning model for processing to obtain the position information of the first intersection, wherein the first machine learning model is obtained by training in the following way: acquiring a training data set, training a neural network model based on the training data set, and generating a first machine learning model, wherein the training data set comprises: an image of the surroundings of the vehicle collected while the vehicle is traveling on the traveling path, and a position tag of an intersection marked on the image.
Optionally, after determining the position information of the first intersection existing on the driving path of the vehicle according to the image, the method further includes: acquiring historical driving information of a vehicle driving on a driving path, wherein the historical driving information at least comprises: the position information of a second intersection and the corresponding traffic signal light information of the second intersection exist on the driving path; determining whether the position information of the first intersection is included in the position information of the second intersection; and if the position information of the second intersection comprises the position information of the first intersection, determining that the position information of the first intersection is correct information, and otherwise, determining that the position information of the first intersection is wrong information.
Optionally, the determining whether the traffic signal lamp exists at the first intersection includes: judging whether the traffic signal lamp information corresponding to the first intersection can be found from the historical driving information; if the traffic signal lamp information corresponding to the first intersection can be found, determining that the traffic signal lamp exists at the first intersection; and if the traffic signal lamp information corresponding to the first intersection cannot be found, determining that no traffic signal lamp exists at the first intersection.
Optionally, the determining whether the first intersection has a traffic signal lamp further includes: inputting the images of the intersection into a second machine learning model for processing; and judging whether the first intersection has a traffic signal lamp or not according to the output result of the second machine learning model.
Optionally, the controlling the driving state of the vehicle when passing through the first intersection according to the determination result includes: if the first intersection does not have the traffic signal lamp, controlling the vehicle to run at a constant speed or run at a reduced speed to pass through the first intersection; and if the first intersection has the traffic signal lamp, determining the indicating state of the traffic signal lamp, and controlling the driving state of the vehicle when the vehicle passes through the first intersection according to the indicating state of the traffic signal lamp.
Optionally, the controlling the driving state of the vehicle when passing through the first intersection according to the state of the traffic signal lamp comprises: if the indication state of the traffic signal lamp is red, controlling the vehicle to run at a reduced speed so that the vehicle stops running before reaching a stop line; if the indication state of the traffic signal lamp is green, controlling the vehicle to run at a constant speed or run at an accelerated speed to pass through the first intersection; and if the indication state of the traffic signal lamp is yellow, controlling the vehicle to decelerate so that the vehicle stops running before reaching the stop line.
According to another aspect of the embodiments of the present application, there is also provided a control apparatus of an autonomous vehicle, including: the acquisition module is used for acquiring images of the surrounding environment of the vehicle in the running process of the vehicle; the determining module is used for determining the position information of a first intersection existing on the driving path of the vehicle according to the image, wherein the first intersection is the position where the driving path intersects with other roads; the judging module is used for judging whether a traffic signal lamp exists at the first intersection or not; and the control module is used for controlling the running state of the vehicle when the vehicle passes through the first intersection according to the judgment result.
According to another aspect of the embodiments of the present application, there is also provided an autonomous vehicle, including: the system comprises an image acquisition device and a controller, wherein the image acquisition device is used for acquiring an image of the surrounding environment of the vehicle in the running process of the vehicle; the controller is communicated with the image acquisition equipment and is used for determining the position information of a first intersection existing on a driving path of the vehicle according to the image, wherein the first intersection is the position where the driving path and other roads are crossed; judging whether a traffic signal lamp exists at the first intersection or not; and controlling the running state of the vehicle when the vehicle passes through the first intersection according to the judgment result.
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 an autonomous vehicle.
According to yet 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 when executed performs the above control method of an autonomous vehicle.
In the embodiment of the application, the method comprises the steps of collecting images of the surrounding environment of a vehicle in the running process of the vehicle; determining position information of a first intersection existing on a driving path of the vehicle according to the image, wherein the first intersection is a position where the driving path intersects with other roads; judging whether a traffic signal lamp exists at the first intersection or not; according to the method for controlling the driving state of the vehicle when the vehicle passes through the first intersection according to the judgment result, the position information of the intersection is detected in real time in the driving process of the automatic driving vehicle, whether a traffic signal lamp exists at the intersection is judged, and then the driving state of the vehicle when the vehicle passes through the intersection is controlled according to the judgment result, so that the technical effect of improving the driving safety of the automatic driving vehicle when the automatic driving vehicle passes through the intersection is realized, and the technical problem of poor driving safety of the automatic driving vehicle when the automatic driving vehicle passes through the intersection is 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 control method of an autonomous vehicle according to an embodiment of the application;
fig. 2 is a block diagram of a control apparatus of an autonomous vehicle according to an embodiment of the present application;
fig. 3 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.
In accordance with an embodiment of the present application, there is provided an embodiment of a control method for an autonomous vehicle, wherein the steps illustrated in the flowchart of the figure may be performed in a computer system, such as a set of computer-executable instructions, and wherein, although a logical order is illustrated in the flowchart, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
Fig. 1 is a flowchart of a control method of an autonomous 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 the surrounding environment of the vehicle in the running process of the vehicle;
according to an alternative embodiment of the application, the image of the surroundings of the vehicle is captured by an image capturing device arranged on the vehicle.
Step S104, determining position information of a first intersection on a driving path of the vehicle according to the image, wherein the first intersection is a position where the driving path intersects with other roads;
it should be noted that the first intersection in step S104 refers to an intersection on the current travel path, and is for the purpose of distinguishing the second intersection in the history travel information, and is not limited to a specific intersection.
Step S106, judging whether a traffic signal lamp exists at the first intersection or not;
and S108, controlling the running state of the vehicle when the vehicle passes through the first intersection according to the judgment result.
Through the steps, the position information of the intersection is detected in real time in the process of driving of the automatic driving vehicle, then whether the traffic signal lamp exists at the intersection is judged, and the driving state of the vehicle passing through the intersection is controlled according to the judgment result, so that the technical effect of improving the driving safety of the automatic driving vehicle when the automatic driving vehicle passes through the intersection is realized.
According to an alternative embodiment of the present application, step S104 is implemented by: inputting the image into a first machine learning model for processing to obtain the position information of the first intersection, wherein the first machine learning model is obtained by training in the following way: acquiring a training data set, training a neural network model based on the training data set, and generating a first machine learning model, wherein the training data set comprises: an image of the surroundings of the vehicle collected while the vehicle is traveling on the traveling path, and a position tag of an intersection marked on the image.
In this step, the collected images around the vehicle are input to the machine learning model for processing, and the position information of the intersection is obtained. The technical effect of accurately determining the intersection position information can be achieved by processing the images acquired in the vehicle driving process by using the machine learning model.
According to another alternative embodiment of the present application, after the step S102 is completed, historical driving information of the vehicle on the driving path needs to be acquired, wherein the historical driving information at least includes: and the position information of the second intersection and the corresponding traffic signal lamp information of the second intersection exist on the driving path. Determining whether the position information of the first intersection is included in the position information of the second intersection; and if the position information of the second intersection comprises the position information of the first intersection, determining that the position information of the first intersection is correct information, and otherwise, determining that the position information of the first intersection is wrong information.
In this step, the position information of the intersection identified by the machine learning model in the history driving information is used for verification, for example, the position information of the intersection a is identified by the machine learning model, and the history information is called to determine whether the intersection a is included in the history driving information, if the intersection a is included in the history driving information, the position information of the intersection a identified by the machine learning model is correct, otherwise, the position information of the intersection a identified by the machine learning model is wrong.
The intersection information identified in the driving process is verified through the intersection information in the historical driving information, so that the technical effect of improving the accuracy of intersection identification can be realized.
In some optional embodiments of the present application, when step S106 is executed, it is determined whether the traffic signal light information corresponding to the first intersection can be found from the historical driving information; if the traffic signal lamp information corresponding to the first intersection can be found, determining that the traffic signal lamp exists at the first intersection; and if the traffic signal lamp information corresponding to the first intersection cannot be found, determining that no traffic signal lamp exists at the first intersection.
It should be noted that, since the historical driving information stores the information of the traffic lights corresponding to the intersection from the intersection position information (provided that the traffic lights are provided at the intersection), it is only necessary to search for the traffic lights corresponding to the intersection from the historical information. If the first intersection is provided with the traffic signal lamp, the traffic signal lamp information corresponding to the first intersection can be found from the historical driving information; if the traffic signal lamp is not arranged at the first intersection, the traffic signal lamp information corresponding to the first intersection cannot be searched from the historical driving information.
In other alternative embodiments of the present application, step S106 can also be implemented by the following method: inputting the images of the intersection into a second machine learning model for processing; and judging whether the first intersection has a traffic signal lamp or not according to the output result of the second machine learning model.
It should be noted that the first machine learning model may be the same as the first machine learning model, or may be a different machine learning model.
According to an alternative embodiment of the present application, step S108 is implemented by: if the first intersection does not have the traffic signal lamp, controlling the vehicle to run at a constant speed or run at a reduced speed to pass through the first intersection; and if the first intersection has the traffic signal lamp, determining the indicating state of the traffic signal lamp, and controlling the driving state of the vehicle when the vehicle passes through the first intersection according to the indicating state of the traffic signal lamp.
If no traffic signal lamp exists at the intersection, the vehicle needs to be controlled to decelerate or pass through the intersection at a constant speed; if the intersection has the traffic signal lamp, the indication state of the traffic signal lamp needs to be further identified, and the driving state of the vehicle is controlled according to the indication state of the traffic signal lamp.
In an alternative embodiment of the present application, the controlling the driving state of the vehicle passing through the first intersection according to the state of the traffic light comprises: if the indication state of the traffic signal lamp is red, controlling the vehicle to run at a reduced speed so that the vehicle stops running before reaching a stop line; if the indication state of the traffic signal lamp is green, controlling the vehicle to run at a constant speed or run at an accelerated speed to pass through the first intersection; and if the indication state of the traffic signal lamp is yellow, controlling the vehicle to decelerate so that the vehicle stops running before reaching the stop line.
Fig. 2 is a block diagram of a control apparatus of an autonomous vehicle according to an embodiment of the present application, as shown in fig. 2, the apparatus including:
the acquisition module 20 is used for acquiring images of the surrounding environment of the vehicle in the running process of the vehicle;
the determining module 22 is configured to determine, according to the image, position information of a first intersection existing on a driving path of the vehicle, where the first intersection is a position where the driving path intersects with other roads;
the judging module 24 is used for judging whether a traffic signal lamp exists at the first intersection;
and the control module 26 is used for controlling the running state of the vehicle when the vehicle passes through the first intersection according to the judgment result.
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 structure of an autonomous vehicle according to an embodiment of the present application, which includes, as shown in fig. 3: an image acquisition device 30, and a controller 32, wherein,
the image acquisition device 30 is used for acquiring an image of the surrounding environment of the vehicle during the running process of the vehicle;
a controller 32, in communication with the image acquisition device 30, for determining position information of a first intersection existing on a driving path of the vehicle according to the image, where the first intersection is a position where the driving path intersects with other roads; judging whether a traffic signal lamp exists at the first intersection or not; and controlling the running state of the vehicle when the vehicle passes through the first intersection according to the judgment result.
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.
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 automatic driving vehicle when the program runs.
The nonvolatile storage medium stores a program for executing the following functions: collecting images of the surrounding environment of the vehicle in the running process of the vehicle; determining position information of a first intersection existing on a driving path of the vehicle according to the image, wherein the first intersection is a position where the driving path intersects with other roads; judging whether a traffic signal lamp exists at the first intersection or not; and controlling the running state of the vehicle when the vehicle passes through the first intersection according to the judgment result.
The embodiment of the application also provides a processor which is used for operating the program stored in the memory, wherein the program is operated to execute the control method of the automatic driving vehicle.
The processor is configured to process a program that performs the following functions: collecting images of the surrounding environment of the vehicle in the running process of the vehicle; determining position information of a first intersection existing on a driving path of the vehicle according to the image, wherein the first intersection is a position where the driving path intersects with other roads; judging whether a traffic signal lamp exists at the first intersection or not; and controlling the running state of the vehicle when the vehicle passes through the first intersection according to the judgment result.
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 an autonomous vehicle, characterized by comprising:
acquiring an image of the surrounding environment of a vehicle in the running process of the vehicle;
determining position information of a first intersection existing on a driving path of the vehicle according to the image, wherein the first intersection is a position where the driving path intersects with other roads;
judging whether a traffic signal lamp exists at the first intersection or not;
and controlling the running state of the vehicle when the vehicle passes through the first intersection according to the judgment result.
2. The method of claim 1, wherein determining position information of a first intersection present on a travel path of the vehicle from the image comprises:
inputting the image into a first machine learning model for processing to obtain the position information of the first intersection, wherein the first machine learning model is obtained by training in the following way:
obtaining a training data set, training a neural network model based on the training data set, and generating the first machine learning model, wherein the training data set comprises: an image of the surroundings of the vehicle collected while the vehicle is traveling on the travel path and a position tag of an intersection marked on the image.
3. The method according to claim 1 or 2, characterized in that after determining position information of a first intersection present on a travel path of the vehicle from the image, the method further comprises:
acquiring historical driving information of the vehicle driving on the driving path, wherein the historical driving information at least comprises: the position information of a second intersection and the corresponding traffic signal light information of the second intersection exist on the driving path;
determining whether the position information of the first intersection is included in the position information of the second intersection;
and if the position information of the second intersection comprises the position information of the first intersection, determining that the position information of the first intersection is correct information, and otherwise, determining that the position information of the first intersection is wrong information.
4. The method of claim 3, wherein determining whether a traffic signal is present at the first intersection comprises:
judging whether the traffic signal lamp information corresponding to the first intersection can be found from the historical driving information; if the traffic signal lamp information corresponding to the first intersection can be found, determining that a traffic signal lamp exists at the first intersection; and if the traffic signal lamp information corresponding to the first intersection cannot be found, determining that no traffic signal lamp exists at the first intersection.
5. The method of claim 1, wherein determining whether a traffic signal is present at the first intersection further comprises:
inputting the images of the intersection into a second machine learning model for processing;
and judging whether a traffic signal lamp exists at the first intersection or not according to the output result of the second machine learning model.
6. The method according to claim 1, wherein controlling the driving state of the vehicle when passing through the first intersection according to the determination result comprises:
if the first intersection does not have the traffic signal lamp, controlling the vehicle to run at a constant speed or run at a reduced speed to pass through the first intersection;
and if the first intersection has the traffic signal lamp, determining the indicating state of the traffic signal lamp, and controlling the driving state of the vehicle when the vehicle passes through the first intersection according to the indicating state of the traffic signal lamp.
7. The method of claim 6, wherein controlling the driving state of the vehicle through the first intersection as a function of the state of the traffic light comprises:
if the indication state of the traffic signal lamp is a red light, controlling the vehicle to run at a reduced speed, and stopping the vehicle from running before reaching a stop line;
if the indication state of the traffic signal lamp is green, controlling the vehicle to run at a constant speed or run at an accelerated speed to pass through the first intersection;
and if the indication state of the traffic signal lamp is a yellow lamp, controlling the vehicle to run at a reduced speed, and stopping the vehicle before reaching a stop line.
8. A control apparatus of an autonomous 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 an image of the surrounding environment of a vehicle in the running process of the vehicle;
the determining module is used for determining position information of a first intersection existing on a driving path of the vehicle according to the image, wherein the first intersection is a position where the driving path is crossed with other roads;
the judging module is used for judging whether a traffic signal lamp exists at the first intersection or not;
and the control module is used for controlling the running state of the vehicle when the vehicle passes through the first intersection according to the judgment result.
9. An autonomous vehicle, comprising: an image acquisition device and a controller, wherein,
the image acquisition equipment is used for acquiring an image of the surrounding environment of the vehicle in the running process of the vehicle;
the controller is communicated with the image acquisition equipment and is used for determining position information of a first intersection existing on a driving path of the vehicle according to the image, wherein the first intersection is a position where the driving path is crossed with other roads; judging whether a traffic signal lamp exists at the first intersection or not; and controlling the running state of the vehicle when the vehicle passes through the first intersection according to the judgment result.
10. A non-volatile storage medium characterized by comprising a stored program, wherein a device on which the non-volatile storage medium is stored is controlled to execute the control method of an autonomous vehicle according to any one of claims 1 to 7 when the program is executed.
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| CN202110331395.3A CN113085861A (en) | 2021-03-26 | 2021-03-26 | Control method and device for automatic driving vehicle and automatic driving vehicle |
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| CN202110331395.3A CN113085861A (en) | 2021-03-26 | 2021-03-26 | Control method and device for automatic driving vehicle and automatic driving vehicle |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114373321A (en) * | 2021-12-01 | 2022-04-19 | 北京天兵科技有限公司 | Path optimization method, system, device and medium for single trip of individual |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114373321A (en) * | 2021-12-01 | 2022-04-19 | 北京天兵科技有限公司 | Path optimization method, system, device and medium for single trip of individual |
| CN114373321B (en) * | 2021-12-01 | 2023-08-25 | 北京天兵科技有限公司 | Path optimization method, system, device and medium for individual single trip |
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