CN112590814A - Vehicle automatic driving control method and system based on Internet of vehicles - Google Patents
Vehicle automatic driving control method and system based on Internet of vehicles Download PDFInfo
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- CN112590814A CN112590814A CN202011495906.7A CN202011495906A CN112590814A CN 112590814 A CN112590814 A CN 112590814A CN 202011495906 A CN202011495906 A CN 202011495906A CN 112590814 A CN112590814 A CN 112590814A
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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
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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
- B60W60/0011—Planning or execution of driving tasks involving control alternatives for a single driving scenario, e.g. planning several paths to avoid obstacles
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Abstract
The invention provides a vehicle automatic driving control method and system based on an internet of vehicles, which determine a driving path of a vehicle according to a real-time position and a destination position of the vehicle, adjust the driving path by combining an actual traffic condition, and simultaneously acquire and analyze a road condition environment image to determine the existence state information of an obstacle, thereby adjusting the motion state of the vehicle and carrying out early warning operation of traffic violation behaviors, so that the adaptive driving path and/or motion state adjustment can be effectively carried out according to the actual traffic state of a current driving area of the vehicle, and the intelligent degree and safety of vehicle automatic driving are improved.
Description
Technical Field
The invention relates to the technical field of automatic driving vehicles, in particular to a vehicle automatic driving control method and system based on an internet of vehicles.
Background
The automatic driving has become a main trend of intelligent vehicle development, and the automatic driving vehicle acquires different objects existing on a road surface by using different types of sensors during the vehicle driving process, and judges the relative position relationship between the different objects and the vehicle, so as to adjust and control the driving route and driving state parameters of the vehicle, thereby ensuring that the vehicle can safely and quickly reach a destination. However, the automatic driving vehicle in the prior art can only move according to a predetermined driving route, and cannot adaptively adjust a driving path and/or a movement state according to an actual traffic state of a current driving area of the vehicle, thereby easily causing the situations that the vehicle is slow to run and traffic violations occur, and reducing the intelligence degree and safety of automatic driving of the vehicle.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a vehicle automatic driving control method and a vehicle automatic driving control system based on an internet of vehicles, which determine a driving path of a vehicle by acquiring the real-time position and the destination position of the vehicle, acquire the actual traffic condition of a road section corresponding to the driving path through the internet of vehicles, adjust the driving path, indicate the vehicle to move according to the adjusted driving path, acquire a road condition environment image of the vehicle in the moving process, analyze and process the road condition environment image, determine the obstacle existence state information of the vehicle in the moving process, adjust the moving state of the vehicle according to the obstacle existence state information, determine whether the vehicle has traffic violation behaviors according to the adjusted moving state, and perform corresponding early warning operation; therefore, the vehicle automatic driving control method and system based on the Internet of vehicles determines the driving path of the vehicle according to the real-time position and the destination position of the vehicle, adjusts the driving path by combining the actual traffic condition, and simultaneously acquires and analyzes the road condition environment image to determine the state information of the obstacle, thereby adjusting the motion state of the vehicle and carrying out the early warning operation of the traffic violation behavior, so that the adaptive driving path and/or motion state adjustment can be effectively carried out according to the actual traffic state of the current driving area of the vehicle, and the intelligent degree and safety of the automatic driving of the vehicle are improved.
The invention provides a vehicle automatic driving control method based on an internet of vehicles, which is characterized by comprising the following steps:
step S1, acquiring the real-time position and the destination position of the vehicle, determining the driving path of the vehicle, and acquiring the actual traffic condition of the road section corresponding to the driving path through the Internet of vehicles, so as to adjust the driving path;
step S2, the vehicle is indicated to move according to the adjusted driving path, a road condition environment image of the vehicle in the moving process is obtained, and the road condition environment image is analyzed and processed, so that the obstacle existing state information of the vehicle in the moving process is determined;
step S3, adjusting the motion state of the vehicle according to the obstacle existing state information, and determining whether the vehicle has traffic violation behaviors according to the adjusted motion state, so as to perform corresponding early warning operation;
further, in step S1, acquiring a real-time location and a destination location of the vehicle, so as to determine a driving route of the vehicle, and acquiring an actual traffic condition of a road segment corresponding to the driving route through the internet of vehicles, so as to adjust the driving route specifically includes:
step S101, positioning and detecting the vehicle to obtain a real-time position of the vehicle, acquiring a voice signal from a user, and performing semantic analysis processing on the voice signal to obtain a destination position which the user expects the vehicle to go to;
step S102, determining the shortest path from the real-time position to the destination position as a driving path according to the real-time position, the destination position and the road network distribution information of the corresponding region;
step S103, acquiring a real-time traffic jam state of a road section corresponding to the driving route through the Internet of vehicles, and adjusting the driving route according to the real-time traffic jam state, so that the driving route avoids the corresponding traffic jam road section;
further, in step S2, the instructing the vehicle to move according to the adjusted driving path, acquiring a road condition environment image of the vehicle in the moving process, and analyzing and processing the road condition environment image, so as to determine the obstacle existing state information of the vehicle in the moving process specifically includes:
step S201, instructing the vehicle to move according to the adjusted driving path, and carrying out binocular shooting on the road condition environment of the vehicle in the moving process so as to obtain a corresponding road condition environment binocular image;
step S202, generating a three-dimensional image about the road condition environment according to the road condition environment binocular image, and converting the three-dimensional image into a pixel grayed three-dimensional image;
step S203, extracting corresponding image texture distribution information from the pixel grayed three-dimensional image, and determining the position and/or the volume shape of an obstacle in the motion process of the vehicle according to the image texture distribution information;
further, in the step S3, the motion state of the vehicle is adjusted according to the obstacle existing state information, and whether the vehicle has a traffic violation is determined according to the adjusted motion state, so that the corresponding early warning operation specifically includes:
step S301, adjusting the driving route direction and/or the driving speed of the vehicle according to the position and/or the volume shape of the obstacle;
step S302, acquiring the actual running route direction and/or the actual running speed of the vehicle after adjustment, and determining whether the vehicle has the solid line pressing behavior according to the actual running route direction and/or determining whether the vehicle has the overspeed behavior according to the actual running speed;
and step S303, when the solid line pressing behavior and/or the overspeed behavior are determined to exist, generating a corresponding early warning signal in a voice form.
The invention also provides a vehicle automatic driving control system based on the Internet of vehicles, which is characterized by comprising a driving path determining module, a driving path adjusting module, a road condition and environment image shooting module, an obstacle determining module, a motion state adjusting module and an early warning operation executing module; wherein the content of the first and second substances,
the driving path determining module is used for acquiring the real-time position and the destination position of the vehicle so as to determine the driving path of the vehicle;
the driving path adjusting module is used for acquiring the actual traffic condition of the road section corresponding to the driving path through the Internet of vehicles so as to adjust the driving path;
the road condition environment image shooting module is used for indicating the vehicle to move according to the adjusted driving path and acquiring a road condition environment image of the vehicle in the moving process;
the obstacle determining module is used for analyzing and processing the road condition environment image so as to determine obstacle existence state information of the vehicle in the moving process;
the motion state adjusting module is used for adjusting the motion state of the vehicle according to the obstacle existing state information;
the early warning operation execution module is used for determining whether the vehicle has traffic violation behaviors according to the adjusted motion state so as to perform corresponding early warning operation;
further, the driving path determining module obtains a real-time position and a destination position of the vehicle, so as to determine the driving path of the vehicle specifically includes:
the method comprises the steps of carrying out positioning detection on a vehicle so as to obtain a real-time position of the vehicle, obtaining a voice signal from a user, and carrying out semantic analysis processing on the voice signal so as to obtain a destination position which the user expects the vehicle to go to;
determining the shortest path from the real-time position to the destination position as a driving path according to the real-time position, the destination position and road network distribution information of the corresponding region;
and the number of the first and second groups,
the driving path adjusting module acquires the actual traffic condition of the road section corresponding to the driving path through the internet of vehicles, so that the adjusting of the driving path specifically comprises the following steps:
acquiring a real-time traffic jam state of a road section corresponding to the driving route through the Internet of vehicles, and adjusting the driving route according to the real-time traffic jam state, so that the driving route avoids the corresponding traffic jam road section;
further, the road condition environment image shooting module indicates that the vehicle moves according to the adjusted driving path, and acquiring the road condition environment image of the vehicle in the moving process specifically includes:
the vehicle is instructed to move according to the adjusted driving path, and the road condition environment of the vehicle in the moving process is subjected to binocular shooting, so that a corresponding road condition environment binocular image is obtained;
and the number of the first and second groups,
the obstacle determining module analyzes and processes the road condition environment image, so that determining obstacle existence state information of the vehicle in the moving process specifically comprises:
generating a three-dimensional image about the road condition environment according to the road condition environment binocular image, and converting the three-dimensional image into a pixel grayed three-dimensional image;
extracting corresponding image texture distribution information from the pixel grayed three-dimensional image, and determining the position and/or the volume shape of an obstacle in the movement process of the vehicle according to the image texture distribution information;
further, the adjusting the motion state of the vehicle according to the obstacle existing state information by the motion state adjusting module specifically includes:
adjusting the driving route direction and/or the driving speed of the vehicle according to the position and/or the volume shape of the obstacle;
and the number of the first and second groups,
the early warning operation execution module determines whether the vehicle has traffic violation behaviors according to the adjusted motion state, so that the corresponding early warning operation specifically comprises the following steps:
acquiring the actual running route direction and/or the actual running speed of the vehicle after adjustment, and determining whether the vehicle has the solid line pressing behavior according to the actual running route direction and/or determining whether the vehicle has the overspeed behavior according to the actual running speed;
and when the existence of the line pressing behavior and/or the overspeed behavior is determined, generating a corresponding early warning signal in a voice form.
Compared with the prior art, the vehicle automatic driving control method and system based on the internet of vehicles determines the driving path of the vehicle by acquiring the real-time position and the destination position of the vehicle, acquires the actual traffic condition of the road section corresponding to the driving path through the internet of vehicles, adjusts the driving path, indicates the vehicle to move according to the adjusted driving path, acquires the road condition environment image of the vehicle in the moving process, analyzes and processes the road condition environment image, determines the obstacle existence state information of the vehicle in the moving process, adjusts the moving state of the vehicle according to the obstacle existence state information, determines whether the vehicle has traffic behaviors or not according to the adjusted moving state, and accordingly performs corresponding early warning operation; therefore, the vehicle automatic driving control method and system based on the Internet of vehicles determines the driving path of the vehicle according to the real-time position and the destination position of the vehicle, adjusts the driving path by combining the actual traffic condition, and simultaneously acquires and analyzes the road condition environment image to determine the state information of the obstacle, thereby adjusting the motion state of the vehicle and carrying out the early warning operation of the traffic violation behavior, so that the adaptive driving path and/or motion state adjustment can be effectively carried out according to the actual traffic state of the current driving area of the vehicle, and the intelligent degree and safety of the automatic driving of the vehicle are improved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a vehicle automatic driving control method based on internet of vehicles according to the present invention.
Fig. 2 is a schematic structural diagram of a vehicle automatic driving control system based on the internet of vehicles provided by the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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 invention.
Referring to fig. 1, a schematic flow chart of a vehicle automatic driving control method based on an internet of vehicles according to an embodiment of the present invention is shown. The vehicle automatic driving control method based on the Internet of vehicles comprises the following steps:
step S1, acquiring the real-time position and the destination position of the vehicle, determining the driving path of the vehicle, and acquiring the actual traffic condition of the road section corresponding to the driving path through the internet of vehicles, thereby adjusting the driving path;
step S2, the vehicle is indicated to move according to the adjusted driving path, and the road condition environment image of the vehicle in the moving process is obtained, and then the road condition environment image is analyzed and processed, so that the obstacle existing state information of the vehicle in the moving process is determined;
and step S3, adjusting the motion state of the vehicle according to the obstacle existence state information, and determining whether the vehicle has traffic violation behaviors according to the adjusted motion state, thereby performing corresponding early warning operation.
The beneficial effects of the above technical scheme are: the vehicle automatic driving control method based on the Internet of vehicles determines the driving path of the vehicle according to the real-time position and the destination position of the vehicle, adjusts the driving path by combining the actual traffic condition, and simultaneously acquires and analyzes the road condition environment image to determine the state information of the obstacle, thereby adjusting the motion state of the vehicle and carrying out the early warning operation of traffic violation behaviors, thus effectively carrying out the adjustment of the adaptive driving path and/or motion state according to the actual traffic state of the current driving area of the vehicle, and further improving the intelligent degree and safety of the automatic driving of the vehicle.
Preferably, in step S1, the obtaining a real-time location and a destination location of the vehicle to determine a driving route of the vehicle, and obtaining an actual traffic condition of a road segment corresponding to the driving route through the internet of vehicles, so as to adjust the driving route specifically includes:
step S101, positioning and detecting the vehicle to obtain the real-time position of the vehicle, acquiring a voice signal from a user, and performing semantic analysis processing on the voice signal to obtain a destination position which the user expects the vehicle to go to;
step S102, determining the shortest path from the real-time position to the destination position as a driving path according to the real-time position, the destination position and the road network distribution information of the corresponding area;
step S103, acquiring a real-time traffic jam state of a road section corresponding to the driving route through the Internet of vehicles, and adjusting the driving route according to the real-time traffic jam state, so that the driving route avoids the corresponding traffic jam road section.
The beneficial effects of the above technical scheme are: the method comprises the steps that semantic analysis processing is carried out on voice signals from a user to obtain the destination position where the user expects the vehicle to go to, the user can conveniently and quickly and accurately indicate the vehicle to go to the corresponding destination on different occasions, the automation degree of vehicle control is improved, and due to the fact that the traffic jam states of different areas in different time periods are different, the real-time traffic jam state of the road section corresponding to the driving path is obtained through the internet of vehicles, the driving path is adjusted, the driving path can effectively avoid the corresponding traffic jam road section, and therefore the intelligent level of driving path adjustment is improved.
Preferably, in step S2, the instructing the vehicle to move according to the adjusted driving path, acquiring a road condition environment image of the vehicle in the moving process, and analyzing and processing the road condition environment image, so as to determine the obstacle existing state information of the vehicle in the moving process specifically includes:
step S201, instructing the vehicle to move according to the adjusted driving path, and carrying out binocular shooting on the road condition environment of the vehicle in the moving process so as to obtain a corresponding road condition environment binocular image;
step S202, generating a three-dimensional image about the road condition environment according to the road condition environment binocular image, and converting the three-dimensional image into a pixel grayed three-dimensional image;
step S203, extracting corresponding image texture distribution information from the pixel grayed three-dimensional image, and determining the position and/or the volume shape of an obstacle in the moving process of the vehicle according to the image texture distribution information.
The beneficial effects of the above technical scheme are: through carrying out binocular shooting on the road condition environment of the vehicle in the moving process, the three-dimensional image of the road condition environment can be rapidly and accurately obtained, and therefore accurate position and/or volume shape calibration can be conveniently carried out on obstacles existing in the vehicle in the moving process.
Preferably, in step S3, the moving state of the vehicle is adjusted according to the obstacle existing state information, and whether the vehicle has a traffic violation is determined according to the adjusted moving state, so that the performing of the corresponding early warning operation specifically includes:
step S301, adjusting the driving route direction and/or the driving speed of the vehicle according to the position and/or the volume shape of the obstacle;
step S302, acquiring the actual running route direction and/or the actual running speed of the vehicle after adjustment, and determining whether the vehicle has the solid line pressing behavior according to the actual running route direction and/or determining whether the vehicle has the overspeed behavior according to the actual running speed;
and step S303, when the solid line pressing behavior and/or the overspeed behavior are determined to exist, generating a corresponding early warning signal in a voice form.
The beneficial effects of the above technical scheme are: the position and/or the volume shape of the obstacle can affect the running of the vehicle to different degrees, the running route direction and/or the running speed of the vehicle can be adjusted according to the position and/or the volume shape of the obstacle, the automatic danger avoiding performance of the running of the vehicle can be improved, in addition, whether the vehicle has the solid line pressing behavior or not is determined according to the actual running route direction and/or whether the vehicle has the overspeed behavior or not is determined according to the actual running speed, the running safety of the vehicle can be ensured, meanwhile, the influence on other vehicles or pedestrians is avoided, and therefore the intelligent degree and the safety of the automatic driving of the vehicle are improved.
Referring to fig. 2, a schematic structural diagram of a vehicle automatic driving control system based on an internet of vehicles according to an embodiment of the present invention is shown. The vehicle automatic driving control system based on the internet of vehicles comprises a driving path determining module, a driving path adjusting module, a road condition environment image shooting module, an obstacle determining module, a motion state adjusting module and an early warning operation executing module; wherein the content of the first and second substances,
the driving path determining module is used for acquiring the real-time position and the destination position of the vehicle so as to determine the driving path of the vehicle;
the driving path adjusting module is used for acquiring the actual traffic condition of the road section corresponding to the driving path through the internet of vehicles so as to adjust the driving path;
the road condition environment image shooting module is used for indicating the vehicle to move according to the adjusted driving path and acquiring a road condition environment image of the vehicle in the moving process;
the obstacle determining module is used for analyzing and processing the road condition environment image so as to determine obstacle existence state information of the vehicle in the moving process;
the motion state adjusting module is used for adjusting the motion state of the vehicle according to the obstacle existing state information;
the early warning operation execution module is used for determining whether the vehicle has traffic violation behaviors according to the adjusted motion state, so that corresponding early warning operation is performed.
The beneficial effects of the above technical scheme are: the vehicle automatic driving control system based on the Internet of vehicles determines the driving path of the vehicle according to the real-time position and the destination position of the vehicle, adjusts the driving path by combining the actual traffic condition, and simultaneously acquires and analyzes the road condition environment image to determine the state information of the obstacle, thereby adjusting the motion state of the vehicle and carrying out the early warning operation of traffic violation behaviors, thus effectively carrying out the adjustment of the adaptive driving path and/or motion state according to the actual traffic state of the current driving area of the vehicle, and further improving the intelligent degree and safety of the automatic driving of the vehicle.
Preferably, the driving path determining module obtains a real-time position and a destination position of the vehicle, so as to determine the driving path of the vehicle specifically includes:
positioning and detecting the vehicle to obtain the real-time position of the vehicle, acquiring a voice signal from a user, and performing semantic analysis processing on the voice signal to obtain a destination position which the user expects the vehicle to go to;
determining the shortest path from the real-time position to the destination position as a driving path according to the real-time position, the destination position and the road network distribution information of the corresponding region;
and the number of the first and second groups,
the driving path adjusting module acquires the actual traffic condition of the road section corresponding to the driving path through the internet of vehicles, so that the adjustment of the driving path specifically comprises the following steps:
and acquiring the real-time traffic jam state of the road section corresponding to the driving route through the internet of vehicles, and adjusting the driving route according to the real-time traffic jam state, so that the driving route avoids the corresponding traffic jam road section.
The beneficial effects of the above technical scheme are: the method comprises the steps that semantic analysis processing is carried out on voice signals from a user to obtain the destination position where the user expects the vehicle to go to, the user can conveniently and quickly and accurately indicate the vehicle to go to the corresponding destination on different occasions, the automation degree of vehicle control is improved, and due to the fact that the traffic jam states of different areas in different time periods are different, the real-time traffic jam state of the road section corresponding to the driving path is obtained through the internet of vehicles, the driving path is adjusted, the driving path can effectively avoid the corresponding traffic jam road section, and therefore the intelligent level of driving path adjustment is improved.
Preferably, the road condition environment image capturing module instructs the vehicle to move according to the adjusted driving path, and acquiring the road condition environment image of the vehicle in the moving process specifically includes:
the vehicle is instructed to move according to the adjusted driving path, and binocular shooting is carried out on the road condition environment of the vehicle in the moving process, so that a corresponding binocular image of the road condition environment is obtained;
and the number of the first and second groups,
the obstacle determining module analyzes and processes the road condition environment image, so that the obstacle existing state information of the vehicle in the moving process is determined to specifically comprise:
generating a three-dimensional image about the road condition environment according to the road condition environment binocular image, and converting the three-dimensional image into a pixel grayed three-dimensional image;
and extracting corresponding image texture distribution information from the pixel grayed three-dimensional image, and determining the position and/or the volume shape of the obstacle in the moving process of the vehicle according to the image texture distribution information.
The beneficial effects of the above technical scheme are: through carrying out binocular shooting on the road condition environment of the vehicle in the moving process, the three-dimensional image of the road condition environment can be rapidly and accurately obtained, and therefore accurate position and/or volume shape calibration can be conveniently carried out on obstacles existing in the vehicle in the moving process.
Preferably, the adjusting the motion state of the vehicle according to the obstacle existing state information by the motion state adjusting module specifically includes:
adjusting the driving route direction and/or the driving speed of the vehicle according to the position and/or the volume shape of the obstacle;
and the number of the first and second groups,
the early warning operation execution module determines whether the vehicle has traffic violation behaviors according to the adjusted motion state, so that the corresponding early warning operation specifically comprises the following steps:
acquiring the actual running route direction and/or the actual running speed of the vehicle after adjustment, and determining whether the vehicle has the solid line pressing behavior according to the actual running route direction and/or determining whether the vehicle has the overspeed behavior according to the actual running speed;
and when the existence of the line pressing behavior and/or the overspeed behavior is determined, generating a corresponding early warning signal in a voice form.
The beneficial effects of the above technical scheme are: the position and/or the volume shape of the obstacle can affect the running of the vehicle to different degrees, the running route direction and/or the running speed of the vehicle can be adjusted according to the position and/or the volume shape of the obstacle, the automatic danger avoiding performance of the running of the vehicle can be improved, in addition, whether the vehicle has the solid line pressing behavior or not is determined according to the actual running route direction and/or whether the vehicle has the overspeed behavior or not is determined according to the actual running speed, the running safety of the vehicle can be ensured, meanwhile, the influence on other vehicles or pedestrians is avoided, and therefore the intelligent degree and the safety of the automatic driving of the vehicle are improved.
As can be seen from the content of the above embodiment, the method and system for controlling automatic driving of a vehicle based on an internet of vehicles determine a driving path of the vehicle by obtaining a real-time position and a destination position of the vehicle, and obtain an actual traffic condition of a road segment corresponding to the driving path through the internet of vehicles, so as to adjust the driving path, instruct the vehicle to move according to the adjusted driving path, obtain a road condition environment image of the vehicle in a moving process, analyze and process the road condition environment image, so as to determine obstacle existence state information of the vehicle in the moving process, adjust a moving state of the vehicle according to the obstacle existence state information, and determine whether the vehicle has a traffic violation behavior according to the adjusted moving state, so as to perform a corresponding early warning operation; therefore, the vehicle automatic driving control method and system based on the Internet of vehicles determines the driving path of the vehicle according to the real-time position and the destination position of the vehicle, adjusts the driving path by combining the actual traffic condition, and simultaneously acquires and analyzes the road condition environment image to determine the state information of the obstacle, thereby adjusting the motion state of the vehicle and carrying out the early warning operation of the traffic violation behavior, so that the adaptive driving path and/or motion state adjustment can be effectively carried out according to the actual traffic state of the current driving area of the vehicle, and the intelligent degree and safety of the automatic driving of the vehicle are improved.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (8)
1. The vehicle automatic driving control method based on the Internet of vehicles is characterized by comprising the following steps:
step S1, acquiring the real-time position and the destination position of the vehicle, determining the driving path of the vehicle, and acquiring the actual traffic condition of the road section corresponding to the driving path through the Internet of vehicles, so as to adjust the driving path;
step S2, the vehicle is indicated to move according to the adjusted driving path, a road condition environment image of the vehicle in the moving process is obtained, and the road condition environment image is analyzed and processed, so that the obstacle existing state information of the vehicle in the moving process is determined;
and step S3, adjusting the motion state of the vehicle according to the obstacle existence state information, and determining whether the vehicle has traffic violation behaviors according to the adjusted motion state, so as to perform corresponding early warning operation.
2. The internet-of-vehicles-based vehicle autopilot control method of claim 1, wherein: in step S1, acquiring a real-time location and a destination location of the vehicle, so as to determine a driving route of the vehicle, and acquiring an actual traffic condition of a road segment corresponding to the driving route through an internet of vehicles, so as to adjust the driving route specifically includes:
step S101, positioning and detecting the vehicle to obtain a real-time position of the vehicle, acquiring a voice signal from a user, and performing semantic analysis processing on the voice signal to obtain a destination position which the user expects the vehicle to go to;
step S102, determining the shortest path from the real-time position to the destination position as a driving path according to the real-time position, the destination position and the road network distribution information of the corresponding region;
step S103, acquiring a real-time traffic jam state of a road section corresponding to the driving route through the Internet of vehicles, and adjusting the driving route according to the real-time traffic jam state, so that the driving route avoids the corresponding traffic jam road section.
3. The internet-of-vehicles-based vehicle autopilot control method of claim 2, wherein: in step S2, the step of instructing the vehicle to move according to the adjusted driving path, acquiring a road condition environment image of the vehicle in the moving process, and analyzing and processing the road condition environment image, so as to determine that the obstacle existing state information of the vehicle in the moving process specifically includes:
step S201, instructing the vehicle to move according to the adjusted driving path, and carrying out binocular shooting on the road condition environment of the vehicle in the moving process so as to obtain a corresponding road condition environment binocular image;
step S202, generating a three-dimensional image about the road condition environment according to the road condition environment binocular image, and converting the three-dimensional image into a pixel grayed three-dimensional image;
step S203, extracting corresponding image texture distribution information from the pixel grayed three-dimensional image, and determining the position and/or the volume shape of an obstacle in the motion process of the vehicle according to the image texture distribution information.
4. The internet-of-vehicles-based vehicle autopilot control method of claim 3, wherein: in the step S3, the motion state of the vehicle is adjusted according to the obstacle existing state information, and whether the vehicle has a traffic violation is determined according to the adjusted motion state, so that the corresponding early warning operation specifically includes:
step S301, adjusting the driving route direction and/or the driving speed of the vehicle according to the position and/or the volume shape of the obstacle;
step S302, acquiring the actual running route direction and/or the actual running speed of the vehicle after adjustment, and determining whether the vehicle has the solid line pressing behavior according to the actual running route direction and/or determining whether the vehicle has the overspeed behavior according to the actual running speed;
and step S303, when the solid line pressing behavior and/or the overspeed behavior are determined to exist, generating a corresponding early warning signal in a voice form.
5. The automatic vehicle driving control system based on the Internet of vehicles is characterized by comprising a driving path determining module, a driving path adjusting module, a road condition and environment image shooting module, an obstacle determining module, a motion state adjusting module and an early warning operation executing module; wherein the content of the first and second substances,
the driving path determining module is used for acquiring the real-time position and the destination position of the vehicle so as to determine the driving path of the vehicle;
the driving path adjusting module is used for acquiring the actual traffic condition of the road section corresponding to the driving path through the Internet of vehicles so as to adjust the driving path;
the road condition environment image shooting module is used for indicating the vehicle to move according to the adjusted driving path and acquiring a road condition environment image of the vehicle in the moving process;
the obstacle determining module is used for analyzing and processing the road condition environment image so as to determine obstacle existence state information of the vehicle in the moving process;
the motion state adjusting module is used for adjusting the motion state of the vehicle according to the obstacle existing state information;
and the early warning operation execution module is used for determining whether the vehicle has traffic violation behaviors according to the adjusted motion state so as to perform corresponding early warning operation.
6. The internet-of-vehicles based vehicle autopilot control system of claim 5 wherein: the driving path determining module acquires a real-time position and a destination position of the vehicle, and thus determining the driving path of the vehicle specifically includes:
the method comprises the steps of carrying out positioning detection on a vehicle so as to obtain a real-time position of the vehicle, obtaining a voice signal from a user, and carrying out semantic analysis processing on the voice signal so as to obtain a destination position which the user expects the vehicle to go to;
determining the shortest path from the real-time position to the destination position as a driving path according to the real-time position, the destination position and road network distribution information of the corresponding region;
and the number of the first and second groups,
the driving path adjusting module acquires the actual traffic condition of the road section corresponding to the driving path through the internet of vehicles, so that the adjusting of the driving path specifically comprises the following steps:
and acquiring the real-time traffic jam state of the road section corresponding to the driving route through the internet of vehicles, and adjusting the driving route according to the real-time traffic jam state, so that the driving route avoids the corresponding traffic jam road section.
7. The internet-of-vehicles based vehicle autopilot control system of claim 6 wherein: the road condition environment image shooting module indicates that the vehicle moves according to the adjusted driving path, and the acquiring of the road condition environment image of the vehicle in the moving process specifically comprises:
the vehicle is instructed to move according to the adjusted driving path, and the road condition environment of the vehicle in the moving process is subjected to binocular shooting, so that a corresponding road condition environment binocular image is obtained; and the number of the first and second groups,
the obstacle determining module analyzes and processes the road condition environment image, so that determining obstacle existence state information of the vehicle in the moving process specifically comprises:
generating a three-dimensional image about the road condition environment according to the road condition environment binocular image, and converting the three-dimensional image into a pixel grayed three-dimensional image;
and extracting corresponding image texture distribution information from the pixel grayed three-dimensional image, and determining the position and/or the volume shape of an obstacle in the movement process of the vehicle according to the image texture distribution information.
8. The internet-of-vehicles based vehicle autopilot control system of claim 7 wherein: the adjusting module of the motion state adjusts the motion state of the vehicle according to the obstacle existing state information, and specifically includes:
adjusting the driving route direction and/or the driving speed of the vehicle according to the position and/or the volume shape of the obstacle;
and the number of the first and second groups,
the early warning operation execution module determines whether the vehicle has traffic violation behaviors according to the adjusted motion state, so that the corresponding early warning operation specifically comprises the following steps:
acquiring the actual running route direction and/or the actual running speed of the vehicle after adjustment, and determining whether the vehicle has the solid line pressing behavior according to the actual running route direction and/or determining whether the vehicle has the overspeed behavior according to the actual running speed;
and when the existence of the line pressing behavior and/or the overspeed behavior is determined, generating a corresponding early warning signal in a voice form.
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