[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

CN115476855A - Intelligent automobile driving method, device, equipment and storage medium - Google Patents

Intelligent automobile driving method, device, equipment and storage medium Download PDF

Info

Publication number
CN115476855A
CN115476855A CN202211184582.4A CN202211184582A CN115476855A CN 115476855 A CN115476855 A CN 115476855A CN 202211184582 A CN202211184582 A CN 202211184582A CN 115476855 A CN115476855 A CN 115476855A
Authority
CN
China
Prior art keywords
driving
historical
automobile
image information
road image
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202211184582.4A
Other languages
Chinese (zh)
Inventor
兰华
刘开勇
何国良
付广
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
SAIC GM Wuling Automobile Co Ltd
Original Assignee
SAIC GM Wuling Automobile Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by SAIC GM Wuling Automobile Co Ltd filed Critical SAIC GM Wuling Automobile Co Ltd
Priority to CN202211184582.4A priority Critical patent/CN115476855A/en
Publication of CN115476855A publication Critical patent/CN115476855A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • 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
    • 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
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
    • B60W10/06—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of combustion engines
    • 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
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/12—Conjoint control of vehicle sub-units of different type or different function including control of differentials
    • 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
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/18—Conjoint control of vehicle sub-units of different type or different function including control of braking systems
    • 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
    • B60W2420/00—Indexing codes relating to the type of sensors based on the principle of their operation
    • B60W2420/40—Photo, light or radio wave sensitive means, e.g. infrared sensors
    • B60W2420/403—Image sensing, e.g. optical camera
    • 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
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • 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
    • B60W2530/00—Input parameters relating to vehicle conditions or values, not covered by groups B60W2510/00 or B60W2520/00
    • 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
    • B60W2555/00—Input parameters relating to exterior conditions, not covered by groups B60W2552/00, B60W2554/00
    • B60W2555/60—Traffic rules, e.g. speed limits or right of way
    • 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
    • B60W2710/00—Output or target parameters relating to a particular sub-units
    • B60W2710/06—Combustion engines, Gas turbines
    • 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
    • B60W2710/00—Output or target parameters relating to a particular sub-units
    • B60W2710/10—Change speed gearings
    • 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
    • B60W2710/00—Output or target parameters relating to a particular sub-units
    • B60W2710/18—Braking system

Landscapes

  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Navigation (AREA)

Abstract

The application discloses an intelligent driving method, an intelligent driving device, intelligent driving equipment and a storage medium for an automobile, and belongs to the technical field of intelligent driving, wherein the method comprises the following steps: acquiring historical road image information and historical driving routes of an automobile; according to the historical road image information, target map data corresponding to the historical driving route are constructed; and if a historical driving route memory driving instruction input by a user is received, determining driving control parameters of the intelligent driving controller according to the target map data so as to enable the automobile to drive along the historical driving route. Therefore, the target map of the historical driving route is constructed according to the historical road image information and the historical driving route of the automobile, so that scenes in which lane-level map positioning cannot be achieved can be clearly displayed, and the intelligent driving map can be more comprehensively covered.

Description

Intelligent automobile driving method, device, equipment and storage medium
Technical Field
The application relates to the field of intelligent driving, in particular to an intelligent driving method, device, equipment and storage medium for an automobile.
Background
In the related art, in order to realize urban cruising or point-to-point intelligent cruising, a high-precision map box hardware capable of displaying lane-level positioning needs to be built in a vehicle.
However, the high-precision map has the problem of insufficient coverage rate, so that the automobile cannot provide urban cruising or point-to-point intelligent cruising service in an area which cannot be covered by the high-precision map.
Content of application
The application mainly aims to provide an automobile intelligent driving method, device, equipment and storage medium, and aims to solve the technical problem that urban cruising or point-to-point intelligent cruising of an automobile is limited to a high-precision map coverage area in the prior art.
In order to achieve the above object, the present application provides an intelligent driving method for an automobile, including:
acquiring historical road image information and historical driving routes of an automobile;
constructing target map data corresponding to the historical driving route according to the historical road image information;
and if a historical driving route memory driving instruction input by a user is received, determining driving control parameters of the intelligent driving controller according to the target map data so as to enable the automobile to drive along the historical driving route.
Optionally, the vehicle is provided with a vehicle-mounted camera, and a vehicle-mounted global positioning system and/or an inertial measurement unit;
the acquiring of the historical reason image information and the historical driving route of the automobile comprises the following steps:
acquiring historical road image information according to a driving picture acquired by a vehicle-mounted camera;
and obtaining the historical driving route by utilizing a vehicle-mounted global positioning system and/or an inertia measuring unit.
Optionally, the constructing target map data corresponding to the historical driving route according to the historical road image information includes:
uploading the historical road image information and the historical driving route to a cloud server so that the cloud server constructs target map data corresponding to the historical driving route according to the historical road image information;
and receiving the target map data returned by the cloud server.
Optionally, the uploading the historical road image information and the historical driving route to a cloud server, so that the cloud server constructs target map data corresponding to the historical driving route according to the historical road image information, including:
encrypting the historical road image information to obtain encrypted historical road image information;
and uploading the encrypted historical road image information to a cloud server, so that the cloud server constructs target map data corresponding to the historical driving route according to the encrypted historical road image information.
Optionally, the determining driving control parameters of the intelligent driving controller according to the target map data includes:
obtaining at least one of driving distance data, automobile pose data or signal lamp data according to the historical driving route;
obtaining driving reference data according to at least one of the driving distance data, the automobile pose data or the signal lamp data;
and determining driving control parameters of the intelligent driving controller according to the driving reference data and the target map data.
Optionally, the constructing target map data corresponding to the historical driving route according to the historical road image information includes:
determining at least one high-frequency driving route corresponding to the user according to the driving frequency of each historical driving route;
and constructing target map data corresponding to the high-frequency driving route according to the historical road image information.
Optionally, the driving control parameters include control parameters of at least one of a vehicle body electronic stability control system, an automatic transmission control unit and an engine management system.
In a second aspect, the present application further provides an intelligent driving device for an automobile, including:
the acquisition module is used for acquiring historical road image information and historical driving routes of the automobile;
the construction module is used for constructing target map data corresponding to the historical driving route according to the historical road image information;
and the determining module is used for determining the driving control parameters of the intelligent driving controller according to the target map data if a historical driving route memory driving instruction input by a user is received, so that the automobile can drive along the historical driving route.
In a third aspect, the present application further provides an apparatus for intelligent driving of an automobile, a memory, a processor, and an intelligent driving program of an automobile stored in the memory and capable of running on the processor, where the intelligent driving program of an automobile is configured to implement the steps of the intelligent driving method of an automobile as described above.
In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, where the program is executed by a processor to implement the intelligent driving method for a vehicle according to any embodiment of the present application.
According to the intelligent automobile driving method provided by the embodiment of the application, historical road image information and historical driving routes of an automobile are obtained; according to the historical road image information, target map data corresponding to the historical driving route are constructed; and if a historical driving route memory driving instruction input by a user is received, determining driving control parameters of the intelligent driving controller according to the target map data so as to enable the automobile to drive along the historical driving route.
Therefore, in the application, the road image through which the user drives the automobile is collected, the historical road image information is obtained, the route through which the user drives the automobile is positioned, the historical driving route is obtained, and the target map data corresponding to the historical driving route is constructed according to the historical road image information. Therefore, when the automobile runs to a special scene, if a user inputs a historical running route to memorize a running instruction, the vehicle-mounted host can control the automobile to automatically drive according to the target map data, and lane-level positioning is realized through the target map data, so that the automobile can realize point-to-point intelligent cruise, and the point-to-point intelligent cruise of the automobile is not limited by the coverage rate of a high-precision map.
Drawings
FIG. 1 is a schematic diagram of a hardware structure of an embodiment of an intelligent driving method for an automobile according to the present application;
FIG. 2 is a schematic flow chart illustrating a first embodiment of an intelligent driving method for a vehicle according to the present application;
FIG. 3 is a schematic flowchart illustrating a second embodiment of the intelligent driving method for a vehicle according to the present application;
FIG. 4 is a schematic flowchart of a third embodiment of an intelligent driving method for a vehicle according to the present application;
FIG. 5 is a schematic flow chart illustrating a fourth embodiment of the intelligent driving method for a vehicle according to the present application;
FIG. 6 is a schematic flow chart illustrating a fifth embodiment of an intelligent driving method for a vehicle according to the present application;
fig. 7 is a schematic structural framework diagram of the first embodiment of the intelligent driving device for the automobile according to the present application.
The implementation, functional features and advantages of the object of the present application will be further explained with reference to the embodiments, and with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In order to realize city cruising or point-to-point intelligent cruising, an intelligent driving system needs to build high-precision map box hardware capable of displaying lane-level positioning in an automobile. However, the high-precision map has the problem of insufficient coverage rate, so that the automobile cannot provide urban cruising or point-to-point intelligent cruising service in an area which cannot be covered by the high-precision map.
Therefore, the method and the device provide a solution, the road image through which the user drives the automobile is collected, historical road image information is obtained, the route through which the user drives the automobile is positioned, a historical driving route is obtained, and then target map data corresponding to the historical driving route is constructed according to the historical road image information. Therefore, when the automobile runs to a special scene, if a user inputs a historical running route to memorize a running instruction, the vehicle-mounted host can control the automobile to automatically drive according to the target map data, and the lane-level positioning is realized through the target map data, so that the automobile can realize point-to-point intelligent cruise, and the point-to-point intelligent cruise of the automobile is not limited by the coverage rate of a high-precision map.
Referring to fig. 1, fig. 1 is a schematic structural diagram of an automobile intelligent driving device in a hardware operating environment according to an embodiment of the present application.
As shown in fig. 1, the intelligent driving of the automobile may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to implement connection communication among these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WIreless-FIdelity (WI-FI) interface). The Memory 1005 may be a Random Access Memory (RAM) Memory, or a Non-Volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration shown in FIG. 1 does not constitute a limitation to intelligent operation of an automobile and may include more or fewer components than those shown, or some components in combination, or a different arrangement of components.
As shown in fig. 1, the memory 1005, which is a storage medium, may include an operating system, a data storage module, a network communication module, a user interface module, and a smart driving program for a vehicle.
In the intelligent automobile driving terminal shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the intelligent automobile driving terminal can be arranged in the intelligent automobile driving terminal, and the intelligent automobile driving terminal calls the intelligent automobile driving program stored in the memory 1005 through the processor 1001 and executes the intelligent automobile driving method provided by the embodiment of the application.
Based on the above hardware structure for intelligent driving of the vehicle but not limited to the above hardware structure, the present application provides a first embodiment of an intelligent driving method of the vehicle. Referring to fig. 2, fig. 2 shows a schematic flow chart of a first embodiment for applying for intelligent driving of an automobile.
It should be noted that, although a logical order is shown in the flow chart, in some cases, the steps shown or described may be performed in an order different than that shown or described herein.
In this embodiment, the intelligent driving method for the automobile includes:
and S10, acquiring historical road image information and historical driving routes of the automobile.
The execution main body of the automobile intelligent driving method is a vehicle-mounted host, the vehicle-mounted host is a vehicle-mounted terminal which is installed on a vehicle driving platform and has various functions of ETC passing, 3G or above wireless communication, online navigation, road condition information, travel guide, shopping, entertainment audio and video and the like, and the vehicle-mounted host can realize information communication between people and a vehicle and between the vehicle and the outside (the vehicle and the vehicle) in function. The vehicle has an onboard camera, an onboard global positioning system and/or an inertial measurement unit. The vehicle-mounted host computer can carry out data transmission with the vehicle-mounted camera, for example, when a user drives a car, the vehicle-mounted camera can transmit the collected road image information to the vehicle-mounted host computer for storage, and historical road image information is obtained.
In a specific embodiment of the present application, the historical road image information refers to a driving road image acquired by a vehicle-mounted camera when a user drives a vehicle. The historical driving route refers to a route which is traveled on a road when the automobile is in daily travel.
For example, when the user is a general user on duty, and the user drives a vehicle to travel, the historical road image information collected by the vehicle-mounted camera is mainly commuting road image information on duty. Meanwhile, the historical driving route from home to company of the user is obtained by Positioning the automobile through a vehicle-mounted GPS (Global Positioning System) and an IMU (Inertial measurement unit).
And S20, constructing target map data corresponding to the historical driving route according to the historical road image information.
In the embodiment of the application, the historical road image information and the historical driving route are acquired simultaneously when the user drives the automobile, so that each image feature in the historical road image information can correspond to each position point in the historical driving route, and therefore the target map data corresponding to the historical driving route can be constructed. Thus, the target map data in the present embodiment may be a set of a plurality of road images, and the road images in the set are arranged in accordance with the corresponding historical travel routes, thereby forming map data having the position data of the spatial distribution of the map elements, and the corresponding graphic features and geographic attributes thereof.
If three bus stops and crossroads are sequentially arranged on the historical driving route, a plurality of images of the three bus stops and the traffic light crossroads are screened out from the historical road image information, and the images are arranged according to the passing sequence of the three bus stops and the crossroads, so that the historical driving route is constructed according to the historical road image information to obtain target map data, the route which a user drives can be comprehensively covered, more accurate map information is obtained, and the map information is acquired from the view angle of the automobile, so that lane-level positioning can be realized.
And S30, if a historical driving route memory driving instruction input by a user is received, determining driving control parameters of the intelligent driving controller according to the target map data so as to enable the automobile to drive along the historical driving route.
Specifically, the driving instruction memorized may be a driving instruction input by the user to control the automobile to travel according to the historical travel route. The driving control parameter may be driving parameter information of the vehicle during driving, such as the speed and direction of driving of the vehicle.
If the user drives the automobile to go home to enter the community parking lot, after the user inputs the memorized driving instruction at the vehicle-mounted host computer, the vehicle-mounted host computer controls the automobile to automatically go to the exclusive parking space of the user by taking the parking lot entrance as a starting point according to the received memorized driving instruction and the target map data under the condition that the user does not intervene, and the parking is finished.
In the embodiment, historical road image information and historical driving routes of the automobile are acquired; constructing target map data corresponding to the historical driving route according to the historical road image information; and if a historical driving route memory driving instruction input by a user is received, determining driving control parameters of the intelligent driving controller according to the target map data so as to enable the automobile to drive along the historical driving route. Therefore, the historical road image information and the historical driving route of the automobile are collected when the user drives the automobile, and therefore the target map data corresponding to the historical route constructed according to the historical road image information can enable the route which the user drives to clearly show in the target map data, so that the automobile can be positioned according to the lane level of the target map data, and the point-to-point intelligent cruise can be achieved by taking the target map data as reference. That is, in this embodiment, the intelligent cruise service of the automobile does not depend on the high-precision map, and therefore the point-to-point intelligent cruise service of the automobile can be prevented from being limited by the coverage rate of the high-precision map, and further the point-to-point intelligent cruise service is provided for more users, so that the user experience is improved.
Further, as an embodiment, referring to fig. 3, the present application provides a second embodiment of the intelligent driving method for a vehicle. Referring to fig. 3, fig. 3 is a flow chart illustrating a second embodiment of the intelligent driving method for a vehicle.
In this embodiment, the step S20 includes:
step S201, uploading the historical road image information and the historical driving route to a cloud server, so that the cloud server constructs target map data corresponding to the historical driving route according to the historical road image information.
Step S202, receiving the target map data returned by the cloud server.
In the embodiment of the application, the automobile is provided with a vehicle-mounted camera, a vehicle-mounted global positioning system and/or an inertia measurement unit; the acquiring of the historical road image information and the historical driving route of the automobile comprises the following steps: acquiring historical road image information according to a driving picture acquired by a vehicle-mounted camera; and obtaining the historical driving route by utilizing a vehicle-mounted global positioning system and/or an inertia measuring unit.
For example, when a user drives an automobile, the vehicle-mounted camera is in an on state, so that the driving picture can be collected to generate historical road image information, such as sign line information of a road surface and surrounding environment information of driving, such as images of passing schools or commercial squares.
The inertial measurement unit is a device for measuring the three-axis attitude angle (or angular velocity) and acceleration of an object. Generally, an IMU (Inertial measurement unit) includes three single-axis accelerometers and three single-axis gyroscopes, the accelerometers detect acceleration signals of an object in three independent axes of a carrier coordinate system, and the gyroscopes detect angular velocity signals of the carrier relative to a navigation coordinate system, measure angular velocity and acceleration of the object in three-dimensional space, and solve the attitude of the object based on the angular velocity and acceleration signals. The accuracy of the collected historical driving route can be improved by Positioning the automobile through a Global Positioning System (GPS) and an Inertial Measurement Unit (IMU).
In this embodiment, the cloud server is a simple, efficient, secure, reliable, and elastically scalable computing service. The vehicle-mounted host uploads the historical road image and the historical driving route acquired by the vehicle-mounted camera to the cloud server, and the cloud server can provide a special intelligent driving map for a user according to the received historical road image and the received historical driving route and in combination with the driving behavior of the user. For example, the cloud server obtains, according to the historical road image information and the historical driving route and according to the historical road image information, landmark points on a route where the user drives the automobile, which are an a cell, a B avenue, a C square and a D primary school respectively, wherein the a cell is a driving starting point or an end point of the automobile, and the D primary school is a driving end point or a starting point of the automobile, and combines the historical driving route obtained by positioning of the GPS and the IMU, so that an exclusive intelligent driving map of the user can be obtained, that is, the exclusive intelligent driving map is a map for the user to pick up children to go to school or go to school.
Therefore, in the application, according to the historical road image information and the historical driving route acquired by driving the automobile by different users, the exclusive intelligent driving map can be formulated for different users.
Further, as an embodiment, referring to fig. 4, the present application provides a third embodiment of an intelligent driving method for an automobile. Referring to fig. 4, fig. 4 is a flowchart illustrating a third embodiment of the intelligent driving method for a vehicle.
In this embodiment, the step S201 includes:
and step S2011, encrypting the historical road image information to obtain the encrypted historical road image information.
And S2012, uploading the encrypted historical road image information to a cloud server so that the cloud server constructs target map data corresponding to the historical driving route according to the encrypted historical road image information.
In the embodiment, in order to protect the trip privacy of the user and prevent the user privacy from being leaked, after the vehicle-mounted camera collects the historical road image information, the vehicle-mounted host encrypts the collected historical road image information to obtain the encrypted historical road image information, and uploads the encrypted historical road image information to the cloud server, so that the trip information of the user can be prevented from being leaked when the historical road image information is uploaded to the cloud server, and the user privacy can be well protected.
Further, as an embodiment, referring to fig. 5, the present application provides a fourth embodiment of an intelligent driving method for an automobile. Referring to fig. 5, fig. 5 is a flow chart illustrating a fourth embodiment of the intelligent driving method for a vehicle.
In this embodiment, the step S30 includes:
step S301, obtaining at least one of driving distance data, automobile pose data or signal lamp data according to the historical driving route;
step S302, obtaining driving reference data according to at least one of the driving distance data, the automobile pose data or the signal lamp data;
and S303, determining driving control parameters of the intelligent driving controller according to the driving reference data and the target map data.
In the embodiment of the present application, the travel distance data refers to information on the distance actually traveled by the user from the start of driving to the end of driving of the automobile. The vehicle pose data includes position information and attitude information of the vehicle. The position information refers to the geographical position information of the user at a certain time, which is obtained according to the positioning of the GPS or IMU; the attitude information refers to the driving state of the vehicle, such as acceleration, deceleration, and orientation, while the user is driving the vehicle. The signal light data refers to the number information of the traffic light intersections and the time information of the traffic light intersections, and the like, which are experienced by the automobile in the historical driving process. The driving reference data refers to user driving behavior data formed according to at least one of driving distance data, automobile pose data or signal lamp data.
If the user is a common office worker, the residence of the user is 4km away from the company, the user can pass through the three traffic light intersections when the user drives the automobile to go to the road of the company, the service time of the user when the user passes through the three traffic light intersections is 8 minutes, and the user can slow down when passing through the three traffic light intersections, so that the driving distance data of the automobile can be determined to be 4km, the automobile position data is the automobile speed reduction for three times, and the signal light data passes through the three traffic light intersections for eight minutes.
In this embodiment, at least one of the travel distance data, the direction data, or the traffic data is obtained according to the historical travel route, so as to obtain the travel data information, and the driving control parameters of the intelligent driving controller are determined according to the travel data information and the target map data, so that the riding experience provided by the vehicle under the intelligent driving control is more suitable for the riding experience provided by the user when actually driving. Wherein the driving control parameters comprise control parameters of at least one of a vehicle body electronic stability control system, an automatic gearbox control unit and an engine management system.
Specifically, an Electronic Stability Control system (ESC) is a novel active safety system of a vehicle, is a further extension of functions of an automobile anti-lock braking system and a traction Control system, and is additionally provided with a yaw rate sensor, a lateral acceleration sensor and a steering wheel angle sensor when the vehicle is steered and driven, and the driving force and the braking force of front and rear wheels and left and right wheels are controlled through an ECU (Electronic Control Unit) to ensure the lateral Stability of the vehicle driving. The automatic Transmission Control Unit (TCU) is a control module for determining a shift point when an automobile is shifted, controlling an automobile shift mechanism to perform a downshift and upshift operation, calculating a motor speed when the automobile is shifted, and calculating an automobile speed. The engine management system is a system that converts the intake air amount of an engine, the cooling water temperature, the engine speed, acceleration and deceleration, and other conditions into electric signals using various sensors and sends the electric signals to a controller. The controller compares the information with the stored information, calculates the information accurately and outputs a control signal. The control parameters of the electronic stability control system of the automobile body are configured, so that automatic safety control of the automobile can be realized, and the driving stability and safety of the automobile under dynamic working conditions such as braking, driving and steering can be effectively improved; the control parameters of the automatic gearbox control unit are configured, so that the automobile can adapt to different working conditions in the driving process, and the automobile gear shifting mechanism is controlled to perform gear shifting and gear shifting operations; and the control parameters of the engine management system are configured, so that the fuel supply amount is accurately controlled, and the oil consumption of the automobile is reduced. By configuring the control parameters of the modules, the vehicle can run safely and stably when the vehicle-mounted host executes the driving instruction memorized by the user, so that the driving instruction can be memorized smoothly.
In the embodiment, according to the target map data and the historical driving route, and when the user is a common office worker, the residence of the user is 4km away from the company, on the way that the user drives the automobile to the company, the user can pass through the three traffic light intersections, the service time of the user passing through the three traffic light intersections is 8 minutes, and meanwhile, the user can slow down and walk to determine the driving control parameters when passing through the three traffic light intersections. Therefore, the driving control parameters of the intelligent driving controller are determined according to the driving data information and the target map data, if the user decelerates and crawls when passing through a traffic light intersection, the control parameters of the automatic gearbox control unit need to be determined to control the automobile gear shifting mechanism to perform gear backing operation, namely, the automobile decelerates and crawls. Therefore, the driving control parameters are the driving reference data and the target map data of the daily driving of the user, and when the user starts the driving memory function, the driving state of the automobile is not greatly different from the driving state of the user when the user drives the automobile, so that the automobile can be ensured to run stably and safely, and the user experience is improved.
Further, as an embodiment, referring to fig. 6, the present application provides a fifth embodiment of an intelligent driving method for an automobile. Referring to fig. 6, fig. 6 is a flowchart illustrating a fifth embodiment of the intelligent driving method for a vehicle.
In this embodiment, the step S20 includes:
step S201A, determining at least one high-frequency driving route corresponding to the user according to the driving frequency of each historical driving route;
step S202A, constructing target map data corresponding to the high-frequency driving route according to the historical road image information.
In the embodiment of the present application, the high-frequency travel route may be a route in which, of the user daily travel routes, the travel frequency is higher among all the historical travel routes. For example, according to the historical travel route of the user in 7 months, the number of times of the commuting route on duty is 22, the number of times of the dining-out route on duty is 18, and the number of times of the playing route on trip is 5, so that the high-frequency travel route of the user in 7 months can be the commuting route on duty or the dining-out route, and a commuting map or a dining-out map can be constructed for the user according to commuting historical road image information or dining-out historical road image information collected by the vehicle-mounted camera.
In this embodiment, at least one high-frequency driving route corresponding to the user is determined according to the driving frequency of each historical driving route, target map data corresponding to the high-frequency driving route is constructed according to the historical road image corresponding to the high-frequency driving route, and an exclusive target map can be constructed for the user according to the requirements of different users. If the user is a common office worker, the constructed target map is a commuting map; and when the user is a student, the constructed target map is a map for learning. Therefore, according to the method and the device, the map data corresponding to the high-frequency driving route is constructed according to the historical road image information, and the map data can be adjusted according to different requirements of different users, so that the exclusive intelligent driving map is provided for the different users.
Based on the same application concept, the intelligent automobile driving device is provided, and referring to fig. 6, fig. 6 is a schematic module diagram of a first embodiment of the intelligent automobile driving device.
The acquisition module 10 is used for acquiring historical road image information and historical driving routes of the automobile;
the construction module 20 is configured to construct target map data corresponding to the historical driving route according to the historical road image information;
and the determining module 30 is configured to determine a driving control parameter of the intelligent driving controller according to the target map data if a historical driving route memory driving instruction input by a user is received, so that the automobile drives along the historical driving route.
It should be noted that, in the present embodiment, for each implementation of the intelligent driving apparatus for an automobile and the technical effects achieved by the implementation of the intelligent driving method for an automobile in the foregoing embodiment, detailed description is omitted here.
According to the technical scheme of the embodiment, the historical road image information and the historical driving route of the automobile are acquired through mutual matching of the functional modules; according to the historical road image information, target map data corresponding to the historical driving route are constructed; and if a historical driving route memory driving instruction input by a user is received, determining driving control parameters of the intelligent driving controller according to the target map data so as to enable the automobile to drive along the historical driving route. Therefore, the target map of the historical driving route is constructed according to the historical road image information and the historical driving route of the automobile, when the automobile drives to a special scene, if a user inputs the historical driving route to memorize a driving instruction, the vehicle-mounted host can control the automobile to automatically drive according to the target map data, and lane-level positioning is achieved through the target map data, so that the automobile can achieve point-to-point intelligent cruising, and the point-to-point intelligent cruising of the automobile is not limited by the coverage rate of a high-precision map.
In addition, an embodiment of the present application further provides a computer storage medium, where an intelligent automobile driving program is stored on the storage medium, and when the intelligent automobile driving program is executed by a processor, the steps of the intelligent automobile driving method as above are implemented. Therefore, a detailed description thereof will be omitted. In addition, the beneficial effects of the same method are not described in detail. For technical details not disclosed in embodiments of the computer-readable storage medium referred to in the present application, reference is made to the description of embodiments of the method of the present application. It is determined that the program instructions may be deployed to be executed on one computing device or on multiple computing devices located at one site or distributed across multiple sites and interconnected by a communication network, as examples.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
It should be noted that the above-described embodiments of the apparatus are merely illustrative, and 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 multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. In addition, in the drawings of the embodiments of the apparatus provided in the present application, the connection relationship between the modules indicates that there is a communication connection therebetween, and may be implemented as one or more communication buses or signal lines. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that the present application can be implemented by software plus necessary general-purpose hardware, and certainly can also be implemented by special-purpose hardware including special-purpose integrated circuits, special-purpose CPUs, special-purpose memories, special-purpose components and the like. Generally, functions performed by computer programs can be easily implemented by corresponding hardware, and specific hardware structures for implementing the same functions may be various, such as analog circuits, digital circuits, or dedicated circuits. However, for the present application, the implementation of a software program is more preferable. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, where the computer software product is stored in a readable storage medium, such as a floppy disk, a usb disk, a removable hard disk, a Read-only memory (ROM), a random-access memory (RAM), a magnetic disk or an optical disk of a computer, and includes instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods of the embodiments of the present application.
The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application, or which are directly or indirectly applied to other related technical fields, are included in the scope of the present application.

Claims (10)

1. An intelligent driving method for an automobile, wherein the automobile is provided with an intelligent driving controller, and the method comprises the following steps:
acquiring historical road image information and historical driving routes of an automobile;
constructing target map data corresponding to the historical driving route according to the historical road image information;
and if a historical driving route memory driving instruction input by a user is received, determining driving control parameters of the intelligent driving controller according to the target map data so as to enable the automobile to drive along the historical driving route.
2. The intelligent driving method for the automobile according to claim 1, wherein the automobile is provided with an on-board camera, an on-board global positioning system and/or an inertial measurement unit;
the acquiring of the historical reason image information and the historical driving route of the automobile comprises the following steps:
acquiring historical road image information according to a driving picture acquired by a vehicle-mounted camera;
and obtaining the historical driving route by utilizing a vehicle-mounted global positioning system and/or an inertia measuring unit.
3. The intelligent driving method for the automobile according to claim 1, wherein the constructing of the target map data corresponding to the historical driving route according to the historical road image information comprises:
uploading the historical road image information and the historical driving route to a cloud server so that the cloud server can construct target map data corresponding to the historical driving route according to the historical road image information;
and receiving the target map data returned by the cloud server.
4. The intelligent driving method for the automobile according to claim 3, wherein the uploading the historical road image information and the historical driving route to a cloud server so that the cloud server constructs target map data corresponding to the historical driving route according to the historical road image information comprises:
encrypting the historical road image information to obtain encrypted historical road image information;
uploading the encrypted historical road image information to a cloud server, so that the cloud server constructs target map data corresponding to the historical driving route according to the encrypted historical road image information.
5. The intelligent driving method for automobile according to claim 1, wherein the determining the driving control parameters of the intelligent driving controller according to the target map data comprises:
obtaining at least one of driving distance data, automobile pose data or signal lamp data according to the historical driving route;
obtaining driving reference data according to at least one of the driving distance data, the automobile pose data or the signal lamp data;
and determining driving control parameters of the intelligent driving controller according to the driving reference data and the target map data.
6. The intelligent driving method for the automobile according to claim 1, wherein the constructing of the target map data corresponding to the historical driving route according to the historical road image information comprises:
determining at least one high-frequency driving route corresponding to the user according to the driving frequency of each historical driving route;
and constructing target map data corresponding to the high-frequency driving route according to the historical road image information.
7. The intelligent driving method for the automobile according to any one of claims 1-6, wherein the driving control parameters comprise control parameters of at least one of an electronic stability control system of the automobile body, an automatic transmission control unit and an engine management system.
8. An intelligent driving device for an automobile, which is characterized by comprising:
the acquisition module is used for acquiring historical road image information and historical driving routes of the automobile;
the construction module is used for constructing target map data corresponding to the historical driving route according to the historical road image information;
and the determining module is used for determining the driving control parameters of the intelligent driving controller according to the target map data if a historical driving route memory driving instruction input by a user is received, so that the automobile can drive along the historical driving route.
9. An automobile intelligent driving device, characterized by comprising: a processor, a memory and a vehicle intelligent driving program stored in the memory, wherein the vehicle intelligent driving program when executed by the processor realizes the steps of the vehicle intelligent driving method according to any one of claims 1 to 7.
10. A computer-readable storage medium, wherein a vehicle intelligent driving program is stored on the computer-readable storage medium, and when executed by a processor, the vehicle intelligent driving program implements the vehicle intelligent driving method according to any one of claims 1 to 7.
CN202211184582.4A 2022-09-27 2022-09-27 Intelligent automobile driving method, device, equipment and storage medium Pending CN115476855A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202211184582.4A CN115476855A (en) 2022-09-27 2022-09-27 Intelligent automobile driving method, device, equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202211184582.4A CN115476855A (en) 2022-09-27 2022-09-27 Intelligent automobile driving method, device, equipment and storage medium

Publications (1)

Publication Number Publication Date
CN115476855A true CN115476855A (en) 2022-12-16

Family

ID=84393220

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202211184582.4A Pending CN115476855A (en) 2022-09-27 2022-09-27 Intelligent automobile driving method, device, equipment and storage medium

Country Status (1)

Country Link
CN (1) CN115476855A (en)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108820042A (en) * 2018-05-25 2018-11-16 东软集团股份有限公司 A kind of automatic Pilot method and device
KR20210089603A (en) * 2020-06-29 2021-07-16 베이징 바이두 넷컴 사이언스 앤 테크놀로지 코., 엘티디. Vehicle cruise control method, device, electronic equipment and storage medium
CN114132343A (en) * 2021-11-30 2022-03-04 上汽通用五菱汽车股份有限公司 Vehicle tracking method, device, system and computer readable storage medium
CN114670865A (en) * 2020-12-24 2022-06-28 莱德弗利士株式会社 Method, device and computer program for generating driving route of automatic driving vehicle

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108820042A (en) * 2018-05-25 2018-11-16 东软集团股份有限公司 A kind of automatic Pilot method and device
US20190360831A1 (en) * 2018-05-25 2019-11-28 Neusoft Corporation Automatic driving method and device
KR20210089603A (en) * 2020-06-29 2021-07-16 베이징 바이두 넷컴 사이언스 앤 테크놀로지 코., 엘티디. Vehicle cruise control method, device, electronic equipment and storage medium
CN114670865A (en) * 2020-12-24 2022-06-28 莱德弗利士株式会社 Method, device and computer program for generating driving route of automatic driving vehicle
CN114132343A (en) * 2021-11-30 2022-03-04 上汽通用五菱汽车股份有限公司 Vehicle tracking method, device, system and computer readable storage medium

Similar Documents

Publication Publication Date Title
EP4141736A1 (en) Lane tracking method and apparatus
US11260852B2 (en) Collision behavior recognition and avoidance
CN112729316B (en) Positioning method and device of automatic driving vehicle, vehicle-mounted equipment, system and vehicle
CN108162974B (en) Vehicle control using road angle data
JP7526795B2 (en) Autonomous driving device, vehicle control method
CN109952491B (en) Method and system for generating a representation of an object detected by a perception system of a vehicle
CN115427251A (en) Predictive regenerative braking
CN112654959B (en) Picture display method, intelligent vehicle, storage medium and device
CN110789533A (en) Data presentation method and terminal equipment
US11774259B2 (en) Mapping off-road entries for autonomous vehicles
CN211956223U (en) Lane change track planning system
CN111413990A (en) Lane change track planning system
CN109774720A (en) High-precision map visualization method, device and storage medium
US11685408B1 (en) Driving difficulty heat maps for autonomous vehicles
DE102020103633A1 (en) ROUTE PLANNING FUSION FOR A VEHICLE
JP2020095506A (en) Platooning management system
CN113252022A (en) Map data processing method and device
US12085935B2 (en) Open door reconstruction for sensor simulation
CN115330923A (en) Point cloud data rendering method and device, vehicle, readable storage medium and chip
WO2022080214A1 (en) Vehicle control method, map server, device for vehicle, and map data structure
CN115205365A (en) Vehicle distance detection method and device, vehicle, readable storage medium and chip
CN115476855A (en) Intelligent automobile driving method, device, equipment and storage medium
US20230160709A1 (en) Providing information to navigate to a parking space preferred by an operator of a vehicle
CN117073666A (en) Method and apparatus for vehicle positioning with infrastructure cameras
CN115930955A (en) Navigation data transmission method, device, storage medium and vehicle

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination