CN110806748A - Automatic driving system based on artificial intelligence - Google Patents
Automatic driving system based on artificial intelligence Download PDFInfo
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- CN110806748A CN110806748A CN201911024399.6A CN201911024399A CN110806748A CN 110806748 A CN110806748 A CN 110806748A CN 201911024399 A CN201911024399 A CN 201911024399A CN 110806748 A CN110806748 A CN 110806748A
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- vehicle
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
- G05D1/0278—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using satellite positioning signals, e.g. GPS
Abstract
The invention relates to the technical field of artificial intelligence driving systems, and discloses an automatic driving system based on artificial intelligence. The invention can realize the accurate control of the running condition and the stability performance of the vehicle under the complex road condition by arranging the safety module, the radar device and the image data processing module, can modify the route in time according to the implemented road condition, reduce the travel time, ensure the safety and the high reliability of the artificial intelligent automatic driving system, ensure the general application and the daily life of the automatic driving system, and solve the problems that the existing automatic driving system mostly uses various external identification sensors such as a vehicle-mounted camera, a radar and the like to identify objects, road marks and identifications around the vehicle, and the automatic driving system lacks strong intelligent effect and cannot accurately judge the condition to control the vehicle under the complex environment.
Description
Technical Field
The invention relates to the technical field of artificial intelligence driving systems, in particular to an automatic driving system based on artificial intelligence.
Background
An automatic driving automobile is also called an unmanned automobile, a computer driving automobile or a wheeled mobile robot, and is an intelligent automobile which realizes unmanned driving through a computer system. The automatic driving automobile depends on the cooperation of artificial intelligence, visual calculation, radar, monitoring device and global positioning system, so that the computer can operate the motor vehicle automatically and safely without any active operation of human.
However, most of the existing automatic driving systems recognize objects (vehicles, pedestrians, structures, etc.), road signs and signs (markings such as road surface painting such as a division line, parking marks, etc.) around the own vehicle by using various external recognition sensors such as a vehicle-mounted camera and a radar, etc., and such automatic driving systems lack a strong intelligent effect, cannot control the vehicle by accurately judging the conditions even in a complicated environment, and cannot be generally applied to daily life.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides an automatic driving system based on artificial intelligence, which solves the problems that the existing automatic driving system mostly uses various external identification sensors such as vehicle-mounted cameras and radars to identify objects (vehicles, pedestrians, structures and the like), road signs and marks (road surface painting such as zone lines, parking marks and the like) around the vehicle, the automatic driving system lacks strong intelligent effect, the condition cannot be accurately judged to control the vehicle under complex environment, and the automatic driving system cannot be generally applied to daily life.
(II) technical scheme
In order to achieve the purpose, the invention provides the following technical scheme: an automatic driving system based on artificial intelligence comprises a control unit, an image data processing module, a GPS module, a power supply module, a safety module and a radar device.
Preferably, the safety module includes collecting and analyzing driving data, vehicle condition data, line environment data, driving plans, and dynamic data related to weather and disaster conditions.
Preferably, the control unit comprises a master control unit and a slave control unit, and the control unit is connected with the image data processing module.
Preferably, the image data processing module comprises a front-end camera device, a front-end laser radar device and a data processing module.
Preferably, the GPS module is an integrated circuit that integrates an RF chip, a baseband chip, and a core CPU, and adds related peripheral circuits.
An automated driving system based on artificial intelligence, comprising the steps of:
s1: the method comprises the steps of firstly starting a power module to start the whole vehicle, then inputting the detailed position information of a destination, acquiring the coordinates of the destination by a GPS module, and analyzing the accurate distance between the current position and the destination and the predicted running time.
S2: and acquiring a plurality of navigation routes by the radar device, planning the most appropriate route according to the driving time period, the road condition and the number of the traffic lights, and preferentially selecting the screened route.
S3: the control unit starts to start, controls the whole vehicle to enter a driving stage, starts to work by the image data processing module in the driving process, and collects images and videos in the driving process.
And S4, in the driving process of the vehicle, the safety module controls the driving speed and the stability of the whole vehicle, analyzes various data of the whole vehicle, transmits warning commands in time, controls the real-time monitoring and data analysis of the vehicle traveling route, and avoids the condition of deviation of the vehicle or error in road selection in the driving process of the vehicle.
S4: and analyzing the reverse direction of the forward route before the vehicle drives to the traffic signal lamp, and transmitting a lane change instruction to enable the whole vehicle to carry out lane change driving.
S5: whether a running instruction of a running vehicle executed at a traffic signal lamp needs to wait for a red light or not is judged during running, the safety distance between the running vehicle and a preceding vehicle is analyzed, braking is carried out in time, and the safety of passengers in the vehicle is guaranteed.
S6: the running process collects the surrounding road condition information by 360 degrees, pedestrians and non-motor vehicles are avoided in advance, the rear vehicle is warned, and the collision of the rear vehicle is avoided.
S7: the radar device timely acquires and analyzes the latest road condition, avoids the blocking condition of the road, maximally reduces the driving time, and ensures timely and rapid reaching of the destination.
S8: after the whole vehicle runs to the destination, the GPS module quickly acquires the specific position information of the parking lot closest to the destination, the radar device quickly positions and plans a travel route, and finally the control unit controls the whole vehicle to run to the inside of the parking lot and executes a parking command.
(III) advantageous effects
The invention provides an automatic driving system based on artificial intelligence, which has the following beneficial effects:
the invention can realize the accurate control of the running condition and the stable performance of the vehicle under the complex road condition by arranging the safety module, the radar device and the image data processing module, and can modify the route in time according to the implementation road condition, reduce the travel time, ensure the safety and high reliability of the artificial intelligent automatic driving system, so that the automatic driving system can be widely applied and used in daily life, solve the problems that the existing automatic driving system mostly uses various external identification sensors such as vehicle-mounted cameras, radars and the like to identify objects (vehicles, pedestrians, structures and the like), road signs and marks (road surface painting such as zone lines, parking marks and the like), the automatic driving system lacks strong intelligent effect, and can not accurately judge the condition to control the vehicle under a complex environment, so that the automatic driving system can not be universally applied to the problems of daily life.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example (b):
the invention provides a technical scheme that: an automatic driving system based on artificial intelligence comprises a control unit, an image data processing module, a GPS module, a power supply module, a safety module and a radar device, wherein the automatic driving function of a self vehicle is realized by executing the control unit, the safety module is used for controlling a target track and a target speed program of the self vehicle, outputting a target control value for input, such as a set of the target track and the target speed or a target control quantity of each actuator, from external information, such as environment information, road information and the like around the self vehicle and vehicle information, such as vehicle speed, rudder angle, yaw rate and the like, and planning a driving track of a whole vehicle and a command of the speed of the whole vehicle according to traffic rules and road requirements, the image data processing module is used for memorizing image information related to the peripheral environment and shooting and recording surrounding static objects and moving objects, and collecting images of the vehicle running track near the whole vehicle, recording the shapes and positions of objects such as road surface painting and marks of lane dividing lines and the like, transmitting the recorded shapes and positions to the control unit, controlling the running condition of the whole vehicle by the control unit, and safely running according to the traffic road rule.
Specifically, the safety module includes collecting and analyzing driving data, vehicle condition data, line environment data, driving plans, and dynamic data related to weather and disaster conditions.
Specifically, the control unit comprises a master control unit and a slave control unit, and the control unit is connected with the image data processing module.
Specifically, the image data processing module comprises a front-end camera device, a front-end laser radar device and a data processing module.
Specifically, the GPS module is an integrated circuit formed by integrating an RF chip, a baseband chip, and a core CPU, and by adding related peripheral circuits.
An automated driving system based on artificial intelligence, comprising the steps of:
s1: the method comprises the steps of firstly starting a power module to start the whole vehicle, then inputting the detailed position information of a destination, acquiring the coordinates of the destination by a GPS module, and analyzing the accurate distance between the current position and the destination and the predicted running time.
S2: and acquiring a plurality of navigation routes by the radar device, planning the most appropriate route according to the driving time period, the road condition and the number of the traffic lights, and preferentially selecting the screened route.
S3: the control unit starts to start and controls the whole vehicle to enter a driving stage, the image data processing module starts to work in the driving process and collects images and videos in the driving process,
and S4, in the driving process of the vehicle, the safety module controls the driving speed and the stability of the whole vehicle, analyzes various data of the whole vehicle, transmits warning commands in time, controls the real-time monitoring and data analysis of the vehicle traveling route, and avoids the condition of deviation of the vehicle or error in road selection in the driving process of the vehicle.
S4: and analyzing the reverse direction of the forward route before the vehicle drives to the traffic signal lamp, and transmitting a lane change instruction to enable the whole vehicle to carry out lane change driving.
S5: whether a running instruction of a running vehicle executed at a traffic signal lamp needs to wait for a red light or not is judged during running, the safety distance between the running vehicle and a preceding vehicle is analyzed, braking is carried out in time, and the safety of passengers in the vehicle is guaranteed.
S6: the running process collects the surrounding road condition information by 360 degrees, pedestrians and non-motor vehicles are avoided in advance, the rear vehicle is warned, and the collision of the rear vehicle is avoided.
S7: the radar device timely acquires and analyzes the latest road condition, avoids the blocking condition of the road, maximally reduces the driving time, and ensures timely and rapid reaching of the destination.
S8: after the whole vehicle runs to the destination, the GPS module quickly acquires the specific position information of the parking lot closest to the destination, the radar device quickly positions and plans a travel route, and finally the control unit controls the whole vehicle to run to the inside of the parking lot and executes a parking command.
When the system is used, the power supply module is started firstly, the whole vehicle starts to start, the detailed position information of a destination is input, the GPS module acquires the coordinates of the destination, the accurate distance between the current position and the destination and the predicted driving time are analyzed, the radar device acquires a plurality of navigation routes, the most appropriate route is planned according to the driving time interval, the road condition and the number of traffic lights, the selected route is preferentially selected, the control unit starts to start and controls the whole vehicle to enter the driving stage, the image data processing module starts to work in the driving process and collects images and videos in the driving process, the safety module controls the driving speed and the stability of the whole vehicle in the driving process of the vehicle, simultaneously analyzes various data of the whole vehicle, timely transmits a warning command and controls the real-time monitoring and data analysis of the driving route of the vehicle, the condition that the vehicle deviates from a route or the road selection is wrong in the driving process is avoided, the reverse direction of a forward route is analyzed before the vehicle is driven to a traffic signal lamp, a lane change instruction is transmitted, the whole vehicle is driven in a lane change way, whether the driving instruction executed by the driving vehicle at the traffic signal lamp needs to wait for a red light is judged in the driving process, the safe distance between the driving instruction and the front vehicle is analyzed, the braking is carried out in time, the safety of passengers in the vehicle is guaranteed, 360-degree acquisition is carried out on surrounding road condition information in the driving process, pedestrians and non-motor vehicles are avoided in advance, meanwhile, the rear vehicle is warned, the condition that the rear vehicle collides is avoided, a device can acquire and analyze the newest road condition in time, the road blocking condition of the road is avoided, the driving time is maximally reduced, the vehicle can reach the destination in time and quickly, and after the whole vehicle is driven to the destination, and finally, the control unit controls the whole vehicle to run into the parking lot and executes a parking command.
In conclusion, the invention can realize the accurate control of the running condition and the stability performance of the vehicle under the complex road condition by arranging the safety module, the radar device and the image data processing module, and can modify the route in time according to the implementation road condition, reduce the travel time, ensure the safety and high reliability of the artificial intelligent automatic driving system, so that the automatic driving system can be widely applied and used in daily life, solve the problems that the existing automatic driving system mostly uses various external identification sensors such as vehicle-mounted cameras, radars and the like to identify objects (vehicles, pedestrians, structures and the like), road signs and marks (road surface painting such as zone lines, parking marks and the like), the automatic driving system lacks strong intelligent effect, and can not accurately judge the condition to control the vehicle under a complex environment, so that the automatic driving system can not be universally applied to the problems of daily life.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Claims (6)
1. An automatic driving system based on artificial intelligence, its characterized in that: the system comprises a control unit, an image data processing module, a GPS module, a power supply module, a safety module and a radar device.
2. The automated driving system based on artificial intelligence of claim 1, wherein: the safety module includes the collection and analysis of driving data, vehicle condition data, line environment data, driving plans, and dynamic data related to weather and disaster conditions.
3. The automated driving system based on artificial intelligence of claim 1, wherein: the control unit comprises a main control unit and a slave control unit, and is connected with the image data processing module.
4. The automated driving system based on artificial intelligence of claim 1, wherein: the image data processing module comprises a front-end camera device, a front-end laser radar device and a data processing module.
5. The automated driving system based on artificial intelligence of claim 1, wherein: the GPS module is an integrated circuit which is formed by integrating an RF chip, a baseband chip and a core CPU and adding related peripheral circuits.
6. The automated artificial intelligence based driving system of claim 1, comprising the steps of:
s1: firstly, starting a power module to start the whole vehicle, inputting the detailed position information of a destination, acquiring the coordinates of the destination by a GPS module, and analyzing the accurate distance between the current position and the destination and the predicted running time;
s2: acquiring a plurality of navigation routes by a radar device, planning the most appropriate route according to the driving time period, the road condition and the number of traffic lights, and preferentially selecting the screened route;
s3: the control unit starts to start, controls the whole vehicle to enter a driving stage, starts to work by the image data processing module in the driving process, and collects images and videos in the driving process;
s4, in the driving process of the vehicle, the safety module controls the driving speed and the stability of the whole vehicle, analyzes various data of the whole vehicle, transmits warning commands in time, controls the real-time monitoring and data analysis of the vehicle traveling route, and avoids the condition of deviation of the vehicle or error in road selection in the driving process of the vehicle;
s4: analyzing the reverse direction of the advancing route before the vehicle drives to the traffic signal lamp, and transmitting a lane changing instruction to enable the whole vehicle to carry out lane changing driving;
s5: judging whether a running instruction executed by a running vehicle at a traffic signal lamp needs to wait for a red light or not during running, analyzing the safety distance from the running vehicle to a preceding vehicle, and braking in time to ensure the safety of passengers in the vehicle;
s6: the method comprises the following steps of acquiring surrounding road condition information at 360 degrees in the driving process, avoiding pedestrians and non-motor vehicles in advance, warning a rear vehicle and avoiding the collision of the rear vehicle;
s7: the radar device timely acquires and analyzes the latest road condition, avoids the blocking condition of the road, maximally reduces the driving time, and ensures that the destination is timely and quickly reached;
s8: after the whole vehicle runs to the destination, the GPS module quickly acquires the specific position information of the parking lot closest to the destination, the radar device quickly positions and plans a travel route, and finally the control unit controls the whole vehicle to run to the inside of the parking lot and executes a parking command.
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| CN201911024399.6A CN110806748A (en) | 2019-10-25 | 2019-10-25 | Automatic driving system based on artificial intelligence |
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| CN201911024399.6A CN110806748A (en) | 2019-10-25 | 2019-10-25 | Automatic driving system based on artificial intelligence |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112382054A (en) * | 2020-11-11 | 2021-02-19 | 大连理工大学 | Automobile driving early warning prompting system and method based on vehicle-road cooperation |
| CN112706835A (en) * | 2021-01-07 | 2021-04-27 | 济南北方交通工程咨询监理有限公司 | Expressway unmanned marking method based on image navigation |
| CN113050654A (en) * | 2021-03-29 | 2021-06-29 | 中车青岛四方车辆研究所有限公司 | Obstacle detection method, vehicle-mounted obstacle avoidance system and method for inspection robot |
| CN113778085A (en) * | 2021-08-30 | 2021-12-10 | 武汉海昌信息技术有限公司 | Unmanned vehicle control method and system based on artificial intelligence and readable storage medium |
| CN114666382A (en) * | 2022-03-17 | 2022-06-24 | 北京斯年智驾科技有限公司 | Parallel driving system for automatic driving semi-mounted collecting card |
-
2019
- 2019-10-25 CN CN201911024399.6A patent/CN110806748A/en active Pending
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112382054A (en) * | 2020-11-11 | 2021-02-19 | 大连理工大学 | Automobile driving early warning prompting system and method based on vehicle-road cooperation |
| CN112382054B (en) * | 2020-11-11 | 2022-05-13 | 大连理工大学 | Automobile driving early warning prompting system and method based on vehicle-road cooperation |
| CN112706835A (en) * | 2021-01-07 | 2021-04-27 | 济南北方交通工程咨询监理有限公司 | Expressway unmanned marking method based on image navigation |
| CN112706835B (en) * | 2021-01-07 | 2022-04-19 | 济南北方交通工程咨询监理有限公司 | Expressway unmanned marking method based on image navigation |
| CN113050654A (en) * | 2021-03-29 | 2021-06-29 | 中车青岛四方车辆研究所有限公司 | Obstacle detection method, vehicle-mounted obstacle avoidance system and method for inspection robot |
| CN113778085A (en) * | 2021-08-30 | 2021-12-10 | 武汉海昌信息技术有限公司 | Unmanned vehicle control method and system based on artificial intelligence and readable storage medium |
| CN114666382A (en) * | 2022-03-17 | 2022-06-24 | 北京斯年智驾科技有限公司 | Parallel driving system for automatic driving semi-mounted collecting card |
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