CN111880174A - Roadside service system for supporting automatic driving control decision and control method thereof - Google Patents
Roadside service system for supporting automatic driving control decision and control method thereof Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
- G01S13/865—Combination of radar systems with lidar systems
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
- G01S13/867—Combination of radar systems with cameras
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
- G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
- G01S17/931—Lidar systems specially adapted for specific applications for anti-collision purposes of land vehicles
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
- G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
- G01S2013/9316—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles combined with communication equipment with other vehicles or with base stations
Abstract
The invention discloses a roadside service system for supporting automatic driving control decision, which comprises an automobile end, a roadside system and a cloud platform server, wherein the roadside system is a device arranged beside a road, the roadside system internally comprises a sensor assembly, a roadside data processing unit for receiving signals of the sensor assembly, and a roadside communication unit which is connected with the roadside data processing unit and sends the signals outwards, the roadside communication unit sends the signals to the automobile end and the cloud platform server, and the cloud platform server is communicated with the automobile end. The invention can improve the environmental information perception capability of the unmanned automobile, and simultaneously can provide information and management support for intelligent traffic, and the road side service system in key road sections and special traffic environments is beneficial to improving traffic safety. Through comprehensive management and scheduling of the background, the traffic efficiency of the universe can be improved.
Description
Technical Field
The invention relates to the technical field of intelligent networked automobiles.
Background
The road side service system mainly comprises a road side laser radar, a camera, a millimeter wave radar, a road side communication system, a road side data processing unit, a mobile communication terminal and a cloud platform server.
With the continuous development of technologies such as big data, 5G communication and machine learning, vehicle-road cooperation, automatic driving, intelligent traveling and the like based on artificial intelligence have become the key of the development of intelligent traffic systems. At present, the unmanned technology has been applied in specific scenes, but the ability of the automatic driving automobile to cope with sudden situations is still insufficient on open roads, especially at complex traffic intersections in cities. The single-vehicle perception has to be provided with a plurality of laser radars in order to deal with complex road conditions, and the cost of automatic driving is improved invisibly. Thus, vehicle-to-road coordination is clearly an important condition for large-scale, commercial landing of autonomous vehicles, both from a safety and cost perspective.
Roadside perception system based on laser radar erects multi-thread laser radar at key crossing, the relatively poor special road of sight, can cooperate multiple sensors such as camera, millimeter wave radar simultaneously, including the passerby, the object is whole to be brought into perception scope with road surface information, the roadside can send perception processing result for the vehicle through V2X, also can be through mobile network or basic edge network with data transmission to backend server, backend server sends corresponding instruction information to the vehicle according to the calculated result.
The laser radar can quickly acquire distance information in a scanning plane and acquire the outer contour of the obstacle in the scanning plane, and meanwhile, the laser radar is not influenced by illumination conditions, but the characteristics of the obstacle such as the shape and texture information cannot be acquired; machine vision can provide richer planar information, but is susceptible to lighting conditions. The two environment perception sensors can realize functional complementation, and through establishing a coordinate conversion model among the laser radar, the camera and the vehicle body, the laser radar data and the image pixel data are unified into the same coordinate system for identification processing.
Selecting a proper clustering method by combining the data characteristics of the laser radar, and performing shape matching and template matching on the clustered laser radar data to determine an area of interest; vehicle detection is carried out on the region of interest through Haar-like features and an AdaBoost algorithm, and then Kalman prediction tracking is achieved through data features of the vehicle in the laser radar. After the clustering segmentation is realized on the barrier data points by using the laser radar, different barrier types become candidate areas. And generating a classifier consisting of a plurality of different weak classification features through statistical learning of the image samples, completing inspection of the candidate region by using the classifier, and finally performing feature fusion with the obstacle feature parameters extracted after laser radar clustering segmentation to output target attribute parameters.
In the aspect of road edge calculation, a new road side system in the future comprehensively constructs multiple technologies and capabilities such as a plurality of built-in communication modes such as LTE-V/5G, the provision of multiple sensor interfaces and a local map system, the provision of signal timing information and peripheral moving object information, the provision of vehicle cooperative decision and the like into a road side edge calculation node. The coordination driving between vehicles and workshops and between vehicles and roads can reduce the probability of accidents by means of accident early warning and avoidance. The automobile needs to interact data obtained locally through radars, cameras and the like with surrounding vehicles and road infrastructure through edge gateways, and the perception range is improved, so that cooperation between vehicles and between vehicle roads is achieved.
The vehicle-road cooperative cloud can sense the density, speed and the like of vehicles through interaction with the vehicle edge computing nodes and the road edge computing nodes, so that the vehicles on the road are guided to avoid congested road sections, and efficient traffic scheduling is realized. At an intersection, the vehicle-mounted edge calculation may inform the road edge calculation node of the current road conditions in conjunction with the road traffic conditions. And the road edge computing node collects the information of nearby roads, and sends reasonable road traffic scheduling instructions Bluetooth and WiFi through a big data algorithm, wherein the Bluetooth and the WiFi are mainly used for short-range communication among intelligent devices in the vehicle.
Based on the roadside lidar technology, the perception information fusion technology, the edge computing technology, the cloud computing technology and the vehicle-road cooperation technology, at present, a system capable of supporting unmanned control decision-making does not exist, the perception capability of real-time traffic information cannot be improved for unmanned driving, and the vehicle is assisted to carry out global path planning.
In order to promote the development and construction of an intelligent traffic system, accelerate the large-scale and commercial landing application of the unmanned technology, guarantee traffic safety, improve traffic efficiency and form a safe, efficient and environment-friendly road traffic system, a roadside service system for supporting unmanned control decision is needed.
Disclosure of Invention
The invention aims to solve the technical problem of realizing a road side service system for supporting unmanned control decision. The system analyzes real-time traffic information through edge calculation and cloud calculation by fusing multiple perception modes of road sides, provides the real-time traffic information for the unmanned vehicle, solves the problem that the single vehicle perception capability of the unmanned vehicle is not enough, can promote the development of intelligent traffic, and forms an intelligent traffic solution meeting the future driving environment requirements.
In order to achieve the purpose, the invention adopts the technical scheme that: the utility model provides a roadside service system for supporting automatic driving control decision-making, includes car end, roadside system and cloud platform server, the roadside system is for installing the device beside the road, and inside includes the sensor subassembly, receives the roadside data processing unit of sensor subassembly signal, connects the roadside data processing unit signal of roadside and the roadside communication unit who outwards sends, roadside communication unit sends signal transmission to car end and cloud platform server, cloud platform server and car end communication.
Sensor assembly fixes in the road top, gathers the road conditions information on road surface, sensor assembly includes:
laser radar: a module for acquiring road environment information;
a camera: the module is used for acquiring data of traffic flow and assisting laser in object classification and point cloud clustering;
millimeter wave radar: a module for object identification and obstacle detection on a road surface.
The roadside systems are multiple and distributed beside a set road, collected information is uniformly sent to the same cloud platform server, and the cloud platform server collects the acquired information of all the roadside systems to form real-time road condition information of a monitored road section.
The vehicle end is communicated with a road side system near the current position, and the road side system establishing communication with the vehicle end sends acquired information to the vehicle end.
The control method based on the roadside service system for supporting the automatic driving control decision comprises the following steps:
the roadside system acquires data information acquired by the sensor assembly in real time;
the road side system analyzes the data information to obtain real-time road condition information of the position of the road side system;
the road side system sends the road condition information to a cloud platform server in real time;
the cloud platform server collects the road condition information of all the road side systems to form real-time road condition information;
and the cloud platform server sends the real-time road condition information to the automobile end which acquires the road condition information with the cloud platform server at present.
And after the automobile end acquires the real-time road condition information, if the automobile is in an automatic driving state, adjusting a driving path according to the real-time road condition information and a set path method.
When the automobile end runs into a region monitored by a road side system, the road side system establishes communication with the automobile end and sends the obstacle information of the road surface and the motion trail of the automobile end to the automobile end, and the automobile end carries out real-time control decision according to the acquired obstacle information and the motion trail of the automobile.
The invention can improve the environmental information perception capability of the unmanned automobile, and simultaneously can provide information and management support for intelligent traffic, and the road side service system in key road sections and special traffic environments is beneficial to improving traffic safety. Through comprehensive management and scheduling of the background, the traffic efficiency of the universe can be improved.
Drawings
The following is a brief description of the contents of each figure in the description of the present invention:
FIG. 1 is a schematic structural diagram of a roadside service system for supporting unmanned control decisions;
FIG. 2 is a schematic diagram of a roadside service system working flow for supporting unmanned control decision.
Detailed Description
The following description of the embodiments with reference to the drawings is provided to describe the embodiments of the present invention, and the embodiments of the present invention, such as the shapes and configurations of the components, the mutual positions and connection relationships of the components, the functions and working principles of the components, the manufacturing processes and the operation and use methods, etc., will be further described in detail to help those skilled in the art to more completely, accurately and deeply understand the inventive concept and technical solutions of the present invention.
The invention relates to a roadside service system for supporting unmanned control decision. The system is mainly used for assisting an unmanned vehicle to make a control decision by means of a perception mode of roadside multi-source data fusion and vehicle-road communication or data information uploaded to a cloud-end platform for calculation processing, solving the problems of single-vehicle sensing and insufficient calculation capacity, improving the safety of the vehicle, providing important technical support for unmanned application and providing cloud-vehicle-road cooperative integrated application for future travel.
As shown in fig. 1, the roadside service system for supporting an automatic driving control decision includes an automobile end, a roadside system and a cloud platform server, wherein one cloud platform server is generally provided and is in communication with the automobile end and the roadside system through a wireless network, the automobile end is installed on an automobile with corresponding functions, the roadside system is provided with a plurality of systems, the higher the density is, the more comprehensive and accurate the acquired information is, the higher the density is, the more comprehensive and accurate the information is, the more comprehensive the information is, the more accurate the information is, the more comprehensive the information can be configured as required, or the more comprehensive the information is.
The road side system comprises a sensor assembly, a road side data processing unit for receiving signals of the sensor assembly and a road side communication unit for connecting the signals of the road side data processing unit and sending the signals to the outside, the road side communication unit sends the signals to the automobile end and the cloud platform server, the sensor assembly collects traffic information in real time and sends the traffic information to the road side data processing unit, and the road side data processing unit performs fusion processing on radar and visual information to form data and parameters such as object classification, obstacle identification and motion tracks of objects;
the sensor assembly includes: the roadside lidar is a specific lidar applied to road environment, and the field angle, the water resistance, the dust resistance and other performances of the roadside lidar meet the requirements of outdoor long-term stable work. The camera is a module which is used for carrying out data acquisition on traffic flow and can assist laser to carry out object classification and point cloud clustering. Millimeter wave radar refers to equipment used on the road side for object recognition and obstacle detection.
The roadside communication system is a comprehensive communication system comprising vehicle-to-road direct communication and roadside-to-cloud server communication.
The roadside data processing unit is equipment for receiving data of the radar and the camera, processing and calculating the data, and performing data interaction on a processing result with the vehicle and the cloud server through roadside communication equipment.
The cloud platform server is used for receiving edge calculation information, carrying out centralized calculation, classification and storage, sending a processing result to the vehicle and roadside equipment, and communicating with the automobile end.
The road side systems are distributed beside a set road, collected information is uniformly sent to the same cloud platform server or cloud platform servers of the jurisdiction, and the cloud platform servers collect the acquired information of all the road side systems to form real-time road condition information of a monitored road section. The vehicle end communicates with a road side system near the current position, the road side system establishing communication with the vehicle end sends acquired information to the vehicle end, the vicinity can be judged through GPS positioning, and when the vehicle runs within a set distance of a certain road side system, a communication relation is automatically established.
The control method based on the roadside service system for supporting the automatic driving control decision comprises the following steps:
the roadside system acquires data information acquired by the sensor assembly in real time;
the road side system analyzes the data information to obtain real-time road condition information of the position of the road side system, and performs fusion processing on the radar and the visual information to form data and parameters such as object classification, obstacle identification and the movement track of the object;
the road side system sends the road condition information to a cloud platform server in real time;
the cloud platform server collects the road condition information of all the road side systems to form real-time road condition information;
and the cloud platform server sends the real-time road condition information to the automobile end which acquires the road condition information with the cloud platform server at present.
And after the automobile end acquires the real-time road condition information, if the automobile is in an automatic driving state, adjusting a driving path according to the real-time road condition information and a set path method.
When the automobile end runs into a region monitored by a road side system (a communication relation state is established), the road side system establishes communication with the automobile end and sends barrier information of a road surface and a motion trail of the automobile end to the automobile end (the motion trail of the automobile end can be judged by acquiring vehicle license plate information through a camera and can also be judged by utilizing a GPS (global positioning system) of the automobile end), the automobile end carries out real-time control decision according to the acquired barrier information and the motion trail of the automobile, and the automobile end can cooperate to control the automobile through third visual angle information.
The invention has been described above with reference to the accompanying drawings, it is obvious that the invention is not limited to the specific implementation in the above-described manner, and it is within the scope of the invention to apply the inventive concept and solution to other applications without substantial modification.
Claims (7)
1. A roadside service system for supporting automated driving control decisions, characterized by: the road side system comprises a sensor assembly, a road side data processing unit for receiving signals of the sensor assembly and a road side communication unit for connecting the road side data processing unit signals and sending the signals outwards, wherein the road side communication unit sends the signals to the automobile end and the cloud platform server, and the cloud platform server is communicated with the automobile end.
2. The roadside service system for supporting automated driving control decisions of claim 1, wherein the sensor assembly is fixed above a road and collects road condition information of the road surface, the sensor assembly comprising:
laser radar: a module for acquiring road environment information;
a camera: the module is used for acquiring data of traffic flow and assisting laser in object classification and point cloud clustering;
millimeter wave radar: a module for object identification and obstacle detection on a road surface.
3. The roadside service system for supporting automated driving control decisions of claim 1 or 2, wherein: the roadside systems are multiple and distributed beside a set road, collected information is uniformly sent to the same cloud platform server, and the cloud platform server collects the acquired information of all the roadside systems to form real-time road condition information of a monitored road section.
4. The roadside service system for supporting automated driving control decisions of claim 3, wherein: the vehicle end is communicated with a road side system near the current position, and the road side system establishing communication with the vehicle end sends acquired information to the vehicle end.
5. The control method of the roadside service system for supporting automatic driving control decision according to any one of claims 1 to 4, characterized by:
the roadside system acquires data information acquired by the sensor assembly in real time;
the road side system analyzes the data information to obtain real-time road condition information of the position of the road side system;
the road side system sends the road condition information to a cloud platform server in real time;
the cloud platform server collects the road condition information of all the road side systems to form real-time road condition information;
and the cloud platform server sends the real-time road condition information to the automobile end which acquires the road condition information with the cloud platform server at present.
6. The method of controlling a roadside service system according to claim 5, wherein: and after the automobile end acquires the real-time road condition information, if the automobile is in an automatic driving state, adjusting a driving path according to the real-time road condition information and a set path method.
7. The control method of the roadside service system according to claim 5 or 6, characterized in that: when the automobile end runs into a region monitored by a road side system, the road side system establishes communication with the automobile end and sends the obstacle information of the road surface and the motion trail of the automobile end to the automobile end, and the automobile end carries out real-time control decision according to the acquired obstacle information and the motion trail of the automobile.
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| CN117452407A (en) * | 2023-12-26 | 2024-01-26 | 哈尔滨工业大学(深圳)(哈尔滨工业大学深圳科技创新研究院) | Radar data service system and method for vehicle-mounted auxiliary driving system |
| CN117452407B (en) * | 2023-12-26 | 2024-03-08 | 哈尔滨工业大学(深圳)(哈尔滨工业大学深圳科技创新研究院) | Radar data service system and method for vehicle-mounted auxiliary driving system |
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