CN114655230A - Intelligent driving decision-making system based on roadside multi-sensors - Google Patents
Intelligent driving decision-making system based on roadside multi-sensors Download PDFInfo
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- CN114655230A CN114655230A CN202111593730.3A CN202111593730A CN114655230A CN 114655230 A CN114655230 A CN 114655230A CN 202111593730 A CN202111593730 A CN 202111593730A CN 114655230 A CN114655230 A CN 114655230A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
- B60W40/04—Traffic conditions
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
- B60W40/06—Road conditions
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W2050/0001—Details of the control system
- B60W2050/0043—Signal treatments, identification of variables or parameters, parameter estimation or state estimation
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2552/00—Input parameters relating to infrastructure
- B60W2552/53—Road markings, e.g. lane marker or crosswalk
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2554/00—Input parameters relating to objects
- B60W2554/20—Static objects
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2554/00—Input parameters relating to objects
- B60W2554/40—Dynamic objects, e.g. animals, windblown objects
- B60W2554/402—Type
- B60W2554/4029—Pedestrians
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2554/00—Input parameters relating to objects
- B60W2554/40—Dynamic objects, e.g. animals, windblown objects
- B60W2554/404—Characteristics
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2554/00—Input parameters relating to objects
- B60W2554/40—Dynamic objects, e.g. animals, windblown objects
- B60W2554/404—Characteristics
- B60W2554/4041—Position
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2554/00—Input parameters relating to objects
- B60W2554/40—Dynamic objects, e.g. animals, windblown objects
- B60W2554/404—Characteristics
- B60W2554/4042—Longitudinal speed
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- 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
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- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Transportation (AREA)
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- Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Human Computer Interaction (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses an intelligent driving decision system based on roadside multi-sensors, which collects static data and dynamic data of a traffic environment in real time through a roadside data sensing end, and enables the timeliness of the data to be stronger and the data to respond to the environmental change in time through increasing the collection frequency of the environmental data; fusing multi-source heterogeneous data through a roadside data processing end, and calculating to obtain a real-time static and dynamic representation map of the traffic environment; the roadside intelligent decision-making end obtains information such as path planning of the intelligent networked automobile in a road in real time through the communication module according to the traffic environment static and dynamic representation map output by the roadside data processing end, the drivable area calculation module calculates the drivable area of the intelligent networked automobile, the driving decision-making calculation module obtains a decision-making instruction of the intelligent networked automobile, the decision-making instruction is transmitted to the intelligent networked automobile through the communication module, roadside decision-making information is provided for the intelligent networked automobile, and the intelligent networked automobile combines the decision-making information with the roadside decision-making information, so that a more stable and reliable decision can be obtained, and the driving safety and reliability of the intelligent networked automobile are improved.
Description
Technical Field
The invention relates to the field of intelligent transportation, in particular to an intelligent driving decision-making system based on roadside multi-sensors.
Background
At present, the intelligent networked automobile is widely concerned by various national scholars as a leading-edge technology of the current intelligent networked traffic technology, and more stable and reliable decision information should be provided for the intelligent networked automobile in order to improve the safety and reliability of the intelligent networked automobile in the driving process. Because the perception of the intelligent networked automobile to the traffic environment has a blind area, a certain safety risk exists in the decision made based on the perception information of the intelligent networked automobile. With the development of the intelligent road side technology, the intelligent driving decision can be carried out on the vehicle at the road side end based on the information acquisition and processing technology of the road side sensor, and the intelligent networked automobile can obtain more stable and reliable driving decision information by combining the road side decision information and the decision information of the intelligent networked automobile, so that the driving safety and reliability are improved.
Therefore, if the roadside-based multi-source heterogeneous sensor real-time traffic environment data is used for making an intelligent driving decision at the roadside end, the problem needs to be solved by the technical personnel in the field.
Disclosure of Invention
In view of the above, the invention provides an intelligent driving decision system based on roadside multi-sensors, which can automatically acquire and process real-time traffic environment data, can calculate driving area and driving decision information through data fusion and environment representation, and can provide stable and reliable real-time decision information for intelligent networked automobiles.
In order to achieve the purpose, the invention adopts the following technical scheme:
an intelligent driving decision system based on roadside multi-sensors, the system comprising:
the road side data sensing end is provided with a plurality of sensors and a processing module, and each sensor can acquire and process traffic environment data respectively to obtain multi-source heterogeneous real-time traffic environment data.
And the road side data processing end receives the multi-source heterogeneous real-time traffic environment data output by the road side data sensing end, performs information fusion on the multi-source heterogeneous data, performs traffic environment characterization on the fused information, and obtains a traffic environment real-time characterization map.
And the road side intelligent decision end receives the traffic environment real-time representation map output by the road side data processing end, calculates the real-time drivable area of the vehicle, and then calculates the driving decision information of the intelligent networked automobile by combining the driving information of the intelligent networked automobile.
Further, the roadside data sensing terminal includes:
the camera is used for acquiring and outputting real-time video data of a traffic environment;
the image data processing module is used for processing the video data acquired by the camera, acquiring and outputting static and dynamic traffic data, wherein the static traffic environment data comprise lane line positions, shapes and numbers, lane identification information, traffic sign information, static obstacle volume, position and the like, and the dynamic traffic environment data comprise traffic participants (vehicles, pedestrians, non-motor vehicles and the like), category, position, volume, speed and the like;
the system comprises a laser radar, a data acquisition unit and a data processing unit, wherein the laser radar is used for acquiring and outputting real-time point cloud data of a road traffic environment;
the point cloud data processing module is used for processing real-time point transportation data output by the laser radar 102, acquiring and outputting static and dynamic traffic data, including static obstacle volume, position data, and data such as categories, positions, volumes, speeds and the like of traffic participants (vehicles, pedestrians, non-motor vehicles and the like);
the millimeter wave radar is used for collecting and outputting real-time radar data of the traffic environment;
the radar data processing module is used for processing the millimeter wave radar data, acquiring and outputting static and dynamic traffic data, including static obstacle position data and data of positions, speeds and the like of traffic participants (vehicles, pedestrians, non-motor vehicles and the like);
the camera, the image data processing module, the laser radar, the point cloud data processing module, the millimeter wave radar and the radar data module are arranged on a road side elevated platform and used for collecting and processing real-time traffic environment data, and the camera is connected with the image data processing module, the laser radar is connected with the point cloud data processing module, and the millimeter wave radar is connected with the radar data processing module.
Further, the roadside data processing end includes:
and the data fusion module is connected with the output roadside sensing end, respectively outputs static and dynamic environment data to the image data processing module, the point cloud data processing module and the radar data processing module for information fusion, and finely fuses static data and dynamic data according to the characteristics of the data of different data processing modules.
And the environment representation module represents the traffic environment according to the static traffic environment data and the dynamic traffic environment data output by the data fusion module to obtain a real-time representation map.
Further, the static data fusion mainly takes the static environment data output by the image data processing module as a reference, and fuses the static environment data output by the point cloud data processing module and the radar data processing module to obtain more accurate static traffic environment data such as lane line position, shape and quantity, lane identification information, traffic sign information, and volume and position of static obstacles.
Further, the dynamic environment data fusion mainly takes the dynamic environment data output by the point cloud data processing unit as a reference, and the dynamic environment data output by the image data processing module and the radar data processing module are fused to obtain more accurate dynamic traffic environment data such as the category, the position, the volume, the speed and the like of traffic participants (vehicles, pedestrians, non-motor vehicles and the like).
Further, the simplified expression and the characteristic expression of the representation map to the traffic environment data pair mainly comprise two layers of maps: static traffic maps and dynamic traffic maps; the static traffic data and the dynamic traffic data are respectively mapped on a static traffic map and a dynamic traffic map in the form of points, lines and plane geometry according to a top view angle, attribute information such as shape size, position, speed, category and the like is given to each object, traffic environment characteristics are simply expressed, and the method can be used for rapid calculation.
Further, the roadside intelligent decision terminal includes:
the driving area calculation module is used for calculating the driving area of the intelligent networked automobile in the road.
And the decision-making calculation module is used for calculating a decision-making space of the intelligent networked automobile in the road and can be used for execution of the intelligent networked automobile controller.
And the communication module is used for carrying out information interaction with the intelligent networking automobile.
Furthermore, the intelligent decision-making terminal is connected with the road-side data processing terminal, receives a real-time representation map output by the road-side data processing terminal, the drivable area calculation module is connected with the driving decision-making calculation module and the driving decision-making calculation module is connected with the communication module, the drivable area calculation module calculates the drivable area of the intelligent internet automobile according to the real-time representation map and outputs the drivable area to the driving decision-making calculation module, the driving decision-making calculation module calculates local motion decision-making information of the intelligent internet automobile according to the intelligent internet automobile global path planning data and the drivable area obtained by the communication module, and the decision-making information can be output to the intelligent internet automobile through the communication module. The communication module can acquire data such as global path planning of the intelligent networked automobile and the like, and can also output the motion decision information output by the driving decision calculation module to the intelligent networked automobile.
Further, the motion decision information refers to decision information of an intelligent networked automobile in a road, and mainly comprises straight traveling and steering, wherein the straight traveling information comprises information such as expected acceleration, expected deceleration and expected speed, and the steering information comprises information such as expected acceleration, expected deceleration, steering angle and steering duration.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a schematic structural composition diagram of an intelligent driving decision making system based on roadside multi-sensors provided by the invention.
Fig. 2 is a schematic diagram of static data fusion of an intelligent driving decision system based on roadside multi-sensors provided by the invention.
Fig. 3 is a schematic diagram of dynamic data fusion of an intelligent driving decision system based on roadside multi-sensors provided by the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to the attached figure 1, the embodiment of the invention discloses an intelligent driving decision system based on a roadside multi-sensor, which comprises:
an intelligent driving decision system based on roadside multi-sensors, the system comprising:
drive test data perception end 1, drive test data perception end 1 are equipped with a plurality of sensors and processing module, and each sensor can gather and handle traffic environment data respectively, obtains the heterogeneous real-time traffic environment data of multisource.
And the road side data processing end 2 receives the multi-source heterogeneous real-time traffic environment data output by the road side data sensing end 1, performs information fusion on the multi-source heterogeneous data, performs traffic environment characterization on the fused information, and obtains a traffic environment real-time characterization map.
And the roadside intelligent decision-making end 3 receives the traffic environment real-time representation map output by the roadside data processing end 2, calculates a real-time drivable area of the vehicle, and then calculates driving decision information of the intelligent networked automobile by combining the driving information of the intelligent networked automobile.
In a specific implementation process, the roadside data sensing terminal 1 includes:
the camera 101 is used for collecting and outputting real-time video data of a traffic environment;
the image data processing module 104 is used for processing the video data acquired by the camera 101, acquiring and outputting static and dynamic traffic data, including static traffic environment data such as lane line positions, shapes and numbers, lane identification information, traffic sign information, the volume and position of a static obstacle and the like, and dynamic traffic environment data such as the category, position, volume and speed of traffic participants (vehicles, pedestrians, non-motor vehicles and the like);
the laser radar 102 is used for collecting and outputting real-time point cloud data of a road traffic environment;
the point cloud data processing module 105, the point transport data processing module 105 processes the real-time point transport data output by the laser radar 102, and obtains and outputs static and dynamic traffic data, including static obstacle volume, position data, and data of types, positions, volumes, speeds and the like of traffic participants (vehicles, pedestrians, non-motor vehicles and the like);
the millimeter wave radar 103 is used for collecting and outputting real-time radar data of the traffic environment;
the radar data processing module 106 is used for processing the millimeter wave radar data, acquiring and outputting static and dynamic traffic data, including static obstacle position data and data of positions, speeds and the like of traffic participants (vehicles, pedestrians, non-motor vehicles and the like);
the camera 101, the image data processing module 104, the laser radar 102, the point cloud data processing module 105, the millimeter wave radar 103 and the radar data module 106 are arranged on the road side elevated platform and used for collecting and processing real-time traffic environment data, and the camera 101 is connected with the image data processing module 104, the laser radar 102 is connected with the point cloud data processing module 105, and the millimeter wave radar 103 is connected with the radar data processing module 106.
The roadside data processing terminal 2 includes:
and the data fusion module 201 is connected with the roadside sensing terminal 1, static and dynamic environment data are respectively output by the image data processing module 104, the point cloud data processing module 105 and the radar data processing module 106 for information fusion, and the information fusion comprises static data fusion and dynamic data fusion according to the characteristics of data of different data processing modules.
And the environment representation module 202, the environment representation module 202 represents the traffic environment according to the static traffic environment data and the dynamic traffic environment data output by the data fusion module 201, so as to obtain a real-time representation map.
The roadside intelligent decision terminal 3 includes:
the drivable area calculating module 301 is used for calculating a drivable area of the intelligent networked automobile in the road.
The driving decision calculation module 302, the decision calculation module 302 is used for calculating the driving decision information of the intelligent networked automobile in the road, and can be used for the execution of the intelligent networked automobile controller.
And the communication module 303, the communication module 303 is used for performing information interaction with the intelligent internet automobile.
The intelligent networked automobile 4 is an intelligent automobile which runs in a roadside perception range and has certain perception and networking functions, and the intelligent networked automobile 4 can perform information interaction with a roadside end with the networking function.
The intelligent decision terminal 3 is connected with the roadside data processing terminal 2, the communication module 303 can acquire data such as global path planning of the intelligent networked automobile 4, and can also output the motion decision information output by the driving decision calculation module 302 to the intelligent networked automobile 4.
Referring to fig. 2, the data fusion module 201 mainly uses the image static data 108 output by the image data processing module 104 as a reference, fuses the point cloud static data 107 output by the point cloud data processing module 105 and the radar static data 109 output by the radar data processing module 106 to obtain more accurate static traffic data 203 such as lane line positions, shapes, and numbers, lane identification information, traffic sign information, and volumes and positions of static obstacles, and the environment characterization module 202 obtains a static traffic map 204 according to the static traffic data 203.
Referring to fig. 3, the data fusion module 201 uses the point cloud dynamic data 110 output by the point cloud data processing module 105 as a reference, and fuses the image dynamic data 111 output by the image data processing module 104 and the radar dynamic data 112 output by the radar data processing module 104 to obtain more accurate dynamic traffic data 205 of the traffic participants (vehicles, pedestrians, non-motor vehicles, etc.) such as categories, positions, volumes, speeds, etc., and the environment characterization module 202 obtains the static traffic map 206 according to the dynamic traffic data 205.
The embodiment provides an intelligent driving decision system based on a roadside multi-sensor, which collects static data and dynamic data of a traffic environment in real time through a roadside data sensing end, and increases the collection frequency of the environmental data to ensure that the timeliness of the data is stronger and the data response environment changes in time; fusing multi-source heterogeneous data through a roadside data processing end, and calculating to obtain a real-time traffic environment fine representation map; the roadside intelligent decision-making end obtains information such as path planning of the intelligent networked automobile in a road in real time through the communication module according to the fine environment representation map output by the roadside data processing end, the drivable area calculation module calculates the drivable area of the intelligent networked automobile, the driving decision-making calculation module obtains a decision-making instruction of the intelligent networked automobile, the decision-making instruction is transmitted to the intelligent networked automobile through the communication module, roadside decision-making information is provided for the intelligent networked automobile, and the intelligent networked automobile combines the decision-making information with the roadside decision-making information, so that a more stable and reliable decision can be obtained, and the driving safety and reliability of the intelligent networked automobile are improved.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (7)
1. An intelligent driving decision system based on roadside multi-sensors is characterized by comprising:
the road side data acquisition terminal 1 is used for acquiring various environmental data in a road environment by the road side data sensing terminal 1;
the road side data processing terminal 2 is used for fusing various traffic environment data and representing traffic environments to obtain a static traffic map and a dynamic traffic map;
and the intelligent roadside decision-making terminal 3 outputs driving decision-making information of the intelligent networked automobile.
2. The roadside multi-sensor based intelligent driving decision system as claimed in claim 1, wherein the roadside data collection end 1 comprises:
the camera 101 is used for collecting and outputting real-time video data of a traffic environment;
the image data processing module 104 is used for processing the video data acquired by the camera 101, acquiring and outputting static and dynamic traffic data, including static traffic environment data such as lane line positions, shapes and numbers, lane identification information, traffic sign information, the volume and position of a static obstacle and the like, and dynamic traffic environment data such as the category, position, volume and speed of traffic participants (vehicles, pedestrians, non-motor vehicles and the like);
the system comprises a laser radar 102, a data acquisition unit and a data processing unit, wherein the laser radar 102 is used for acquiring and outputting real-time point cloud data of a road traffic environment;
the point cloud data processing module 105 is used for processing real-time point transportation data output by the laser radar 102, acquiring and outputting static and dynamic traffic data, wherein the static and dynamic traffic data comprise static obstacle volume, position data, and data such as categories, positions, volumes, speeds and the like of traffic participants (vehicles, pedestrians, non-motor vehicles and the like);
the millimeter wave radar 103 is used for collecting and outputting real-time radar data of the traffic environment;
and the radar data processing module 106 is configured to process the millimeter wave radar data, and acquire and output static and dynamic traffic data, which includes static obstacle position data and data of positions and speeds of traffic participants (vehicles, pedestrians, non-motor vehicles, and the like).
3. The roadside multi-sensor based intelligent driving decision system as claimed in claim 2, wherein the camera 101, the image data processing module 104, the laser radar 102, the point cloud data processing module 105, the millimeter wave radar 103 and the radar data module 106 are arranged on a roadside elevated platform for collecting and processing real-time traffic environment data, and the camera 101 is connected with the image data processing module 104, the laser radar 102 is connected with the point cloud data processing module 105, and the millimeter wave radar 103 is connected with the radar data processing module 106.
4. The roadside multi-sensor based intelligent driving decision system as claimed in claim 1, wherein the roadside data processing end 2 comprises:
the data fusion module 201, the data fusion module 201 is connected with the roadside sensing terminal 1, and respectively outputs static and dynamic environment data to the image data processing module 104, the point cloud data processing module 105 and the radar data processing module 106 for information fusion, and the information fusion includes static data fusion and dynamic data fusion according to the characteristics of different data processing modules;
and the environment representation module 202, wherein the environment representation module 202 represents the traffic environment according to the static traffic environment data and the dynamic traffic environment data output by the data fusion module 201, so as to obtain a real-time representation map.
5. The roadside multi-sensor based intelligent driving decision system as claimed in claim 1, wherein the roadside intelligent decision terminal 3 comprises:
the driving area calculation module 301 is used for calculating a driving area of the intelligent networked automobile in the road;
and the decision calculation module 302 is used for calculating the driving decision information of the intelligent networked automobile in the road, and can be used for execution of the intelligent networked automobile controller.
And the communication module 303 is used for carrying out information interaction with the intelligent internet automobile.
6. The roadside multi-sensor-based intelligent driving decision making system as claimed in claim 5, wherein the intelligent networked automobile 4 is an intelligent automobile with certain sensing and networking functions and capable of performing information interaction with a road side end with a networking function, and the intelligent automobile drives in a roadside sensing range.
7. The roadside multi-sensor-based intelligent driving decision system as claimed in claim 5, wherein the intelligent decision terminal 3 is connected to the roadside data processing terminal 2, and the communication module 303 may obtain data such as global path planning of the intelligent internet automobile 4, and may also output motion decision information output by the driving decision calculation module 302 to the intelligent internet automobile 4.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117496711A (en) * | 2023-11-14 | 2024-02-02 | 南京智慧交通信息股份有限公司 | 5G-based man-vehicle road integrated intelligent traffic system and method |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117496711A (en) * | 2023-11-14 | 2024-02-02 | 南京智慧交通信息股份有限公司 | 5G-based man-vehicle road integrated intelligent traffic system and method |
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