CN112885092A - Highway vehicle and road cooperative cloud control platform system based on intelligent edge computing - Google Patents
Highway vehicle and road cooperative cloud control platform system based on intelligent edge computing Download PDFInfo
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- CN112885092A CN112885092A CN202110106756.4A CN202110106756A CN112885092A CN 112885092 A CN112885092 A CN 112885092A CN 202110106756 A CN202110106756 A CN 202110106756A CN 112885092 A CN112885092 A CN 112885092A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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- G—PHYSICS
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- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
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Abstract
The invention provides an intelligent edge computing-based highway vehicle-road cooperative cloud control platform system, which relates to the technical field of highway information services and comprises an edge computing unit, wherein the output end of the edge computing unit is electrically connected with a road side unit, the output end of the road side unit is electrically connected with a vehicle-mounted unit, the output end of the vehicle-mounted unit is electrically connected with a vehicle-mounted display terminal, the vehicle-mounted unit can acquire vehicle satellite positioning information in a positioning period, the road side unit has LTE-V2X PC5 and LTE Uu dual-mode communication capacity, accords with 3GPP R14LTE-V2X protocol specifications, and can realize direct communication among devices and communication based on a cellular network. According to the invention, by setting the intelligent edge computing-based highway vehicle-road cooperative cloud control platform system, the precision required by vehicle positioning is reduced, a high-precision map is not required to be configured, the cost required by information service is reduced, and the implementation is simpler, so that the intelligent edge computing-based highway vehicle-road cooperative cloud control platform system has higher popularization and application values and prospects in the aspect of driving assistance information service.
Description
Technical Field
The invention relates to the technical field of highway information service, in particular to a highway vehicle-road cooperative cloud control platform system based on intelligent edge computing.
Background
At present, along with the rapid increase of motor vehicle drivers and motor vehicle reserves in China, the traffic flow of expressways also rises sharply, and the traffic problem is severe day by day. Use novel intelligent networking road traffic system of car networking technique, car road cooperative technology etc. as the core, for thoroughly solving current traffic problem and providing effective way, car road cooperative system is based on technologies such as wireless communication, sensing detection and acquires vehicle and road information, carries out the interaction and the sharing of information through car, car road communication, fully realizes the effective cooperation of car and road, guarantees traffic safety, improves current efficiency to form the road traffic system of safety, high efficiency and environmental protection.
In the aspect of highway personalized information service application, the existing system is generally based on vehicle positioning information and pushes personalized information prompts for different users by combining information such as traffic events, road dangerous conditions and the like monitored by road sides. The traffic events and other information monitored by the roadside can be accurately positioned on a specific lane, but the conventional navigation map generally has no lane information on an expressway, and the common positioning accuracy is in the meter level, so that the requirement of lane-level positioning is not met. Therefore, for realizing the information service of the highway lane level, high-precision positioning is mostly needed and a high-precision map is configured, but the cost is inevitably increased and the implementation complexity is inevitably brought, and the difficulty of popularization and application is increased.
Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides an intelligent edge computing-based highway vehicle-road cooperative cloud control platform system.
In order to achieve the purpose, the invention adopts the following technical scheme: the intelligent edge computing-based highway vehicle-road cooperative cloud control platform system comprises an edge computing unit, wherein the output end of the edge computing unit is electrically connected with a road side unit, the output end of the road side unit is electrically connected with an on-board unit, and the output end of the on-board unit is electrically connected with an on-board display terminal.
Preferably, the on-board unit is capable of acquiring vehicle satellite positioning information within a positioning period.
Preferably, the road side unit has dual-mode communication capability of LTE-V2X PC5 and LTE Uu, conforms to 3GPP R14LTE-V2X protocol specification, and can realize direct communication among devices and communication based on a cellular network.
Preferably, the vehicle-mounted display terminal can realize vehicle-mounted information prompt and an interactive terminal.
Preferably, the operation steps are as follows:
s1: the vehicle-mounted unit acquires vehicle satellite positioning information in a positioning period, corrects positioning in a lane-level positioning mode through a common civil Beidou/GPS satellite positioning technology and a lane cooperation mode, and achieves the lane-level positioning function.
S2: the edge calculation unit detects traffic incidents and passing vehicles on the road in real time, and the information of the traffic incidents positioned on the lane comprises: roadblock, construction, block up, park, line ball, turn around, retrograde motion, pedestrian, shed thing, lane change, occupy emergent lane and the current vehicle information include: the vehicle type, the lane flow, the lane speed, the vehicle head distance, the vehicle head time distance, the lane time occupancy, the lane space occupancy, the queuing length and the road traffic passing state are sent to a road side unit, meanwhile, the edge calculation unit realizes the detection, the positioning and the tracking of a vehicle target, and can give necessary information such as the position coordinate, the advancing speed, the target ID and the like of an image where the vehicle is located in real time.
S3: the road side unit broadcasts the traffic event information and the passing vehicle information through the PC, repackages the road side traffic event and the traffic parameter data received by the road side unit from the edge calculation unit through the network interface, and broadcasts the road side traffic event and the traffic parameter data to the outside through the PC5 interface.
S4: after receiving the traffic event and traffic parameter data broadcast by the road side unit through the PC5, the vehicle-mounted unit unpacks the data according to the standard and standardized data format, thereby obtaining all traffic state information around the current vehicle, including data of traffic events, passing vehicles and the like, the vehicle-mounted unit matches the vehicle positioning data obtained in step S1 with the passing vehicle data, the data of the passing vehicles with the minimum distance is selected by calculating the different distances between the data of the vehicle and the data of the passing vehicles, the data is judged to be the data of the vehicle, thereby obtaining the data of the driving lane of the vehicle, realizing the lane-level positioning of the vehicle, adding the speed parameter as the matching parameter when a plurality of data of different lanes are used as the alternative data, if the only vehicle data can not be selected at the moment, the algorithm selects data of a plurality of sampling periods to carry out matching calculation, and the correct matched vehicle is found by calculating the difference value of the data in different sampling periods.
S5: after matching the correct lane data of the vehicle, the vehicle-mounted unit transmits the traffic event information, the passing vehicle information and the vehicle information to the vehicle-mounted display terminal for display through the HMI interface, and because the obtained traffic event information, the passing vehicle information and the vehicle information are all based on lane level, the common navigation map can be adopted to combine with the lane number information to generate the lane level map data, and the traffic event information, the vehicle and other vehicles around can be displayed at the relative positions on the map.
Preferably, the vehicle-mounted unit in S1 integrates a GNSS positioning module, the civil Beidou/GPS satellite is adopted to realize the real-time positioning of the vehicle, and the positioning precision is meter level.
Preferably, both the traffic event detected in S2 and the collected traffic parameter data can be accurately located on a particular lane.
Preferably, the high-gain antenna is adopted by the road side unit in S3, and the coverage range can reach more than 1 km.
Preferably, the frequency of the positioning data samples of the vehicle and the frequency of the traffic event and traffic parameter data broadcast by the road side unit in S4 are both 100 ms.
Preferably, the lane-level map data generated by combining the ordinary navigation map with the lane number information in S5 may be downloaded to the vehicle-mounted display terminal in an off-line manner, so as to increase the speed of map display.
Compared with the prior art, the invention has the advantages and positive effects that,
compared with a lane-level positioning and display system based on high-precision positioning and high-precision maps, the system adopts a common satellite positioning and widely used navigation map, does not need to increase a high-precision positioning module, avoids the increase of cost, does not need to acquire the high-precision maps, reduces the complexity of system deployment, carries out real-time detection on traffic events and passing vehicles on roads through an edge computing unit, obtains vehicle satellite positioning information in a positioning period through a vehicle-mounted unit, corrects the positioning in a road cooperation mode, thereby realizing the lane-level positioning function, reduces the precision required by vehicle positioning through arranging the highway road-based intelligent edge computing and cloud control platform system, does not need to configure the high-precision maps, reduces the cost required by information service, and ensures that the implementation is simpler, therefore, the method has more popularization and application values and prospects in the aspect of driving assistance information service.
Drawings
FIG. 1 is a schematic overall structure diagram of a highway vehicle-road cooperative cloud control platform system based on intelligent edge computing according to the present invention;
fig. 2 is a schematic diagram of the operation steps of the highway vehicle-road cooperative cloud control platform system based on intelligent edge computing according to the present invention.
Illustration of the drawings:
1. an edge calculation unit; 2. a road side unit; 3. an on-board unit; 4. and (5) a vehicle-mounted display terminal.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, the present invention will be further described with reference to the accompanying drawings and examples. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and thus the present invention is not limited to the specific embodiments of the present disclosure.
In an embodiment, as shown in fig. 1 and fig. 2, the invention provides an intelligent edge computing-based highway vehicle-road cooperative cloud control platform system, which includes an edge computing unit 1, wherein an output end of the edge computing unit 1 is electrically connected with a road side unit 2, an output end of the road side unit 2 is electrically connected with an on-board unit 3, and an output end of the on-board unit 3 is electrically connected with an on-board display terminal 4.
Further, the on-board unit 3 can acquire the vehicle satellite positioning information in the positioning period.
Further, the road side unit 2 has dual-mode communication capability of LTE-V2X PC5 and LTE Uu, conforms to the 3GPP R14LTE-V2X protocol specification, and can realize direct communication among devices and communication based on a cellular network.
Further, the vehicle-mounted display terminal 4 can realize vehicle-mounted information prompt and interactive terminal
Further, the operation steps are as follows:
s1: the vehicle-mounted unit 3 acquires vehicle satellite positioning information in a positioning period, and the vehicle-mounted unit 3 corrects positioning in a lane-level positioning mode through a common civil Beidou/GPS satellite positioning technology and a lane cooperation mode.
S2: the edge calculation unit 1 detects traffic events and passing vehicles on roads in real time, and includes the traffic event information positioned on lanes: roadblock, construction, block up, park, line ball, turn around, retrograde motion, pedestrian, shed thing, lane change, occupy emergent lane and the current vehicle information include: the vehicle type, the lane flow, the lane speed, the vehicle head distance, the vehicle head time distance, the lane time occupancy, the lane space occupancy, the queuing length and the road traffic passing state are sent to the road side unit 2, meanwhile, the edge calculation unit 1 realizes the detection, the positioning and the tracking of the vehicle target, and can give necessary information such as the position coordinate, the advancing speed, the target ID and the like of the image where the vehicle is located in real time.
S3: the road side unit 2 broadcasts the traffic event information and the traffic vehicle information through the PC5, and the road side unit 2 repacks the road side traffic event and the traffic parameter data received from the edge calculation unit 1 through the network interface and broadcasts the road side traffic event and the traffic parameter data to the outside through the PC5 interface.
S4: after receiving the traffic event and traffic parameter data broadcast by the road side unit 2 through the PC5, the on-board unit 3 unpacks the data according to the standard data format, thereby obtaining all traffic state information around the current vehicle, including data of traffic events, passing vehicles, etc., the on-board unit 3 matches the vehicle positioning data obtained in step S1 with the passing vehicle data, the data of the passing vehicles with the minimum distance is selected by calculating the different distances between the data of the vehicle and the data of the passing vehicles, the data is judged to be the data of the vehicle, thereby obtaining the data of the driving lane of the vehicle, realizing the lane-level positioning of the vehicle, adding the speed parameter as the matching parameter when a plurality of data of different lanes are used as the alternative data, if the only vehicle data can not be selected at the moment, the algorithm selects data of a plurality of sampling periods to carry out matching calculation, and the correct matched vehicle is found by calculating the difference value of the data in different sampling periods.
S5: after matching the correct lane data of the vehicle, the vehicle-mounted unit 3 transmits the traffic event information, the traffic vehicle information and the vehicle information to the vehicle-mounted display terminal 4 through the HMI interface for display, and since the obtained traffic event information, the traffic vehicle information and the vehicle information are already based on the lane level, it is possible to generate the map data of the lane level by using the general navigation map in combination with the lane number information, and display the relative positions of the traffic event information, the vehicle and other vehicles around on the map.
Furthermore, the vehicle-mounted unit 3 in the S1 integrates a GNSS positioning module, and the civil Beidou/GPS satellite is adopted to realize the real-time positioning of the vehicle, and the positioning precision is meter level.
Further, both the traffic event detected in S2 and the collected traffic parameter data may be accurately located on a particular lane.
Furthermore, in S3, the roadside unit 2 uses a high-gain antenna, and the coverage area can reach more than 1 km.
Further, the frequency of the positioning data samples of the vehicle and the frequency of the traffic event and traffic parameter data broadcast by the roadside unit 2 in S4 are both 100 ms.
Further, the lane-level map data generated by the general navigation map in combination with the lane number information in S5 may be downloaded to the vehicle-mounted display terminal 4 in an off-line manner, so as to increase the speed of map display.
Compared with a lane-level positioning and display system based on high-precision positioning and high-precision maps, the system adopts common satellite positioning and widely used navigation maps, does not need to increase a high-precision positioning module, avoids the increase of cost, does not need to acquire the high-precision maps, reduces the complexity of system deployment, detects traffic events and passing vehicles on roads in real time through the edge computing unit 1, obtains vehicle satellite positioning information in a positioning period through the vehicle-mounted unit 3, corrects the positioning in a way of vehicle-road cooperation, thereby realizing the function of lane-level positioning, reduces the precision required by vehicle positioning, does not need to configure the high-precision maps, and reduces the cost required by information service through the intelligent edge computing-based highway-vehicle-road cooperation cloud control platform system, and the implementation is simpler, so that the method has more popularization and application values and prospects in the aspect of driving assistance information service
The above description is only a preferred embodiment of the present invention, and not intended to limit the present invention in other forms, and any person skilled in the art may apply the above modifications or changes to the equivalent embodiments with equivalent changes by using the technical contents disclosed in the above description to other fields, but any simple modification, equivalent change and change made to the above embodiments according to the technical essence of the present invention still belong to the protection scope of the technical solution of the present invention.
Claims (10)
1. Highway vehicle and road is cloud accuse platform system in coordination based on intelligence edge computing, including edge computing element (1), its characterized in that: the edge computing device is characterized in that the output end of the edge computing unit (1) is electrically connected with a road side unit (2), the output end of the road side unit (2) is electrically connected with an on-board unit (3), and the output end of the on-board unit (3) is electrically connected with an on-board display terminal (4).
2. The intelligent edge computing-based highway vehicle-road cooperative cloud control platform system according to claim 1, wherein: the on-board unit (3) is capable of acquiring vehicle satellite positioning information within a positioning period.
3. The intelligent edge computing-based highway vehicle-road cooperative cloud control platform system according to claim 1, wherein: the road side unit (2) has dual-mode communication capabilities of LTE-V2X PC5 and LTE Uu, conforms to 3GPP R14LTE-V2X protocol specifications, and can realize direct communication among devices and communication based on a cellular network.
4. The intelligent edge computing-based highway vehicle-road cooperative cloud control platform system according to claim 1, wherein: the vehicle-mounted display terminal (4) can realize vehicle-mounted information prompt and an interactive terminal.
5. The intelligent edge computing-based highway vehicle-road cooperative cloud control platform system according to claim 1, wherein: the operation steps are as follows:
s1: the vehicle-mounted unit (3) acquires vehicle satellite positioning information in a positioning period, and the vehicle-mounted unit (3) corrects positioning in a lane-level positioning mode through a common civil Beidou/GPS satellite positioning technology and a lane cooperation mode.
S2: the edge calculation unit (1) detects traffic events and passing vehicles on roads in real time, and the information of the traffic events positioned on the lanes comprises: roadblock, construction, block up, park, line ball, turn around, retrograde motion, pedestrian, shed thing, lane change, occupy emergent lane and the current vehicle information include: the vehicle type, the lane flow, the lane speed, the vehicle head distance, the vehicle head time distance, the lane time occupancy, the lane space occupancy, the queuing length and the road traffic passing state are sent to the road side unit (2), meanwhile, the edge calculation unit (1) realizes the detection, the positioning and the tracking of a vehicle target, and can give necessary information such as the position coordinate, the advancing speed, the target ID and the like of an image where the vehicle is located in real time.
S3: the road side unit (2) broadcasts the traffic event information and the passing vehicle information through the PC5, and the road side unit (2) repacks the road side traffic event and the traffic parameter data received from the edge calculation unit (1) through the network interface and broadcasts the road side traffic event and the traffic parameter data to the outside through the PC5 interface.
S4: after receiving the traffic event and the traffic parameter data broadcasted by the road side unit (2) through the PC5, the vehicle-mounted unit (3) unpacks the data according to the data format of the standard specification, so as to obtain all the traffic state information around the current vehicle, including the data of the traffic event, the passing vehicle and the like, the vehicle-mounted unit (3) matches the vehicle positioning data obtained in the step S1 with the passing vehicle data, selects the passing vehicle data with the minimum distance by calculating the different distances between the vehicle and the passing vehicle data, judges the data as the vehicle data, so as to obtain the data of the driving lane of the vehicle, realize the lane-level positioning of the vehicle, when a plurality of data of different lanes are used as the alternative data, the speed parameter is added as the matching parameter, if the only vehicle data can not be selected at the moment, the algorithm selects the data of a plurality of sampling periods for matching calculation, the correct matching vehicle is found by calculating the difference of the data during different sampling periods.
S5: after matching the correct lane data of the vehicle, the vehicle-mounted unit (3) transmits the traffic event information, the traffic vehicle information and the vehicle information to the vehicle-mounted display terminal (4) through the HMI interface for display, and because the obtained traffic event information, the traffic vehicle information and the vehicle information are all based on lane level, the common navigation map can be adopted to combine the lane number information to generate the map data of the lane level, and the traffic event information, the vehicle and other vehicles around can be displayed at the relative positions on the map.
6. The intelligent edge computing-based highway vehicle-road cooperative cloud control platform system according to claim 5, wherein: and the vehicle-mounted unit (3) in the S1 integrates a GNSS positioning module, and the civil Beidou/GPS satellite is adopted to realize the real-time positioning of the vehicle, and the positioning precision is meter level.
7. The intelligent edge computing-based highway vehicle-road cooperative cloud control platform system according to claim 5, wherein: both the traffic events detected in S2 and the collected traffic parameter data may be accurately located on a particular lane.
8. The intelligent edge computing-based highway vehicle-road cooperative cloud control platform system according to claim 5, wherein: and the road side unit (2) in the S3 adopts a high-gain antenna, and the coverage range can reach more than 1 km.
9. The intelligent edge computing-based highway vehicle-road cooperative cloud control platform system according to claim 5, wherein: the frequency of the positioning data samples of the vehicle and the frequency of the traffic event and traffic parameter data broadcast by the roadside unit (2) in S4 are both 100 ms.
10. The intelligent edge computing-based highway vehicle-road cooperative cloud control platform system according to claim 5, wherein: the lane-level map data generated by combining the common navigation map with the lane number information in the S5 can be downloaded to the vehicle-mounted display terminal (4) in an off-line mode, so that the speed of map display is improved.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113888871A (en) * | 2021-10-20 | 2022-01-04 | 上海电科智能***股份有限公司 | Automatic handling linkage system and method for highway traffic incident |
| CN114374952A (en) * | 2021-12-24 | 2022-04-19 | 联通智网科技股份有限公司 | Traffic event information sending method and device and edge cloud server |
| CN114396959A (en) * | 2022-03-25 | 2022-04-26 | 华砺智行(武汉)科技有限公司 | Lane matching positioning method, device, equipment and medium based on high-precision map |
| CN115394100A (en) * | 2022-07-22 | 2022-11-25 | 上海交通大学 | Intelligent roadside system facing vehicle-road cooperation |
| CN117558129A (en) * | 2023-11-14 | 2024-02-13 | 长沙云软信息技术有限公司 | Intelligent positioning system and method for expressway construction |
-
2021
- 2021-01-26 CN CN202110106756.4A patent/CN112885092A/en active Pending
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113888871A (en) * | 2021-10-20 | 2022-01-04 | 上海电科智能***股份有限公司 | Automatic handling linkage system and method for highway traffic incident |
| CN114374952A (en) * | 2021-12-24 | 2022-04-19 | 联通智网科技股份有限公司 | Traffic event information sending method and device and edge cloud server |
| CN114396959A (en) * | 2022-03-25 | 2022-04-26 | 华砺智行(武汉)科技有限公司 | Lane matching positioning method, device, equipment and medium based on high-precision map |
| CN114396959B (en) * | 2022-03-25 | 2022-08-30 | 华砺智行(武汉)科技有限公司 | Lane matching positioning method, device, equipment and medium based on high-precision map |
| CN115394100A (en) * | 2022-07-22 | 2022-11-25 | 上海交通大学 | Intelligent roadside system facing vehicle-road cooperation |
| CN117558129A (en) * | 2023-11-14 | 2024-02-13 | 长沙云软信息技术有限公司 | Intelligent positioning system and method for expressway construction |
| CN117558129B (en) * | 2023-11-14 | 2024-06-11 | 长沙云软信息技术有限公司 | Intelligent positioning system and method for expressway construction |
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