CN112309156A - Traffic light passing strategy based on 5G hierarchical decision - Google Patents
Traffic light passing strategy based on 5G hierarchical decision Download PDFInfo
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- CN112309156A CN112309156A CN202011289230.6A CN202011289230A CN112309156A CN 112309156 A CN112309156 A CN 112309156A CN 202011289230 A CN202011289230 A CN 202011289230A CN 112309156 A CN112309156 A CN 112309156A
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- G—PHYSICS
- G08—SIGNALLING
- 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
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096708—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control
- G08G1/096725—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control where the received information generates an automatic action on the vehicle control
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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
- G08G1/0125—Traffic data processing
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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
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
-
- G—PHYSICS
- G08—SIGNALLING
- 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
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096766—Systems involving transmission of highway information, e.g. weather, speed limits where the system is characterised by the origin of the information transmission
- G08G1/096775—Systems involving transmission of highway information, e.g. weather, speed limits where the system is characterised by the origin of the information transmission where the origin of the information is a central station
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- Traffic Control Systems (AREA)
Abstract
The invention discloses a traffic light passing strategy based on 5G grading decision, which comprises the following steps: 1. the vehicle transmits vehicle data to the edge cloud; the cloud server transmits information of all traffic lights to the edge cloud server; 2. the edge cloud server calculates whether the vehicle can pass through the traffic light or not; 3. the edge cloud server sends the instruction to the vehicle end; 4. and the vehicle end controls the vehicle through a vehicle control algorithm built in the automatic driving controller according to the instruction issued by the edge cloud server. The invention promotes the development of 5G industry, reduces the road accident rate and reduces the cost of automatically driving the automobile.
Description
Technical Field
The invention relates to a grading decision method for an automatic driving automobile based on a 5G communication network, in particular to a traffic light passing strategy based on a 5G grading decision.
Background
Through the research integration analysis related to the current intersection passing algorithm aiming at the traffic lights of the automatic driving automobile, the current main research has two directions:
1. patent application No. CN201810510657.0, patent publication No. CN108694841A, optimizes the acceleration curve for the speed curve in a distance before the traffic light intersection. For example, a cost function integrating comfort, safety, timeliness and economy is designed, and a series of candidate accelerations are screened by using the cost function, so that an optimal acceleration curve and an optimal vehicle speed curve are obtained.
2. Patent application No. CN201711069177.7 and patent publication No. CN107871398A are directed to how to obtain traffic light information. An image recognition algorithm is designed according to the patent, and the traffic lights are recognized according to images captured by a driving recorder, and then a prompt is given to a driver.
The emphasis of the prior patent is mainly on how to sense traffic light information and how to optimize a vehicle speed curve. And the whole calculation process is placed at the vehicle end.
In fact, the traffic light information is identified purely by the sensor, and the problems that the sensing range is limited, the identification is possibly inaccurate, the time cannot be accurately obtained and the like exist. In addition, the calculation capacity of the vehicle end is limited, and the calculation process is placed on the vehicle end, so that the calculation pressure of the vehicle end is high, and the cost of a single vehicle is increased.
In summary, the present invention relates to a traffic light passing policy based on 5G hierarchical decision.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a traffic light passing strategy based on 5G hierarchical decision, and by utilizing the advantages of low delay and high reliability of 5G communication, a vehicle end transmits vehicle data to an edge cloud server, and by utilizing the advantages of wide coverage range and strong computing capability of a cloud server, the traffic light passing strategy stores real-time information of all traffic lights and sends the traffic light information to the edge cloud server, and the edge cloud server performs computation based on the information of the vehicle end and the cloud end and finally feeds back the computation result to the vehicle end to realize traffic light passing.
In order to achieve the purpose, the invention is realized by the following technical scheme: the architecture based on the 5G grading decision comprises a vehicle end, an edge cloud end, a cloud end and software and hardware, wherein the vehicle end, the edge cloud end and the cloud end are all provided with the software and the hardware so as to complete the calculation of a traffic light passing strategy;
the vehicle end is as follows: deploying data uploading and receiving equipment, sending vehicle positioning data, vehicle parameters and the like to an edge cloud end in real time, and receiving an instruction sent by the edge cloud end; and designing a whole vehicle control algorithm in the automatic driving controller, and controlling the whole vehicle according to the instruction issued by the edge cloud.
The edge cloud end: deploying data uploading and receiving equipment, and receiving vehicle data sent by a vehicle end and traffic light information sent by a cloud server in real time; and the calculated instruction is sent to the vehicle end; after data transmitted by the vehicle end and the cloud server are obtained, the edge cloud server firstly judges the traffic light closest to the vehicle;
the cloud side: deploying equipment and software for transmitting information to the edge cloud server; and transmitting the real-time information of all traffic lights to the edge cloud server.
After the edge far end obtains data transmitted by the vehicle end and the cloud server, the edge cloud server firstly judges the traffic light closest to the vehicle, and the specific steps are as follows:
a, calculating the distance between the vehicle and all traffic lights, outputting all traffic light numbers smaller than 100 meters to the next step, and if not, stopping the subsequent calculation.
b, calculating the difference between the vehicle course angle and the course angle of the position where the traffic light is input in the previous step, outputting the course angle with the error smaller than 30 degrees to the next step, and if not, stopping the calculation.
c, judging the advancing direction (left turning, right turning or straight going) of the vehicle at the front traffic light by utilizing the overall planning of the vehicle, comparing the advancing direction with the traffic light input in the previous step, outputting the traffic light number meeting the condition to the next step, and stopping the calculation if the advancing direction is not the left turning, the right turning or straight going direction.
And d, comparing the distances between the vehicle and all the traffic lights input in the previous step, and outputting the traffic light number with the minimum distance.
After the judgment of the number of the next traffic light in front of the vehicle is finished, whether the vehicle can pass through the traffic light is judged, a command for parking or normal passing is obtained, and the command is sent to the vehicle end.
The traffic light passing strategy based on the 5G grading decision comprises the following steps:
1. the vehicle transmits vehicle data to the edge cloud; the cloud server transmits information of all traffic lights to the edge cloud server;
2. the edge cloud server calculates whether the vehicle can pass through the traffic light or not;
3. the edge cloud server sends the instruction to the vehicle end;
4. and the vehicle end controls the vehicle through a vehicle control algorithm built in the automatic driving controller according to the instruction issued by the edge cloud server.
The invention has the beneficial effects that: the invention promotes the development of 5G industry, reduces the road accident rate and reduces the cost of automatically driving the automobile.
Drawings
The invention is described in detail below with reference to the drawings and the detailed description;
FIG. 1 is a policy flow diagram of the present invention;
FIG. 2 is a flow chart of the present invention for determining whether a vehicle can pass a traffic light ahead.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific embodiments.
Referring to fig. 1-2, the following technical solutions are adopted in the present embodiment: the architecture based on the 5G grading decision comprises a vehicle end, an edge cloud end, a cloud end and software and hardware, wherein the vehicle end, the edge cloud end and the cloud end are all provided with the software and the hardware so as to complete the calculation of a traffic light passing strategy;
the vehicle end is as follows: deploying data uploading and receiving equipment, sending vehicle positioning data, vehicle parameters and the like to an edge cloud end in real time, and receiving an instruction sent by the edge cloud end; and designing a whole vehicle control algorithm in the automatic driving controller, and controlling the whole vehicle according to the instruction issued by the edge cloud.
The edge cloud end: deploying data uploading and receiving equipment, and receiving vehicle data sent by a vehicle end and traffic light information sent by a cloud server in real time; and the calculated instruction is sent to the vehicle end; after data transmitted by the vehicle end and the cloud server are obtained, the edge cloud server firstly judges the traffic light closest to the vehicle;
the cloud side: deploying equipment and software for transmitting information to the edge cloud server; and transmitting the real-time information of all traffic lights to the edge cloud server.
After the edge far end obtains the data transmitted from the vehicle end and the cloud server, the edge cloud server will first determine the traffic light closest to the vehicle, as shown in fig. 2, and the specific steps are as follows:
a, calculating the distance between the vehicle and all traffic lights, outputting all traffic light numbers smaller than 100 meters to the next step, and if not, stopping the subsequent calculation.
b, calculating the difference between the vehicle course angle and the course angle of the position where the traffic light is input in the previous step, outputting the course angle with the error smaller than 30 degrees to the next step, and if not, stopping the calculation.
c, judging the advancing direction (left turning, right turning or straight going) of the vehicle at the front traffic light by utilizing the overall planning of the vehicle, comparing the advancing direction with the traffic light input in the previous step, outputting the traffic light number meeting the condition to the next step, and stopping the calculation if the advancing direction is not the left turning, the right turning or straight going direction.
And d, comparing the distances between the vehicle and all the traffic lights input in the previous step, and outputting the traffic light number with the minimum distance.
After the judgment of the number of the next traffic light in front of the vehicle is finished, whether the vehicle can pass through the traffic light is judged, a command for parking or normal passing is obtained, and the command is sent to the vehicle end.
The traffic light passing strategy based on the 5G grading decision comprises the following steps:
1. the vehicle transmits vehicle data to the edge cloud; the cloud server transmits information of all traffic lights to the edge cloud server;
2. the edge cloud server calculates whether the vehicle can pass through the traffic light or not;
3. the edge cloud server sends the instruction to the vehicle end;
4. and the vehicle end controls the vehicle through a vehicle control algorithm built in the automatic driving controller according to the instruction issued by the edge cloud server.
In the specific embodiment, based on a 5G hierarchical decision framework, the traffic light passing calculation process of the vehicle is carried out on the edge cloud server. By utilizing the advantages of low time delay and high reliability of 5G communication, the vehicle end transmits the vehicle data to the edge cloud server. In addition, the cloud server has the advantages of wide coverage and high computing power, stores real-time information of all traffic lights and sends the traffic light information to the edge cloud server. And the edge cloud server calculates based on the information of the vehicle end and the cloud end, and finally feeds back the calculation result to the vehicle end to realize traffic light passing.
The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (3)
1. The architecture based on the 5G grading decision is characterized by comprising a vehicle end, an edge cloud end, a cloud end and software and hardware, wherein the vehicle end, the edge cloud end and the cloud end are all provided with the software and the hardware so as to complete the calculation of a traffic light passing strategy;
the vehicle end is as follows: deploying data uploading and receiving equipment, sending vehicle positioning data, vehicle parameters and the like to an edge cloud end in real time, and receiving an instruction sent by the edge cloud end; designing a whole vehicle control algorithm in the automatic driving controller, and controlling the whole vehicle according to a command issued by the edge cloud;
the edge cloud end: deploying data uploading and receiving equipment, and receiving vehicle data sent by a vehicle end and traffic light information sent by a cloud server in real time; and the calculated instruction is sent to the vehicle end; after data transmitted by the vehicle end and the cloud server are obtained, the edge cloud server firstly judges the traffic light closest to the vehicle;
the cloud side: deploying equipment and software for transmitting information to the edge cloud server; and transmitting the real-time information of all traffic lights to the edge cloud server.
2. The architecture of claim 1, wherein after the edge remote end obtains data from the vehicle end and the cloud server, the edge cloud server first determines a traffic light closest to the vehicle, and the specific steps are as follows:
(a) calculating the distance between the vehicle and all traffic lights, outputting all traffic light numbers smaller than 100 meters to the next step, and stopping subsequent calculation if the traffic light numbers are not smaller than 100 meters;
(b) calculating the difference between the vehicle course angle and the course angle of the position where the traffic light is input in the previous step, outputting the course angle with the error smaller than 30 degrees to the next step, and stopping calculation if the difference is not;
(c) judging the advancing direction of the vehicle at the traffic light in front by utilizing the overall planning of the vehicle, comparing the advancing direction with the traffic light input in the previous step, outputting the traffic light number meeting the conditions to the next step, and stopping calculation if the advancing direction does not meet the conditions;
(d) comparing the distances between the vehicle and all the traffic lights input in the previous step, and outputting the traffic light number with the minimum distance;
after the judgment of the number of the next traffic light in front of the vehicle is finished, whether the vehicle can pass through the traffic light is judged, a command for parking or normal passing is obtained, and the command is sent to the vehicle end.
3. The traffic light passing strategy based on the 5G grading decision is characterized by comprising the following steps:
(1) the vehicle transmits vehicle data to the edge cloud; the cloud server transmits information of all traffic lights to the edge cloud server;
(2) the edge cloud server calculates whether the vehicle can pass through the traffic light or not;
(3) the edge cloud server sends the instruction to the vehicle end;
(4) and the vehicle end controls the vehicle through a vehicle control algorithm built in the automatic driving controller according to the instruction issued by the edge cloud server.
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| CN202011289230.6A CN112309156A (en) | 2020-11-18 | 2020-11-18 | Traffic light passing strategy based on 5G hierarchical decision |
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| CN202011289230.6A CN112309156A (en) | 2020-11-18 | 2020-11-18 | Traffic light passing strategy based on 5G hierarchical decision |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115440070A (en) * | 2022-07-22 | 2022-12-06 | 中智行(苏州)科技有限公司 | Automatic driving traffic signal lamp information acquisition system and method based on vehicle and road coordination |
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Patent Citations (6)
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| CN109035832A (en) * | 2018-09-12 | 2018-12-18 | 清华大学苏州汽车研究院（吴江） | Signal lamp intersection intelligence traffic system based on V2X communication |
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Application publication date: 20210202 |