CN114937352A - Intelligent scheduling method and system suitable for cloud service of fleet - Google Patents
Intelligent scheduling method and system suitable for cloud service of fleet Download PDFInfo
- Publication number
- CN114937352A CN114937352A CN202210874496.XA CN202210874496A CN114937352A CN 114937352 A CN114937352 A CN 114937352A CN 202210874496 A CN202210874496 A CN 202210874496A CN 114937352 A CN114937352 A CN 114937352A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- positioning data
- distance
- fleet
- longitude
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/22—Platooning, i.e. convoy of communicating vehicles
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/20—Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
- G08G1/202—Dispatching vehicles on the basis of a location, e.g. taxi dispatching
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W4/44—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention provides an intelligent scheduling method and system suitable for fleet cloud service, comprising the steps that a vehicle machine of each vehicle uploads positioning data to a fleet cloud server, and the fleet cloud server generates a driving direction according to a starting point and a stopping point; determining the queuing sequence of each vehicle according to the positioning data and the driving direction corresponding to each vehicle code, and generating a sequencing set in the driving direction; calculating to obtain a first spacing distance and a second spacing distance according to the number of vehicles and the types of the vehicles in the sorting set; if the first positioning data and the third positioning data do not meet the requirement of the first spacing distance, sending a deceleration scheduling prompt to a vehicle machine of a vehicle code corresponding to the first positioning data; and if the second positioning data and the third positioning data do not meet the requirement of the second spacing distance, sending a speed-up scheduling prompt to the vehicle machine of the vehicle code corresponding to the second positioning data.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to an intelligent scheduling method and system suitable for cloud service of a fleet.
Background
When large quantities of goods are transported and a large number of personnel are dispatched, a plurality of vehicles are often used for unified transportation, and at the moment, the plurality of vehicles form a transportation fleet. In order to ensure that goods arrive at a designated place (such as a certain gas station and a certain service area) uniformly, and simultaneously enable a plurality of vehicles to assist each other when an emergency occurs, and facilitate a manager to manage the vehicles in a fleet, the overall length of the fleet needs to be controlled to prevent the vehicles from falling behind.
On the premise of achieving the purpose of controlling the overall length of a fleet, the distance between vehicles needs to be monitored, and corresponding scheduling is performed when the distance between the vehicles does not meet corresponding requirements. Therefore, a scheduling method is needed to monitor the distance between vehicles in a fleet and schedule corresponding vehicles so that all vehicles in the fleet have a suitable distance.
Disclosure of Invention
The embodiment of the invention provides an intelligent scheduling method and system suitable for a fleet cloud service, which can monitor the distance between vehicles in a fleet, and remind and schedule a driver in time when the distance between certain vehicles in the fleet does not meet the requirement, so that all vehicles in the fleet have a proper distance.
In a first aspect of the embodiments of the present invention, an intelligent scheduling method suitable for a cloud service of a fleet is provided, including:
receiving fleet configuration data of a user, the fleet configuration data including vehicle codes, starting points, and ending points of a plurality of vehicles;
in the running process of a motorcade, the vehicle machine of each vehicle uploads positioning data to a motorcade cloud server, and the motorcade cloud server generates a running direction according to the starting point and the ending point after judging that the positioning data corresponding to each vehicle code is received in real time;
determining the queuing sequence of each vehicle according to the positioning data and the driving direction corresponding to each vehicle code, and generating a sequencing set in the driving direction;
extracting first positioning data of a vehicle closest to the end point, second positioning data of a vehicle closest to the start point and third positioning data of a vehicle centered in the sequencing set in real time;
calculating a first spacing distance and a second spacing distance according to the number of vehicles and the types of the vehicles in the sorting set, wherein the first spacing distance is the required distance between the vehicle closest to the end point and the vehicle in the middle, and the second spacing distance is the required distance between the vehicle closest to the start point and the vehicle in the middle;
if the first positioning data and the third positioning data do not meet the requirement of the first spacing distance, sending a deceleration scheduling prompt to a vehicle machine of a vehicle code corresponding to the first positioning data;
and if the second positioning data and the third positioning data are judged not to meet the requirement of the second spacing distance, sending a speed-up scheduling prompt to a vehicle machine of the vehicle code corresponding to the second positioning data.
In a second aspect of the embodiments of the present invention, an intelligent scheduling system suitable for a fleet cloud service is provided, including:
a receiving module for receiving fleet configuration data of a user, the fleet configuration data including vehicle codes, starting points, and ending points of a plurality of vehicles;
the generation module is used for uploading positioning data to a fleet cloud server by a vehicle machine of each vehicle in the running process of a fleet, and the fleet cloud server generates a running direction according to the starting point and the end point after judging that the positioning data corresponding to each vehicle code is received in real time;
the determining module is used for determining the queuing sequence of each vehicle according to the positioning data and the driving direction corresponding to each vehicle code and generating a sequencing set in the driving direction;
the extraction module is used for extracting first positioning data of a vehicle closest to the end point, second positioning data of the vehicle closest to the start point and third positioning data of a vehicle centered in the sequencing set in real time;
the calculation module is used for calculating a first spacing distance and a second spacing distance according to the number of vehicles and the types of the vehicles in the sorting set, wherein the first spacing distance is the required distance between the vehicle closest to the end point and the vehicle in the center, and the second spacing distance is the required distance between the vehicle closest to the start point and the vehicle in the center;
the first reminding module is used for sending a deceleration scheduling reminding to a vehicle machine of a vehicle code corresponding to the first positioning data if the first positioning data and the third positioning data are judged not to meet the requirement of the first spacing distance;
and the second reminding module is used for sending a speed-up scheduling reminding to the vehicle machine of the vehicle code corresponding to the second positioning data if the requirement of the second spacing distance is not met between the second positioning data and the third positioning data.
Has the advantages that:
1. according to the scheme, the vehicles are sequenced according to the positioning data and the driving directions corresponding to the vehicle codes in the fleet to obtain a sequencing set in the corresponding driving directions, then a head vehicle, a middle vehicle and a tail vehicle are determined by combining the sequencing set, and a first spacing distance and a second spacing distance are calculated. Controlling the speed of the head car by using the first spacing distance so as to control the distance between the head car and the middle car and realize the management of all the cars between the head car and the middle car; controlling the speed of the tail car by using the second spacing distance so as to control the distance between the tail car and the middle car and realize the management of all the cars between the tail car and the middle car; the sectional adjustment and control of the motorcade are realized through the mode, so that the control of the whole length of the motorcade can be effectively realized;
2. the scheme can obtain the sequencing set by adopting two modes. One is to combine the longitude direction and the longitude value to obtain a corresponding sorting set, and meanwhile, in the process of obtaining the sorting set, the scheme adopts different sorting modes in combination with different pairs of sorting sets in the longitude direction, so that the last vehicle in the sorting set is the vehicle closest to the end point, and the first vehicle in the sorting set is the vehicle closest to the start point; the other method is to combine the latitude direction and the latitude value to obtain a corresponding sorting set, and meanwhile, in the process of obtaining the sorting set, the scheme adopts different sorting modes to the sorting sets in combination with different latitude directions, so that the last vehicle in the sorting set is the vehicle closest to the end point, and the first vehicle in the sorting set is the vehicle closest to the start point; according to the scheme, the vehicles in the sorted set are sorted in sequence in the driving direction, and the head data, the tail data and the middle data in the sorted set are directly processed in the subsequent calculation, so that the data processing efficiency is improved, and the data processing amount is reduced;
3. in the process of calculating the first spacing distance and the second spacing distance, the method and the device can perform comprehensive calculation by referring to the number of vehicles, the types of the vehicles and other factors to obtain the first spacing distance and the second spacing distance which are suitable for the types of the vehicles and the number of the vehicles, so that the method and the device can adapt to different scenes to adjust the first spacing distance and the second spacing distance to obtain a proper adjustment range, and flexibly regulate and control the fleet.
Drawings
Fig. 1 is a schematic flowchart of an intelligent scheduling method suitable for a cloud service of a fleet according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an intelligent scheduling system suitable for a fleet cloud service according to the present disclosure.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, 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 obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein.
It should be understood that, in the various embodiments of the present invention, the sequence numbers of the processes do not mean the execution sequence, and the execution sequence of the processes should be determined by the functions and the internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
It should be understood that in the present application, "comprising" and "having" and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements explicitly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be understood that, in the present invention, "a plurality" means two or more. "and/or" is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "comprises A, B and C" and "comprises A, B, C" means that A, B, C all comprise, "comprises A, B or C" means that one of A, B, C comprises, "comprises A, B and/or C" means that any 1 or any 2 or 3 of A, B, C comprises.
It should be understood that in the present invention, "B corresponding to a", "a corresponds to B", or "B corresponds to a" means that B is associated with a, and B can be determined from a. Determining B from a does not mean determining B from a alone, but may also be determined from a and/or other information. And the matching of A and B means that the similarity of A and B is greater than or equal to a preset threshold value.
As used herein, "if" may be interpreted as "at … …" or "when … …" or "in response to a determination" or "in response to a detection", depending on the context.
The technical solution of the present invention will be described in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.
Referring to fig. 1, which is a schematic flow diagram of an intelligent scheduling method suitable for a fleet cloud service provided in an embodiment of the present invention, the intelligent scheduling method suitable for the fleet cloud service includes S1-S7:
s1, the user' S fleet configuration data is received, the fleet configuration data including vehicle codes, starting points, and ending points for a plurality of vehicles.
The scheme firstly allocates relevant data to the motorcade, and the allocation data comprises vehicle codes, a starting point and an ending point.
Illustratively, the fleet includes 5 vehicles, and needs to reach point B from point a, the scheme sets a vehicle code, for example {1, 2, 3, 4, 5}, where the starting point is point a and the ending point is point B.
And S2, in the running process of the motorcade, the locomotive of each vehicle uploads positioning data to the motorcade cloud server, and the motorcade cloud server generates a running direction according to the starting point and the ending point after judging that the positioning data corresponding to each vehicle code is received in real time.
In the process that the fleet reaches the point B from the point A, the vehicle machine of each vehicle uploads positioning data to the fleet cloud server, and the fleet cloud server generates a driving direction according to the starting point and the end point after judging that the positioning data corresponding to each vehicle code is received in real time, for example, after judging that the positioning data corresponding to 5 vehicle codes are received in real time, the fleet cloud server generates a driving direction according to the point A and the point B.
In some embodiments, S2 (where, during the driving process of the fleet, the vehicle machine of each vehicle uploads positioning data to a fleet cloud server, and the fleet cloud server generates a driving direction according to the starting point and the ending point after determining that the positioning data corresponding to each vehicle code is received in real time) includes S21-S24:
and S21, acquiring a start coordinate of the start point and an end coordinate of the end point, wherein the start coordinate comprises a start longitude and a start latitude, and the end coordinate comprises an end longitude and an end latitude.
Illustratively, the starting coordinate of the starting point a is: (
， 
) Wherein the starting longitude may be
The starting dimension may be
(ii) a The termination coordinate of the termination point B is (
，
) Wherein the end longitude may be
The terminating dimension may be
。
And S22, comparing the starting longitude with the ending longitude to obtain the longitude direction, wherein the longitude direction is the longitude value increase or the longitude value decrease.
It will be appreciated that the present scheme will start longitude
And end longitude
By comparison, if the starting longitude
Less than end longitude
A longitude value indicating a longitude direction is incremented; similarly, if the start longitude
Greater than terminal longitude
The longitude value in the longitude direction is described as decreasing.
And S23, comparing the starting latitude with the ending latitude to obtain the latitude direction, wherein the latitude direction is latitude value increase or latitude value decrease.
It will be appreciated that the present scheme will start dimension
And terminating dimension
Comparing if starting dimension
Less than the terminal dimension
The dimension value of the dimension direction is increased; similarly, if the starting dimension is
Greater than the terminating dimension
Description of the inventionThe dimension value in the direction of the degrees is reduced.
And S24, obtaining the driving direction of the motorcade according to any one or more of the longitude direction and the latitude direction.
It can be understood that the driving direction of the fleet can be determined according to the longitude direction, the driving direction of the fleet can also be determined according to the latitude direction, and the driving direction of the fleet can also be obtained by combining the longitude direction and the latitude direction.
And S3, determining the queuing sequence of each vehicle according to the positioning data and the driving direction corresponding to each vehicle code, and generating a sequencing set in the driving direction.
According to the scheme, the queuing sequence of each vehicle is determined according to the positioning data and the driving direction obtained in the step, and a sequencing set in the driving direction is obtained.
The scheme may utilize the following two embodiments to determine the relevant sorted sets:
first, a related sorting set is obtained according to the longitude direction, which is as follows:
in some embodiments, S3 (the determining the queuing order of each vehicle according to the corresponding positioning data and driving direction encoded by each vehicle, generating the sorted set in the driving direction) includes S31-S33:
and S31, when the driving direction is the longitude direction, extracting longitude positioning information in the positioning data corresponding to each vehicle code.
It can be understood that the present solution is to determine in the longitudinal direction, so that the longitudinal positioning information in the positioning data corresponding to each vehicle code is extracted.
And S32, if the driving direction is a longitude direction and the longitude value is increased, sorting all the vehicle codes according to the longitude positioning information in an ascending order, and generating a sorting set in the driving direction.
It will be appreciated that if the direction of travel is longitudinal and the longitude value increases, the present solution would sort all vehicle codes in ascending order according to their longitude location information, generating a sorted set in the direction of travel.
Illustratively, the sorted set in the direction of travel may be {1, 2, 3, 4, 5 }. Here, the longitude-location information in {1, 2, 3, 4, 5} is sequentially larger.
When the longitude values increase in the longitudinal direction and the longitude positioning information sequentially increases, the vehicle corresponding to the number 5 in {1, 2, 3, 4, 5} is closest to the ending point B, and similarly, the vehicle corresponding to the number 1 is farthest from the ending point B.
And S33, if the driving direction is the longitude direction and the longitude value is decreased, sorting all the vehicle codes in descending order according to the longitude positioning information thereof, and generating a sorting set in the driving direction.
Contrary to step S32, if the driving direction is the longitudinal direction and the longitudinal value decreases, the present solution sorts all the vehicle codes in descending order according to their longitudinal positioning information, and generates a sorted set in the driving direction.
Illustratively, the sorted set in the direction of travel may be 5, 4, 3, 2, 1. Here, the longitude-positioning information in {5, 4, 3, 2, 1} is successively smaller.
When the longitude in the longitudinal direction decreases and the longitude positioning information decreases sequentially, the vehicle corresponding to number 1 in {5, 4, 3, 2, 1} is closest to the end point B, and similarly, the vehicle corresponding to number 5 is farthest from the end point B.
Secondly, a related sorting set is obtained according to the latitude direction, which specifically includes:
in other embodiments, S3 (determining the queuing order of each vehicle according to the positioning data and the driving direction corresponding to each vehicle code, and generating the sorted set in the driving direction) includes S34-S36:
and S34, when the driving direction is the latitude direction, latitude positioning information in the positioning data corresponding to each vehicle code is extracted.
It can be understood that the present solution is judged in the latitudinal direction, so that the latitudinal positioning information in the positioning data corresponding to each vehicle code is extracted.
And S35, if the driving direction is the latitude direction and the latitude value is increased, sorting all the vehicle codes in an ascending order according to the latitude positioning information to generate a sorting set in the driving direction.
It can be understood that if the driving direction is the latitude direction and the latitude value is increased, the scheme sorts all the vehicle codes in ascending order according to the latitude positioning information thereof, and generates a sorted set in the driving direction.
Illustratively, the sorted set in the direction of travel may be {1, 2, 3, 4, 5 }. Among these, the latitude positioning information in {1, 2, 3, 4, 5} is successively larger.
When the latitude position information increases in the latitude direction and the latitude values increase in order, the vehicle numbered 5 in {1, 2, 3, 4, 5} is closest to the ending point B, and similarly, the vehicle numbered 1 is farthest from the ending point B.
And S36, if the driving direction is the latitude direction and the latitude value is reduced, sorting all the vehicle codes in descending order according to the latitude positioning information to generate a sorting set in the driving direction.
Contrary to step S35, if the driving direction is the latitude direction and the latitude value decreases, the present solution sorts all the vehicle codes in descending order according to their latitude positioning information, and generates a sorted set in the driving direction.
Illustratively, the sorted set in the direction of travel may be 5, 4, 3, 2, 1. Wherein, the latitude positioning information in {5, 4, 3, 2, 1} becomes smaller in turn.
When the latitude is decreased in the latitude direction and the latitude positioning information is sequentially decreased, the vehicle numbered 1 in {5, 4, 3, 2, 1} is closest to the ending point B, and similarly, the vehicle numbered 5 is farthest from the ending point B.
It can be understood that the vehicle corresponding to the last code in the sorted set determined by the two methods is closest to the termination point B, and the vehicle corresponding to the first code is farthest from the termination point B.
And S4, extracting the first positioning data of the vehicle closest to the end point, the second positioning data of the vehicle closest to the start point and the third positioning data of the vehicle in the middle in the sorting set in real time.
This scheme will obtain 3 positioning data, be the first positioning data of the nearest vehicle of distance termination point in the sequencing set respectively to and the second positioning data of the nearest vehicle of distance starting point, and the third positioning data of the vehicle placed in the middle.
It can be understood that the scheme can acquire the positioning data of the head car, the tail car and the intermediate car.
In some embodiments, S4 (the real-time extraction of the first positioning data of the vehicle closest to the end point, the second positioning data of the vehicle closest to the start point, the third positioning data of the vehicle centered within the sorted set) includes S41-S44:
and S41, extracting the vehicle corresponding to the last vehicle code in the sequencing set as the vehicle closest to the end point, and determining the positioning data of the vehicle closest to the end point as the first positioning data.
It is understood that the vehicle corresponding to the last code in the sorted set determined in step S3 is closest to the termination point B, and the vehicle corresponding to the first code is farthest from the termination point B.
According to the scheme, the vehicle corresponding to the last vehicle code in the sequencing set is extracted as the vehicle closest to the end point, and then the positioning data of the vehicle closest to the end point is determined to be the first positioning data.
Illustratively, the vehicle closest to the end point corresponds to 5 of {1, 2, 3, 4, 5} or 1 of {5, 4, 3, 2, 1 }.
And S42, extracting the vehicle corresponding to the first vehicle code in the sorted set as the vehicle closest to the starting point, and determining the positioning data of the vehicle closest to the starting point as second positioning data.
According to the scheme, the vehicle corresponding to the first vehicle code in the sequencing set is extracted as the vehicle closest to the starting point, and then the positioning data of the vehicle closest to the starting point is determined as the second positioning data.
Illustratively, the vehicle closest to the starting point corresponds to 1 of {1, 2, 3, 4, 5} or 5 of {5, 4, 3, 2, 1 }.
And S43, if the number of the vehicle codes in the sorting set is judged to be an odd number, the positioning data corresponding to the vehicle code in the middle of the sorting set is taken as third positioning data.
Illustratively, if the number of the vehicle codes in {1, 2, 3, 4, 5} is 5, and 5 is an odd number, the present solution will use the positioning data corresponding to the vehicle code (3) centered in the sorted set as the third positioning data.
And S44, if the number of the vehicle codes in the sorting set is judged to be an even number, the positioning data corresponding to the 2 centered vehicle codes in the sorting set is taken as fourth positioning data, and the average value of the two fourth positioning data is taken as third positioning data.
For example, if the number of vehicle codes in {1, 2, 3, 4} is 4, and 4 is an even number, the present solution will use the positioning data corresponding to the vehicle codes (2 and 3) located in the middle of the sorted set as the fourth positioning data, and then use the average of the two fourth positioning data as the third positioning data.
It should be noted that this scheme is applicable to 3 and scenes more than 3, need 3 cars at least and can form the motorcade of this scheme, and to 2 and 1 scenes, because the vehicle is less, fine regulation and control between the driver need not this scheme and intervene the calculation.
And S5, calculating a first spacing distance and a second spacing distance according to the number of the vehicles and the types of the vehicles in the sorting set, wherein the first spacing distance is the required distance between the vehicle closest to the end point and the vehicle in the middle, and the second spacing distance is the required distance between the vehicle closest to the start point and the vehicle in the middle.
This scheme will calculate the required distance of the nearest vehicle of distance termination point and vehicle placed in the middle, obtain first spacing distance, will calculate the required distance of the nearest vehicle of distance starting point and vehicle placed in the middle, obtain the second spacing distance.
In some embodiments, S5 (the first separation distance and the second separation distance are calculated according to the number of vehicles and the types of vehicles in the sorted set, the first separation distance is a required distance between a vehicle closest to the end point and a centered vehicle, and the second separation distance is a required distance between a vehicle closest to the start point and the centered vehicle) includes S51:
and S51, acquiring the standard spacing distance corresponding to the vehicle type.
It is understood that the vehicles are of different types and the standard separation distance is different, for example, the standard separation distance for large trucks may be 1000 meters, and the standard separation distance for small trucks may be 600 meters.
And S52, comparing the number of the vehicles with a preset number to obtain a distance conversion coefficient, and calculating according to the distance conversion coefficient and the standard spacing distance to obtain the current spacing distance.
The distance conversion coefficient is larger, the number of vehicles indicating a fleet is larger, the number of vehicles is larger, the corresponding current spacing distance is larger, and therefore the current spacing distance can be calculated according to the distance conversion coefficient and the standard spacing distance, and the current spacing distance is obtained.
The current separation distance is calculated by the following formula,
wherein the content of the first and second substances,
for the purpose of the current separation distance,
as to the number of vehicles,
in order to be a predetermined number of the components,
the value is normalized for the quantity,
in order to convert the coefficients for the distance,
in order to be the standard separation distance,
is a preset constant value;
number of vehicles in the above formula
The larger the corresponding distance conversion coefficient
The larger the corresponding current separation distance
The larger.
Wherein the preset number
May be 2, preset constant value
May be 3.
And S53, acquiring the number of first intervals between the vehicle closest to the end point and the vehicle in the middle, and calculating according to the number of the first intervals, the current interval distance and the first distance weight value to obtain the first interval distance.
It should be noted that, the larger the number of the first spacing segments is, the larger the current spacing distance is, and the larger the corresponding first spacing distance is.
And S54, obtaining the number of second interval segments of the vehicle closest to the starting point and the vehicle in the middle, and calculating according to the number of the second interval segments, the current interval distance and the second distance weight value to obtain a second interval distance.
It should be noted that, the larger the number of the second spacing segments is, the larger the current spacing distance is, and the larger the corresponding second spacing distance is.
Wherein the first spacing distance and the second spacing distance are calculated by the following formula,
wherein the content of the first and second substances,
the first distance is a distance between the first and second electrodes,
the number of the first interval segments is the same as the number of the first interval segments,
is a first weight value of the distance,
for the second separation distance, the first separation distance,
the number of the second interval segments is,
is the second distance weight value.
In the above formula, the first distance weight value
And a second distance weight value
May be preset manually.
And S6, if the first positioning data and the third positioning data are judged not to meet the requirement of the first spacing distance, sending a deceleration scheduling prompt to the vehicle machine of the vehicle code corresponding to the first positioning data.
It can be understood that, if the first positioning data and the third positioning data do not satisfy the requirement of the first separation distance, which indicates that the distance between the head car and the intermediate car is too large, the scheme can send the deceleration scheduling prompt to the car machine of the car code corresponding to the first positioning data, so as to reduce the distance between the head car and the intermediate car, and enable the first positioning data and the third positioning data to satisfy the requirement of the first separation distance.
In some embodiments, S6 (if it is determined that the first positioning data and the third positioning data do not satisfy the requirement of the first separation distance, sending a deceleration scheduling reminder to a vehicle machine of a vehicle code corresponding to the first positioning data) includes:
and calculating according to the first positioning data and the third positioning data to obtain the first monitoring distance information, and if the first monitoring distance information is greater than the first spacing distance, sending a deceleration scheduling prompt to a vehicle machine of a vehicle code corresponding to the first positioning data. It can be understood that, this scheme can be calculated first locating data, third locating data, obtains first monitoring distance information, if first monitoring distance information is greater than first interval distance explains that the distance between first car and the middle car is too big, can send the speed reduction scheduling to the car machine of the vehicle code that first locating data corresponds and remind this moment to reduce the distance between first car and the middle car, make first locating data and third locating data satisfy the requirement of first interval distance.
The first monitoring distance information is calculated by the following formula,
wherein the content of the first and second substances,
in order to monitor the distance information for the first time,
as the longitude information in the first positioning data,
as the longitude information in the third positioning data,
as latitude information in the first positioning data,
for the latitude information in the third positioning data,
is a distance conversion value.
In the above formula, the first monitoring distance information can be obtained by using longitude difference and latitude difference
. Wherein the distance conversion value
May be manually preset.
And S7, if the second positioning data and the third positioning data are judged not to meet the requirement of the second spacing distance, sending a speed-up scheduling prompt to the vehicle machine with the vehicle code corresponding to the second positioning data.
It can be understood that, if the second positioning data and the third positioning data do not satisfy the requirement of the second spacing distance, it indicates that the distance between the tail car and the intermediate car is too large, and the speed-raising scheduling reminder can be sent to the car machine of the vehicle code corresponding to the second positioning data in the scheme, so as to reduce the distance between the tail car and the intermediate car, and the second positioning data and the third positioning data satisfy the requirement of the second spacing distance.
In some embodiments, S7 (if it is determined that the second positioning data and the third positioning data do not satisfy the requirement of the second separation distance, sending the speed-up scheduling reminder to the vehicle machine with the vehicle code corresponding to the second positioning data) includes:
and calculating according to the second positioning data and the third positioning data to obtain second monitoring distance information, and if the second monitoring distance information is greater than the second spacing distance, sending a speed-up scheduling prompt to a vehicle machine of a vehicle code corresponding to the second positioning data. It can be understood that this scheme can be calculated second positioning data, third positioning data, obtains second monitoring distance information, if second monitoring distance information is greater than second interval distance explains that the distance between trailer and the middle car is too big, can send the speed raising dispatch to the car machine of the vehicle code that the second positioning data corresponds and remind this moment to reduce the distance between trailer and the middle car, make second positioning data and third positioning data satisfy the requirement of second interval distance.
The second monitoring distance information is calculated by the following formula,
wherein the content of the first and second substances,
for the second monitoring distance information to be the second monitoring distance information,
is the longitude information in the second positioning data,
as the longitude information in the third positioning data,
for the latitude information in the second positioning data,
for the latitude information in the third positioning data,
is a distance conversion value.
In the above formula, the second monitoring distance information can be obtained by using longitude difference and latitude difference
. Wherein the distance conversion value
May be preset manually.
Referring to fig. 2, the schematic structural diagram of the intelligent scheduling system suitable for the cloud service of the fleet according to the present embodiment is shown, and the intelligent scheduling system suitable for the cloud service of the fleet includes:
a receiving module for receiving fleet configuration data of a user, the fleet configuration data including vehicle codes, starting points, and ending points of a plurality of vehicles;
the generation module is used for uploading positioning data to a fleet cloud server by a vehicle machine of each vehicle in the travelling process of a fleet, and after the fleet cloud server judges that the positioning data corresponding to each vehicle code is received in real time, the travelling direction is generated according to the starting point and the ending point;
the determining module is used for determining the queuing sequence of each vehicle according to the positioning data and the driving direction corresponding to each vehicle code and generating a sequencing set in the driving direction;
the extraction module is used for extracting first positioning data of a vehicle closest to an end point, second positioning data of a vehicle closest to a start point and third positioning data of a vehicle in the middle in the sequencing set in real time;
the calculation module is used for calculating a first spacing distance and a second spacing distance according to the number of vehicles and the types of the vehicles in the sorting set, wherein the first spacing distance is the required distance between the vehicle closest to the end point and the vehicle in the center, and the second spacing distance is the required distance between the vehicle closest to the start point and the vehicle in the center;
the first reminding module is used for sending a deceleration scheduling reminding to a vehicle machine of a vehicle code corresponding to the first positioning data if the first positioning data and the third positioning data are judged not to meet the requirement of the first spacing distance;
and the second reminding module is used for sending a speed-up scheduling reminding to the vehicle machine of the vehicle code corresponding to the second positioning data if the requirement of the second spacing distance is not met between the second positioning data and the third positioning data.
The apparatus in the embodiment shown in fig. 2 can be correspondingly used to perform the steps in the method embodiment shown in fig. 1, and the implementation principle and technical effect are similar, which are not described herein again.
The present invention also provides a storage medium having a computer program stored therein, the computer program being executable by a processor to implement the methods provided by the various embodiments described above.
The storage medium may be a computer storage medium or a communication medium. Communication media includes any medium that facilitates transfer of a computer program from one place to another. Computer storage media may be any available media that can be accessed by a general purpose or special purpose computer. For example, a storage medium is coupled to the processor such that the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an Application Specific Integrated Circuits (ASIC). Additionally, the ASIC may reside in user equipment. Of course, the processor and the storage medium may reside as discrete components in a communication device. The storage medium may be read-only memory (ROM), random-access memory (RAM), CD-ROMs, magnetic tapes, floppy disks, optical data storage devices, and the like.
The present invention also provides a program product comprising execution instructions stored in a storage medium. The at least one processor of the device may read the execution instructions from the storage medium, and the execution of the execution instructions by the at least one processor causes the device to implement the methods provided by the various embodiments described above.
In the above embodiments of the terminal or the server, it should be understood that the Processor may be a Central Processing Unit (CPU), other general-purpose processors, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor, or in a combination of hardware and software modules.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. An intelligent scheduling method suitable for a fleet cloud service is characterized by comprising the following steps:
receiving fleet configuration data for a user, the fleet configuration data including vehicle codes, starting points, and ending points for a plurality of vehicles;
in the running process of a motorcade, the vehicle machine of each vehicle uploads positioning data to a motorcade cloud server, and the motorcade cloud server generates a running direction according to the starting point and the ending point after judging that the positioning data corresponding to each vehicle code is received in real time;
determining the queuing sequence of each vehicle according to the positioning data and the driving direction corresponding to each vehicle code, and generating a sequencing set in the driving direction;
extracting first positioning data of a vehicle closest to the end point, second positioning data of a vehicle closest to the start point and third positioning data of a vehicle centered in the sequencing set in real time;
calculating a first spacing distance and a second spacing distance according to the number of vehicles and the types of the vehicles in the sorting set, wherein the first spacing distance is the required distance between the vehicle closest to the end point and the vehicle in the middle, and the second spacing distance is the required distance between the vehicle closest to the start point and the vehicle in the middle;
if the first positioning data and the third positioning data are judged not to meet the requirement of the first spacing distance, sending a deceleration scheduling prompt to a vehicle machine of a vehicle code corresponding to the first positioning data;
and if the second positioning data and the third positioning data are judged not to meet the requirement of the second spacing distance, sending a speed-up scheduling prompt to the vehicle machine of the vehicle code corresponding to the second positioning data.
2. The intelligent scheduling method for the cloud services of the fleet according to claim 1,
in the driving process of the fleet, the vehicle machine of each vehicle uploads positioning data to the fleet cloud server, and after the fleet cloud server judges that the positioning data corresponding to each vehicle code is received in real time, the fleet cloud server generates a driving direction according to the starting point and the end point, including:
acquiring a starting coordinate of a starting point and an ending coordinate of an ending point, wherein the starting coordinate comprises a starting longitude and a starting latitude, and the ending coordinate comprises an ending longitude and an ending latitude;
comparing the starting longitude with the ending longitude to obtain a longitude direction, wherein the longitude direction is a longitude value increase or a longitude value decrease;
comparing the starting latitude with the ending latitude to obtain a latitude direction, wherein the latitude direction is latitude value increase or latitude value decrease;
and obtaining the driving direction of the motorcade according to any one or more of the longitude direction and the latitude direction.
3. The intelligent scheduling method for the cloud services of the fleet according to claim 2,
determining the queuing sequence of each vehicle according to the positioning data and the driving direction corresponding to each vehicle code, and generating a sequencing set in the driving direction, wherein the sequencing set comprises:
when the driving direction is the longitude direction, longitude positioning information in positioning data corresponding to each vehicle code is extracted;
if the driving direction is a longitude direction and the longitude value is increased, sorting all vehicle codes in an ascending order according to the longitude positioning information of the vehicle codes to generate a sorting set in the driving direction;
and if the driving direction is the longitude direction and the longitude value is decreased, sorting all the vehicle codes in descending order according to the longitude positioning information thereof, and generating a sorting set in the driving direction.
4. The intelligent scheduling method for the cloud services of the fleet according to claim 2,
the method comprises the following steps of determining the queuing sequence of each vehicle according to the positioning data and the driving direction corresponding to each vehicle code, and generating a sorting set in the driving direction, wherein the sorting set comprises:
when the driving direction is the latitude direction, latitude positioning information in positioning data corresponding to each vehicle code is extracted;
if the driving direction is a latitude direction and the latitude value is increased, sequencing all vehicle codes in an ascending order according to the latitude positioning information of the vehicle codes to generate a sequencing set in the driving direction;
and if the driving direction is the latitude direction and the latitude value is reduced, sorting all the vehicle codes in a descending order according to the latitude positioning information of the vehicle codes, and generating a sorting set in the driving direction.
5. The intelligent scheduling method suitable for the fleet cloud service according to any one of claims 3 or 4,
the real-time extraction of the first positioning data of the vehicle closest to the end point, the second positioning data of the vehicle closest to the start point and the third positioning data of the vehicle in the middle in the sequencing set comprises the following steps:
extracting a vehicle corresponding to the last vehicle code in the sequencing set as a vehicle closest to the end point, and determining positioning data of the vehicle closest to the end point as first positioning data;
extracting a vehicle corresponding to a first vehicle code in the sequencing set as a vehicle closest to the starting point, and determining positioning data of the vehicle closest to the starting point as second positioning data;
if the number of the vehicle codes in the sorting set is judged to be an odd number, positioning data corresponding to the vehicle codes in the middle of the sorting set is taken as third positioning data;
if the number of the vehicle codes in the sorting set is judged to be an even number, the positioning data corresponding to 2 centered vehicle codes in the sorting set is used as fourth positioning data, and the average value of the two fourth positioning data is used as third positioning data.
6. The intelligent scheduling method suitable for the fleet cloud service according to claim 5,
the calculating according to the number of vehicles and the types of vehicles in the sorting set to obtain a first spacing distance and a second spacing distance, wherein the first spacing distance is a required distance between a vehicle closest to the end point and a centered vehicle, and the second spacing distance is a required distance between a vehicle closest to the start point and the centered vehicle, and the method comprises the following steps:
acquiring a standard spacing distance corresponding to the vehicle type;
comparing the number of the vehicles with a preset number to obtain a distance conversion coefficient, and calculating according to the distance conversion coefficient and a standard spacing distance to obtain a current spacing distance;
the current separation distance is calculated by the following formula,
wherein the content of the first and second substances,
for the purpose of the current separation distance,
as to the number of vehicles,
in order to be a predetermined number of the components,
the value is normalized for the number of bits,
in order to convert the coefficients for the distance,
in order to be the standard separation distance,
is a preset constant value;
acquiring the number of first interval sections of a vehicle closest to an end point and a vehicle in the middle, and calculating according to the number of the first interval sections, the current interval distance and a first distance weight value to obtain a first interval distance;
and obtaining the number of second interval segments of the vehicle closest to the starting point and the vehicle in the middle, and calculating according to the number of the second interval segments, the current interval distance and a second distance weight value to obtain a second interval distance.
7. The intelligent scheduling method for the fleet cloud service according to claim 6, wherein the first separation distance and the second separation distance are calculated by the following formula,
wherein the content of the first and second substances,
is a first distance of separation, and is,
the number of the first interval segments is the same as the number of the first interval segments,
is a first weight value of the distance,
for the second separation distance, the first separation distance,
the number of the second interval segments is,
is the second distance weight value.
8. The intelligent scheduling method suitable for the fleet cloud service according to claim 7,
if the first positioning data and the third positioning data are judged not to meet the requirement of the first spacing distance, a deceleration scheduling prompt is sent to a vehicle machine of a vehicle code corresponding to the first positioning data, and the method comprises the following steps:
calculating according to the first positioning data and the third positioning data to obtain first monitoring distance information, and if the first monitoring distance information is greater than the first spacing distance, sending a deceleration scheduling prompt to a vehicle machine of a vehicle code corresponding to the first positioning data;
the first monitoring distance information is calculated by the following formula,
wherein the content of the first and second substances,
in order to monitor the distance information for the first time,
as the longitude information in the first positioning data,
as the longitude information in the third positioning data,
as latitude information in the first positioning data,
for the latitude information in the third positioning data,
is a distance conversion value.
9. The intelligent scheduling method suitable for the fleet cloud service according to claim 7,
if judge unsatisfied second interval distance's requirement between second positioning data, the third positioning data, then send the scheduling of speeding up to the car machine of the vehicle code that corresponds with the second positioning data and remind, include:
calculating according to the second positioning data and the third positioning data to obtain second monitoring distance information, and if the second monitoring distance information is greater than the second spacing distance, sending a speed-up scheduling prompt to a vehicle machine with a vehicle code corresponding to the second positioning data;
the second monitoring distance information is calculated by the following formula,
wherein the content of the first and second substances,
for the second monitored-distance information to be,
is the longitude information in the second positioning data,
as the longitude information in the third positioning data,
for the latitude information in the second positioning data,
for the latitude information in the third positioning data,
is a distance conversion value.
10. The utility model provides an intelligent scheduling system suitable for cloud of vehicle team service which characterized in that includes:
a receiving module for receiving fleet configuration data of a user, the fleet configuration data including vehicle codes, starting points, and ending points of a plurality of vehicles;
the generation module is used for uploading positioning data to a fleet cloud server by a vehicle machine of each vehicle in the running process of a fleet, and the fleet cloud server generates a running direction according to the starting point and the end point after judging that the positioning data corresponding to each vehicle code is received in real time;
the determining module is used for determining the queuing sequence of each vehicle according to the positioning data and the driving direction corresponding to each vehicle code and generating a sequencing set in the driving direction;
the extraction module is used for extracting first positioning data of a vehicle closest to the end point, second positioning data of the vehicle closest to the start point and third positioning data of a vehicle centered in the sequencing set in real time;
the calculation module is used for calculating a first spacing distance and a second spacing distance according to the number of vehicles and the types of the vehicles in the sorting set, wherein the first spacing distance is the required distance between the vehicle closest to the end point and the vehicle in the center, and the second spacing distance is the required distance between the vehicle closest to the start point and the vehicle in the center;
the first reminding module is used for sending a deceleration scheduling reminding to a vehicle machine of a vehicle code corresponding to the first positioning data if the first positioning data and the third positioning data are judged not to meet the requirement of the first spacing distance;
and the second reminding module is used for sending a speed-up scheduling reminding to the vehicle machine of the vehicle code corresponding to the second positioning data if the requirement of the second spacing distance is not met between the second positioning data and the third positioning data.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210874496.XA CN114937352B (en) | 2022-07-25 | 2022-07-25 | Intelligent scheduling method and system suitable for fleet cloud service |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210874496.XA CN114937352B (en) | 2022-07-25 | 2022-07-25 | Intelligent scheduling method and system suitable for fleet cloud service |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114937352A true CN114937352A (en) | 2022-08-23 |
| CN114937352B CN114937352B (en) | 2022-10-04 |
Family
ID=82868950
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210874496.XA Active CN114937352B (en) | 2022-07-25 | 2022-07-25 | Intelligent scheduling method and system suitable for fleet cloud service |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114937352B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116823088A (en) * | 2023-07-17 | 2023-09-29 | 中国人民解放军陆军勤务学院 | Plateau food transportation method and device based on data processing |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100256835A1 (en) * | 2009-04-06 | 2010-10-07 | Gm Global Technology Operations, Inc. | Fail-safe speed profiles for cooperative autonomous vehicles |
| CN105160865A (en) * | 2015-08-05 | 2015-12-16 | 深圳市航盛电子股份有限公司 | Vehicle formation driving control system and method |
| CN111433700A (en) * | 2017-12-08 | 2020-07-17 | 克诺尔商用车制动系统有限公司 | Method for moving a vehicle fleet on the basis of a predefinable overall operating strategy associated with the vehicle fleet |
| CN111613044A (en) * | 2019-02-22 | 2020-09-01 | 青岛海信网络科技股份有限公司 | Fleet following early warning method and device and electronic equipment |
| CN112164217A (en) * | 2020-09-14 | 2021-01-01 | 南京航空航天大学 | Automatic driving vehicle queue running management system and control method thereof |
-
2022
- 2022-07-25 CN CN202210874496.XA patent/CN114937352B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100256835A1 (en) * | 2009-04-06 | 2010-10-07 | Gm Global Technology Operations, Inc. | Fail-safe speed profiles for cooperative autonomous vehicles |
| CN105160865A (en) * | 2015-08-05 | 2015-12-16 | 深圳市航盛电子股份有限公司 | Vehicle formation driving control system and method |
| CN111433700A (en) * | 2017-12-08 | 2020-07-17 | 克诺尔商用车制动系统有限公司 | Method for moving a vehicle fleet on the basis of a predefinable overall operating strategy associated with the vehicle fleet |
| CN111613044A (en) * | 2019-02-22 | 2020-09-01 | 青岛海信网络科技股份有限公司 | Fleet following early warning method and device and electronic equipment |
| CN112164217A (en) * | 2020-09-14 | 2021-01-01 | 南京航空航天大学 | Automatic driving vehicle queue running management system and control method thereof |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116823088A (en) * | 2023-07-17 | 2023-09-29 | 中国人民解放军陆军勤务学院 | Plateau food transportation method and device based on data processing |
| CN116823088B (en) * | 2023-07-17 | 2024-01-30 | 中国人民解放军陆军勤务学院 | Plateau food transportation method and device based on data processing |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114937352B (en) | 2022-10-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110189006B (en) | Scheduling method and device for vehicle, computer equipment and storage medium thereof | |
| CN113160602B (en) | Intelligent bus dispatching simulation system | |
| CN109410568B (en) | Get-off site presumption method and system based on user portrait and transfer rule | |
| CN114743401B (en) | Data visualization bus dispatching management platform based on bus digital transformation | |
| CN114937352B (en) | Intelligent scheduling method and system suitable for fleet cloud service | |
| WO2023274071A1 (en) | Driving behavior monitoring method and apparatus, electronic device, and storage medium | |
| CN112083456B (en) | Freight state identification method, device, equipment and storage medium | |
| WO2022116447A1 (en) | Bus dispatching method and apparatus, and computer device and medium | |
| CN108389392A (en) | A kind of traffic accident responsibility identification system based on machine learning | |
| CN111583713A (en) | Vehicle driving early warning method and device | |
| CN114049786A (en) | Real-time bus dispatching duty dispatching method, system and equipment based on passenger flow data | |
| CN113592272A (en) | Dispatching method for public transport and tour bus | |
| CN117391894A (en) | Patrol robot collaborative violation evidence obtaining method, system and medium | |
| CN111243261A (en) | Bus lane borrowing use scheduling method and system | |
| CN108241866A (en) | A kind of method, apparatus guided to driving behavior and vehicle | |
| CN112116241B (en) | Intelligent public traffic scheduling method | |
| CN116205460A (en) | Bus stop announcement generation method, device and application based on passenger portrait and ETA data | |
| CN115620525A (en) | Short-time traffic passenger demand prediction method based on time-varying dynamic Bayesian network | |
| CN113022576B (en) | Driving style analysis method, system and device for different driving task stages | |
| CN114266490A (en) | Efficient and accurate comprehensive transportation network security risk point identification method | |
| CN113298350A (en) | Artificial intelligence-based bus comprehensive supervision and service system | |
| CN113447037A (en) | Stroke yaw detection method and device | |
| CN112037515B (en) | DNN-based bus detailed scheduling method | |
| CN117592788B (en) | Bus running risk identification method and device | |
| CN114596708B (en) | Intelligent scheduling system, method, apparatus and computer program product |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |