Background
With the development of sensor technology and the gradual falling of the idea of interconnection of everything, the internet of things and the application technology thereof are gradually replacing the traditional non-internet of things network, and become a new form of internet interaction.
With the gradual deepening of the idea of interconnection of everything, the internet of things is regarded as another wave of information technology revolution after the internet. The industrial value brought by the Internet of things is 30 times larger than that of the Internet, and the Internet of things becomes the information industry service of the next trillion-element level. The first industrial wave represented by a computer and the second industrial wave represented by the internet and a mobile communication network have passed, and now face the third industrial wave against the background of the internet of things. Various intelligent equipment applications and character sensing are gradually popularized to all aspects of society. The internet of things is about to replace the internet, and the internet is about to disappear, and the internet is not a trend but a reality.
The Internet of things is an important component of a new generation of information technology and is also an important development stage of the information era. The Internet of things (IoT) is known as Internet of things (IoT), and as the name suggests, the Internet of things is the Internet to which things are connected. The internet of things utilizes communication technologies such as local networks or the internet to connect sensors, controllers, machines, personnel, objects and the like together in a new mode to form networks for people to objects and objects to link with each other and realize informatization, remote management control and intellectualization.
Along with the development of the internet of things, the short boards faced by the internet of things are more obvious. What are the internet of things faced with? First, personal privacy and security issues are critical. During the use of the RFID, the embedding of personal information may cause partial information leakage, and the serious point may even threaten personal property and life safety, which will become a key of future technical innovation. Secondly, the cost is high, and the popularization difficulty is high. In the initial stage of the development of the internet of things, part of chips and equipment in China come from abroad, and the expensive cost of the chips and the equipment greatly improves the difficulty of popularization. And thirdly, the Internet of things belongs to a novel industry, and no uniform industry standard exists. The introduction of the internet of things has been so far for less than 20 years that china and even the world have no unified industrial standard, and even the definition of the internet of things has produced a plurality of versions. And fourthly, the core technology and the independent research and development consciousness are lacked. For some core technologies of the internet of things, such as the RFID technology and the like, the method is too dependent on foreign countries and has no independent intellectual property.
Among various basic applications of the Internet of things, unmanned driving in the field of automobile manufacturing particularly highlights the activity of the unmanned driving.
The definition of unmanned technology in the field is relatively mature. Generally, the unmanned technology is a complex of multi-leading-edge subjects such as sensors, computers, artificial intelligence, communication, navigation positioning, pattern recognition, machine vision, intelligent control and the like. An unmanned vehicle, also called an automatic vehicle or a wheeled mobile robot, is an unmanned ground vehicle for transporting power. The ideal unmanned automobile can drive from the place A to the place B without human operation, and the unmanned automobile can be completed by the machine without regard to the complicated environment and the severe weather on the way. The core of the unmanned automobile lies in the unmanned technology, and if the automobile industry is the crown of manufacturing industry, the unmanned technology is the pearl on the crown. The unmanned vehicle can be realized by multi-door technology integration, and the unmanned vehicle is not a single new technology, wherein the single new technology comprises radar, laser radar, a camera, a GPS, computer vision, a decision system, an operating system, a high-precision map, real-time positioning, mechanical control, energy consumption heat dissipation management and the like. Although unmanned automobiles appear to be highly fantastic, in reality the illusion is coming into reality. Since the 50 s of the 20 th century, ground unmanned vehicle research was conducted in western developed countries and a series of achievements were achieved. It can be summarized here as three main stages. In the first stage, before the 80's of the 20 th century, ground driverless vehicles were focused on remote control driving, subject to lags in the development of key technologies such as hardware technology, graphics processing, and data fusion. In the second phase, after the 80's of the 20 th century, ground unmanned vehicles were further developed with the breakthrough of autonomous vehicle technology and other related technologies, emerging as diverse autonomous and semi-autonomous mobile platforms. However, due to the limitations of the performances of key components such as a positioning navigation device, an obstacle recognition sensor, a calculation control processor and the like, the unmanned vehicle at that time realizes autonomous driving to a certain extent, but has low driving speed and weak environmental adaptability. In the third stage, since the 90 s of the 20 th century, semi-automatic ground unmanned vehicles have been further developed due to breakthroughs in the technologies of computers, artificial intelligence, robot control and the like. Part of the ground unmanned vehicles participate in military actual combat, and the combat capability of the ground unmanned vehicles is verified, so that people can see the development prospect of the ground unmanned vehicles, the enthusiasm of various countries for researching and developing the ground unmanned vehicles is greatly stimulated, and the research climax is also promoted. Driven by military needs and incentives for technological development, countries in the united states, germany, italy, etc. have been leading around the world in terms of unmanned vehicle technology. After the 21 st century, with the great improvement of physical computing capacity, the rapid development of dynamic vision technology and the rapid development of artificial intelligence technology, the key technologies of route navigation, obstacle avoidance, burst decision and the like are solved, and the unmanned driving technology makes a breakthrough progress.
The invention provides an intelligent management system of an unmanned delivery vehicle based on the technology of Internet of things and an implementation method thereof, wherein the driving information and the delivery information of the unmanned delivery vehicle are acquired by arranging an Internet of things acquirer corresponding to a plurality of unmanned delivery vehicles, the acquired information is sent to a regional management node in each region, the driving quota management of the unmanned delivery vehicle is realized on an intelligent system management layer of the unmanned delivery vehicle through regional information integration and data statistics of the driving working intensity of the unmanned delivery vehicle, the comprehensive system management and the issuing of related operation instructions are carried out on an intelligent management system platform end of the unmanned delivery vehicle, the network slice management of the unmanned delivery vehicle is implemented through the intelligent management of the unmanned delivery vehicle with a four-layer framework, the differentiated management instructions are arranged in each region, and the intelligent management system platform end of the unmanned delivery vehicle is based on an instruction pool management mode of the intelligent management system platform end of the unmanned delivery vehicle, the comprehensive management and control capability of the system is improved, and the better performance level of the unmanned distribution vehicle management system is achieved.
Disclosure of Invention
The invention aims to provide an intelligent management system of an unmanned distribution vehicle based on the technology of the Internet of things and an implementation method thereof.
In order to achieve the purpose, the technical scheme of the invention is as follows:
an intelligent management system of an unmanned distribution vehicle based on internet of things technology, the system comprises:
the system comprises a plurality of unmanned distribution vehicles, a plurality of remote monitoring devices and a plurality of remote monitoring devices, wherein each unmanned distribution vehicle is provided with an Internet of things collector and is used for collecting driving information and distribution information of the corresponding unmanned distribution vehicle;
the distribution information at least comprises an article type ID and an article counting number ID which are distributed by each unmanned distribution vehicle, and the distribution information is directly sent to an intelligent management system platform end of the unmanned distribution vehicle;
the system comprises a plurality of regional logistics management nodes, a plurality of remote management nodes and a plurality of remote management nodes, wherein each regional logistics management node is used for determining a plurality of unmanned distribution vehicles belonging to the region based on the region identifications of the unmanned distribution vehicles in the region and managing the unmanned distribution vehicles in the region;
each regional logistics management node also collects the running information of a plurality of unmanned distribution vehicles in the region based on the Internet of things; determining the area running quota consumption rate M (k) based on the collected running information of the unmanned distribution vehicles in the area, wherein k is the area identification of each area;
the plurality of regional logistics management nodes also transmit regional driving quota consumption rates M (k) to an intelligent management layer of the unmanned delivery vehicle, wherein k is a regional identifier of each region;
the intelligent system management layer of the unmanned delivery vehicle is used for receiving the regional running quota consumption rates M (k) transmitted to the intelligent management system regulation layer of the unmanned delivery vehicle by the plurality of regional logistics management nodes, sequencing the regional running quota consumption rates M (k), and acquiring two regions with the highest and the next highest regional running quota consumption rates M (k) and the regional logistics management nodes corresponding to the two regions;
the intelligent system management layer of the unmanned delivery vehicle further requests a first management instruction to the intelligent management system platform end of the unmanned delivery vehicle based on the acquired highest region of the region running quota consumption rate M (k) and the region logistics management node P1 corresponding to the highest region, and receives the first management instruction sent by the intelligent management system platform end of the unmanned delivery vehicle;
and the number of the first and second groups,
requesting a second management instruction to an intelligent unmanned delivery vehicle management system platform end and receiving the second management instruction sent by the intelligent unmanned delivery vehicle management system platform end based on the acquired regional driving quota consumption rate M (k) secondary high region and a regional logistics management node P2 corresponding to the regional driving quota consumption rate M (k);
the first management instruction is from a first management instruction pool of an intelligent management system platform end of the unmanned distribution vehicle, and the second management instruction is from a second management instruction pool of the intelligent management system platform end of the unmanned distribution vehicle; the first management instruction is used for controlling quota adjustment or area control of a highest area of an area driving quota consumption rate M (k), and the second management instruction is used for controlling quota adjustment or area control of a second highest area of the area driving quota consumption rate M (k);
the intelligent management system platform end of the unmanned delivery vehicle is used for executing the intelligent management system management of the unmanned delivery vehicle based on the uploaded driving information and delivery information of the unmanned delivery vehicle and the acquired regional driving quota consumption rate M (k), the highest region and the corresponding regional logistics management node P1 thereof, the acquired regional driving quota consumption rate M (k), the next highest region and the corresponding regional logistics management node P2 thereof;
the intelligent management system platform end of the unmanned distribution vehicle is also used for storing and updating the first management instruction pool and the second management instruction pool, and selecting the first management instruction and the second management instruction according to a specific strategy based on an instruction request of a management layer of the intelligent management system of the unmanned distribution vehicle.
Preferably, the plurality of unmanned delivery vehicles further store their own unmanned delivery vehicle IDs and zone identifications.
Preferably, the driving information of the unmanned delivery vehicle at least includes:
the distance traveled by the unmanned distribution vehicle in an operation cycle;
the unmanned delivery vehicle is allowed to run for a quota total distance in an operation period;
the proportion K1 of the distance traveled by the unmanned delivery vehicle in an operation period to the total allowed quota distance traveled by the unmanned delivery vehicle;
the running weight reference value W1 of the unmanned delivery vehicle.
Preferably, the intelligent management system platform end of the unmanned delivery vehicle is configured to execute intelligent management system management of the unmanned delivery vehicle based on the uploaded driving information and delivery information of the unmanned delivery vehicle and the obtained regional driving quota consumption rate m (k), the highest region and the corresponding regional logistics management node P1 thereof, the obtained regional driving quota consumption rate m (k), the next highest region and the corresponding regional logistics management node P2 thereof, and at least includes: and sending a corresponding first management instruction and a second management instruction to an intelligent system management layer of the unmanned delivery vehicle.
Preferably, the internet of things collector is further in communication with internet of things collectors installed on other nearby unmanned distribution vehicles, so that the driving information and the distribution information of the unmanned distribution vehicles collected by the internet of things collector can be relayed and forwarded.
Meanwhile, the invention discloses an implementation method of the intelligent management system of the unmanned distribution vehicle based on the technology of the Internet of things, and the method comprises the following steps:
the method comprises the following steps: operating a plurality of unmanned distribution vehicles and an Internet of things collector installed on each unmanned distribution vehicle, and collecting driving information and distribution information of the corresponding unmanned distribution vehicles;
the distribution information at least comprises an article type ID and an article counting number ID which are distributed by each unmanned distribution vehicle, and the distribution information is directly sent to an intelligent management system platform end of the unmanned distribution vehicle;
step two: operating a plurality of regional logistics management nodes, determining a plurality of unmanned distribution vehicles belonging to the region based on the region identifications of the unmanned distribution vehicles in the region, and managing the unmanned distribution vehicles in the region;
each regional logistics management node also collects the running information of a plurality of unmanned distribution vehicles in the region based on the Internet of things; determining the area running quota consumption rate M (k) based on the collected running information of the unmanned distribution vehicles in the area, wherein k is the area identification of each area;
the plurality of regional logistics management nodes also transmit regional driving quota consumption rates M (k) to an intelligent management layer of the unmanned delivery vehicle, wherein k is a regional identifier of each region;
step three: operating an unmanned delivery vehicle intelligent system management layer to receive the regional driving quota consumption rates M (k) transmitted to an unmanned delivery vehicle intelligent management system adjustment layer by the plurality of regional logistics management nodes, sequencing the regional driving quota consumption rates M (k), and acquiring two highest and second highest regional driving quota consumption rates M (k) and the corresponding regional logistics management nodes thereof; the intelligent system management layer of the unmanned delivery vehicle further requests a first management instruction to the intelligent management system platform end of the unmanned delivery vehicle based on the acquired region running quota consumption rate M (k) and the region logistics management node P1 corresponding to the highest region, and receives the first management instruction sent by the intelligent management system platform end of the unmanned delivery vehicle;
and the number of the first and second groups,
requesting a second management instruction to an intelligent unmanned delivery vehicle management system platform end and receiving the second management instruction sent by the intelligent unmanned delivery vehicle management system platform end based on the acquired regional driving quota consumption rate M (k) secondary high region and a regional logistics management node P2 corresponding to the regional driving quota consumption rate M (k);
the first management instruction is from a first management instruction pool of an intelligent management system platform end of the unmanned distribution vehicle, and the second management instruction is from a second management instruction pool of the intelligent management system platform end of the unmanned distribution vehicle; the first management instruction is used for controlling quota adjustment or area control of a highest area of an area driving quota consumption rate M (k), and the second management instruction is used for controlling quota adjustment or area control of a second highest area of the area driving quota consumption rate M (k);
step four: operating the intelligent management system platform of the unmanned delivery vehicle to execute the management of the intelligent management system of the unmanned delivery vehicle based on the uploaded driving information and the distribution information of the unmanned delivery vehicle and the acquired regional driving quota consumption rate M (k), the highest region and the corresponding regional logistics management node P1 thereof, the acquired regional driving quota consumption rate M (k), the next highest region and the corresponding regional logistics management node P2 thereof; the intelligent management system platform end of the unmanned distribution vehicle is further used for storing and updating the first management instruction pool and the second management instruction pool, and selecting the first management instruction and the second management instruction according to a specific strategy based on an instruction request of a management layer of the intelligent management system of the unmanned distribution vehicle.
Preferably, the plurality of unmanned delivery vehicles further store their own unmanned delivery vehicle IDs and zone identifications.
Preferably, the driving information of the unmanned delivery vehicle at least includes:
the distance traveled by the unmanned distribution vehicle in an operation cycle;
the unmanned delivery vehicle is allowed to run for a quota total distance in an operation period;
the proportion K1 of the distance traveled by the unmanned delivery vehicle in an operation period to the total allowed quota distance traveled by the unmanned delivery vehicle;
the running weight reference value W1 of the unmanned delivery vehicle.
Preferably, the intelligent management system platform end of the unmanned delivery vehicle is configured to execute intelligent management system management of the unmanned delivery vehicle based on the uploaded driving information and delivery information of the unmanned delivery vehicle and the obtained regional driving quota consumption rate m (k), the highest region and the corresponding regional logistics management node P1 thereof, the obtained regional driving quota consumption rate m (k), the next highest region and the corresponding regional logistics management node P2 thereof, and at least includes: and sending a corresponding first management instruction and a second management instruction to an intelligent system management layer of the unmanned delivery vehicle.
Preferably, the internet of things collector is further in communication with internet of things collectors installed on other nearby unmanned distribution vehicles, so that the driving information and the distribution information of the unmanned distribution vehicles collected by the internet of things collector can be relayed and forwarded.
The invention provides an intelligent management system of an unmanned delivery vehicle based on the technology of Internet of things and an implementation method thereof, wherein the driving information and the delivery information of the unmanned delivery vehicle are acquired by arranging an Internet of things acquirer corresponding to a plurality of unmanned delivery vehicles, the acquired information is sent to a regional management node in each region, the driving quota management of the unmanned delivery vehicle is realized on an intelligent system management layer of the unmanned delivery vehicle through regional information integration and data statistics of the driving working intensity of the unmanned delivery vehicle, the comprehensive system management and the issuing of related operation instructions are carried out on an intelligent management system platform end of the unmanned delivery vehicle, the network slice management of the unmanned delivery vehicle is implemented through the intelligent management of the unmanned delivery vehicle with a four-layer framework, the differentiated management instructions are arranged in each region, and the intelligent management system platform end of the unmanned delivery vehicle is based on an instruction pool management mode of the intelligent management system platform end of the unmanned delivery vehicle, the comprehensive management and control capability of the system is improved, and the better performance level of the unmanned distribution vehicle management system is achieved.
Detailed Description
The following describes several embodiments and advantageous effects of the internet of things technology-based unmanned delivery vehicle intelligent management system and the implementation method thereof claimed by the present invention in detail, so as to facilitate more detailed examination and decomposition of the present invention.
For better understanding of the technical solutions of the present invention, the following detailed descriptions of the embodiments of the present invention are provided with reference to the accompanying drawings.
It should be understood that the described embodiments are only some embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be understood that the term "and/or" as used herein is merely one type of association that describes 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. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
It should be understood that although the terms first, second, etc. may be used in embodiments of the invention to describe methods and corresponding apparatus, these keywords should not be limited to these terms. These terms are only used to distinguish keywords from each other. For example, the first management instruction and the like may also be referred to as the second management instruction, and similarly, the second management instruction and the like may also be referred to as the first management instruction, without departing from the scope of the embodiments of the present invention.
The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrases "if determined" or "if detected (a stated condition or event)" may be interpreted as "when determined" or "in response to a determination" or "when detected (a stated condition or event)" or "in response to a detection (a stated condition or event)", depending on the context.
As shown in the accompanying drawings 1-4 of the specification, the accompanying drawings 1-4 of the specification are one of the embodiments of the intelligent management system for the unmanned delivery vehicle based on the internet of things technology and the specific inter-module relation thereof, the system includes:
the system comprises a plurality of unmanned distribution vehicles, a plurality of remote monitoring devices and a plurality of remote monitoring devices, wherein each unmanned distribution vehicle is provided with an Internet of things collector and is used for collecting driving information and distribution information of the corresponding unmanned distribution vehicle;
the distribution information at least comprises an article type ID and an article counting number ID which are distributed by each unmanned distribution vehicle, and the distribution information is directly sent to an intelligent management system platform end of the unmanned distribution vehicle;
the system comprises a plurality of regional logistics management nodes, a plurality of remote management nodes and a plurality of remote management nodes, wherein each regional logistics management node is used for determining a plurality of unmanned distribution vehicles belonging to the region based on the region identifications of the unmanned distribution vehicles in the region and managing the unmanned distribution vehicles in the region;
each regional logistics management node also collects the running information of a plurality of unmanned distribution vehicles in the region based on the Internet of things; determining the area running quota consumption rate M (k) based on the collected running information of the unmanned distribution vehicles in the area, wherein k is the area identification of each area;
as a stackable embodiment, each unmanned delivery vehicle is preset with the operating mileage of a specific quota by the system, and when the quota expires without being changed, redistributed, updated, and the like, the unmanned delivery vehicle sleeps or waits. For example, the operating mileage of the unmanned delivery vehicle a is preset with a 20KM quota, which represents the unmanned delivery persistent operation capability of the corresponding unmanned delivery vehicle in the state of the internet of things, or represents the unmanned optimal loss-resistant overhead capability of the corresponding unmanned delivery vehicle in the state of the internet of things, that is, after 20KM is operated, the operation of the unmanned delivery vehicle is suspended, and after a certain period of time is waited, the quota is reallocated, so that the corresponding unmanned delivery vehicle can maintain the optimal depreciation loss, the loss-resistant power of the unmanned delivery vehicle is improved, and the fault replacement rate and the loss depreciation period of the unmanned delivery vehicle in the system are reduced.
As a stackable embodiment, each regional logistics management node further acquires driving information of a plurality of unmanned distribution vehicles in the region based on the internet of things; and determining the regional driving quota consumption rate M based on the collected driving information of the plurality of unmanned distribution vehicles in the region, specifically: the logistics management nodes in each area count the number cout of the unmanned delivery vehicles in the area, collect the driving information sent by each unmanned delivery vehicle, and calculate the quota consumption value comsu (i) of the unmanned delivery vehicle based on the distance traveled by each unmanned delivery vehicle in one operation period, the quota total distance allowed to be traveled by the unmanned delivery vehicle in one operation period, the proportion K1 of the distance traveled by the unmanned delivery vehicle in one operation period to the quota total distance allowed to be traveled, and the driving weight reference value W1 of the unmanned delivery vehicle, wherein i is the unmanned delivery vehicle ID of the unmanned delivery vehicle, and as a stackable embodiment, comsu (i) is K1W 1. Subsequently, the regional logistics management node accumulates regional quota consumption values comsu (i) of all the unmanned vehicles in the region to obtain regional driving quota consumption rate M, that is, M is (Σ comsu (i), i is the ID of the unmanned vehicle in the region.
As a stackable embodiment, the one operation cycle may be 1 week, or 1 day, or a cycle determined by a system administrator to operate the intelligent management system of the driverless distribution vehicle based on the internet of things technology.
The plurality of regional logistics management nodes also transmit regional driving quota consumption rates M (k) to an intelligent management layer of the unmanned delivery vehicle, wherein k is a regional identifier of each region;
the intelligent system management layer of the unmanned delivery vehicle is used for receiving the regional running quota consumption rates M (k) transmitted to the intelligent management system regulation layer of the unmanned delivery vehicle by the plurality of regional logistics management nodes, sequencing the regional running quota consumption rates M (k), and acquiring two regions with the highest and the next highest regional running quota consumption rates M (k) and the regional logistics management nodes corresponding to the two regions;
the intelligent system management layer of the unmanned delivery vehicle further requests a first management instruction to the intelligent management system platform end of the unmanned delivery vehicle based on the acquired highest region of the region running quota consumption rate M (k) and the region logistics management node P1 corresponding to the highest region, and receives the first management instruction sent by the intelligent management system platform end of the unmanned delivery vehicle;
and the number of the first and second groups,
requesting a second management instruction to an intelligent unmanned delivery vehicle management system platform end and receiving the second management instruction sent by the intelligent unmanned delivery vehicle management system platform end based on the acquired regional driving quota consumption rate M (k) secondary high region and a regional logistics management node P2 corresponding to the regional driving quota consumption rate M (k);
the first management instruction is from a first management instruction pool of an intelligent management system platform end of the unmanned distribution vehicle, and the second management instruction is from a second management instruction pool of the intelligent management system platform end of the unmanned distribution vehicle; the first management instruction is used for controlling quota adjustment or area control of a highest area of an area driving quota consumption rate M (k), and the second management instruction is used for controlling quota adjustment or area control of a second highest area of the area driving quota consumption rate M (k);
the intelligent management system platform end of the unmanned delivery vehicle is used for executing the intelligent management system management of the unmanned delivery vehicle based on the uploaded driving information and delivery information of the unmanned delivery vehicle and the acquired regional driving quota consumption rate M (k), the highest region and the corresponding regional logistics management node P1 thereof, the acquired regional driving quota consumption rate M (k), the next highest region and the corresponding regional logistics management node P2 thereof;
the intelligent management system platform end of the unmanned distribution vehicle is also used for storing and updating the first management instruction pool and the second management instruction pool, and selecting the first management instruction and the second management instruction according to a specific strategy based on an instruction request of a management layer of the intelligent management system of the unmanned distribution vehicle.
As a stackable embodiment, the platform end of the intelligent management system for unmanned delivery vehicles is further configured to store and update the first management instruction pool and the second management instruction pool, and select the first management instruction and the second management instruction according to a specific policy based on an instruction request of a management layer of the intelligent management system for unmanned delivery vehicles, specifically: the intelligent management system platform end of the unmanned distribution vehicle stores and updates a first management instruction pool, wherein the first management instruction pool at least comprises; the regional logistics management node P1 is instructed to execute instructions for the unmanned delivery vehicles in the region to be stopped for a certain period of time, and the regional logistics management node P1 is instructed to execute instructions for the unmanned delivery vehicles in the region to be increased indiscriminately by a quota, wherein the quota increase may be based on a certain unit, such as 10KM increments each time, or on a certain proportion, such as 10KM increments each time, or manually determined by system management personnel or preset in the system; and an instruction for instructing the regional logistics management node P1 to execute an instruction for increasing a quota for the difference of unmanned delivery vehicles in the region, where as a stackable embodiment, the instruction for instructing the regional logistics management node P1 to execute the instruction for increasing the quota for the difference of unmanned delivery vehicles in the region specifically is as follows: and according to the driving weight reference value W1 of each unmanned delivery vehicle, carrying out the quota differential increase on the unmanned delivery vehicles in the region based on the specific initial quota distribution value and the driving weight reference value W1 of each unmanned delivery vehicle. For example, with a specific initial quota allocation of 1KM, as a superimposable example, the system may set the individual unmanned delivery vehicles within the area to differentially increase by a quota of 1KM W1W 100%, where W1 is the driving weight reference W1 for each unmanned delivery vehicle, and may have different values.
The intelligent management system platform end of the unmanned distribution vehicle stores and updates a second management instruction pool, wherein the second management instruction pool at least comprises; the regional logistics management node P2 is configured to instruct the regional logistics management node P2 to perform an indiscriminate quota increase for an unattended delivery vehicle in a region, wherein the quota increase may be based on a specific unit, such as 10KM increments, or a specific proportion, such as 10KM increments, or manually determined by a system administrator or preset in the system; and an instruction for instructing the regional logistics management node P2 to execute an instruction for increasing a quota for the difference of unmanned delivery vehicles in the region, where as a stackable embodiment, the instruction for instructing the regional logistics management node P1 to execute the instruction for increasing the quota for the difference of unmanned delivery vehicles in the region specifically is as follows: and according to the driving weight reference value W1 of each unmanned delivery vehicle, carrying out the quota differential increase on the unmanned delivery vehicles in the region based on the specific initial quota distribution value and the driving weight reference value W1 of each unmanned delivery vehicle. For example, with a specific initial quota allocation of 1KM, as a superimposable example, the system may set the individual unmanned delivery vehicles within the area to differentially increase by a quota of 1KM W1W 100%, where W1 is the driving weight reference W1 for each unmanned delivery vehicle, and may have different values.
As a stackable embodiment, the selecting the first management instruction and the second management instruction according to a specific policy may be: according to a first management instruction and a second management instruction selected from the first management instruction pool and the second management instruction pool by a system administrator, taking the first management instruction and the second management instruction as a selected first management instruction and a selected second management instruction; or, alternately selecting a first management instruction and a second management instruction from the first management instruction pool and the second management instruction pool according to a specific sequence; or, based on a specific avoidance strategy, after deleting specific management instructions from the first management instruction pool and the second management instruction pool, randomly selecting the first management instruction and the second management instruction from the rest management instructions in the corresponding instruction pools, or selecting instructions from the second management instruction pool only by referring to the method, and always selecting instructions which indicate the unmanned delivery vehicles in the execution area of the regional logistics management node P1 to stop for a specific time from the first management instruction pool.
As a superimposable preferred embodiment, the plurality of unmanned distribution vehicles further store their own unmanned distribution vehicle IDs and zone identifications.
As another superimposable preferred embodiment, the driving information of the unmanned distribution vehicle at least includes:
the distance traveled by the unmanned distribution vehicle in an operation cycle;
the unmanned delivery vehicle is allowed to run for a quota total distance in an operation period;
the proportion K1 of the distance traveled by the unmanned delivery vehicle in an operation period to the total allowed quota distance traveled by the unmanned delivery vehicle;
the running weight reference value W1 of the unmanned delivery vehicle.
As another stackable preferred embodiment, the intelligent management system platform end of the unmanned delivery vehicle is configured to execute intelligent management system management of the unmanned delivery vehicle based on the uploaded driving information and delivery information of the unmanned delivery vehicle and the obtained regional driving quota consumption rate m (k), the highest region and the corresponding regional logistics management node P1 thereof, the obtained regional driving quota consumption rate m (k), the next highest region and the corresponding regional logistics management node P2 thereof, and at least includes: and sending a corresponding first management instruction and a second management instruction to an intelligent system management layer of the unmanned delivery vehicle.
As shown in the specification and the attached fig. 5, the specification and the attached fig. 5 are schematic diagrams of a preferred display embodiment of interconnection of internet of things collectors of nearby unmanned distribution vehicles in an intelligent management system of the unmanned distribution vehicles based on internet of things technology.
As another stackable preferred embodiment, the internet of things collector is also communicated with internet of things collectors installed on other nearby unmanned distribution vehicles, so that the driving information and the distribution information of the unmanned distribution vehicles collected by the internet of things collector can be relayed and forwarded.
Meanwhile, the invention discloses an implementation method of the intelligent management system of the unmanned distribution vehicle based on the technology of the Internet of things, and the method comprises the following steps:
step S102: operating a plurality of unmanned distribution vehicles and an Internet of things collector installed on each unmanned distribution vehicle, and collecting driving information and distribution information of the corresponding unmanned distribution vehicles;
the distribution information at least comprises an article type ID and an article counting number ID which are distributed by each unmanned distribution vehicle, and the distribution information is directly sent to an intelligent management system platform end of the unmanned distribution vehicle;
step S104: operating a plurality of regional logistics management nodes, determining a plurality of unmanned distribution vehicles belonging to the region based on the region identifications of the unmanned distribution vehicles in the region, and managing the unmanned distribution vehicles in the region;
each regional logistics management node also collects the running information of a plurality of unmanned distribution vehicles in the region based on the Internet of things; determining the area running quota consumption rate M (k) based on the collected running information of the unmanned distribution vehicles in the area, wherein k is the area identification of each area;
the plurality of regional logistics management nodes also transmit regional driving quota consumption rates M (k) to an intelligent management layer of the unmanned delivery vehicle, wherein k is a regional identifier of each region;
step S106: operating an unmanned delivery vehicle intelligent system management layer to receive the regional driving quota consumption rates M (k) transmitted to an unmanned delivery vehicle intelligent management system adjustment layer by the plurality of regional logistics management nodes, sequencing the regional driving quota consumption rates M (k), and acquiring two highest and second highest regional driving quota consumption rates M (k) and the corresponding regional logistics management nodes thereof; the intelligent system management layer of the unmanned delivery vehicle further requests a first management instruction to the intelligent management system platform end of the unmanned delivery vehicle based on the acquired region running quota consumption rate M (k) and the region logistics management node P1 corresponding to the highest region, and receives the first management instruction sent by the intelligent management system platform end of the unmanned delivery vehicle;
and the number of the first and second groups,
requesting a second management instruction to an intelligent unmanned delivery vehicle management system platform end and receiving the second management instruction sent by the intelligent unmanned delivery vehicle management system platform end based on the acquired regional driving quota consumption rate M (k) secondary high region and a regional logistics management node P2 corresponding to the regional driving quota consumption rate M (k);
the first management instruction is from a first management instruction pool of an intelligent management system platform end of the unmanned distribution vehicle, and the second management instruction is from a second management instruction pool of the intelligent management system platform end of the unmanned distribution vehicle; the first management instruction is used for controlling quota adjustment or area control of a highest area of an area driving quota consumption rate M (k), and the second management instruction is used for controlling quota adjustment or area control of a second highest area of the area driving quota consumption rate M (k);
step S108: operating the intelligent management system platform of the unmanned delivery vehicle to execute the management of the intelligent management system of the unmanned delivery vehicle based on the uploaded driving information and the distribution information of the unmanned delivery vehicle and the acquired regional driving quota consumption rate M (k), the highest region and the corresponding regional logistics management node P1 thereof, the acquired regional driving quota consumption rate M (k), the next highest region and the corresponding regional logistics management node P2 thereof; the intelligent management system platform end of the unmanned distribution vehicle is further used for storing and updating the first management instruction pool and the second management instruction pool, and selecting the first management instruction and the second management instruction according to a specific strategy based on an instruction request of a management layer of the intelligent management system of the unmanned distribution vehicle.
As another preferable embodiment that can be superimposed, the plurality of unmanned distribution vehicles further store their own unmanned distribution vehicle IDs and zone identifications.
As another superimposable preferred embodiment, the driving information of the unmanned distribution vehicle at least includes:
the distance traveled by the unmanned distribution vehicle in an operation cycle;
the unmanned delivery vehicle is allowed to run for a quota total distance in an operation period;
the proportion K1 of the distance traveled by the unmanned delivery vehicle in an operation period to the total allowed quota distance traveled by the unmanned delivery vehicle;
the running weight reference value W1 of the unmanned delivery vehicle.
As another stackable preferred embodiment, the intelligent management system platform end of the unmanned delivery vehicle is configured to execute intelligent management system management of the unmanned delivery vehicle based on the uploaded driving information and delivery information of the unmanned delivery vehicle and the obtained regional driving quota consumption rate m (k), the highest region and the corresponding regional logistics management node P1 thereof, the obtained regional driving quota consumption rate m (k), the next highest region and the corresponding regional logistics management node P2 thereof, and at least includes: and sending a corresponding first management instruction and a second management instruction to an intelligent system management layer of the unmanned delivery vehicle.
As another stackable preferred embodiment, the internet of things collector is also communicated with internet of things collectors installed on other nearby unmanned distribution vehicles, so that the driving information and the distribution information of the unmanned distribution vehicles collected by the internet of things collector can be relayed and forwarded.
The invention provides an intelligent management system of an unmanned delivery vehicle based on the technology of Internet of things and an implementation method thereof, wherein the driving information and the delivery information of the unmanned delivery vehicle are acquired by arranging an Internet of things acquirer corresponding to a plurality of unmanned delivery vehicles, the acquired information is sent to a regional management node in each region, the driving quota management of the unmanned delivery vehicle is realized on an intelligent system management layer of the unmanned delivery vehicle through regional information integration and data statistics of the driving working intensity of the unmanned delivery vehicle, the comprehensive system management and the issuing of related operation instructions are carried out on an intelligent management system platform end of the unmanned delivery vehicle, the network slice management of the unmanned delivery vehicle is implemented through the intelligent management of the unmanned delivery vehicle with a four-layer framework, the differentiated management instructions are arranged in each region, and the intelligent management system platform end of the unmanned delivery vehicle is based on an instruction pool management mode of the intelligent management system platform end of the unmanned delivery vehicle, the comprehensive management and control capability of the system is improved, and the better performance level of the unmanned distribution vehicle management system is achieved.
In all the above embodiments, in order to meet the requirements of some special data transmission and read/write functions, the above method and its corresponding devices may add devices, modules, devices, hardware, pin connections or memory and processor differences to expand the functions during the operation process.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described method, apparatus and unit may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the method steps into only one logical or functional division may be implemented in practice in another manner, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as individual steps of the method, apparatus separation parts may or may not be logically or physically separate, or may not be physical units, and may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, the method steps, the implementation thereof, and the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The above-described method and apparatus may be implemented as an integrated unit in the form of a software functional unit, which may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) or a Processor (Processor) to execute some steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), an NVRAM, a magnetic disk, or an optical disk, and various media capable of storing program codes.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
It should be noted that: the above embodiments are only used to explain and illustrate the technical solution of the present invention more clearly, and not to limit the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.