CN116266294A - Intelligent dispatching system and method for vehicles in park - Google Patents

Intelligent dispatching system and method for vehicles in park Download PDF

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Publication number
CN116266294A
CN116266294A CN202111538145.3A CN202111538145A CN116266294A CN 116266294 A CN116266294 A CN 116266294A CN 202111538145 A CN202111538145 A CN 202111538145A CN 116266294 A CN116266294 A CN 116266294A
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vehicle
vehicles
park
information
server
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周俊
茅恺
阮颖群
张明月
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Guangdong Eshore Technology Co Ltd
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Guangdong Eshore Technology Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06311—Scheduling, planning or task assignment for a person or group
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06315—Needs-based resource requirements planning or analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/083—Shipping
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

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Abstract

The invention discloses an intelligent dispatching system and method for vehicles in a park, and relates to the field of automatic driving of the park. The scheme is provided for solving the problem of low automatic driving participation in the prior art, and mainly comprises a server, a control unit and a control unit, wherein the server is used for processing scheduling requirements according to time periods after reaching a preset time trigger point; acquiring the number of vehicles in each sub-area queue at the current time point and in the corresponding time period, and generating vehicle allocation demand information when the difference value is greater than a threshold value; calculating platform truck loading efficiency, determining the total queuing number of the queue vehicles in the park and the adjustable vehicles outside the park, and generating adjustable information; and determining the ID and the position information of the adjustable vehicle outside the park, generating vehicle allocation information, and sending the vehicle allocation information to the vehicle-mounted end of the allocated vehicle. The advantage is that the driver is replaced by an automatic dispatch service and automatic driving of the vehicle. The optimal configuration of the operation is realized, the optimal decision is made, the operation efficiency and the equipment utilization rate are improved, the error rate is reduced, and the operation cost of a park is reduced.

Description

Intelligent dispatching system and method for vehicles in park
Technical Field
The invention relates to the field of automatic driving in a park, in particular to an intelligent scheduling system and method for vehicles in the park.
Background
Numerous campuses have completed informatization and digital transformation, but at present, the application and management of informatization and digital application of the campuses are still in running-in period, and there are numerous contradictions of management and execution, especially general-purpose business of the campuses. Such as vehicle dispatching management, and the phenomena of queuing congestion, vehicle jam and the like in the peak loading period of a park are easy to cause the problem of confusion caused by contradiction of drivers. Therefore, daily operation of the park is not facilitated, goods are slowly transferred and are poor in timeliness, meanwhile, the problem of park congestion can occur, poor experiences are brought to clients and carriers, order loss is caused, and further development of the industry is not facilitated.
In the management flow, logic judgment is mostly adopted to finish the dispatching of warehouse sites, mechanical operation, production dispatching, park vehicles and the like. The job scheduling and resource allocation are mainly based on working experience, data application technologies such as AI and the like are not enabled in a park, the optimal allocation cannot be achieved, the intelligent level is low, and the cost is high. Information service capability and transportation service capability for a campus performance index system are also often important concerns for the operation of the campus.
The efficient management of the park vehicles can be a key point of development in the park field, and how to improve the park operation efficiency by utilizing the automatic driving technology, especially aiming at park congestion and confusion caused by the park peak period, is a problem which needs to be solved by the technicians in the field.
Disclosure of Invention
The invention aims to provide an intelligent dispatching system and method for vehicles in a park, which are used for solving the problems in the prior art.
The invention discloses an intelligent dispatching system and method for vehicles in a park, comprising the following steps:
the server is in communication connection with the platform end, the gate end and all the vehicle-mounted ends and is used for processing the scheduling requirement according to a time period after reaching a preset time trigger point; acquiring the number of vehicles in each sub-area queue of the current time point and the corresponding time period, and waiting for the next time period to monitor the threshold value when the difference value between the number of orders in the month table queue and the number of vehicles in the queue is not more than the threshold value; when the difference value is larger than the threshold value, generating vehicle allocation demand information; calculating platform truck loading efficiency, determining the total queuing number of the queue vehicles in the park and the adjustable vehicles outside the park, and generating adjustable information; determining the ID and the position information of the adjustable vehicle outside the park, generating vehicle allocation information, and sending the vehicle allocation information to a vehicle-mounted end with the allocated vehicle;
each vehicle is independently provided with a vehicle-mounted end and used for acquiring position information, state information and operation information of the corresponding vehicle and uploading the position information, the state information and the operation information to the server; the vehicle allocation information sent by the server is received, a vehicle allocation planning path is generated according to the position information, and an automatic driving control instruction is generated in allocation planning time, so that the vehicle to be allocated automatically runs to a target position;
the platform end is used for acquiring platform loading efficiency and sending the platform loading efficiency to the server;
and the gate port end is used for communicating with the server, counting and releasing vehicles entering and exiting the park.
And the server performs weighted prediction on the order trend of the subsequent time period according to the current order quantity.
The server controls the number of vehicle queues going in and out of the park and reaching the dock through the gate end so as to adjust the congestion peak and the operation underestimation time period in the park.
The vehicle-mounted terminal carries out cycle self-checking on the vehicle at intervals and reports the position information and the state information to the server
If the abnormal state is found during self-checking, the abnormal state and the abnormal information are sent to the server at certain time intervals until the self-checking returns to the normal state.
The platform loading efficiency is the loading amount in unit time; the loading amount is the running amount of the vehicle, or the volume of the loaded and unloaded goods, or the weight of the loaded and unloaded goods.
The vehicle is an automatically driven automobile having an automobile driving automation level not lower than level L3.
And the vehicle-mounted terminal and the server are in communication connection through a 5G public network integration mode.
And the vehicle-mounted terminal acquires the position information through 5G hybrid positioning.
The intelligent dispatching method for the vehicles in the park utilizes the intelligent dispatching system for intelligent dispatching of the vehicles.
The intelligent dispatching system and method for the vehicles in the park have the advantages that drivers are replaced by automatic dispatching services and automatic driving of the vehicles. The optimal configuration of the operation is realized, the optimal decision is made, the operation efficiency and the equipment utilization rate are improved, the error rate is reduced, and the operation cost of a park is reduced.
Drawings
FIG. 1 is a schematic diagram of a intelligent dispatching system for vehicles in a campus according to the present invention;
fig. 2 is a schematic flow chart of a method for intelligent dispatching of vehicles in a campus according to the present invention.
Detailed Description
The intelligent dispatching system for the vehicles in the park, as shown in fig. 1, comprises a dock end arranged in the park, a gate end arranged at a physical fence of the park, a vehicle-mounted end carried on the vehicle and a server. The method is mainly used for solving the vehicle loading requirements of vehicles in different periods of peaks and valleys, and can be suitable for vehicle data and trend prediction in different periods, different types of parks and different park positions to respond vehicle scheduling after data collection and accumulation.
The server can be a local server, a server group formed by a plurality of server devices, a cloud server and the like. The system can be configured in physical machine rooms of a logistics center in a park, can be configured in cloud and other modes, and is mainly in communication connection with each functional end through a network. The system is used for being in communication connection with a platform end, a gate end and all vehicle-mounted ends, and is used for processing scheduling requirements according to time periods after reaching a preset time trigger point; acquiring the number of vehicles in each sub-area queue of the current time point and the corresponding time period, and waiting for the next time period to monitor the threshold value when the difference value between the number of orders in the month table queue and the number of vehicles in the queue is not more than the threshold value; when the difference value is larger than the threshold value, generating vehicle allocation demand information; calculating platform truck loading efficiency, determining the total queuing number of the queue vehicles in the park and the adjustable vehicles outside the park, and generating adjustable information; and determining the ID and the position information of the adjustable vehicle outside the park, generating vehicle allocation information, and sending the vehicle allocation information to the vehicle-mounted end of the allocated vehicle.
The platform end is naturally carried on the platform and is used for acquiring platform loading efficiency and sending the platform loading efficiency to the server.
The gate port can be arranged in one or more modes according to physical distribution of the garden, or can be arranged to divide the garden into the garden, parallel subareas and the like for multipath arrangement. A gate is naturally carried with a gate end for communicating with the server, counting and releasing vehicles coming in and going out of the park.
Each vehicle is independently provided with a vehicle-mounted end and used for acquiring position information, state information and operation information of the corresponding vehicle and uploading the position information, the state information and the operation information to the server; and receiving vehicle allocation information issued by the server, generating a vehicle allocation planning path according to the position information, and generating an automatic driving control instruction at allocation planning time so that the vehicle to be allocated automatically runs to a target position. The vehicle location situation includes at least in/out of the park, in a specific sub-area of the park, etc.
The automatic driving classification of the vehicle is obtained based on classification of GB/T40429-2021 automatic driving classification of the automobile.
The workflow of the intelligent scheduling system for vehicles in a park and a corresponding management method are shown in fig. 2:
step S1, at a preset time trigger point, a server acquires vehicle position information and vehicle state information, order state information, garden gate state information and platform state information.
The vehicle is an automatically driven automobile having an automobile driving automation level not lower than level L3. The vehicle and the server may be implemented through, but are not limited to, a 5G communication interface and employ, but are not limited to, a 5G public network integration mode (PNI-NPN).
The vehicle position information can be actively reported to the server through, but not limited to, 5G hybrid positioning; the server may be actively acquired through the communication interface when needed.
Each vehicle-mounted terminal performs self-checking according to a preset circulation time point, and reports position information and state information to a server at a trigger time. Meanwhile, if the abnormal state is encountered during the timing self-checking, the abnormal state and the abnormal information are sent to the server at preset time intervals until the self-checking abnormal state is relieved or the vehicle active reporting service is closed.
The server can request the position, the state information and the operation state information from the vehicle-mounted terminal according to a preset trigger time point and a preset time trigger rule. The vehicle-mounted terminal obtains position information through 5G hybrid positioning and performs self-checking, generates feedback data and sends the feedback data to the server.
Step S2, counting the number of vehicles in each area queue at the current time point;
and the server matches the acquired vehicle position information, the vehicle operation state and the park area range, and counts the number of vehicles in the queuing of each area.
Step S3, inquiring the total number of the missed orders and the number of the received orders at the current time point;
the server queries the total number of unanswered orders and the number of orders taken through the background interface for further calculation.
An unfilled order refers to an order submitted by a carrier and that has been reviewed by the order group, the server leaving an order unassigned to the vehicle. The order quantity taken refers to the order submitted by the carrier and has been reviewed by the order group, the order that the server dispatched to the vehicle.
And S4, when the difference between the number of the received orders and the total number of the vehicle queues in the platform area queues is larger than a threshold value, the server generates vehicle allocation requirement information. The total number of vehicle queues in the dock area queue refers to the sum of the number of vehicles in the dock area that are not in a cargo state or other job state and are in the job state. The vehicle deployment demand information includes, among other things, deployment demands of vehicles that are able to enter the campus.
And S5, calculating platform truck loading efficiency by the server, determining the total number of the queues of the vehicles in each zone of the entering park, counting the position information of the vehicles which can be allocated outside the park, and generating the allocation information. The platform loading efficiency refers to the loading amount per unit time. The loading amount can be the number of vehicles or the volume or weight of goods. The total number of queuing vehicles in each zone refers to the sum of vehicles which are in-park queuing vehicles, dock queuing vehicles, out-of-park queuing vehicles, and are not in a loading state or other working state. The vehicles which can be allocated outside the statistical park refer to vehicles which have vehicle position information outside the park and have no abnormal states. The adjustable dispatch information includes, among other things, vehicle dispatch requirements to enter the campus area for queuing.
S6, determining an out-of-garden adjustable vehicle ID and vehicle position information; the server generates vehicle allocation information including the priority of entering the garden according to the determined adjustable vehicles. In general, the vehicle allocation requirement information is completed before the configurable information is completed.
And S7, entering the waiting queue serial number, the vehicle serial number, the position information and the information of the allocation planning time, and sending the allocation information to each vehicle to be allocated by the server through the ID of the vehicle to be allocated.
And S8, generating a vehicle allocation planning path by the vehicle to be allocated according to the information of the parking position, and generating an automatic driving control instruction in allocation planning time to start the vehicle to be allocated, so that the vehicle to be allocated automatically runs to the parking position according to the vehicle allocation planning path.
And S9, the server performs weighted prediction on the follow-up order trend according to the order data quantity, and controls the queue quantity of the entering area, the exiting area and the platform area. Weighted prediction of subsequent order trends is but one way of prediction, and various prediction algorithms may be substituted here, and is not limited to weighted prediction. The number of queues in the garden-in area, the garden-out area and the dock area is the number of openings of the garden-in gate, the garden-out gate and the dock.
It will be apparent to those skilled in the art from this disclosure that various other changes and modifications can be made which are within the scope of the invention as defined in the appended claims.

Claims (10)

1. An intelligent scheduling system for vehicles in a campus, comprising:
the server is in communication connection with the platform end, the gate end and all the vehicle-mounted ends and is used for processing the scheduling requirement according to a time period after reaching a preset time trigger point; acquiring the number of vehicles in each sub-area queue of the current time point and the corresponding time period, and waiting for the next time period to monitor the threshold value when the difference value between the number of orders in the month table queue and the number of vehicles in the queue is not more than the threshold value; when the difference value is larger than the threshold value, generating vehicle allocation demand information; calculating platform truck loading efficiency, determining the total queuing number of the queue vehicles in the park and the adjustable vehicles outside the park, and generating adjustable information; determining the ID and the position information of the adjustable vehicle outside the park, generating vehicle allocation information, and sending the vehicle allocation information to a vehicle-mounted end with the allocated vehicle;
each vehicle is independently provided with a vehicle-mounted end and used for acquiring position information, state information and operation information of the corresponding vehicle and uploading the position information, the state information and the operation information to the server; the vehicle allocation information sent by the server is received, a vehicle allocation planning path is generated according to the position information, and an automatic driving control instruction is generated in allocation planning time, so that the vehicle to be allocated automatically runs to a target position;
the platform end is used for acquiring platform loading efficiency and sending the platform loading efficiency to the server;
and the gate port end is used for communicating with the server, counting and releasing vehicles entering and exiting the park.
2. The intelligent on-campus vehicle scheduling system of claim 1, wherein the server weights and predicts the trend of the orders for the subsequent time period by the current order quantity.
3. The intelligent scheduling system for vehicles on a campus of claim 1, wherein the server controls the number of vehicle queues in and out of the campus and to the dock via the gate end to adjust the congestion peak and job underestimation period on the campus.
4. The intelligent dispatching system for vehicles in a campus according to claim 1, wherein the vehicle-mounted terminal performs cycle self-checking on the vehicle at intervals, and reports the position information and the state information to the server.
5. The intelligent scheduling system for vehicles in a campus of claim 4, wherein if an abnormal state is found during self-test, the abnormal state and abnormal information are sent to the server at intervals until the self-test returns to a normal state.
6. The intelligent scheduling system for vehicles in a campus of claim 1, wherein the dock loading efficiency is the loading per unit time; the loading amount is the running amount of the vehicle, or the volume of the loaded and unloaded goods, or the weight of the loaded and unloaded goods.
7. The intelligent scheduling system for vehicles on a campus of claim 1, wherein the vehicles are autonomous vehicles having a level L3 or not lower in an automotive automation class.
8. The intelligent dispatching system for vehicles in a campus of claim 1, wherein the vehicle-mounted terminal and the server are in communication connection through a 5G public network integration mode.
9. The intelligent scheduling system for vehicles in a campus of claim 1, wherein the on-board terminal obtains the location information through 5G hybrid positioning.
10. An intelligent dispatching method for vehicles in a park, which is characterized in that the intelligent dispatching system for vehicles is used for intelligent dispatching of vehicles.
CN202111538145.3A 2021-12-15 2021-12-15 Intelligent dispatching system and method for vehicles in park Pending CN116266294A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111538145.3A CN116266294A (en) 2021-12-15 2021-12-15 Intelligent dispatching system and method for vehicles in park

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Application Number Priority Date Filing Date Title
CN202111538145.3A CN116266294A (en) 2021-12-15 2021-12-15 Intelligent dispatching system and method for vehicles in park

Publications (1)

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CN116266294A true CN116266294A (en) 2023-06-20

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