CN109215333B - Scheduling configuration method and system - Google Patents
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- CN109215333B CN109215333B CN201710550972.1A CN201710550972A CN109215333B CN 109215333 B CN109215333 B CN 109215333B CN 201710550972 A CN201710550972 A CN 201710550972A CN 109215333 B CN109215333 B CN 109215333B
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- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
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- G08G1/202—Dispatching vehicles on the basis of a location, e.g. taxi dispatching
Abstract
The invention relates to a scheduling configuration method and a system, wherein the scheduling configuration method comprises the following steps: the method for receiving the task data sent by the user terminal by the cloud server comprises the following steps: the method comprises the steps of task numbering, task starting point position information, task end point position information, task carrying capacity and task time; the method for receiving the vehicle state data sent by the plurality of vehicle-mounted terminals comprises the following steps: the method comprises the following steps that (1) vehicle-mounted terminal ID, driver ID, vehicle type information, vehicle position information, vehicle carrying capacity and vehicle idle time are obtained; matching the task starting point position information, the task end point position information, the task carrying capacity and the task time with the vehicle starting information, the vehicle carrying capacity and the vehicle idle time to determine various task vehicle schemes; acquiring running time reference data and task cost consumption reference data of the getting-off type information of each road section according to the road section information; determining an optimal route and an optimal task vehicle scheme, and generating vehicle dispatching information; and inquiring the order data and the order splicing data in the task management database.
Description
Technical Field
The invention relates to the field of vehicle safety, in particular to a scheduling configuration method and a scheduling configuration system.
Background
The tire is an important component of a vehicle, is directly contacted with a road surface, bears the weight of the vehicle, and is used for buffering the impact suffered by the vehicle when the vehicle runs together with a vehicle suspension. The state of the tire directly affects the riding comfort, ride comfort and driving safety of the vehicle. The good tire state can ensure that the vehicle has good adhesion with the road surface, and the traction, braking and passing performance of the vehicle are improved. More importantly, good tire condition is an important prerequisite for safe driving. In actual driving, the tire condition is affected by the road condition and changes accordingly. Therefore, how to accurately adapt the route conditions to the tires becomes one of the problems facing the enterprise managers and drivers.
At present, the adaptation of the route condition and the tire is only based on a manual judgment level, and an enterprise manager or a driver selects a driving route and a required tire according to experience. This method is susceptible to human factors, and the determination result is often inaccurate. Therefore, how to accurately adapt the route condition and the tire without being influenced by human factors is one of the difficulties to be solved in the field of current vehicle safety.
Disclosure of Invention
The invention aims to provide a scheduling configuration method and a scheduling configuration system aiming at the defects of the prior art, and the scheduling configuration method and the scheduling configuration system are used for calculating various feasible task vehicle schemes based on task routes, task quantities and task time of vehicles and calculating the optimal task vehicle scheme with the lowest cost and the highest efficiency according to information such as vehicle conditions, road conditions, task time and the like in the various feasible task vehicle schemes. The scheduling method is beneficial to reasonably scheduling vehicles, reducing travel cost and improving travel efficiency for drivers and managers, so that the drivers and the managers can execute travel tasks more smoothly and conveniently.
In order to achieve the above object, in a first aspect, the present invention provides a scheduling configuration method, where the scheduling configuration method includes:
the method comprises the steps that a cloud server receives task data sent by a user; the task data includes: the method comprises the steps of task numbering, task starting point position information, task end point position information, task carrying capacity and task time;
receiving corresponding vehicle state data sent by a plurality of vehicle-mounted terminals; the vehicle state data includes: the method comprises the following steps that (1) vehicle-mounted terminal ID, driver ID, vehicle type information, vehicle position information, vehicle carrying capacity and vehicle idle time are obtained;
matching the task starting point position information, the task end point position information, the task carrying capacity and the task time with the vehicle position information, the vehicle carrying capacity and the vehicle idle time to determine a plurality of task vehicle schemes; the task vehicle scheme comprises vehicle type information and the number corresponding to each vehicle type;
generating one or more pieces of information of the simulated planned route according to the position information of the task starting point and the position information of the task end point; the information of each simulated planned route comprises information of a plurality of node positions;
according to the node positions, carrying out route splitting on the simulated planned route to obtain road section information of a plurality of road sections;
acquiring running time reference data and task cost consumption reference data of the vehicle type information under each road section according to the road section information;
determining an optimal route and an optimal task vehicle scheme in the simulated planning route according to the running time reference data and the task cost consumption reference data of each task vehicle scheme;
generating vehicle dispatching information according to the optimal route and the optimal vehicle scheme;
and sending the vehicle dispatching information to the vehicle-mounted terminal according to the vehicle-mounted terminal ID of the vehicle-mounted terminal.
Preferably, the method further comprises:
the cloud server determines the residual transport capacity according to the vehicle dispatching information;
and inquiring list data in a task management database according to the residual transport capacity, the task starting point position information, the task ending point position information and the task time.
Further preferably, the method further comprises:
the cloud server determines a list-making task number according to the list-making data;
and the cloud server sends the list-making task number to the vehicle-mounted terminal according to the vehicle-mounted terminal ID.
Preferably, the method further comprises:
and the cloud server inquires order matching data in a task management database according to the task starting point position information, the task end point position information and the task time.
Further preferably, the method further comprises:
determining the bill-sharing carrying capacity according to the bill-sharing data;
updating the task vehicle scheme according to the order-sharing carrying capacity and the task carrying capacity;
and generating updated vehicle dispatching information according to the updated task vehicle scheme.
Preferably, the method further comprises:
the mobile terminal accesses the cloud server according to the vehicle-mounted terminal ID;
and the cloud server receives the task starting point position information, the task end point position information and the mobile terminal ID which are sent by the mobile terminal.
Further preferably, the method further comprises:
and the cloud server sends the vehicle dispatching information to the mobile terminal according to the mobile terminal ID.
Preferably, the method further comprises;
the cloud server determines a management terminal ID of a management terminal corresponding to the vehicle-mounted terminal according to the vehicle-mounted terminal ID;
and the cloud server receives the task starting point position information, the task end point position information and the management terminal ID which are sent by the management terminal.
Further preferably, the method further comprises:
and the cloud server sends the vehicle dispatching information to the management terminal according to the management terminal ID.
In a second aspect, the information exception handling system for tire networking provided by the invention comprises the vehicle-mounted terminal and the cloud server as described in the first aspect.
According to the scheduling configuration method provided by the embodiment of the invention, various feasible task vehicle schemes are calculated based on the task route, the task amount and the task time of the vehicle, and the optimal task vehicle scheme with the lowest cost and the highest efficiency is calculated according to the information such as the vehicle condition, the road section condition, the task time and the like in the various feasible task vehicle schemes. The scheduling method is beneficial to reasonably scheduling vehicles, reducing travel cost and improving travel efficiency for drivers and managers, so that the drivers and the managers can execute travel tasks more smoothly and conveniently.
Drawings
Fig. 1 is a flowchart of a scheduling configuration method according to an embodiment of the present invention;
fig. 2 is a block diagram of a scheduling configuration system according to an embodiment of the present invention.
Detailed Description
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
In order to better understand the technical solution of the present invention, an application scenario of the scheduling configuration method proposed by the present invention is first introduced.
In the application scenario of the embodiment, the vehicle needs to complete the driving task, and a vehicle-mounted terminal is loaded on each driving task, and is used for communicating with the cloud server and performing data interaction, so as to implement data processing and analysis on the network side.
The embodiment of the invention firstly provides a scheduling configuration method, which is implemented in a scheduling configuration system, the flow chart of the method is shown in figure 1, and the method comprises the following steps:
specifically, the task data is some task information of the vehicle to perform the task at this time. The task data includes: task number, task starting point position information, task ending point position information, task carrying capacity and task time.
In a specific example, if the user has a driving task 1 to be completed, the user sends to the cloud server: and the task data comprises a task number of 001, task starting point position information of a direction a, task end point position information of a direction b, task carrying capacity of 1 ton and task time of 6 hours.
specifically, the vehicle state data includes: the vehicle-mounted terminal ID, the driver ID, the vehicle type information, the vehicle position information, the vehicle carrying capacity and the vehicle idle time.
The vehicle-mounted terminal has a vehicle-mounted terminal ID capable of determining identity information of the vehicle-mounted terminal, and the cloud server can confirm the vehicle bound by the vehicle-mounted terminal through the vehicle-mounted terminal ID as the vehicle-mounted terminal and the vehicle are in one-to-one binding relationship. The driver ID is the identity information of the driver, the position of the current vehicle represented by the vehicle position information, the vehicle carrying capacity represents the maximum vehicle carrying capacity, and the vehicle idle time represents the time when the vehicle can execute the running task.
specifically, the task vehicle plan includes vehicle type information and a corresponding number of each vehicle type, and may be understood as a usage plan of the vehicle in the running task. The task time may be understood as a deadline time for completion of the travel task. In practical situations, different vehicles have different loading standards, and the vehicles are not always capable of driving, and the vehicles need to determine whether the vehicles can be driven according to the time of drivers, and the vehicles themselves also need to take time for maintenance. Therefore, when the task vehicle scheme is confirmed, the task starting point position information, the task ending point position information, the task carrying capacity and the task time are matched with the vehicle position information, the vehicle carrying capacity and the vehicle idle time to match the vehicles which can meet the task requirement, namely the vehicle model and the required vehicle number which can execute the running task are determined.
It should be noted that the vehicle models and the number of vehicles of the cloud server can be arranged and combined, so that a plurality of vehicle models and the number of required vehicles can be obtained, and therefore, a plurality of vehicle schemes can be provided for the running task.
For example, the mission load of the driving mission 1 is 10 tons, and the mission time is 10 hours. The bearing capacity of the vehicle X is 2 tons, and the driving time is 2 hours; the vehicle Y has a carrying capacity of 3 tons and a travelable time of 3 hours. The mission vehicle scenario that may perform the travel mission 1 includes: 2 vehicles X plus 2 vehicles Y, 5 or more vehicles X, 4 or more vehicles Y, and other vehicle alignment combinations that can satisfy the travel task 1.
in particular, the simulated planned route may be understood as a driving road path that enables a vehicle to travel from a starting point to an ending point. The cloud server has an electronic map, or the cloud server can acquire the electronic map from other servers. The electronic map comprises information such as geographic position information of a vehicle running place, road length information, road real-time congestion degree information and the like. The cloud server inputs the task starting point position information and the task end point position information of the vehicle in the electronic map, and generates one or more road paths capable of realizing vehicle driving, namely information of a simulated planned route in the electronic map. These roads can theoretically allow the vehicle to reach the destination from the starting point, but the road conditions of different roads are different, and the influence on the vehicle driving is also different.
For example, vehicle X plans to travel from origin a to destination B, where both route A and route B may lead from origin a to destination B, where route A is more jerky than route B and route B is shorter than route A. Then, there must be an optimal route for vehicle X for route a and route B, and vehicle X needs to select a route from route a or route B to travel so that vehicle X can reach destination B more quickly and safely.
specifically, the cloud server sets one or more route nodes in the simulation planning route according to the information of the simulation planning route in the electronic map, that is, the simulation planning route is split into a plurality of simulation planning road sections to obtain a plurality of road section information, and a connection point between each simulation planning road section is a node of the simulation planning route. The rule for setting the nodes may be set according to the road name, the road length, the distribution of the road signal lights, or other rules with certain logics.
For example, the simulated planned route a starts at a1 and ends at an. a 1-an has a signal light and a curve, so that a node a2 can be set at the signal light, a3 can be set at the curve, and the route a is split into three simulation planning road sections, specifically: a1-a2 is the first simulated planned route segment, a2-a3 is the second simulated planned route segment, and a3-an is the third simulated planned route segment.
specifically, in general, different models of vehicles travel the same distance on different road sections with different travel times and different travel costs. For example, if the vehicle X and the vehicle Y are two vehicles of different models, and the vehicle X travels faster than the vehicle Y on the road segment a but is more fuel-consuming than the vehicle Y, the travel time reference data of the vehicle X is smaller than the travel time reference data of the vehicle Y, and the mission cost consumption reference data of the vehicle X is larger than the mission cost consumption reference data of the vehicle Y.
Step 160, determining an optimal route and an optimal task vehicle scheme in the simulated planning route according to the running time reference data and the task cost consumption reference data of each task vehicle scheme;
specifically, the travel time reference data and the task cost consumption reference data obtained by the cloud server may both correspond to corresponding vehicle type information, and may also correspond to corresponding respective task vehicle schemes through the vehicle type information. Therefore, the cloud server can arrange and combine the running time reference data, the task cost consumption reference data and each task vehicle scheme corresponding to the vehicle type information through the vehicle type information to obtain the optimal route and the optimal task vehicle scheme which are relatively shortest in vehicle running time, relatively shortest in vehicle task cost consumption and relatively shortest in route.
The optimal route is a route traveled by the vehicle to perform the driving task on the premise that the vehicle driving time is relatively shortest, the vehicle task cost consumption is relatively minimum, and the route is relatively shortest. The optimal task vehicle scheme is that on the premise that the vehicle running time is relatively shortest, the vehicle task cost consumption is relatively minimum, and the route is relatively shortest, the vehicle type information of the vehicle for executing the situational task and the required quantity corresponding to each vehicle type are obtained.
specifically, the vehicle dispatch information can be understood as a final dispatch plan of the driving task. And the cloud server combines the optimal route and the optimal vehicle scheme to generate vehicle dispatching information. The vehicle dispatch information includes a task driving route, vehicle types of the respective vehicles required for the task, and the number of the respective vehicles required for the task.
specifically, the cloud server confirms the identity of the vehicle-mounted terminal according to the ID of the vehicle-mounted terminal, so that a vehicle in which the vehicle-mounted terminal is located is confirmed, and vehicle dispatching information is sent to the vehicle, so that a driver in the vehicle can execute a corresponding running task according to the vehicle dispatching information.
In one embodiment, the cloud server may also confirm remaining capacity from the vehicle dispatch information.
The remaining capacity is understood to be the capacity of the vehicle to also perform other driving tasks during the driving task. The cloud server is provided with a task management database, and the task management database is provided with a plurality of task data. And the cloud server inquires the list data of the residual transport capacity, the task starting point position information, the task end point position information and the task time in the vehicle dispatching information range in a task management database according to the residual transport capacity, the task starting point position information, the task end point position information and the task time.
The summary data also corresponds to a driving task, which can be understood as a second driving task that can be executed at the same time as the first driving task, and the execution of the second driving task does not affect the execution of the first driving task. The order collection comprises a task number, order collection task starting point position information, order collection task end point position information, order collection task carrying capacity and order collection task time. And the cloud server sends the list-gathering task number to the vehicle-mounted terminal so that the vehicle-mounted terminal can give a corresponding prompt to the driver. The method for planning and executing all the running tasks in a comprehensive mode can save the running cost of the vehicle to the maximum extent.
In another specific example, after step 110, the cloud server may first query the task management database for the hash data according to the task number, the task start position information, the task end position information, the task capacity, and the task time. Matching and combining the list making data with various task vehicle schemes and various routes, and then obtaining the final vehicle dispatching information through the steps 120-170. The vehicle dispatching information comprises a single task, and the vehicle capacity in the vehicle dispatching information is closer to a saturation state.
In addition, the cloud server can also inquire the order data in the task management database according to the position information of the task starting point, the position information of the task ending point and the task time, determine the order loading capacity according to the order data, and update the task vehicle scheme according to the order loading capacity and the task loading capacity.
Preferably, the cloud server further sends the vehicle dispatching information to the mobile terminal and the management terminal.
The mobile terminal may be a mobile phone or any software in a mobile device with General Packet Radio Service (GPRS) connectivity. The mobile terminal is provided with a mobile terminal ID, the mobile terminal is accessed into the cloud server according to the ID of the vehicle-mounted terminal, and the cloud server sends vehicle dispatching information to the mobile terminal according to the mobile terminal ID. In a specific example, the cloud server sends the vehicle dispatch information to the mobile terminal in the form of short message, telephone voice or push according to the mobile terminal ID.
The management terminal can be understood as a device for managing the vehicle-mounted terminal by a manager, one management terminal can correspond to a plurality of vehicle-mounted terminals, and the manager can manage or check a plurality of vehicle-mounted terminals below the management terminal through one management terminal. The management terminal is provided with an ID of the management terminal, the ID of the management terminal corresponds to the ID of the vehicle-mounted terminal, the cloud server determines the terminal ID of the corresponding management terminal according to the ID of the vehicle-mounted terminal corresponding to the tire ID, and the vehicle dispatching information is sent to the management terminal according to the terminal ID of the management terminal. And the management terminal allocates the corresponding vehicle according to the vehicle allocation information. In a specific example, the management terminal manages a vehicle-mounted terminal of a fleet of vehicles, and the management terminal manages the running tasks of the whole fleet of vehicles according to vehicle dispatching information of the vehicles in the fleet of vehicles.
According to the scheduling configuration method provided by the embodiment of the invention, various feasible task vehicle schemes are calculated based on the task route, the task amount and the task time of the vehicle, and the optimal task vehicle scheme with the lowest cost and the highest efficiency is calculated according to the information such as the vehicle condition, the road section condition, the task time and the like in the various feasible task vehicle schemes. The scheduling method is beneficial to reasonably scheduling vehicles, reducing travel cost and improving travel efficiency for drivers and managers, so that the drivers and the managers can execute travel tasks more smoothly and conveniently.
Correspondingly, an embodiment of the present invention further provides a scheduling configuration system for implementing the scheduling configuration method, a block diagram of which is shown in fig. 2, where the scheduling configuration system includes: the system comprises an in-vehicle terminal 1, a cloud server 2, a management terminal 3 and a mobile terminal 4.
The vehicle-mounted terminal 1 is located in a vehicle cab and connected with the cloud server 2 through a GPRS network. The cloud server 2 is also connected with the management terminal 3 and the mobile terminal 4 through a GPRS network.
When the scheduling configuration system works, the process is as follows.
The vehicle-mounted terminal 1 sends the task data to the cloud server 2, the cloud server 2 processes and analyzes the task data to obtain vehicle dispatching information, and the vehicle dispatching information is sent to the management terminal 3 and the mobile terminal 4.
The scheduling configuration system provided by the embodiment of the invention calculates a plurality of feasible task vehicle schemes based on the task route, the task amount and the task time of the vehicle, and calculates the optimal task vehicle scheme with the lowest cost and the highest efficiency according to the information such as the vehicle condition, the road section condition, the task time and the like in the plurality of feasible task vehicle schemes. The scheduling method is beneficial to reasonably scheduling vehicles, reducing travel cost and improving travel efficiency for drivers and managers, so that the drivers and the managers can execute travel tasks more smoothly and conveniently. In addition, the scheduling configuration system provided by the embodiment of the invention has low cost and good compatibility, is easy to load on the existing vehicle, and is used for upgrading and reconstructing the existing vehicle management system.
Those of skill would further appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware, a software module executed by a processor, or a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (8)
1. A scheduling configuration method, comprising:
the method comprises the steps that a cloud server receives task data sent by a user; the task data includes: the method comprises the steps of task numbering, task starting point position information, task end point position information, task carrying capacity and task time;
receiving corresponding vehicle state data sent by a plurality of vehicle-mounted terminals; the vehicle state data includes: the method comprises the following steps that (1) vehicle-mounted terminal ID, driver ID, vehicle type information, vehicle position information, vehicle carrying capacity and vehicle idle time are obtained;
matching the task starting point position information, the task end point position information, the task carrying capacity and the task time with the vehicle position information, the vehicle carrying capacity and the vehicle idle time to determine a plurality of task vehicle schemes; the task vehicle scheme comprises vehicle type information and the number corresponding to each vehicle type;
generating one or more pieces of information of the simulated planned route according to the position information of the task starting point and the position information of the task end point; the information of each simulated planned route comprises information of a plurality of node positions;
according to the node positions, carrying out route splitting on the simulated planned route to obtain road section information of a plurality of road sections;
acquiring running time reference data and task cost consumption reference data of the vehicle type information under each road section according to the road section information;
determining an optimal route and an optimal task vehicle scheme in the simulated planning route according to the running time reference data and the task cost consumption reference data of each task vehicle scheme;
generating vehicle dispatching information according to the optimal route and the optimal vehicle scheme;
sending the vehicle dispatching information to the vehicle-mounted terminal according to the vehicle-mounted terminal ID of the vehicle-mounted terminal;
wherein the method further comprises:
the cloud server determines the residual transport capacity according to the vehicle dispatching information;
inquiring list data in a task management database according to the residual transport capacity, the task starting point position information, the task end point position information and the task time;
wherein the method further comprises:
the cloud server determines a list-making task number according to the list-making data;
and the cloud server sends the list-making task number to the vehicle-mounted terminal according to the vehicle-mounted terminal ID.
2. The scheduling configuration method of claim 1, wherein the method further comprises:
and the cloud server inquires order matching data in a task management database according to the task starting point position information, the task end point position information and the task time.
3. The scheduling configuration method of claim 2, further comprising:
determining the bill-sharing carrying capacity according to the bill-sharing data;
updating the task vehicle scheme according to the order-sharing carrying capacity and the task carrying capacity;
and generating updated vehicle dispatching information according to the updated task vehicle scheme.
4. The scheduling configuration method of claim 1, wherein the method further comprises:
the mobile terminal accesses the cloud server according to the vehicle-mounted terminal ID;
and the cloud server receives the task starting point position information, the task end point position information and the mobile terminal ID which are sent by the mobile terminal.
5. The scheduling configuration method of claim 4, wherein the method further comprises:
and the cloud server sends the vehicle dispatching information to the mobile terminal according to the mobile terminal ID.
6. The scheduling configuration method of claim 1, wherein the method further comprises:
the cloud server determines a management terminal ID of a management terminal corresponding to the vehicle-mounted terminal according to the vehicle-mounted terminal ID;
and the cloud server receives the task starting point position information, the task end point position information and the management terminal ID which are sent by the management terminal.
7. The scheduling configuration method of claim 6, further comprising:
and the cloud server sends the vehicle dispatching information to the management terminal according to the management terminal ID.
8. A scheduling configuration system, characterized in that the system comprises the scheduling configuration method according to any of the claims 1-7.
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| US20230136829A1 (en) * | 2020-03-18 | 2023-05-04 | Uisee (Shanghai) Automotive Technologies Ltd | Multi-vehicle coordination-based vehicle scheduling system and method, electronic apparatus, and storage medium |
| CN111626578A (en) * | 2020-05-18 | 2020-09-04 | 上海东普信息科技有限公司 | Distribution method, device, equipment and storage medium of logistics truck |
| CN113771878B (en) * | 2021-09-27 | 2023-01-20 | 荆州智达电动汽车有限公司 | Port automatic driving vehicle global route guiding method based on full operation scene |
| CN115994673B (en) * | 2023-03-16 | 2023-06-16 | 交通运输部水运科学研究所 | Grain base monitoring method, system and storage medium based on Internet of things |
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| CN104866997A (en) * | 2015-06-10 | 2015-08-26 | 南京大学 | Intelligent pairing method applied to online stowage of vehicles and goods |
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| CN106779164A (en) * | 2016-11-23 | 2017-05-31 | 北京小米移动软件有限公司 | Automobile type configuration method, device and terminal in logistics management |
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