Vehicle loading rate calculation method and device, computer equipment and storage medium

Abstract

The application relates to a vehicle loading rate calculation method and device, computer equipment and a storage medium. The application can replace the traditional manual calculation of line loading rate, is more rapid and accurate, can output qualified line loading rate in time, and is convenient for screening out unqualified line loading rate for further adjustment and processing. The method comprises the following steps: obtaining a vehicle identity, querying a transportation line type of a transportation line where the vehicle is located according to the vehicle identity, calculating a line loading rate of the vehicle on the transportation line according to the transportation line type, judging whether the line loading rate is between a preset upper quantile and a preset lower quantile, and outputting the line loading rate of the vehicle on the transportation line if yes.

Description

Technical Field

[0001] This application relates to the field of logistics and transportation technology, and in particular to a method, apparatus, computer equipment, and storage medium for calculating vehicle loading rate. Background Technology

[0002] With the rapid development of the logistics industry, the selection of transportation routes and cargo loading planning have gradually become important research directions for improving logistics efficiency.

[0003] There are three main factors affecting loading rate. First, the distribution of transportation points and route planning. For example, secondary transfer stations that are very close to each other may require passing through a primary transfer station before reaching the secondary transfer station. Second, the distribution of cargo weight and volume. There is a significant difference between the weight ratio and volume ratio of cargo. That is, when the cargo is far less than half the load capacity of the vehicle, the volume has already filled the carriage. Third, whether the cargo supply is sufficient.

[0004] Traditional methods for calculating vehicle load factor typically involve on-site manual prediction based on experience or manual calculation. However, this approach has the problem that a large amount of data is not optimally utilized, is time-consuming and labor-intensive, and the accuracy of manual predictions cannot be guaranteed. Summary of the Invention

[0005] Therefore, it is necessary to provide a method, apparatus, computer equipment, and storage medium for calculating vehicle loading rate to address the aforementioned technical problems.

[0006] A method for calculating vehicle loading rate, the method comprising:

[0007] Obtain vehicle identification;

[0008] The type of transportation route the vehicle is on can be determined based on the vehicle identification identifier.

[0009] Calculate the vehicle's route loading rate on the transport route based on the transport route type;

[0010] Determine whether the line loading rate is between a preset upper quantile and a preset lower quantile;

[0011] If so, output the line loading rate of the vehicle on the transport route.

[0012] In one embodiment, the transport route type includes direct routes; calculating the route load factor of the vehicle on the transport route based on the transport route type includes:

[0013] The loading weight of the vehicle and the full load weight of the vehicle are obtained at the originating station on the transportation route, which is a direct route.

[0014] The ratio between the loading weight at the originating station and the full load weight of the vehicle is taken as the line loading rate of the vehicle on the transportation route.

[0015] In one embodiment, the transport route type includes a stopover route; calculating the route load rate of the vehicle on the transport route based on the transport route type includes:

[0016] Identify the loading and unloading type of the vehicle at each stop on the transportation route, which is a stop route.

[0017] If the loading and unloading type of each stop is loading only and not unloading, then obtain the cumulative value of the loading volume of each stop.

[0018] The ratio between the cumulative value of the cargo volume and the full load weight of the vehicle is taken as the route loading rate of the vehicle on the transportation route.

[0019] In one embodiment, after identifying the loading and unloading type of the vehicle at each stop on the transport route of the transit route type being a transit route, the method further includes:

[0020] If the loading and unloading types at each stop include both loading and unloading or only unloading, then the outgoing load at each stop is obtained; the outgoing load is the actual load of the vehicle when it departs after completing loading or unloading at the stop.

[0021] The maximum outgoing load is determined from the outgoing loads at each of the aforementioned stop points;

[0022] The ratio between the maximum outgoing load and the full load weight of the vehicle is taken as the line loading rate of the vehicle on the transportation route.

[0023] In one embodiment, after the step of determining whether the line load rate is between a preset upper quantile and a preset lower quantile, the method further includes:

[0024] If not, the load rate verification process will be triggered.

[0025] In one embodiment, the trigger load rate verification process includes:

[0026] If the vehicle's line loading rate on the transportation route is outside the preset upper and lower quantiles, a first prompt message is output; the first prompt message is used to prompt the adjustment of the load in the vehicle to reduce the line loading rate to the average loading rate.

[0027] In one embodiment, the vehicle loading rate calculation method runs on a big data platform; the big data platform includes Hadoop, Spark, and Hive tools.

[0028] A vehicle loading rate calculation device, the device comprising:

[0029] The vehicle identification module is used to obtain vehicle identification information.

[0030] The transportation route type query module is used to query the transportation route type of the vehicle based on the vehicle identification identifier.

[0031] The route loading rate calculation module is used to calculate the route loading rate of the vehicle on the transport route according to the type of transport route.

[0032] The interval judgment module is used to determine whether the line loading rate is between a preset upper quantile and a preset lower quantile.

[0033] The line loading rate output module is used to output the line loading rate of the vehicle on the transport route if the condition is met.

[0034] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps in the vehicle loading rate calculation method embodiment described above.

[0035] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the vehicle loading rate calculation method embodiment described above.

[0036] The aforementioned vehicle loading rate calculation method, apparatus, computer equipment, and storage medium acquire vehicle identification information, query the transportation route type of the vehicle based on the vehicle identification information, calculate the vehicle's loading rate on that transportation route based on the transportation route type, and determine whether the loading rate falls between a preset upper quantile and a preset lower quantile. If so, the loading rate of the vehicle on the transportation route is output. This method can replace traditional manual calculation of loading rates, is faster and more accurate, and can promptly output qualified loading rates, facilitating the screening of unqualified loading rates for further adjustment and processing. Attached Figure Description

[0037] Figure 1 This is an application environment diagram of the vehicle loading rate calculation method in one embodiment;

[0038] Figure 2 This is a flowchart illustrating a method for calculating vehicle loading rate in one embodiment;

[0039] Figure 3 This is a flowchart illustrating the vehicle loading rate calculation method in another embodiment;

[0040] Figure 4 This is a structural block diagram of a vehicle loading rate calculation device in one embodiment;

[0041] Figure 5 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0043] The vehicle loading rate calculation method provided in this application can be applied to, for example... Figure 1 In the application environment shown, terminal 101 communicates with server 102 via a network. Terminal 101 can be a terminal device used to measure and obtain the loading and unloading volume of a vehicle, such as, but not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. Server 102 can be implemented as a standalone server or a server cluster composed of multiple servers; in this application, it can be a big data computing platform.

[0044] In one embodiment, such as Figure 2 As shown, a method for calculating vehicle loading rate is provided, which can be applied to... Figure 1 Taking server 102 as an example, the explanation includes the following steps:

[0045] Step S201: Obtain vehicle identification;

[0046] Among them, vehicle identification refers to a certificate that can be used to uniquely identify a vehicle, such as a license plate number.

[0047] Specifically, vehicle identification information, such as license plate number, is obtained through terminals 101 distributed at various locations. Staff members, such as vehicle drivers, enter vehicle identification information, as well as arrival time, departure time, and loading / unloading details at each location, through terminals 101 at various locations. Server 101 obtains this detailed information and stores it in the database.

[0048] Step S202: Query the transportation route type of the transportation route where the vehicle is located based on the vehicle identification.

[0049] The transportation routes are categorized into two types: direct routes and routes with stops. A direct route means the vehicle departs from point A (the starting point) loaded with goods and proceeds directly to point B (the destination) for unloading without stopping at any other station. A route with stops means the vehicle passes through other stations between the starting and ending points, where unloading or loading operations are performed.

[0050] Specifically, the real-time status of vehicles at each station is recorded by terminal 101. The database stores the specific task information of each vehicle, such as a direct trip from A to B, or a trip from A to D after stopping at B and C for loading and unloading. Therefore, server 101 can query the database based on the vehicle's identification to find the type of transportation route on the current transportation route, such as a direct route or a stopover route.

[0051] Step S203: Calculate the line loading rate of the vehicle on the above-mentioned transportation route according to the transportation route type;

[0052] Among them, the route loading rate represents the amount of goods loaded on each vehicle on each route. This indicator can reflect whether the transported goods on each route are reasonably allocated and reflect the degree of control over information such as routes, customers, and orders in transportation management.

[0053] Specifically, the corresponding calculation method is selected based on the type of transportation route to calculate the route loading rate of the current vehicle on the transportation route. Different types of transportation routes correspond to different calculation methods.

[0054] Step S204: Determine whether the line loading rate is between the preset upper quantile and the preset lower quantile;

[0055] Specifically, an appropriate interval can be set according to historical statistical data or actual needs. This interval includes a preset upper quantile and a preset lower quantile. It is determined whether the calculated line load rate is within this interval (including the interval endpoints). That is, if the preset interval is [a, b], it is determined whether the line load rate is greater than or equal to a and less than or equal to b.

[0056] Step S205: If yes, output the line loading rate of the above vehicles on the above transportation route.

[0057] Specifically, if the calculated line load rate is within the range (including the endpoints of the range), the line load rate is output to a preset storage location or displayed on a display device.

[0058] In the above embodiment, a vehicle identification number is obtained, and the transportation route type of the vehicle is located is queried based on the vehicle identification number. The route loading rate of the vehicle on that transportation route is calculated based on the route type. It is then determined whether the route loading rate falls between a preset upper quantile and a preset lower quantile. If so, the route loading rate of the vehicle on the transportation route is output. This method can replace the traditional manual calculation of route loading rates, is faster and more accurate, and can promptly output qualified route loading rates. This facilitates the screening of unqualified route loading rates for further adjustment and processing, further improving the level of automated management of goods transported on the route.

[0059] In one embodiment, the above-mentioned transportation route type includes direct routes, and the above-mentioned step S203 includes: obtaining the loading weight of the vehicle at the originating station and the full load weight of the vehicle on the transportation route of the transportation route type of direct routes; and taking the ratio between the loading weight of the vehicle at the originating station and the full load weight of the vehicle as the route loading rate of the vehicle on the transportation route.

[0060] The loading weight at the originating station refers to the total weight of goods loaded onto the vehicle at the originating station. Generally, the originating station only loads goods and does not unload them. Therefore, this weight can be understood as the vehicle's departure weight at the originating station, i.e., the actual weight of goods loaded on the vehicle at departure. The full load weight refers to the weight of goods when the vehicle is fully loaded. Here, the full load weight refers to the calculated full load weight after loading different types of goods onto vehicles of different models, lengths, brands, and uses. It varies for different models but is comparable for vehicles of the same series. Specifically, when the transportation route is a direct route, the route loading rate = total weight of waybills on the route / full load weight of the vehicle. For example, if a route starts at point A with 50kg loaded and is fully loaded with 100kg, then the total weight on this route is 50kg, and the route loading rate is (50 / 100)*100% = 50%.

[0061] In the above embodiment, the line loading rate of the direct route is obtained by determining that the transportation route type is a direct route and combining it with the corresponding calculation method, which facilitates further processing of the line loading rate.

[0062] In one embodiment, the above-mentioned transportation route type includes a stop route, and the above-mentioned step S203 includes: identifying the loading and unloading type of the vehicle at each stop on the transportation route of the stop route; if the loading and unloading type of each stop is loading only and not unloading, then obtaining the cumulative value of the loading volume at each stop; and taking the ratio between the cumulative value of the loading volume and the full load weight of the vehicle as the route loading rate of the vehicle on the transportation route.

[0063] Specifically, a stopover route is one that requires stopping at other stations along the way for loading and unloading operations. If loading is only done at the stopover points and no unloading is performed, then the loading rate = cumulative waybill weight on the route / vehicle's full load weight. For example, if a route starts at point A and loads 30kg, stops at point B and loads 20kg, stops at point C and loads 10kg, for a full load of 100kg, then the cumulative weight on this route is 30 + 20 + 10 = 60kg, and the loading rate is (60 / 100) * 100% = 60%.

[0064] In the above embodiment, the loading rate of the transit route is obtained by determining that the transportation route is a stopover route and that it is a loading-only route. This is combined with the corresponding calculation method to facilitate further processing of the loading rate.

[0065] In one embodiment, after identifying the loading and unloading type of the vehicle at each stop on the transport route of the transit route type being a transit route, the method further includes:

[0066] If the loading and unloading types at each stop include both loading and unloading or only unloading, then the outgoing load at each stop is obtained; the outgoing load is the actual load when the vehicle departs after completing loading or unloading at the stop; the maximum outgoing load is determined from the outgoing loads at each stop; the ratio between the maximum outgoing load and the vehicle's full load weight is taken as the vehicle's line loading rate on the transportation route.

[0067] Specifically, if loading and unloading occur at stop points, the line loading rate = maximum outgoing waybill weight at stop points on the line / vehicle full load weight. For example, if 40kg is loaded at the originating point A, 30kg is loaded and 10kg is unloaded at stop point B, and 10kg is loaded and 30kg is unloaded at stop point C, with a full load of 100kg, then the outgoing weight at point A is 40kg, the outgoing weight at point B is 40+30-10=60kg, and the outgoing weight at point C is 60+10-30=40kg. Therefore, the maximum outgoing weight on this line is at point B, and the loading rate is (60 / 100)*100%=60%.

[0068] If unloading is only done at the stopover points and no loading is done at the stopover points, the line loading rate = maximum outgoing waybill weight at the stopover points on the line / vehicle full load weight. For example, if 100kg is loaded at the origin point A, then 20kg is unloaded at the stopover point B, and 10kg is unloaded at the stopover point C, resulting in a full load of 100kg, then the outgoing weight at point A is 100kg, the outgoing weight at stopover point B is 100-20=80kg, and the outgoing weight at stopover point C is 80-10=70kg. Therefore, the maximum outgoing weight is at point A, and the loading rate is (100 / 100)*100%=100%.

[0069] In the above embodiments, by determining that the transportation route type is a stopover route and that it is a loading and unloading type or a unloading-only type, the route loading rate of the stopover route is obtained by combining the corresponding calculation method, which facilitates further processing of the route loading rate.

[0070] In one embodiment, after step S204, the method further includes: if not, triggering a load rate verification process.

[0071] Specifically, if the calculated line load rate is higher than the preset upper digit or lower than the preset lower digit, the load rate verification process is triggered, which involves extracting the line and the corresponding vehicle number and outputting them to the corresponding processing terminal for further processing.

[0072] The above embodiments, by extracting the load rates of lines that do not meet the requirements and triggering the load rate verification process, facilitate the improvement of logistics management.

[0073] In one embodiment, the above-mentioned trigger load rate verification process includes: if the line load rate of the vehicle on the transportation route is outside the preset upper quantile and the preset lower quantile, then outputting a first prompt message; the first prompt message is used to prompt the adjustment of the load in the vehicle to reduce the line load rate to the average load rate.

[0074] Specifically, when the load rate of a route is higher than the preset upper threshold or lower than the preset lower threshold, the route and its corresponding vehicle identification number can be extracted to form a first alert message, which is sent to the corresponding processing terminal to prompt relevant personnel to perform a loading rate verification. This verification is based on the calculated load rate. For routes with high load rates, the high proportion of small documents in the shipments is considered. The load rate is then adjusted to match the average load of goods carried by vehicles of the same type, distance, and direction to reach the average load rate. Furthermore, it's important to check for vehicle-shipment separation on high-load-rate routes. For example, if a shipment is shown as loaded at point A on this route but is not actually on the vehicle, this can be determined by checking for unloading operations at subsequent stops or destinations. If no unloading operation occurs, the weight corresponding to this shipment needs to be removed to correct the load rate. For low-load routes carrying larger shipments, such as cotton (which is bulky but lightweight), scientific loading methods, such as a proper mix of heavy and light cargo, are needed to improve the load rate.

[0075] The above embodiments, by triggering specific loading rate verification processes, facilitate timely adjustment of transshipment rates and improve logistics management.

[0076] In one embodiment, the above-described vehicle loading rate calculation method runs on a big data platform; the big data platform includes Hadoop, Spark, and Hive tools.

[0077] Specifically, the vehicle loading rate calculation method in this application can be cleverly combined with Spark + Hadoop + Hive tools for processing. Spark is a fast and general-purpose computing engine for large-scale data processing; Hadoop is an open-source framework that allows writing and running distributed applications to process large-scale data, designed specifically for offline and large-scale data analysis; Hadoop includes HDFS (Hadoop Distributed File System, used for data storage) and MapReduce (used for data processing); Hive is a data warehouse tool; it is a wrapper around MapReduce, and its underlying implementation is a MapReduce program; Hive can map structured data files (e.g., data categorized by fields) into a virtual table and provide SQL-like query functionality. This vehicle loading rate calculation system includes a data acquisition component and a data processing component, wherein:

[0078] 1) Data acquisition component:

[0079] 1.1 Vehicle transportation information (including loading weight, unloading weight, vehicle loading rate, and transportation route type at each station) is collected through terminal tracking. This information is then sent to the business system (which includes a front-end and a back-end) and stored in multiple MySQL databases on the front-end. In response to user data processing requests, the front-end synchronizes the corresponding target data to a Kafka cluster in real-time via MySQL binlog (for real-time computation). The Kafka cluster consumes this target data and synchronizes it in real-time to Hadoop's HDFS (Hadoop Distributed File System), mapping it to HIVE tables (for offline computation). This method allows users to promptly identify vehicles with loading rate issues and track and locate problems, ensuring the normal operation of the transportation process.

[0080] 1.2 Synchronization of basic parcel information (basic parcel information includes waybill number, sender and recipient basic information such as sender and recipient name, address, telephone number, customer monthly billing card number, product type, delivery time, freight, weight, consigned items, etc.), directly consumes the two Kafka topics provided by the parcel system for operating and calculating waybills. The consumed data is parsed into structured data and written to the Hadoop HDFS system, and mapped to Hive tables; the consumed data is also written to HBase as cache data for real-time calculation.

[0081] 1.3 Synchronization of express loading and unloading operation information: Direct consumption of express routing Kafka topic information provided by the comprehensive visualization system; consumption data is parsed into structured data and written into the Hadoop HDFS system, and mapped to Hive tables.

[0082] 2) Data processing components

[0083] The data processing component can process data in both offline and real-time states, as follows:

[0084] 2.1 Offline status:

[0085] 2.1.1 Utilizing the Spark and MapReduce computing frameworks for big data, a batch processing job is launched to read data from Hive tables. During the batch processing job, the loading and unloading operations (2-10 times) of each express shipment generate tens of millions or even hundreds of millions of shipment routing information. The data from loading and unloading operations at each stop is sorted, summarized, and compared to obtain the dispatch weight of each express shipment at each stop. This type of task uses the Spark-submit method to submit SparkSQL tasks to YARN for execution. For computational tasks involving route loading and vehicle transportation information with data volumes in the millions, Hive tasks are generated and submitted to YARN for execution. Combining the above information on routes, vehicle transportation, and express shipment loading and unloading operations, the dispatch weight at each stop and the corresponding weight distribution of various products are calculated. The dispatch weights at each stop are merged and sorted, and the largest dispatch weight is selected as the loading weight (i.e., the numerator of the loading rate). Simultaneously, the weight distribution of various products corresponding to the loading weight is obtained.

[0086] 2.1.2 The vehicle weight loading rate results are mainly stored in the Hadoop HDFS system and mapped to Hive tables for use by data analysis and visualization tools.

[0087] 2.2 Real-time status:

[0088] 2.2.1 Using SparkStream+Kafka+HBASE, we consume real-time route loading and vehicle transportation information data from Kafka. We assign a unique identifier, or vehicle tag, to each vehicle for each shipment loaded at each stop. When the vehicle tag is not empty, it means there are shipments on the vehicle and it is being transported normally. This triggers a calculation, which parses the shipment loading and unloading information on the vehicle tag. The shipment loading and unloading operation records are sorted, summarized, and compared to obtain the dispatch weight of each shipment at each stop. After summarizing and calculating the dispatch weight of each stop, the dispatch weights of each stop are merged and sorted. The largest dispatch weight is selected as the loading weight, i.e., the numerator of the loading rate. If the vehicle tag is empty, the vehicle information is considered as planned transportation information, meaning the shipment has not been loaded and is discarded.

[0089] 2.2.2 The vehicle weight loading rate results are mainly stored in Tidb (for visualization tools) and ElasticSearch (for fast searching).

[0090] The above embodiments improve the calculation speed by combining the vehicle loading rate calculation method with big data computing tools, which is beneficial for real-time allocation of goods and vehicles after outputting the loading rate in actual logistics scenarios.

[0091] In one embodiment, such as Figure 3 As shown, Figure 3 The flowchart illustrates a method for calculating vehicle load-carrying rate in a specific application scenario, which roughly includes the following steps:

[0092] 1. Determine whether the route is direct or involves a stopover:

[0093] Direct routes: The loading rate of a route = the total weight of the waybill on the route / the full load weight of the vehicle. For example, if a route starts at point A and is loaded with 50kg, and is fully loaded with 100kg, then the total weight on this route is 50kg, and the loading rate is (50 / 100)*100%=50%.

[0094] Stopover routes: If loading is only done at the stopover point and no unloading is done, then the loading rate = cumulative waybill weight on the route / full load weight of the vehicle. For example, if a route starts at point A and loads 30kg, stops at point B and loads 20kg, stops at point C and loads 10kg, with a full load of 100kg, then the cumulative weight on this route is 30 + 20 + 10 = 60kg, and the loading rate is (60 / 100) * 100% = 60%.

[0095] If loading and unloading occur at stopover points, the line loading rate = maximum outgoing waybill weight at each stopover point / vehicle full load weight. For example, if 40kg is loaded at origin point A, 30kg is loaded and 10kg is unloaded at stopover point B, and 10kg is loaded and 30kg is unloaded at stopover point C, resulting in a full load of 100kg, then the outgoing weight at point A is 40kg, the outgoing weight at point B is 40 + 30 - 10 = 60kg, and the outgoing weight at point C is 60 + 10 - 30 = 40kg. Therefore, the maximum outgoing weight on this line is at point B, and the loading rate is (60 / 100) * 100% = 60%.

[0096] If unloading is only done at the stopover points and no loading is done at the stopover points, the line loading rate = maximum outgoing waybill weight at the stopover points on the line / vehicle full load weight. For example, if 100kg is loaded at the origin point A, then 20kg is unloaded at the stopover point B, and 10kg is unloaded at the stopover point C, resulting in a full load of 100kg, then the outgoing weight at point A is 100kg, the outgoing weight at stopover point B is 100-20=80kg, and the outgoing weight at stopover point C is 80-10=70kg. Therefore, the maximum outgoing weight is at point A, and the loading rate is (100 / 100)*100%=100%.

[0097] 2. Loading Rate Verification: Based on the calculated loading rate above, verification is performed. For routes with high loading rates, is it due to a high proportion of small documents among the consignments? The loading rate for such routes is adjusted to match the average load capacity of vehicles of the same type, distance, and direction. Additionally, is vehicle-part separation observed on high-loading-rate routes? For example, if a shipment is shown as loaded at point A on this route but is not actually on the vehicle, this can be determined by checking for unloading operations at subsequent stopovers or destinations. If no unloading occurs, the shipment needs to be removed, and the loading rate corrected. For low-loading routes handling larger consignments, such as cotton, the loading rate needs to be improved through scientific loading methods, such as a proper mix of heavy and light cargo.

[0098] The above embodiments provide a method for calculating the weight loading rate based on logistics transportation scenarios under different route types, and can verify and correct the loading rate, which can be applied to real-time allocation of goods and vehicles.

[0099] It should be understood that, although Figure 1-3 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1-3 At least some of the steps in the process may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but may be executed at different times. The execution order of these steps or stages is not necessarily sequential, but may be executed in turn or alternately with other steps or at least some of the steps or stages in other steps.

[0100] In one embodiment, such as Figure 4 As shown, a vehicle loading rate calculation device 400 is provided, including: a vehicle identification module 401, a transportation route type query module 402, a route loading rate calculation module 403, a section judgment module 404, and a route loading rate output module 405, wherein:

[0101] Vehicle identification module 401 is used to acquire vehicle identification;

[0102] The transportation route type query module 402 is used to query the transportation route type of the transportation route to which the vehicle is located based on the vehicle identification identifier;

[0103] The route loading rate calculation module 403 is used to calculate the route loading rate of the vehicle on the transport route according to the type of transport route.

[0104] The interval judgment module 404 is used to determine whether the line loading rate is between a preset upper quantile and a preset lower quantile;

[0105] The line loading rate output module 405 is used to output the line loading rate of the vehicle on the transport route if the condition is met.

[0106] In one embodiment, the transportation route type includes a direct route; the route loading rate calculation module 403 is further configured to: obtain the loading weight at the originating station and the full load weight of the vehicle on the transportation route of the direct route type; and use the ratio between the loading weight at the originating station and the full load weight of the vehicle as the route loading rate of the vehicle on the transportation route.

[0107] In one embodiment, the transportation route type includes a stop route; the route loading rate calculation module 403 is further configured to: identify the loading and unloading type of the vehicle at each stop on the transportation route of the stop route type; if the loading and unloading type of each stop is a loading-only-no-unloading type, then obtain the cumulative loading amount of each stop; and use the ratio between the cumulative loading amount and the full load weight of the vehicle as the route loading rate of the vehicle on the transportation route.

[0108] In one embodiment, the line load rate calculation module 403 is further configured to:

[0109] If the loading and unloading types at each stop include both loading and unloading or only unloading, then the outgoing load at each stop is obtained; the outgoing load is the actual load of the vehicle when it departs after completing loading or unloading at the stop; the maximum outgoing load is determined from the outgoing loads at each stop; the ratio between the maximum outgoing load and the full load weight of the vehicle is taken as the route loading rate of the vehicle on the transportation route.

[0110] In one embodiment, the line load rate output module 405 is further configured to: if not, trigger a load rate verification process.

[0111] In one embodiment, a loading rate verification unit is further included, configured to: output a first prompt message if the line loading rate of the vehicle on the transportation route is outside the preset upper quantile and the preset lower quantile; the first prompt message is used to prompt the adjustment of the load in the vehicle to reduce the line loading rate to the average loading rate.

[0112] In one embodiment, the vehicle loading rate calculation method runs on a big data platform; the big data platform includes Hadoop, Spark, and Hive tools.

[0113] Specific limitations regarding the vehicle loading rate calculation device can be found in the limitations of the vehicle loading rate calculation method described above, and will not be repeated here. Each module in the aforementioned vehicle loading rate calculation device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0114] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 5 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores route station information, vehicle numbers, vehicle load rates, and cargo-related data. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a method for calculating vehicle load rates.

[0115] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0116] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps as described in the vehicle loading rate calculation method embodiment above.

[0117] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps as described in the vehicle loading rate calculation method embodiment above.

[0118] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0119] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0120] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for calculating vehicle loading rate, characterized in that, Applied to a big data computing platform, the method includes: In response to a data processing request, the vehicle identification and loading / unloading operation information of each parcel during vehicle transportation are obtained; the vehicle identification and the loading / unloading operation information are collected through terminals distributed at various stations and synchronized to the big data computing platform. Based on the vehicle identification, query the database to determine the transportation route type of the transportation route the vehicle is on; Calculating the vehicle's route loading rate on the transportation route based on the transportation route type and the express loading and unloading operation information includes: identifying the loading and unloading type of the vehicle at each stop on the transportation route type of a stop route; if the loading and unloading type at each stop is a loading-only type, then obtaining the cumulative loading amount at each stop based on the vehicle's express loading and unloading operation information; using the ratio between the cumulative loading amount and the vehicle's full load weight as the vehicle's route loading rate on the transportation route; if the loading and unloading types at each stop include both loading and unloading types or only unloading types, then obtaining the outgoing loading amount at each stop based on the vehicle's express loading and unloading operation information; the outgoing loading amount is the actual loading amount of the vehicle when it departs after completing loading or unloading at the stop; determining the maximum outgoing loading amount from the outgoing loading amounts at each stop; and using the ratio between the maximum outgoing loading amount and the vehicle's full load weight as the vehicle's route loading rate on the transportation route. Determine whether the line loading rate is between a preset upper quantile and a preset lower quantile; If so, output the line loading rate of the vehicle on the transportation route; If not, the loading rate verification process is triggered, including: if the vehicle's line loading rate on the transportation route is outside the preset upper and lower quantiles, a first prompt message is obtained based on the transportation route and the vehicle's identification, and the first prompt message is output to the processing terminal; the first prompt message is used to prompt the adjustment of the load in the vehicle so that the line loading rate correction reaches the average loading rate.

2. The method according to claim 1, characterized in that, The transportation route type includes direct routes; the calculation of the vehicle's route loading rate on the transportation route based on the transportation route type and the express loading and unloading operation information includes: The loading weight at the originating station and the full load weight of the vehicle are obtained for the transportation route type of direct route; the loading weight at the originating station is obtained based on the express loading and unloading operation information of the vehicle. The ratio between the loading weight at the originating station and the full load weight of the vehicle is taken as the line loading rate of the vehicle on the transportation route.

3. The method according to any one of claims 1 to 2, characterized in that, The vehicle loading rate calculation method runs on a big data platform; the big data platform includes Hadoop, Spark, and Hive tools; wherein Hadoop is used to obtain vehicle transportation information; Spark is used to calculate the route loading rate; and Hive is used to store and query the vehicle transportation information and the route loading rate.

4. A vehicle loading rate calculation device, characterized in that, The device, applied to a big data computing platform, includes: The vehicle identification module is used to respond to data processing requests and acquire vehicle identification and express loading and unloading operation information of each express item during vehicle transportation; the vehicle identification and the express loading and unloading operation information are collected by terminals distributed at various stations and synchronized to the big data computing platform. The transportation route type query module is used to query the database for the transportation route type of the vehicle based on the vehicle identification identifier. The route loading rate calculation module is used to calculate the route loading rate of the vehicle on the transportation route based on the transportation route type and the express loading and unloading operation information. This includes: identifying the loading and unloading type of the vehicle at each stop on the transportation route type of a stop route; if the loading and unloading type at each stop is a loading-only type, then obtaining the cumulative loading volume at each stop based on the vehicle's express loading and unloading operation information; using the ratio between the cumulative loading volume and the vehicle's full load weight as the route loading rate of the vehicle on the transportation route; if the loading and unloading types at each stop include both loading and unloading types or only unloading types, then obtaining the outgoing loading volume at each stop based on the vehicle's express loading and unloading operation information; the outgoing loading volume is the actual loading volume of the vehicle when it departs after completing loading or unloading at the stop; determining the maximum outgoing loading volume from the outgoing loading volumes at each stop; and using the ratio between the maximum outgoing loading volume and the vehicle's full load weight as the route loading rate of the vehicle on the transportation route. The interval judgment module is used to determine whether the line loading rate is between a preset upper quantile and a preset lower quantile. The route loading rate output module is used to output the route loading rate of the vehicle on the transportation route if the condition is met; otherwise, it triggers a loading rate verification process, including: if the route loading rate of the vehicle on the transportation route is outside a preset upper quantile and a preset lower quantile, a first prompt message is obtained based on the transportation route and the vehicle identification, and the first prompt message is output to the processing terminal; the first prompt message is used to prompt the adjustment of the load in the vehicle so that the route loading rate correction reaches the average loading rate.

5. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 3.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 3.

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