Vehicle cargo loading method, device, computer equipment and storage medium

Abstract

The present application provides a vehicle cargo loading method, device, computer equipment and storage medium, which relate to the field of logistics and transportation technology. The method includes: obtaining the target weather forecast information of the pre-planned logistics transportation route within a preset future time period; according to the target weather forecast information, using a preset vehicle cargo loading model, determining the transportation cargo corresponding to the target weather forecast information as the candidate transportation cargo, determining the transportation vehicle type corresponding to the candidate transportation cargo as the candidate transportation vehicle type, and generating a vehicle cargo loading result, the vehicle cargo loading result includes: information of the logistics transportation route, information of the preset future time period, information of the candidate transportation cargo and information of the candidate transportation vehicle type, and the vehicle cargo loading result is used to indicate that the candidate transportation cargo is transported along the logistics transportation route using the candidate transportation vehicle type within the preset future time period. The present application can determine the best vehicle cargo loading plan according to weather conditions to improve the efficiency and safety of cargo transportation.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics management, and in particular to a vehicle cargo loading method, device, computer equipment and storage medium. Background Art

[0002] Vehicle transportation is an important mode of transportation. With the development of social economy and the continuous improvement of road network construction, vehicle transportation has provided more and more enterprises and people with faster and more borderless services.

[0003] The weather conditions during cargo transportation are the main factors affecting the timeliness of cargo transportation. For example, bad weather conditions will seriously increase the cargo transportation time, which is fatal to some goods with high timeliness requirements. Therefore, how to decide the type of cargo to be transported and the type of vehicle used to transport the cargo according to the weather conditions during transportation is crucial to improving the efficiency and safety of cargo transportation. Summary of the invention

[0004] The purpose of the present invention is to provide a vehicle cargo p loading method, device, computer equipment and storage medium to address the deficiencies in the above-mentioned prior art, so as to determine the best vehicle cargo loading plan according to weather conditions and improve the efficiency and safety of cargo transportation.

[0005] To achieve the above purpose, the technical solution adopted in the embodiment of the present application is as follows:

[0006] In a first aspect, an embodiment of the present application provides a method for loading cargo on a vehicle, the method comprising:

[0007] Obtain target weather forecast information for pre-planned logistics transportation routes within a preset future time period;

[0008] According to the target weather forecast information, a preset vehicle cargo loading model is used to determine the transport cargo corresponding to the target weather forecast information as a candidate transport cargo, and to determine the transport vehicle type corresponding to the candidate transport cargo as a candidate transport vehicle type; wherein the vehicle cargo loading model is pre-integrated with: a correspondence between preset weather information and transport cargo, and a correspondence between preset transport cargo and transport vehicle type;

[0009] Generate a vehicle cargo loading result, the vehicle cargo loading result including: information of the logistics transportation route, information of the preset future time period, information of the candidate transportation cargo and information of the candidate transportation vehicle type, the vehicle cargo loading result is used to indicate that the candidate transportation cargo is transported along the logistics transportation route using the candidate transportation vehicle type within the preset future time period.

[0010] Optionally, the obtaining of target weather forecast information for a pre-planned logistics transportation route within a preset future time period includes:

[0011] Obtaining the predicted arrival time of each location point in the logistics transportation route within the preset future time period;

[0012] According to the predicted arrival time of each location point and the location information of each location point, query the weather forecast information of each location point at the corresponding predicted arrival time;

[0013] The target weather forecast information is determined according to the weather forecast information of each location point at the corresponding predicted arrival time.

[0014] Optionally, querying weather forecast information of each location point at a corresponding predicted arrival time according to the predicted arrival time of each location point and the location information of each location point includes:

[0015] Obtaining a weather forecast database for the preset future time period in the preset area where the logistics transportation route is located;

[0016] According to the predicted arrival time of each location point and the location information of each location point, the weather forecast information of each location point at the corresponding predicted arrival time is queried from the weather forecast database.

[0017] Optionally, before generating the vehicle cargo loading result, the method further includes:

[0018] Calculating the transportation cost of the candidate transportation cargo according to the weather information influence coefficient of the candidate transportation cargo and the target weather forecast information;

[0019] The vehicle cargo loading result also includes: the transportation cost of the candidate transportation cargo.

[0020] Optionally, before calculating the transportation cost of the candidate transported goods according to the weather information influence coefficient of the candidate transported goods and the target weather forecast information, the method further includes:

[0021] Obtaining a variety of weather forecast information for a plurality of locations in the logistics transportation route at corresponding predicted arrival times;

[0022] The weather information impact coefficient of the target weather forecast information is calculated based on the preset impact coefficients of the candidate transport cargo in the multiple weather forecast information and the time proportion of each weather forecast information in the preset future time period.

[0023] Optionally, before calculating the weather information impact coefficient of the target weather forecast information according to the preset impact coefficients of the candidate transported goods in the multiple weather forecast information and the time proportion of each weather forecast information in the preset future time period, the method further includes:

[0024] Acquire multiple historical transportation costs corresponding to the multiple historical weather information of the candidate transported goods within a preset historical time period; the preset historical time period is a historical time period corresponding to a preset time period to which the preset future time period belongs, and the preset time period and the historical time period are the same time period in years;

[0025] The preset impact coefficient is calculated according to the multiple historical weather information and the multiple historical transportation costs.

[0026] Optionally, before determining, based on the target weather forecast information, using a preset vehicle cargo loading model to determine that the transport cargo corresponding to the target weather forecast information is the candidate transport cargo, and determining that the transport vehicle type corresponding to the candidate transport cargo is the candidate transport vehicle type, the method further includes:

[0027] The vehicle cargo loading model is established based on the transport cargo matched with various weather information and the transport vehicle types matched with various transport cargoes.

[0028] In a second aspect, an embodiment of the present application further provides a vehicle cargo loading device, the device comprising:

[0029] An acquisition module is used to obtain target weather forecast information for a pre-planned logistics transportation route within a preset future time period;

[0030] A loading module is used to determine, according to the target weather forecast information, the transported goods corresponding to the target weather forecast information as candidate transported goods, and to determine the transport vehicle type corresponding to the candidate transported goods as the candidate transport vehicle type by using a preset vehicle cargo loading model; wherein the vehicle cargo loading model pre-integrates: a correspondence between preset weather information and transported goods, and a correspondence between preset transported goods and transport vehicle types;

[0031] A result generation module is used to generate a vehicle cargo loading result, wherein the vehicle cargo loading result includes: information of the logistics transportation route, information of the preset future time period, information of the candidate transportation cargo, and information of the candidate transportation vehicle model. The vehicle cargo loading result is used to indicate that the candidate transportation cargo is transported along the logistics transportation route using the candidate transportation vehicle model within the preset future time period.

[0032] Optionally, the acquisition module includes:

[0033] An arrival time acquisition unit, used to acquire the predicted arrival time of each location point in the logistics transportation route within the preset future time period;

[0034] A weather forecast information query unit, configured to query the weather forecast information of each location point at the corresponding predicted arrival time according to the predicted arrival time of each location point and the location information of each location point;

[0035] The target weather forecast information determination unit is used to determine the target weather forecast information according to the weather forecast information of each location point at the corresponding predicted arrival time.

[0036] Optionally, the weather forecast information query unit includes:

[0037] A weather forecast database acquisition subunit, used to acquire a weather forecast database in a preset future time period in a preset area where the logistics transportation route is located;

[0038] The weather forecast information query subunit is used to query the weather forecast information of each location point at the corresponding predicted arrival time from the weather forecast database according to the predicted arrival time of each location point and the location information of each location point.

[0039] Optionally, the device further comprises:

[0040] A transportation cost calculation module, used to calculate the transportation cost of the candidate transportation goods according to the weather information influence coefficient of the candidate transportation goods and the target weather forecast information;

[0041] The vehicle cargo loading result also includes: the transportation cost of the candidate transportation cargo.

[0042] Optionally, the device further comprises:

[0043] A weather forecast information acquisition module, used to acquire a variety of weather forecast information at a plurality of locations in the logistics transportation route at corresponding predicted arrival times;

[0044] The weather information impact coefficient calculation module is used to calculate the weather information impact coefficient of the target weather forecast information based on the preset impact coefficients of the candidate transport goods in the multiple weather forecast information and the time proportion of each weather forecast information in the preset future time period.

[0045] Optionally, the device further comprises:

[0046] A historical transportation cost acquisition module is used to acquire a plurality of historical transportation costs corresponding to the candidate transported goods under a plurality of historical weather information within a preset historical time period; the preset historical time period is a historical time period corresponding to a preset time period to which the preset future time period belongs, and the preset time period and the historical time period are the same time period in years;

[0047] The preset impact coefficient calculation module is used to calculate the preset impact coefficient according to the multiple historical weather information and the multiple historical transportation costs.

[0048] Optionally, the device further comprises:

[0049] The model building module is used to build the vehicle cargo loading model according to the transport cargo matched with a plurality of weather information and the transport vehicle types matched with a plurality of transport cargoes.

[0050] In a third aspect, an embodiment of the present application further provides a computer device, comprising: a processor, a storage medium and a bus, wherein the storage medium stores program instructions executable by the processor, and when the computer device is running, the processor communicates with the storage medium via the bus, and the processor executes the program instructions to perform the steps of the vehicle cargo loading method as described in any of the above embodiments.

[0051] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the vehicle cargo loading method as described in any of the above embodiments are executed.

[0052] The beneficial effects of this application are:

[0053] The present application provides a vehicle cargo loading method, device, computer equipment and storage medium, which obtains the target weather forecast information of the pre-planned logistics transportation route in a preset future time period; according to the target weather forecast information, a preset vehicle cargo loading model is used to determine the transportation cargo corresponding to the target weather forecast information as the candidate transportation cargo, and the transportation vehicle type corresponding to the candidate transportation cargo is determined as the candidate transportation vehicle type, wherein the vehicle cargo loading model is pre-integrated with: the correspondence between the preset weather information and the transportation cargo, and the correspondence between the preset transportation cargo and the transportation vehicle type; generate a vehicle cargo loading result, the vehicle cargo loading result includes: information of the logistics transportation route, information of the preset future time period, information of the candidate transportation cargo and information of the candidate transportation vehicle type, and the vehicle cargo loading result is used to indicate that the candidate transportation cargo is transported along the logistics transportation route using the candidate transportation vehicle type in the preset future time period. Based on the target weather forecast information, the present application uses the vehicle cargo loading model to determine the candidate transportation cargo and the candidate transportation vehicle type, which can fully consider the cargo suitable for transportation in different weather conditions, and select the most matching transportation vehicle type for the cargo, so as to ensure the safety of the cargo during transportation and improve the efficiency of cargo transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0055] Figure 1 A schematic diagram of the structure of a vehicle cargo loading system provided in an embodiment of the present application;

[0056] Figure 2 A schematic diagram of a vehicle cargo loading method provided in an embodiment of the present application;

[0057] Figure 3 A structural schematic diagram of a vehicle cargo loading model provided in an embodiment of the present application;

[0058] Figure 4 A schematic diagram of a flow chart of another method for loading cargo onto a vehicle provided in an embodiment of the present application;

[0059] Figure 5 A schematic diagram of dividing logistics transportation routes provided in an embodiment of the present application;

[0060] Figure 6 A schematic diagram of a flow chart of another vehicle cargo loading method provided in an embodiment of the present application;

[0061] Figure 7 A schematic diagram of a flow chart of another vehicle cargo loading method provided in an embodiment of the present application;

[0062] Figure 8 A schematic diagram of the structure of a vehicle cargo loading device provided in an embodiment of the present application;

[0063] Fig. 9 A schematic diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments.

[0065] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for which protection is sought, but merely represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0066] The terms "including" and "having" and any variations thereof in the description and claims of the present invention are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products or apparatuses.

[0067] It should be noted that, in the absence of conflict, the features in the embodiments of the present application may be combined with each other.

[0068] The vehicle cargo loading method provided in the embodiment of the present application is applied to a vehicle cargo loading system on a computer device. The vehicle cargo loading system is run on the computer device to execute the vehicle cargo loading method provided in the embodiment of the present application and generate a vehicle cargo loading result.

[0069] Please refer to Figure 1 , is a structural diagram of a vehicle cargo loading system provided in an embodiment of the present application, such as Figure 1 As shown, the vehicle cargo loading system includes: a vehicle cargo loading device 10, a route planning device 20, and a meteorological center 30.

[0070] The vehicle cargo loading device 10 and the route planning device 20 are both software devices running on a computer device. The vehicle cargo loading device 10 is connected to the path planning device 20 in communication. The transportation starting point and the transportation end point are input into the path planning device 20 to generate a logistics transportation route in the path planning device 20. The vehicle cargo loading device 10 obtains the logistics transportation route from the path planning device 20. In a possible implementation, if the path planning device 20 generates multiple logistics transportation routes based on the transportation starting point and the transportation end point, the best logistics transportation route can be selected from the multiple logistics transportation routes according to the preset route selection rules. For example, the preset route selection rules can be the shortest distance, the least highway toll, the least number of traffic lights, etc., which are not limited in this application.

[0071] The vehicle cargo loading device 10 is also connected in communication with the meteorological center 30 to obtain from the meteorological center 30 a weather forecast database for a preset future time period in a preset area where the logistics transportation route is located, and based on the logistics transportation route and the preset future time period for transportation, query the target weather forecast information for the pre-planned logistics transportation route within the preset future time period from the weather forecast database.

[0072] The vehicle cargo loading device 10 is pre-configured with a vehicle cargo loading model 11, so that according to the target weather forecast information, the vehicle cargo loading model 11 is used to determine that the transport cargo corresponding to the target weather forecast information is the candidate transport cargo, determine the transport vehicle type corresponding to the candidate transport cargo as the candidate transport vehicle type, and generate a vehicle cargo loading result, the vehicle cargo loading result includes: information on the logistics transportation route, information on the preset future time period, information on the candidate transport cargo and information on the candidate transport vehicle type, and the vehicle cargo loading result is used to indicate that the candidate transport cargo is transported along the logistics transportation route using the candidate transport vehicle type within the preset future time period.

[0073] In an optional embodiment, the vehicle cargo loading system also includes: a weather forecast device, which is in communication with the meteorological center 30 to periodically and synchronously obtain weather forecast information for a preset area where the logistics transportation route is located from the meteorological center, store the weather forecast information in a weather forecast database, and input the logistics transportation route and the preset future time period into the weather forecast device, so that the weather forecast device determines the target weather forecast information from the weather forecast database based on the logistics transportation route and the preset future time period.

[0074] Based on the above vehicle cargo loading system, the present application embodiment also provides a vehicle cargo loading method. Figure 2 , is a flow chart of a vehicle cargo loading method provided in an embodiment of the present application, such as Figure 2 As shown, the method includes:

[0075] S10: Obtain target weather forecast information for a pre-planned logistics transportation route within a preset future time period.

[0076] In this embodiment, the pre-planned logistics transportation route is the optimal logistics transportation route determined by the path planning device according to the transportation starting point and transportation end point input by the transportation dispatcher, and the preset future time period is the estimated transportation time period calculated according to the preset departure time, the distance length of the logistics transportation route, and the average speed limit of the logistics transportation route. After determining the logistics transportation route and the preset future time period of transportation, the target weather forecast information on the logistics transportation route within the preset future time period is obtained from the meteorological center; or the target weather forecast information on the logistics transportation route within the preset future time period is obtained from the meteorological center.

[0077] S20: According to the target weather forecast information, a preset vehicle cargo loading model is used to determine the transport cargo corresponding to the target weather forecast information as the candidate transport cargo, and determine the transport vehicle model corresponding to the candidate transport cargo as the candidate transport vehicle model.

[0078] In this embodiment, the vehicle cargo loading model is pre-integrated with: the correspondence between preset weather information and transported cargo, and the correspondence between preset transported cargo and transport vehicle type. The vehicle cargo loading device uses the vehicle cargo loading model to determine, based on the preset target weather information obtained from the meteorological center, that the transported cargo corresponding to the target weather forecast information is the candidate transported cargo, and determines the transport vehicle type corresponding to the candidate transported cargo as the candidate transport vehicle type.

[0079] In an optional embodiment, before the above S20, the method further includes:

[0080] A vehicle cargo loading model is established based on the transport goods matched with various weather information and the transport vehicle types matched with various transport goods.

[0081] In this embodiment, multiple historical transportation data are obtained, and the multiple historical transportation data include: multiple historical weather information, transportation goods and transportation vehicle types corresponding to each historical weather information, transportation duration, and transportation status of the goods. According to the multiple historical transportation data, transportation goods that match multiple weather information and transportation vehicle types that match multiple transportation goods are determined to establish a corresponding relationship between weather forecast information and transportation goods, and a corresponding relationship between transportation goods and transportation vehicle types, and obtain a vehicle cargo loading model. In an optional embodiment, the transportation goods that match multiple weather information and transportation vehicle types that match multiple transportation goods can be determined based on the experience of transportation dispatchers, or deep learning can be performed on multiple historical transportation data to determine the transportation goods that match multiple weather information and transportation vehicle types that match multiple transportation goods.

[0082] S30: Generate vehicle cargo loading results.

[0083] In this embodiment, after the vehicle cargo loading device determines the candidate transport cargo and the candidate transport vehicle model according to the vehicle cargo loading model, the vehicle cargo loading result is generated according to the information of the logistics transportation route, the information of the preset future time period, the information of the candidate transport cargo and the information of the candidate transport vehicle model. The vehicle cargo loading result is used to indicate the use of the candidate transport vehicle model to transport the candidate transport cargo along the logistics transportation route within the preset future time period.

[0084] In an optional embodiment, the vehicle cargo loading model corresponds to at least one candidate transport cargo for each weather information, and each candidate transport cargo corresponds to at least one candidate transport vehicle model. When the target weather forecast information corresponds to two candidate transport cargoes, and the two candidate transport cargoes each correspond to one candidate transport vehicle model, or the target weather forecast information corresponds to one candidate transport cargo, and the candidate transport cargo corresponds to two candidate transport vehicle models, the vehicle cargo loading result includes: two vehicle cargo loading plans, and the transportation dispatcher can select the target vehicle cargo loading plan from the two vehicle cargo loading plans according to the current transportation dispatch situation.

[0085] For examples, please refer to Figure 3 , is a structural diagram of a vehicle cargo loading model provided in an embodiment of the present application, such as Figure 3 As shown, the vehicle cargo loading model includes three types of weather information W1, W2 and W3. Weather information W1 corresponds to candidate transport cargo C, candidate transport cargo C corresponds to candidate transport vehicle type A and candidate transport vehicle type B, weather information W2 corresponds to candidate transport cargo A and candidate transport cargo B, candidate transport cargo A corresponds to candidate transport vehicle type C, candidate transport cargo B corresponds to candidate transport vehicle type A, weather information W3 corresponds to candidate transport cargo B, and candidate transport cargo B corresponds to candidate transport vehicle type A.

[0086] The vehicle cargo loading method provided in the embodiment of the present application obtains the target weather forecast information of the pre-planned logistics transportation route in the preset future time period; according to the target weather forecast information, the preset vehicle cargo loading model is used to determine the transportation goods corresponding to the target weather forecast information as the candidate transportation goods, and the transportation model corresponding to the candidate transportation goods is determined as the candidate transportation model, wherein the vehicle cargo loading model is pre-integrated with: the correspondence between the preset weather information and the transportation goods, and the correspondence between the preset transportation goods and the transportation model; the vehicle cargo loading result is generated, and the vehicle cargo loading result includes: the information of the logistics transportation route, the information of the preset future time period, the information of the candidate transportation goods and the information of the candidate transportation model, and the vehicle cargo loading result is used to indicate that the candidate transportation goods are transported along the logistics transportation route in the preset future time period. The embodiment of the present application uses the vehicle cargo loading model to determine the candidate transportation goods and the candidate transportation model based on the target weather forecast information, which can fully consider the goods suitable for transportation in different weather conditions, and select the most matching transportation model for the goods, so as to ensure the safety of the goods during transportation and improve the efficiency of cargo transportation.

[0087] Based on the above embodiment, the present application embodiment also provides another vehicle cargo loading method. Figure 4 , is a flow chart of another vehicle cargo loading method provided in an embodiment of the present application, such as Figure 4 As shown, the above S10 includes:

[0088] S11: Obtain the predicted arrival time of each location point in the logistics transportation route within a preset future time period.

[0089] In this embodiment, when the logistics transportation route is long, for example, across regions, cities, provinces, etc., the weather conditions on the logistics transportation route will change within a preset future time period. In order to obtain accurate target weather forecast information, a path planning device is used to determine multiple location points on the logistics transportation route according to preset path division rules, and the predicted arrival time of each location point is calculated based on the distance between each location point and the average speed limit of the transportation route section between each location point.

[0090] In an optional embodiment, the path division rule may be to divide the logistics transportation route into equal distances, with the distances between each location point being equal, and the estimated arrival time from the starting point to each location point is calculated based on the distance between each location point and the starting point of the logistics transportation route and the average speed limit of the transportation route segment between each location point.

[0091] For examples, please refer to Figure 5 , is a schematic diagram of dividing logistics transportation routes provided in an embodiment of the present application, such as Figure 5As shown, the logistics transportation route is divided into equal distances, and multiple location points are included between the starting point A and the end point Z of the logistics transportation route. The distance between each location point is equal. The time consumption between each location point is calculated based on the distance between each location point and the average speed limit of the transportation route segment between each location point. The predicted arrival time of each location point is determined based on the starting transportation time and the time consumption between each location point.

[0092] S12: According to the predicted arrival time of each location point and the location information of each location point, query the weather forecast information of each location point at the corresponding predicted arrival time.

[0093] In this embodiment, the predicted arrival time and location information of each location point are input into the meteorological center to query the weather forecast information of each location point at the corresponding predicted arrival time. For example, the location information of each location point may be the longitude and latitude of each location point.

[0094] In an optional embodiment, S12 includes: obtaining a weather forecast database within a preset future time period in a preset area where the logistics transportation route is located; querying the weather forecast information of each location point at the corresponding predicted arrival time from the weather forecast database based on the predicted arrival time of each location point and the location information of each location point.

[0095] In this embodiment, if the vehicle cargo loading system includes a weather forecast device, the weather forecast device periodically obtains weather forecast information of the preset area where the logistics transportation route is located from the meteorological center, and stores the weather forecast information in the weather forecast database. After determining the predicted arrival time of each location point and the location information of each location point, the predicted arrival time of each location point and the location information of each location point are input into the weather forecast device, and the weather forecast device queries the weather forecast information of each location point at the corresponding predicted arrival time from the weather forecast database.

[0096] S13: Determine target weather forecast information according to the weather forecast information of each location point at the corresponding predicted arrival time.

[0097] In this embodiment, according to the weather forecast information of each location point at the corresponding predicted arrival time, the number of location points corresponding to the various weather forecast information is counted, and the weather forecast information with the largest number of location points is selected as the target weather forecast information.

[0098] The vehicle cargo loading method provided in the embodiment of the present application obtains the predicted arrival time of each location point in the logistics transportation route within a preset future time period, queries the weather forecast information of each location point at the corresponding predicted arrival time based on the predicted arrival time of each location point and the location information of each location point, and determines the target weather forecast information based on the weather forecast information of each location point at the corresponding predicted arrival time. The embodiment of the present application determines the target weather forecast information of the entire logistics transportation route in the preset future time period through the weather forecast information of each location point on the logistics transportation route at the corresponding predicted arrival time, so that the determined weather information is more accurate, so that the generated vehicle cargo loading result is more accurate.

[0099] In an optional embodiment, before generating the vehicle cargo loading result in S30, the method further includes:

[0100] The transportation cost of the candidate transport goods is calculated based on the weather information influence coefficient of the candidate transport goods and the target weather forecast information; the vehicle cargo loading result also includes: the transportation cost of the candidate transport goods.

[0101] In this embodiment, the weather information impact coefficient is the degree of influence of the weather conditions on the candidate transported goods, and the weather information impact coefficient of the target weather forecast information is the degree of influence of the target weather forecast on the candidate transported goods. In the process of transporting the candidate transported goods, the impact of the weather conditions on the transportation cost is considered to calculate the transportation cost of the candidate transported goods. For example, according to the unit price, quantity, distance of the logistics transportation route and the weather information impact coefficient of the target weather forecast information of the candidate transported goods, the transportation cost of the candidate transported goods is calculated, and the calculation method is: transportation cost = unit price * quantity * distance * weather information impact coefficient.

[0102] After calculating the transportation cost, the vehicle cargo loading device outputs the transportation cost as a part of the vehicle cargo loading result, so as to provide a reference for the transportation dispatcher to select the vehicle cargo loading plan.

[0103] Based on the above embodiments, the present application also provides another method for loading cargo on a vehicle. Figure 6 , is a flow chart of another vehicle cargo loading method provided in an embodiment of the present application, such as Figure 6 As shown, before calculating the transportation cost of the candidate transportation goods according to the weather information influence coefficient of the candidate transportation goods and the target weather forecast information, the method further includes:

[0104] S41: Obtaining a variety of weather forecast information for a plurality of location points in a logistics transportation route at corresponding predicted arrival times.

[0105] In this embodiment, the specific method of obtaining multiple location points in the logistics transportation route, multiple location points at corresponding predicted arrival times, and multiple weather forecast information at multiple location points at corresponding predicted arrival times can be referred to S11-S12 and will not be repeated here.

[0106] S42: Calculate the weather information impact coefficient of the target weather forecast information according to the preset impact coefficients of the candidate transport cargo in the various weather forecast information and the time proportion of each weather forecast information in the preset future time period.

[0107] In this embodiment, the logistics transportation route is divided into multiple location points, and the route segments between each location point are determined to calculate the preset future time sub-segments corresponding to each route segment in the preset future time period. According to each route segment and the corresponding preset future time sub-segment, the duration of at least one weather forecast information in the corresponding preset future time sub-segment of each route segment is obtained from the meteorological center, and the time proportion of each weather forecast information in the preset future time period is counted. According to the preset influence coefficients and time proportions of multiple weather forecast information of candidate transport goods, the weather information influence coefficient of the target weather forecast information is calculated. For example, for the candidate transport goods G1, the multiple weather forecast information in the preset future time period on the logistics transportation route is W1, W2, W3..., the preset influence coefficient of weather forecast information W1 is n1, the time proportion is r1, the preset influence coefficient of weather forecast information W2 is n2, the time proportion is r2, the preset influence coefficient of weather forecast information W3 is n3, the time proportion is r3, and the weather information influence coefficient of the target weather forecast information is N=n1*r1+n2*r2+n3*r3+...

[0108] In an optional embodiment, the present application also provides another vehicle cargo loading method. Figure 7 , is a flow chart of another vehicle cargo loading method provided in an embodiment of the present application, such as Figure 7 As shown, the method also includes:

[0109] S51: Acquire multiple historical transportation costs corresponding to the candidate transport goods under multiple historical weather information within a preset historical time period; the preset historical time period is a historical time period corresponding to a preset time period to which a preset future time period belongs, and the preset time period and the historical time period are the same time period in years.

[0110] In this embodiment, the preset time period to which the preset future time period belongs may be the month, quarter, half a year or year to which the preset future time period belongs, and the preset historical time period is the historical time period corresponding to the preset time period, and the preset historical period and the preset time period are the same time period with a year as the unit. If the weather has a greater impact on the candidate transported goods, the preset time period may select a short period, such as the month or quarter to which the preset future time period belongs; if the weather has a smaller impact on the candidate transported goods, the preset time period may select a long period, such as the half a year or year to which the preset future time period belongs. For example, if the candidate transported goods are perishable goods, and the decay rate of perishable goods in summer transportation is greater than the decay rate in winter transportation, then the preset time period may be determined to be a month or a quarter; if the candidate transported goods are non-perishable goods, and the weather has a smaller impact on non-perishable goods, then the preset time period may be determined to be half a year or a year. After determining the preset time period, in units of years, the historical time period belonging to the same time period as the preset time period is determined as the preset historical time period. For example, the preset future time period is from February 1, 2022 to February 5, 2022, and the preset time period is February, then the preset historical time period can be February 2021, February 2020, etc.

[0111] After determining the preset historical time period, the historical transportation cost used for transporting the candidate transport goods under various historical weather information within the preset historical time period is obtained.

[0112] S52: Calculate a preset impact coefficient based on a plurality of historical weather information and a plurality of historical transportation costs.

[0113] In this embodiment, the influence degree of each weather information on the transportation cost of the candidate transportation goods is calculated according to the historical transportation cost of the candidate transportation goods under different historical weather information, and the preset influence coefficients corresponding to the various weather information are obtained.

[0114] The vehicle cargo loading method provided in the embodiment of the present application obtains multiple weather forecast information corresponding to the predicted arrival time at multiple locations in the logistics transportation route, and calculates the weather information impact coefficient of the target weather forecast information according to the preset impact coefficient of the candidate transported goods in the multiple weather forecast information and the time proportion of each weather forecast information in the preset future time period. The embodiment of the present application calculates the weather information impact coefficient to determine the impact of weather conditions on the cost of cargo transportation, so as to select the best vehicle cargo loading plan and save transportation costs.

[0115] Based on the above embodiments, the present application also provides a vehicle cargo loading device, please refer to Figure 8 , is a schematic diagram of the structure of a vehicle cargo loading device provided in an embodiment of the present application, such as Figure 8 As shown, the device comprises:

[0116] The acquisition module 101 is used to obtain the target weather forecast information of the pre-planned logistics transportation route within a preset future time period;

[0117] The loading module 102 is used to use a preset vehicle cargo loading model according to the target weather forecast information to determine the transport cargo corresponding to the target weather forecast information as the candidate transport cargo, and determine the transport vehicle type corresponding to the candidate transport cargo as the candidate transport vehicle type; wherein the vehicle cargo loading model pre-integrates: the corresponding relationship between the preset weather information and the transport cargo, and the corresponding relationship between the preset transport cargo and the transport vehicle type;

[0118] The result generation module 103 is used to generate a vehicle cargo loading result, which includes: information on the logistics transportation route, information on a preset future time period, information on candidate transportation goods, and information on candidate transportation vehicle models. The vehicle cargo loading result is used to indicate that the candidate transportation goods are transported along the logistics transportation route using the candidate transportation vehicle model within the preset future time period.

[0119] Optionally, the acquisition module 101 includes:

[0120] An arrival time acquisition unit is used to obtain the predicted arrival time of each location point in the logistics transportation route within a preset future time period;

[0121] A weather forecast information query unit, used to query the weather forecast information of each location point at the corresponding predicted arrival time according to the predicted arrival time of each location point and the location information of each location point;

[0122] The target weather forecast information determination unit is used to determine the target weather forecast information according to the weather forecast information of each location point at the corresponding predicted arrival time.

[0123] Optionally, a weather forecast information query unit includes:

[0124] A weather forecast database acquisition subunit is used to acquire a weather forecast database within a preset future time period in a preset area where the logistics transportation route is located;

[0125] The weather forecast information query subunit is used to query the weather forecast information of each location point at the corresponding predicted arrival time from the weather forecast database according to the predicted arrival time of each location point and the location information of each location point.

[0126] Optionally, the device further comprises:

[0127] A transportation cost calculation module, used to calculate the transportation cost of candidate transportation goods according to the weather information influence coefficient of the candidate transportation goods and the target weather forecast information;

[0128] The vehicle cargo loading result also includes: the transportation cost of the candidate transportation cargo.

[0129] Optionally, the device further comprises:

[0130] A weather forecast information acquisition module is used to obtain a variety of weather forecast information at multiple locations in the logistics transportation route at the corresponding predicted arrival time;

[0131] The weather information impact coefficient calculation module is used to calculate the weather information impact coefficient of the target weather forecast information based on the preset impact coefficients of the candidate transport goods in multiple weather forecast information and the time proportion of each weather forecast information in a preset future time period.

[0132] Optionally, the device further comprises:

[0133] The historical transportation cost acquisition module is used to obtain multiple historical transportation costs corresponding to multiple historical weather information of candidate transport goods within a preset historical time period; the preset historical time period is a historical time period corresponding to a preset time period to which the preset future time period belongs, and the preset time period and the historical time period are the same time period in years;

[0134] The preset impact coefficient calculation module is used to calculate the preset impact coefficient based on multiple historical weather information and multiple historical transportation costs.

[0135] Optionally, the device further comprises:

[0136] The model building module is used to build a vehicle cargo loading model based on the transport cargo matched with various weather information and the transport vehicle models matched with various transport cargoes.

[0137] The above-mentioned device is used to execute the method provided by the aforementioned embodiment, and its implementation principle and technical effect are similar, which will not be repeated here.

[0138] The above modules may be one or more integrated circuits configured to implement the above methods, such as one or more application specific integrated circuits (ASICs), or one or more microprocessors, or one or more field programmable gate arrays (FPGAs). For another example, when a module is implemented in the form of a processing element scheduling program code, the processing element may be a general-purpose processor, such as a central processing unit (CPU) or other processor that can call program code. For another example, these modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0139] Please refer to Fig. 9 , is a schematic diagram of a computer device provided in an embodiment of the present application, such as Fig. 9 As shown, the computer device 200 includes: a processor 201, a storage medium 202 and a bus, the storage medium 202 stores program instructions executable by the processor 201, when the computer device 200 is running, the processor 201 and the storage medium 202 communicate through the bus, and the processor 201 executes the program instructions to execute the above method embodiment. The specific implementation method and technical effect are similar and will not be repeated here.

[0140] Optionally, the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor at runtime, it is used to execute the above method embodiment.

[0141] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0142] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0143] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0144] The above-mentioned integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor (English: processor) to perform some steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (English: Read-Only Memory, abbreviated: ROM), random access memory (English: Random Access Memory, abbreviated: RAM), disk or optical disk and other media that can store program codes.

[0145] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for loading cargo on a vehicle, characterized in that: The method comprises: Obtain target weather forecast information for pre-planned logistics transportation routes within a preset future time period; According to the target weather forecast information, a preset vehicle cargo loading model is used to determine the transport cargo corresponding to the target weather forecast information as a candidate transport cargo, and to determine the transport vehicle type corresponding to the candidate transport cargo as a candidate transport vehicle type; wherein the vehicle cargo loading model is pre-integrated with: a correspondence between preset weather information and transport cargo, and a correspondence between preset transport cargo and transport vehicle type; Generate a vehicle cargo loading result, the vehicle cargo loading result including: information of the logistics transportation route, information of the preset future time period, information of the candidate transportation cargo, and information of the candidate transportation vehicle type, the vehicle cargo loading result is used to indicate that the candidate transportation cargo is transported along the logistics transportation route by using the candidate transportation vehicle type within the preset future time period; Before generating the vehicle cargo loading result, the method further includes: Calculating the transportation cost of the candidate transportation cargo according to the weather information influence coefficient of the candidate transportation cargo and the target weather forecast information; The vehicle cargo loading result also includes: the transportation cost of the candidate transportation cargo.

2. The method according to claim 1, characterized in that The obtaining of target weather forecast information for a pre-planned logistics transportation route within a preset future time period includes: Obtaining the predicted arrival time of each location point in the logistics transportation route within the preset future time period; According to the predicted arrival time of each location point and the location information of each location point, query the weather forecast information of each location point at the corresponding predicted arrival time; The target weather forecast information is determined according to the weather forecast information of each location point at the corresponding predicted arrival time.

3. The method according to claim 2, characterized in that The querying of weather forecast information of each location point at a corresponding predicted arrival time according to the predicted arrival time of each location point and the location information of each location point includes: Obtaining a weather forecast database for the preset future time period in the preset area where the logistics transportation route is located; According to the predicted arrival time of each location point and the location information of each location point, the weather forecast information of each location point at the corresponding predicted arrival time is queried from the weather forecast database.

4. The method according to claim 1, characterized in that: Before calculating the transportation cost of the candidate transported goods according to the weather information influence coefficient of the candidate transported goods and the target weather forecast information, the method further includes: Obtaining a variety of weather forecast information for a plurality of locations in the logistics transportation route at corresponding predicted arrival times; The weather information impact coefficient of the target weather forecast information is calculated based on the preset impact coefficients of the candidate transport cargo in the multiple weather forecast information and the time proportion of each weather forecast information in the preset future time period.

5. The method according to claim 4, characterized in that Before calculating the weather information influence coefficient of the target weather forecast information according to the preset influence coefficient of the candidate transported goods in the multiple weather forecast information and the time proportion of each weather forecast information in the preset future time period, the method further includes: Acquire multiple historical transportation costs corresponding to the candidate transport goods under multiple historical weather information within a preset historical time period; the preset historical time period is a historical time period corresponding to a preset time period to which the preset future time period belongs, and the preset time period and the historical time period are the same time period in years; The preset impact coefficient is calculated according to the multiple historical weather information and the multiple historical transportation costs.

6. The method according to claim 1, characterized in that Before determining, based on the target weather forecast information, using a preset vehicle cargo loading model to determine the transport cargo corresponding to the target weather forecast information as a candidate transport cargo, and determining the transport vehicle type corresponding to the candidate transport cargo as a candidate transport vehicle type, the method further includes: The vehicle cargo loading model is established based on the transport cargo matched with various weather information and the transport vehicle types matched with various transport cargoes.

7. A vehicle cargo loading device, characterized in that: The device comprises: An acquisition module is used to obtain target weather forecast information for a pre-planned logistics transportation route within a preset future time period; A loading module is used to determine, according to the target weather forecast information, the transported goods corresponding to the target weather forecast information as candidate transported goods, and to determine the transport vehicle type corresponding to the candidate transported goods as the candidate transport vehicle type by using a preset vehicle cargo loading model; wherein the vehicle cargo loading model pre-integrates: a correspondence between preset weather information and transported goods, and a correspondence between preset transported goods and transport vehicle types; A result generation module is used to generate a vehicle cargo loading result, wherein the vehicle cargo loading result includes: information of the logistics transportation route, information of the preset future time period, information of the candidate transportation cargo, and information of the candidate transportation vehicle type, wherein the vehicle cargo loading result is used to indicate that the candidate transportation cargo is transported along the logistics transportation route by using the candidate transportation vehicle type within the preset future time period; The device also includes: A transportation cost calculation module, used to calculate the transportation cost of the candidate transportation goods according to the weather information influence coefficient of the candidate transportation goods and the target weather forecast information; The vehicle cargo loading result also includes: the transportation cost of the candidate transportation cargo.

8. A computer device, characterized in that: include: A processor, a storage medium and a bus, wherein the storage medium stores program instructions executable by the processor, and when the computer device is running, the processor and the storage medium communicate through the bus, and the processor executes the program instructions to perform the steps of the vehicle cargo loading method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the vehicle cargo loading method according to any one of claims 1 to 6 are executed.

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