A method, apparatus, device and medium for multimodal transport schedule screening

Abstract

The application relates to the field of transportation planning, in particular to a multimodal transport shift screening method, device, equipment and medium. The method comprises the following steps: acquiring node information, expected cargo readiness time and target arrival time, analyzing the node information and the expected cargo readiness time, obtaining a current delivery time, performing difference analysis on the target arrival time and the expected cargo readiness time, obtaining total time efficiency, performing prediction analysis on the node information and the total time efficiency, obtaining total delivery time, screening shifts according to the total delivery time and the current delivery time, and obtaining available shifts. The application has the effect of reducing transportation risks in international logistics.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of transportation planning, and in particular to a multimodal transport schedule screening method, device, equipment and medium. BACKGROUND

[0002] In the logistics industry, there are two parts: domestic logistics and international logistics. The domestic logistics industry is relatively mature, but the demand it can meet is limited. International logistics has a large growth space and can meet people's growing demand for purchases.

[0003] In international logistics, transportation is one of the main activities. The transportation planning on the market currently basically relies on the experience of decision makers to complete, and there is no more scientific and effective planning method. As a result, it is easy to cause the overuse of transportation / storage equipment or the failure of products to be transported in time, and in severe cases, the supply and demand parties cannot complete normal delivery. SUMMARY

[0004] In order to solve the problems existing in the prior art, the present application provides a multimodal transport schedule screening method, device, equipment and medium.

[0005] In a first aspect, the present application provides a multimodal transport schedule screening method, which adopts the following technical solution:

[0006] A multimodal transport schedule screening method, comprising:

[0007] Obtaining node information, estimated arrival time and target arrival time, the node information being used to represent the transportation node information on the transportation route, the estimated arrival time being used to represent the time when the first transportation node prepares the transported goods, and the target arrival time being used to represent the time when the last transportation node prepares the transported goods for delivery;

[0008] Analyzing the node information and the estimated arrival time to obtain a current delivery time, the current delivery time being used to represent the time when the current goods delivery party in the node information prepares the transported goods for delivery;

[0009] Subtracting the target arrival time from the estimated arrival time to obtain a total time, the total time being used to represent the time spent on the transportation nodes and the transportation route therebetween;

[0010] Predicting and analyzing the node information and the total time to obtain a total delivery time;

[0011] Screening the schedule according to the total delivery time and the current delivery time to obtain a usable schedule.

[0012] In another possible implementation manner, the node information and the estimated delivery time are analyzed to obtain a current delivery time, including:

[0013] The node information is used to determine an outgoing node duration, the outgoing node duration being used to represent a duration required by a delivery party of the current goods to deliver the goods;

[0014] The outgoing node duration is used to time-advance the estimated delivery time to obtain the current delivery time;

[0015] In another possible implementation manner, the node information and the total time limit are predicted and analyzed to obtain an outgoing total time limit, including:

[0016] The node information is used to obtain historical transportation data, the historical transportation data being used to represent a duration, a path, equipment, and weather data of the goods on a transportation section in a past time;

[0017] The historical transportation data is input into a trained and improved time prediction model to obtain a subsequent transportation time limit;

[0018] The node information is used to obtain a subsequent node time limit, the subsequent node time limit being used to represent a maximum duration required by a subsequent node to transport the goods;

[0019] The subsequent time limit and the subsequent transportation time limit are subjected to sum operation to obtain a subsequent time limit;

[0020] The total time limit and the subsequent time limit are subjected to difference operation to obtain an outgoing total time limit.

[0021] In another possible implementation manner, a shift period is selected according to the outgoing total time limit and the current delivery time to obtain an available shift period, including:

[0022] The current delivery time is used to obtain a current delivery time of a shift period, the shift period being used to represent a shift of a transportation section between a node and a neighboring node, and the current delivery time being used to represent a time point at which the shift receives the current goods;

[0023] The current delivery time and the estimated delivery time are used to obtain a current time limit;

[0024] The outgoing total time limit and the current time limit are subjected to difference operation to obtain a current transportation time limit;

[0025] The current delivery time and the transportation time limit are used to obtain a current shift period selection condition;

[0026] The shift period is selected according to the current shift period selection condition to obtain the available shift period.

[0027] In another possible implementation manner, the method further includes:

[0028] acquiring preset abnormal situation categories and a transportation situation, the preset abnormal situation categories being used to represent abnormal situations caused by natural factors and abnormal situations caused by equipment operation, and the transportation situation being used to represent an actual transportation situation of the transported article between two adjacent nodes;

[0029] matching the preset abnormal situation categories with the transportation situation, and generating a path planning instruction if a matching result shows a natural abnormality, the path planning instruction being used to re-plan a path that avoids the natural abnormality;

[0030] generating a shift query instruction if the matching result is an equipment abnormality, the shift query instruction being used to query a transportation shift at the same location.

[0031] In another possible implementation manner, the shift is filtered according to the total time limit and the current delivery time to obtain an available shift, and the method further includes:

[0032] setting a detection point according to the node information and a preset detection rule, the detection point being used to represent a node for performing safety quality inspection on the transported article;

[0033] corresponding the working node adjacent to the detection point into a preceding working node and a following working node according to a preset rule;

[0034] if a detection result of any detection point shows an abnormality, determining the preceding working node corresponding to the detection point as a responsible node.

[0035] In another possible implementation manner, the preceding working node corresponding to the detection point is determined as the responsible node, and the method further includes:

[0036] acquiring a freight image in the preceding working node;

[0037] performing action analysis on the freight image to obtain a freight operation;

[0038] matching the freight operation with a preset freight standard, and generating a supervisor screening instruction if the matching is successful, or generating a secondary identification instruction if the matching is unsuccessful, the secondary identification instruction being used to control identification of a rule-violating operation personnel in the freight image.

[0039] In a second aspect, the present application provides a device for screening a multimodal transport shift, including:

[0040] an acquisition module configured to acquire node information, an estimated time of readiness, and a target time of arrival, the node information being indicative of transportation node information on a transportation route, the estimated time of readiness being indicative of a time at which a first transportation node is ready to transport the goods, and the target time of arrival being indicative of a time at which a last transportation node is ready to transport the goods;

[0041] an analysis module configured to analyze the node information and the estimated time of readiness to obtain a current time of shipment, the current time of shipment being indicative of a time at which a current shipment node is ready to transport the goods;

[0042] a maximum time module configured to analyze a difference between the target time of arrival and the estimated time of readiness to obtain a total time, the total time being indicative of a time spent on the transportation nodes and the transportation route therebetween;

[0043] a shipment time module configured to analyze the node information and the total time to obtain a total shipment time;

[0044] a screening module configured to screen a shift based on the total shipment time and the current time of shipment to obtain an available shift.

[0045] In one possible implementation, the analysis module, when analyzing the node information and the estimated time of readiness to obtain the current time of shipment, is specifically configured to:

[0046] a determination module configured to determine a shipment node time based on the node information, the shipment node time being indicative of a time required by a current shipment node to ship the goods;

[0047] a shipment time module configured to delay the estimated time of readiness based on the shipment node time to obtain the current time of shipment.

[0048] In another possible implementation, the shipment time module, when analyzing the node information and the total time to obtain the total shipment time, is specifically configured to:

[0049] a historical subsequent module configured to obtain historical transportation data based on the node information, the historical transportation data being indicative of a time, a path, a device, and weather data of the goods on a transportation route in a past time;

[0050] a subsequent transportation module configured to input the historical transportation data into a trained time prediction model to obtain a subsequent transportation time;

[0051] a subsequent node module configured to obtain a subsequent node time based on the node information, the subsequent node time being indicative of a maximum time spent by a subsequent node in transporting the goods.

[0052] A subsequent time limit module is configured to perform a sum operation on the subsequent time limit and the subsequent transportation time limit to obtain a subsequent time limit;

[0053] A total time limit module is configured to perform a difference operation on the total time limit and the subsequent time limit to obtain a total time limit for sending out.

[0054] In another possible implementation, the screening shift period module is configured to screen shift periods according to the total time limit for sending out and the current delivery time to obtain available shift periods, and specifically configured to:

[0055] A recursive time module is configured to obtain a current receiving time of a shift period based on the current delivery time, the shift period being used to represent a shift of a transportation section between a node and an adjacent node, and the current receiving time being used to represent a time point at which the shift receives current goods;

[0056] A cumulative time limit module is configured to obtain a current time limit based on the estimated good time and the current receiving time;

[0057] A transportation time limit module is configured to perform a difference analysis on the total time limit for sending out and the current time limit to obtain a current transportation time limit;

[0058] A determination screening module is configured to obtain a current shift period screening condition based on the current receiving time and the transportation time limit;

[0059] A screening module is configured to screen shift periods according to the current shift period screening condition to obtain available shift periods.

[0060] In another possible implementation, the device further includes a determination exception module, a natural exception module, and a device exception module, wherein,

[0061] The determination exception module is configured to obtain a preset exception situation category and a transportation situation, the preset exception situation category being used to represent an exception situation caused by a natural factor and an exception situation caused by a device operation, and the transportation situation being used to represent an actual transportation situation of transported goods between two adjacent nodes;

[0062] The natural exception module is configured to match the preset exception situation category with the transportation situation, and if a matching result shows a natural exception, generate a path planning instruction, the path planning instruction being used to re-plan a path that avoids the natural exception;

[0063] The device exception module is configured to, if the matching result is a device exception, generate a shift query instruction, the shift query instruction being used to query a transportation shift at the same location.

[0064] In another possible implementation, the apparatus further includes a detection point setting module, a node dividing module, and a node accountability module, wherein

[0065] The detection point setting module is configured to set a detection point according to the node information and a preset detection rule, the detection point being used to indicate a node for performing a security quality inspection on the transported article;

[0066] The node dividing module is configured to divide the working node adjacent to the monitoring point into a preceding working node and a following working node according to a preset rule;

[0067] The node accountability module is configured to determine the preceding working node corresponding to the detection point as a responsible node if the detection result of any detection point shows an abnormality.

[0068] In another possible implementation, the apparatus further includes an express delivery image obtaining module, an operation analyzing module, and a matching standard module, wherein

[0069] The express delivery image obtaining module is configured to obtain an express delivery image in the preceding working node;

[0070] The operation analyzing module is configured to perform action analysis on the express delivery image to obtain an express delivery operation;

[0071] The matching standard module is configured to match the express delivery operation with a preset express delivery standard, and if the matching is successful, generate a screening instruction for a supervisor, and if the matching is unsuccessful, generate a secondary identification instruction, the secondary identification instruction being used to control identification of a rule-violating operation personnel in the express delivery image.

[0072] In a third aspect, the present application provides an electronic device, which adopts the following technical solution:

[0073] An electronic device includes:

[0074] at least one processor;

[0075] a memory;

[0076] at least one application program, wherein the at least one application program is stored in the memory and is configured to be executed by the at least one processor, and the at least one application program is configured to perform the method for screening a multimodal transport shift as described above.

[0077] In a fourth aspect, a computer-readable storage medium is provided, and the storage medium stores at least one instruction, at least one program, a code set, or an instruction set. The at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor to implement the method for screening a multimodal transport shift as shown in any possible implementation manner of the first aspect.

[0078] To sum up, the present application includes the following beneficial technical effects:

[0079] The present application provides a multimodal transport class period screening method, device, equipment and readable storage medium. Compared with the related art, in the present application, the current delivery time of the current node where the goods are located is obtained by analyzing the obtained node information and the expected goods readiness time. At the same time, the time interval between the target arrival time and the expected goods readiness time is obtained, so as to determine the total time length. Thereafter, the total time is subtracted from the time obtained by predicting through the node information to obtain the total time of the current goods delivery. The current delivery time, the total time and the total time of the current goods delivery are used as screening conditions for screening the available class period, and the available time range of the current goods transportation is gradually determined by predicting the future transportation time. Among them, in the case of many uncertain factors in the future, the worst case in the future transportation process is obtained through the prediction process first, so as to ensure that the current optional class period can avoid the risk of the worst case in the future transportation process, thereby ensuring the normal operation of logistics transportation. BRIEF DESCRIPTION OF DRAWINGS

[0080] Figure 1 is a method flow diagram of a multimodal transport class period screening method according to an embodiment of the present application;

[0081] Figure 2 is a block diagram of a multimodal transport class period screening device according to an embodiment of the present application;

[0082] Figure 3 is a schematic diagram of a multimodal transport class period screening equipment according to an embodiment of the present application. DETAILED DESCRIPTION

[0083] The following will be described in detail in combination with the accompanying drawings. Figures 1-3 The present application will be further described in detail.

[0084] The person skilled in the art can make modifications to the present embodiment without creative contribution after reading the present specification, but as long as it is within the scope of the claims of the present application, it is protected by the patent law.

[0085] In order to make the purpose, technical scheme and advantages of the embodiments of the present application more clear, the technical scheme in the embodiments of the present application will be described clearly and completely in combination with the drawings of the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by the person skilled in the art without creative labor are within the scope of protection of the present application.

[0086] In addition, the term "and / or" used herein is only used to describe an association relationship of associated objects, which means that there can be three relationships, for example, a multi-modal train schedule screening method, device, electronic equipment and storage medium and / or B, which means that there is a multi-modal train schedule screening method, device, equipment and medium alone, a multi-modal train schedule screening method, device, equipment and medium and B exist at the same time, and there are three cases of B alone. In addition, the character " / " in this paper, unless otherwise specified, generally represents that the associated objects before and after are "or" relationship.

[0087] The embodiments of the present application will be further described in detail below with reference to the accompanying drawings of the specification.

[0088] The embodiments of the present application provide a multi-modal train schedule screening method, which is executed by an electronic device, which can be a server or a terminal device. The server can be a standalone physical server, a server cluster composed of multiple physical servers or a distributed system, or a cloud server providing cloud computing services. The terminal device can be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected through wired or wireless communication, and the embodiments of the present application do not limit this. As shown in the figure, the method comprises: Figure 1

[0089] Step A001, obtaining node information, estimated arrival time and target arrival time.

[0090] Step A002, analyzing the node information and the estimated arrival time to obtain the current shipping time.

[0091] The node information includes the position sequence of the transportation nodes and transportation sections on the transportation route, the time length required by the goods at the transportation nodes and the transportation sections, and the historical transportation data. The current shipping time is the time when the current goods sender prepares to ship the transportation goods in the node information. The estimated arrival time is the time when the first transportation node prepares to perfect the transportation goods. The target arrival time is the time when the last transportation node prepares to ship the transportation goods. The current shipping time is the time when the current goods sender prepares to ship the transportation goods in the node information.

[0092] For the embodiments of the present application, the node information, the estimated arrival time and the target arrival time in the storage are obtained.

[0093] The maximum time of the transportation goods staying at the first transportation node on the transportation route and the time point when the supplier perfects the transportation goods at the first transportation node are added to obtain the time when the transportation goods can be shipped from the first transportation node, i.e. the current shipping time.

[0094] ​Specifically, the expected arrival time, the target arrival time, the position sequence in the node information, and the time length are provided by a third party (for example, a transportation platform) in actual application.

[0095] Step A003, the total time is obtained by subtracting the expected arrival time from the target arrival time.

[0096] The total time is the time consumed by the transportation nodes and the transportation routes between the transportation nodes.

[0097] For the embodiment of the present application, the target arrival time is taken as the right endpoint value of the interval, and the expected arrival time is taken as the left endpoint value of the interval, to obtain the interval of the total time, and the length in the interval is taken as the total time.

[0098] Specifically, the method for subtracting the target arrival time from the expected arrival time includes but is not limited to one included in the embodiment of the present application.

[0099] Step A004, the total time is predicted and analyzed based on the node information and the total time, to obtain the sending total time.

[0100] The sending total time is obtained by subtracting the maximum time from the total time obtained in step A003, and the time for the goods to stay in the first transportation node and the first transportation segment is obtained, that is, the sending total time.

[0101] The sending total time is the time for the goods to stay in the first transportation segment on the transportation route.

[0102] For the embodiment of the present application, the maximum time required for the goods to be transported on the remaining transportation segments except the first transportation segment is obtained by predicting based on the historical transportation data of the transportation segments in the node information.

[0103] Specifically, the algorithm used in the prediction includes but is not limited to a time convolution network (TCN) and a recurrent neural network (RNN).

[0104] Step A005, the available shift is obtained by screening the shift based on the sending total time and the current sending time.

[0105] For the embodiment of the present application, the sending total time and the current sending time are combined and taken as a first-level screening condition, and the current sending time is taken as a second-level screening condition.

[0106] When the shift meets the first-level screening condition and the second-level screening condition at the same time, the shift is determined as the available shift.

[0107] The application provides a method for screening of multimodal transport class, and the current delivery time of the current goods at a node is obtained by analyzing the obtained node information and the expected goods readiness time. Meanwhile, the time interval between the target arrival time and the expected goods readiness time is obtained, so as to determine the total time length. Then, the total time length is subtracted from the time obtained by predicting the node information, and the total time length of the current goods delivery is obtained. The current delivery time, the total time length and the total time length of the current goods delivery are used as screening conditions for screening of available classes, and the available time range of the current goods transport is gradually determined by predicting the future transport time length. In the case that there are many uncertain factors in the future, the worst case in the future transport process is obtained through the prediction process, so as to ensure that the current optional class can avoid the risk of the worst case in the future transport process, thereby ensuring the normal operation of the logistics transport.

[0108] In a possible implementation of the embodiment of the application, step A002 includes step A006 (not shown in the figure) and step A007 (not shown in the figure), wherein,

[0109] In step A006, the delivery node time length is determined based on the node information.

[0110] In step A007, the expected goods readiness time is time-advanced according to the delivery node time length, and the current delivery time is obtained.

[0111] The delivery node time length includes the time length of the goods staying at the first transport node, and the expected goods readiness time is the time point at which the first transport node is ready to transport the goods.

[0112] For the embodiment of the application, the first transport node in the node information is determined as the delivery node, and the delivery time length of the first transport node is obtained as the delivery node time length.

[0113] The expected goods readiness time is taken as the time-advanced object, the delivery node time length is taken as the time-advanced length, and the time-advanced result is obtained as the current delivery time.

[0114] For example, the expected goods readiness time is 2000 / 1 / 1 / 9:00, and the delivery node time length is 48h, so the current delivery time is 2000 / 1 / 3 / 9:00.

[0115] In a possible implementation of the embodiment of the application, step A004 includes step A008 (not shown in the figure), step A009 (not shown in the figure), step A010 (not shown in the figure), step A011 (not shown in the figure) and step A012 (not shown in the figure), wherein,

[0116] In step A008, the historical transport data is obtained based on the node information.

[0117] Step A009, input the historical transportation data into the trained time prediction model to obtain the subsequent transportation time efficiency.

[0118] The historical transportation data is the time length, path, equipment, and weather data of the goods on the same transportation section in the past.

[0119] For the embodiments of the present application, the factors that may affect the transportation time efficiency, such as the transportation time length, transportation path, transportation equipment, and weather at the time of transportation generated in the historical transportation section, are correspondingly sorted and divided into a training set and a test set with time as the node. The training set is input into the constructed time series prediction model for training. When the training result approaches the test set, it is determined that the time series prediction model is trained and perfected. Thereafter, the data in the historical transportation data that is the same as the existing transportation condition is input into the time series prediction model as a prediction sample, and the future transportation time obtained is taken as the subsequent transportation time efficiency.

[0120] Specifically, the factors affecting the transportation time efficiency and the selection of the time series prediction model should be selected according to the actual situation. The time series prediction model includes but is not limited to: time convolution network (TCN) and recurrent neural network (RNN).

[0121] Step A010, obtaining the subsequent node time efficiency based on the node information.

[0122] Step A011, performing sum operation on the subsequent node time efficiency and the subsequent transportation time efficiency to obtain the subsequent total time efficiency.

[0123] Step A012, performing difference operation on the total time efficiency and the subsequent total time efficiency to obtain the sending total time efficiency.

[0124] The subsequent node is all non-first transportation nodes in the transportation node, the subsequent node time efficiency is the time length of the goods staying in different subsequent nodes, the subsequent total time efficiency is the total time length of different subsequent nodes, and the sending total time efficiency is the total time length of the goods staying in the first transportation node and the first transportation section.

[0125] For the embodiments of the present application, the total time length of the goods staying in the non-first transportation node in the node information is obtained, the subsequent transportation time efficiency and the subsequent node time efficiency are summed to obtain the subsequent total time efficiency.

[0126] The total time efficiency and the subsequent total time efficiency are subtracted to obtain the total time length of the goods in the first transportation node and the first transportation section, that is, the sending total time efficiency.

[0127] Specifically, the method used for summing / difference is the same as that in step A003, and the embodiments of the present application will not be described again.

[0128] In a possible implementation of the embodiment of the application, the step A005 includes a step A013 (not shown in the figure), a step A014 (not shown in the figure), a step A015 (not shown in the figure), a step A016 (not shown in the figure), and a step A017 (not shown in the figure), wherein

[0129] In the step A013, the current receiving time of the shift is obtained based on the current sending time.

[0130] The shift is a shift used for a transportation section from the first transportation node to a next adjacent transportation node, and the current receiving time is a time point at which the shift receives the current goods.

[0131] For the embodiment of the application, an actual relationship between the current receiving time of the shift and the current sending time is that the current receiving time is greater than or equal to the current sending time. The current receiving time is set according to the current sending time and the actual relationship between the current sending time and the current receiving time.

[0132] In the step A014, the current time limit is obtained based on the expected completion time and the current receiving time.

[0133] The current time limit is a time at which the goods stay at the first transportation node.

[0134] For the embodiment of the application, the current receiving time is taken as a right end point value of an interval, the expected completion time is taken as a left end point value of the interval, an interval of the current time limit is obtained, and a length in the interval is taken as the current time limit.

[0135] Specifically, a method used for obtaining the current time limit based on the current receiving time and the expected completion time includes but is not limited to one included in the embodiment of the application, and details are not described herein.

[0136] In the step A015, the current transportation time limit is obtained by subtracting the current time limit from the total time limit.

[0137] The current transportation time limit is used to represent a time length of the current goods in the latest transportation;

[0138] For the embodiment of the application, the total time limit and the current time limit obtained in the step A015 are subtracted to obtain a time length of the current goods staying at the latest transportation section (i.e., the first transportation section).

[0139] In the step A016, the current shift screening condition is obtained according to the current receiving time and the current transportation time limit.

[0140] In the step A017, the shift is screened according to the current shift screening condition to obtain an available shift.

[0141] For the embodiment of the present application, the current transportation time limit and the current shipping time are taken as the screening conditions, and when the time point at which the shift period starts is greater than or equal to the current shipping time and the total duration of the shift period is less than or equal to the current transportation time limit, the shift period is determined as an available shift period.

[0142] For example, the current transportation time limit is 10 hours, and the current shipping time is 2000 / 1 / 1 / 9:00. If there is an A shift period: 2000 / 1 / 10:00-2000 / 1 / 20:00 and a B shift period: 2000 / 1 / 08:00-2000 / 1 / 21:00, the B shift period is an available shift period.

[0143] In another possible implementation manner of the embodiment of the present application, the actual shift period is determined based on the obtained available shift period, the time at which the actual shift period arrives at the second transportation node is replaced by the expected goods ready time, the second transportation node is taken as the first transportation node in the above embodiment, and all the steps are repeatedly executed to obtain the available shift period of the original second transportation node.

[0144] If there are multiple transportation segments, the expected goods ready time replacement and the first transportation node replacement are repeatedly executed to finally obtain the available shift period of the transportation segment.

[0145] One possible implementation manner of the embodiment of the present application further includes a step A018 (not shown in the figure), a step A019 (not shown in the figure) and a step A020 (not shown in the figure), wherein,

[0146] In the step A018, a preset abnormal situation category and a transportation situation are obtained.

[0147] In the step A019, the preset abnormal situation category is matched with the transportation situation, and if the matching result shows a natural abnormality, a path planning instruction is generated, the path planning instruction being used to re-plan a path avoiding the natural abnormality.

[0148] In the step A020, if the matching result is a device abnormality, a shift query instruction is generated, the shift query instruction being used to query a transportation shift at the same location.

[0149] The preset abnormal situation category is an abnormal situation caused by a natural factor and an abnormal situation caused by device operation, and the transportation situation is an actual transportation situation of a transportation article between two adjacent nodes.

[0150] For the embodiment of the present application, the transportation situation is matched with the preset abnormal situation category, and an instruction is generated according to the matching result.

[0151] Specifically, if the transportation condition is that the equipment / device is damaged, causing the goods to be unable to normally arrive at the adjacent transportation node, it is determined that the equipment is abnormal. At this time, a shift query instruction is generated, the current shift sustainable operation time and the natural parameters such as the current wind direction / water speed that have an influence on the running distance are determined, the above-mentioned time and parameters are input into the neural network model for calculation, and the reachable range with the goods as the center is obtained. Thus, the transportation shift within the reachable range is obtained.

[0152] If the transportation condition is that the weather / climate is bad, causing the goods to be unable to normally arrive at the adjacent transportation node, it is determined that the nature is abnormal. At this time, a path planning instruction is generated, the current goods position is taken as the center, and a range with a radius of 1 km is obtained. It is determined whether there is an alternative path for the normal operation of the current shift. If there is an alternative path, the alternative path is displayed, and the goods position at this time and the corresponding weather / climate condition are recorded.

[0153] If there is no alternative path, the radius is quantitatively enlarged in a cycle, and the above-mentioned step of determining the alternative path is executed. If there is still no alternative path for the normal operation of the current shift after the cycle execution of the step of determining the alternative path for 3 times, the current goods position and the weather / climate condition in the corresponding range after the radius is quantitatively enlarged for 3 times are obtained again, and the two are correspondingly arranged and uploaded.

[0154] In the embodiment of the application, when the radius is quantitatively enlarged in a cycle, the quantitative enlargement should be less than or equal to 1 km and greater than or equal to 0.1 km, and the form of the arranged content is not limited.

[0155] In a possible implementation manner of the embodiment of the application, after the step A005, there are further a step A021 (not shown in the figure), a step A022 (not shown in the figure) and a step A023 (not shown in the figure), wherein,

[0156] In the step A021, a detection point is set according to the node information and a preset detection rule.

[0157] The detection point is a node for safety quality inspection of the transported goods, and the preset detection rule includes a corresponding relationship between the node information and the safety quality inspection node.

[0158] In the embodiment of the application, the transportation nodes and the transportation sections in the node information are all determined as working nodes, and the corresponding quality inspection points are set before the first working process of the working node. For example, the working process of the working node is divided into receiving goods, good goods and delivering goods, and the corresponding quality inspection point is set before the receiving goods.

[0159] In addition, the main contents detected during the safety quality inspection include but are not limited to goods damage, dampness and decline in sanitary condition, which are not limited in the embodiment of the application.

[0160] Step A022, according to a preset rule, the working nodes adjacent to the detection points are divided into front working nodes and rear working nodes.

[0161] Step A023, if the detection result of any detection point shows an abnormality, the front working node corresponding to the detection point is determined as a responsible node.

[0162] The preset rule is the corresponding relationship between the goods handover party and different working nodes, and the responsible node is the node that bears the responsibility for the abnormal goods.

[0163] For the embodiment of the application, the goods delivery party connected by the detection point is determined as the front working node, and the goods receiving party is determined as the rear working node. If the detection result of the detection point is abnormal, the front working node corresponding to the detection point is determined as the responsible node.

[0164] In one possible implementation of the embodiment of the application, before step A023, there are also step A024 (not shown in the figure), step A025 (not shown in the figure) and step A026 (not shown in the figure), wherein,

[0165] Step A024, an image of carrying goods in the front working node is obtained.

[0166] Step A025, action analysis is performed on the image of carrying goods to obtain a carrying operation.

[0167] The image of carrying goods is an image from the beginning of receiving goods to the end of delivering goods.

[0168] For the embodiment of the application, the obtained continuous frame images of carrying goods are spliced to form a video, the position of the personnel appearing in the video is locked, and device recognition, face recognition and action recognition are performed on the position. When it is determined through action recognition that the personnel is handling goods, the personnel handling operation information and the handling object are recorded.

[0169] Step A026, the carrying operation is matched with a preset carrying standard. If the matching is successful, a screening instruction of a supervisory personnel is generated, and if the matching is unsuccessful, a secondary identification instruction is generated, which is used to control identification of a rule-violating operation personnel in the image of carrying goods.

[0170] The preset carrying standard is a corresponding relationship between a handling object and a standard operation mode.

[0171] For the embodiment of the application, the recorded handling object is matched with the handling object in the preset carrying standard, and the standard operation mode corresponding to the handling object is obtained. The recorded handling operation information is matched with the standard operation mode. If the handling operation information satisfies the key points in the standard operation mode, it is determined that the matching is successful; otherwise, if the handling operation information does not satisfy the key points in the standard operation mode, it is determined that the matching is unsuccessful.

[0172] If the determination result is a match success, the processing object is locked according to the supervisor screening instruction, screened in the supervisor list, and the supervisor of the processing object is obtained.

[0173] If the determination result is a match failure, the face recognition of the processing operation information is performed on the personnel who does not match, the identity information of the personnel is obtained according to the secondary identification instruction.

[0174] In summary, through the prediction and planning of the future class period, the risk of abnormal logistics transportation is reduced.

[0175] The above embodiment introduces a multimodal transport class screening method from the perspective of method flow, and the following embodiment introduces a multimodal transport class screening device from the perspective of virtual module or virtual unit. For details, see the following embodiment.

[0176] The embodiment of the present application provides a multimodal transport class screening device, as shown in the figure, which specifically can include: an acquisition information module 21, an analysis shipping module 22, a maximum time limit module 23, an outgoing time limit module 24, and a class screening module 25, wherein, Figure 2

[0177] The acquisition information module 21 is used to acquire node information, estimated goods completion time, and target arrival time, the node information is used to represent the transportation node information on the transportation route, the estimated goods completion time is used to represent the time when the first transportation node prepares the transportation goods, and the target arrival time is used to represent the time when the last transportation node prepares the transportation goods;

[0178] The analysis shipping module 22 is used to analyze the node information and the estimated goods completion time, and obtain the current shipping time, the current shipping time is used to represent the time when the current goods sender in the node information prepares the transportation goods for shipping;

[0179] The maximum time limit module 23 is used to analyze the difference between the target arrival time and the estimated goods completion time, and obtain the total time limit, the total time limit is used to represent the time spent on the transportation nodes and the transportation route therebetween;

[0180] The outgoing time limit module 24 is used to predict and analyze the node information and the total time limit, and obtain the outgoing total time limit;

[0181] The class screening module 25 is used to screen the class period according to the outgoing total time limit and the current shipping time, and obtain the available class period.

[0182] ​In another possible implementation of the embodiments of the present application, the analysis shipping module 22 analyzes the node information and the estimated arrival time to obtain a current shipping time, and is specifically used for:

[0183] determining an outgoing node duration based on the node information, the outgoing node duration being used to represent a duration required by a sender of the current goods for shipping;

[0184] time-advancing the estimated arrival time based on the outgoing node duration to obtain the current shipping time.

[0185] In another possible implementation of the embodiments of the present application, the outgoing time limit module 24 performs prediction analysis on the node information and the total time limit to obtain an outgoing total time limit, and is specifically used for:

[0186] obtaining historical transportation data based on the node information, the historical transportation data being used to represent a duration, a path, equipment, and weather data of the goods on a transportation section in a past time;

[0187] inputting the historical transportation data into a trained and improved time prediction model to obtain a subsequent transportation time limit;

[0188] obtaining a subsequent node time limit based on the node information, the subsequent node time limit being used to represent a maximum duration spent by a subsequent node in transporting the goods;

[0189] performing a sum operation on the subsequent time limit and the subsequent transportation time limit to obtain a subsequent time limit;

[0190] performing a difference operation on the total time limit and the subsequent time limit to obtain the outgoing total time limit.

[0191] In another possible implementation of the embodiments of the present application, the screening shift period module 25 screens a shift period based on the outgoing total time limit and the current shipping time to obtain an available shift period, and is specifically used for:

[0192] obtaining a current arrival time of the shift period based on the current shipping time, the shift period being used to represent a shift of a transportation section between a node and a neighboring node, and the current arrival time being used to represent a time point at which the shift receives the current goods;

[0193] obtaining a current time limit based on the estimated arrival time and the current arrival time;

[0194] performing a difference operation on the outgoing total time limit and the current time limit to obtain a current transportation time limit;

[0195] obtaining a current shift screening condition based on the current arrival time and the transportation time limit;

[0196] Screen the shift according to the current shift screening condition to obtain a usable shift.

[0197] In another possible implementation of the embodiment of the application, the device 20 further comprises a determination exception module, a natural exception module, and a device exception module, wherein,

[0198] The determination exception module is configured to acquire preset exception condition categories and a transportation condition, the preset exception condition categories are used to represent an exception condition caused by a natural factor and an exception condition caused by device operation, and the transportation condition is used to represent an actual transportation condition of a transported article between two adjacent nodes.

[0199] The natural exception module is configured to match the preset exception condition categories with the transportation condition, and if a matching result shows a natural exception, generate a path planning instruction, the path planning instruction being used to re-plan a path avoiding the natural exception.

[0200] The device exception module is configured to, if the matching result is a device exception, generate a shift query instruction, the shift query instruction being used to query a transportation shift at the same location.

[0201] In another possible implementation of the embodiment of the application, the device 20 further comprises a setting detection module, a division node module, and a node accountability module, wherein,

[0202] The setting detection module is configured to set a detection point according to the node information and a preset detection rule, the detection point being used to represent a node for performing a safety quality inspection on the transported article.

[0203] The division node module is configured to divide a working node adjacent to the monitoring point into a front working node and a rear working node according to a preset rule.

[0204] The node accountability module is configured to, if a detection result of any detection point shows an exception, identify a front working node corresponding to the detection point as a responsible node.

[0205] In another possible implementation of the embodiment of the application, the device 20 further comprises an acquisition freight module, an analysis operation module, and a matching standard module, wherein,

[0206] The acquisition freight module is configured to acquire a freight image in the front working node.

[0207] The analysis operation module is configured to perform action analysis on the freight image to obtain a freight operation.

[0208] The matching standard module is configured to match the delivery operation with a preset delivery standard, and if the delivery operation matches the preset delivery standard, a screening instruction for a supervisor is generated, and if the delivery operation does not match the preset delivery standard, a secondary identification instruction is generated, and the secondary identification instruction is configured to control identification of a violator in the delivery image.

[0209] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the system, device and unit described above can refer to the corresponding processes in the foregoing method embodiments, which will not be described here.

[0210] Embodiments of the present application also introduce an electronic device from the perspective of an entity device, such as Figure 3 as shown, Figure 3 The electronic device 300 shown in the figure includes a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, the electronic device 300 can also include a transceiver 304. It should be noted that in actual applications, the transceiver 304 is not limited to one, and the structure of the electronic device 300 does not constitute a limitation on the embodiments of the present application.

[0211] The processor 301 can be a CPU (Central Processing Unit, central processor), a general-purpose processor, a DSP (Digital Signal Processor, data signal processor), an ASIC (Application Specific Integrated Circuit, application specific integrated circuit), an FPGA (Field Programmable Gate Array, field programmable gate array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can implement or execute various exemplary logical blocks, modules and circuits described in combination with the disclosure content of the present application. The processor 301 can also be a combination of computing functions, such as one or more microprocessor combinations, combinations of DSP and microprocessor, etc.

[0212] The bus 302 can include a path for transmitting information between the above-mentioned components. The bus 302 can be a PCI (Peripheral Component Interconnect, peripheral component interconnect) bus or an EISA (Extended Industry Standard Architecture, extended industry standard architecture) bus, etc. The bus 302 can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, Figure 3 In the figure, only one thick line is used to represent, but it does not mean that there is only one bus or only one type of bus.

[0213] The memory 303 can be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited thereto.

[0214] The memory 303 is configured to store application program codes for implementing the solutions of the present application, and the processor 301 is configured to control the execution of the application program codes. The processor 301 is configured to execute the application program codes stored in the memory 303 to implement the content shown in the foregoing method embodiments.

[0215] The electronic device includes, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a digital broadcast receiver, a PDA (Personal Digital Assistant), a PAD (Tablet Personal Computer), a PMP (Portable Multimedia Player), a vehicle-mounted terminal (e.g., a car navigation terminal), and the like, and a fixed terminal such as a digital TV, a desktop computer, and the like, and can also be a server or the like. Figure 3 The electronic device shown is merely an example and should not impose any limitation on the functions and use range of the embodiments of the present application.

[0216] The embodiment of the present application provides a computer readable storage medium, which stores a computer program, and when the computer program is run on a computer, the computer can execute the corresponding content in the foregoing method embodiment. In the embodiment of the present application, the current delivery time of the current node where the goods are located is obtained by analyzing the obtained node information and the expected goods readiness time. Meanwhile, the time interval between the target arrival time and the expected goods readiness time is obtained, so that the total time length is determined. Then, the total time is subtracted from the time obtained by predicting the node information, and the total time of the current goods is obtained. The current delivery time, the total time and the total time of the current goods are used as the screening condition for screening the available time period, and the available time range of the current goods transportation is gradually determined by predicting the future transportation time. In the case that there are many uncertain factors in the future, the worst case in the future transportation process is obtained through the prediction process first, so as to ensure that the current optional time period can avoid the risk of the worst case in the future transportation process, thereby ensuring the normal operation of logistics transportation.

[0217] It should be understood that, although each step in the flowchart of the accompanying drawings is displayed in sequence according to the indication of the arrow, these steps are not necessarily executed in sequence according to the indication of the arrow. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and they can be executed in other sequences. Moreover, at least part of the steps in the flowchart of the accompanying drawings can include multiple sub-steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution sequence is not necessarily sequential, but can be alternately executed with at least part of other steps or sub-steps or stages of other steps.

[0218] The above is only part of the embodiments of the present application, and it should be pointed out that, for ordinary skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, and these improvements and refinements should be regarded as the protection scope of the present application.

Claims

1. A method for selecting multimodal transport schedules, characterized in that, include: The system acquires node information, estimated cargo readiness time, and target arrival time. The node information represents the transportation node information on the transportation route, the estimated cargo readiness time represents the time when the first transportation node will complete the preparation of the transported goods, and the target arrival time represents the time when the last transportation node will prepare the transported goods for dispatch. The node information and the estimated goods readiness time are analyzed to obtain the current shipping time, which is used to indicate the time when the current goods sender in the node information is preparing to ship the goods. The difference analysis between the target arrival time and the expected delivery time is performed to obtain the total timeliness, which is used to represent the time spent on the transportation nodes and the transportation routes between them. The node information and the total lead time are predicted and analyzed to obtain the total lead time for issuance. The available departure times are obtained by filtering the departure schedules based on the total delivery time and the current delivery time. The step of analyzing the node information and the estimated delivery time to obtain the current delivery time includes: The sending node duration is determined based on the node information. The sending node duration is used to represent the time required for the current sender to ship the goods. The sending node duration is the duration for which the goods stay at the first transportation node. The estimated goods readiness time is extended by the time based on the duration of the dispatch node to obtain the current dispatch time; The prediction and analysis of the node information and the total timeliness to obtain the total issuance timeliness includes: Historical transportation data is obtained based on the node information. The historical transportation data is used to represent the duration, route, equipment, and weather data of goods on the transportation segment in the past time. The historical transportation data is input into a well-trained time prediction model to obtain the subsequent transportation timeliness. The subsequent node validity period is obtained based on the node information. The subsequent node validity period is used to represent the maximum time spent by the subsequent node in transporting goods. The subsequent node validity period is the time that the goods stay at each subsequent node. The subsequent node is all non-first transport nodes within the transport node. The total delivery time is obtained by summing the subsequent transportation time with the subsequent node time. The difference between the total effective period and the subsequent total effective period is calculated to obtain the total effective period for issuance; The step of filtering shifts based on the total delivery time and the current shipping time to obtain available shifts includes: The current receiving time of the shift is obtained based on the current shipping time. The shift is used to represent the shift used for the transportation segment between the node and the adjacent node. The current receiving time is used to represent the time when the shift receives the current goods. The current receiving time is greater than or equal to the current shipping time. The current delivery time is obtained based on the estimated delivery time and the current delivery time. Perform a difference analysis between the total delivery time and the current delivery time to obtain the current transportation time. The current schedule selection criteria are obtained based on the current receiving time and the current transportation timeliness. The schedules are filtered according to the current schedule selection criteria to obtain available schedules. Specifically, a schedule is considered available when the start time of the schedule is greater than or equal to the current shipping time and the total duration of the schedule is less than or equal to the current transportation time. This also includes: Obtain preset abnormal situation categories and transportation status. The preset abnormal situation categories are used to represent abnormal situations caused by natural factors and abnormal situations caused by equipment operation. The transportation status is used to represent the actual transportation status of transported goods between two adjacent nodes. The preset abnormal situation category is matched with the transportation situation. If the matching result shows a natural abnormality, a route planning instruction is generated. The route planning instruction is used to replan a route to avoid the natural abnormality. If the matching result indicates that the equipment is faulty, a schedule query instruction is generated, which is used to query transportation schedules for the same location. When the matching result is a natural anomaly, the current cargo location is used as the center and a radius of 1km is used to obtain the range determined by the current cargo location and the radius. It is then determined whether the range contains alternative routes. If alternative routes exist, they are displayed, and the weather / climate conditions corresponding to the current cargo location are recorded. If no alternative routes exist, the radius is cyclically and quantitatively expanded. The range is updated based on the expanded radius, and it is determined whether the updated range contains alternative routes. If no alternative routes exist after three quantitative expansions, the current cargo location and the weather / climate conditions within the range corresponding to the three quantitative expansions are recorded.

2. The method according to claim 1, characterized in that, The process of filtering shifts based on the total delivery time and the current shipping time to obtain available shifts further includes: Detection points are set according to the node information and preset detection rules. The detection points are used to represent nodes for safety quality inspection of transported goods. According to preset rules, the working nodes adjacent to the monitoring points are divided into front working nodes and back working nodes. If the detection result of any of the detection points shows an abnormality, then the previous working node corresponding to the detection point is identified as the responsible node.

3. The method according to claim 2, characterized in that, The step of designating the preceding working node corresponding to the detection point as the responsible node includes, prior to: Acquire the cargo transportation image within the previous working node; Motion analysis is performed on the cargo transportation images to obtain the cargo transportation operation; The delivery operation is matched with preset delivery standards. If a match is found, a screening instruction for supervisors is generated. If a mismatch is found, a secondary identification instruction is generated. The secondary identification instruction is used to control and identify personnel who violate the rules in the delivery image.

4. A multimodal transport schedule screening device, characterized in that, include: The information acquisition module is used to acquire node information, estimated cargo readiness time, and target arrival time. The node information is used to represent the transportation node information on the transportation route, the estimated cargo readiness time is used to represent the time when the first transportation node will complete the preparation of the transported goods, and the target arrival time is used to represent the time when the last transportation node will prepare the transported goods for dispatch. The shipment analysis module is used to analyze the node information and the estimated delivery time to obtain the current shipment time. The current shipment time is used to indicate the time when the current shipment sender prepares to ship the goods in the node information. The maximum timeliness module is used to perform difference analysis between the target arrival time and the expected cargo preparation time to obtain the total timeliness, which represents the time spent on the transportation nodes and the transportation routes between them. The timeliness module predicts and analyzes the node information and the total timeliness to obtain the total timeliness of issuance. The schedule filtering module is used to filter schedules based on the total delivery time and the current delivery time to obtain available schedules; Specifically, when the shipment analysis module analyzes the node information and the estimated delivery time to obtain the current shipment time, it is used for: The sending node duration is determined based on the node information. The sending node duration is used to represent the time required for the current sender to ship the goods. The sending node duration is the duration for which the goods stay at the first transportation node. The estimated goods readiness time is extended by the time based on the duration of the dispatch node to obtain the current dispatch time; Specifically, when the issuance timeliness module performs predictive analysis on the node information and the total timeliness to obtain the total issuance timeliness, it is used for: Historical transportation data is obtained based on the node information. The historical transportation data is used to represent the duration, route, equipment, and weather data of goods on the transportation segment in the past time. The historical transportation data is input into a well-trained time prediction model to obtain the subsequent transportation timeliness. The subsequent node validity period is obtained based on the node information. The subsequent node validity period is used to represent the maximum time spent by the subsequent node in transporting goods. The subsequent node validity period is the time that the goods stay at each subsequent node. The subsequent node is all non-first transport nodes within the transport node. The total delivery time is obtained by summing the subsequent transportation time with the subsequent node time. The difference between the total effective period and the subsequent total effective period is calculated to obtain the total effective period for issuance; Specifically, the schedule filtering module, when filtering schedules based on the total delivery time and the current shipping time to obtain available schedules, is used for: The current receiving time of the shift is obtained based on the current shipping time. The shift is used to represent the shift used for the transportation segment between the node and the adjacent node. The current receiving time is used to represent the time when the shift receives the current goods. The current receiving time is greater than or equal to the current shipping time. The current delivery time is obtained based on the estimated delivery time and the current delivery time. Perform a difference analysis between the total delivery time and the current delivery time to obtain the current transportation time. The current schedule selection criteria are obtained based on the current receiving time and the current transportation timeliness. The schedules are filtered according to the current schedule selection criteria to obtain available schedules. Specifically, a schedule is considered available when the start time of the schedule is greater than or equal to the current shipping time and the total duration of the schedule is less than or equal to the current transportation time. This also includes: An anomaly identification module is used to obtain preset anomaly categories and transportation status. The preset anomaly categories are used to represent anomalies caused by natural factors and anomalies caused by equipment operation. The transportation status is used to represent the actual transportation status of the transported goods between two adjacent nodes. The natural anomaly module is used to match the preset anomaly category with the transportation situation. If the matching result shows a natural anomaly, a route planning instruction is generated. The route planning instruction is used to replan a route to avoid the natural anomaly. The equipment malfunction module is used to generate a shift query instruction when the matching result is equipment malfunction. The shift query instruction is used to query the transportation shifts to the same location. When the matching result is a natural anomaly, the current cargo location is used as the center and a radius of 1km is used to obtain the range determined by the current cargo location and the radius. It is then determined whether the range contains alternative routes. If alternative routes exist, they are displayed, and the weather / climate conditions corresponding to the current cargo location are recorded. If no alternative routes exist, the radius is cyclically and quantitatively expanded. The range is updated based on the expanded radius, and it is determined whether the updated range contains alternative routes. If no alternative routes exist after three quantitative expansions, the current cargo location and the weather / climate conditions within the range corresponding to the three quantitative expansions are recorded.

5. An electronic device, characterized in that, The electronic device includes: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, said at least one application being configured to: perform the method for screening multimodal transport schedules as described in 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 in the computer, the computer is instructed to perform the method for screening multimodal transport schedules as described in any one of claims 1 to 3.

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