A logistics distribution path optimization method and system based on traffic flow prediction

Abstract

The present invention relates to the technical field of path optimization, and specifically discloses a method and system for optimizing a logistics distribution path based on traffic flow prediction, including: obtaining the processed values ​​of all types of traffic data of all road nodes at the current moment and the predicted efficiency values ​​of all road nodes at the current moment based on all types of traffic data of all road nodes at the current moment; obtaining all first predicted distribution points based on the geographical locations of all distribution points, obtaining the transportation evaluation values ​​of all transportation paths of each first predicted distribution point based on the predicted efficiency values ​​of all first predicted distribution points and all road nodes at the current moment, and obtaining the logistics distribution path optimization result based on the transportation evaluation values ​​of all transportation paths of all first predicted distribution points. The present invention realizes the quantification of the transportation efficiency of each transportation path, and clarifies the logistics distribution path to maximize the distribution efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of route optimization, and in particular to a method and system for optimizing a logistics distribution route based on traffic flow prediction. Background Art

[0002] At present, the vehicle routing problem is an important research issue in the current logistics and transportation management. With the vigorous development of e-commerce in my country, the logistics and transportation business has shown explosive growth, which requires the logistics distribution business to change from the previous rough development to fine management in order to improve efficiency and prevent huge waste of resources. The distribution activities at the end of logistics mostly take place in the city. However, the urban population is growing rapidly, and the urban road traffic is in a sub-healthy state, which has a significant impact on the quality of logistics services. How to overcome the pressure of traffic congestion, effectively arrange the travel time and distribution route of the distribution vehicles within the limited time limit, and realize the efficient and low-cost operation of the logistics system is a problem that many companies need to solve urgently. Therefore, the research on the optimization problem of urban logistics vehicle routing based on real-time road conditions has practical significance.

[0003] However, the existing logistics distribution path optimization method and system based on traffic flow prediction only obtains all paths from the starting point of the transportation route through the logistics node to the end point of the transportation route, and selects the selected path that meets the transportation time requirement from all the obtained paths, and does not quantify the transportation efficiency of each transportation path, and does not consider how to arrange the distribution order to maximize the distribution efficiency when there are multiple distribution points. For example, the patent with the publication number "CN109948850A" and the patent name "Logistics Distribution Vehicle Path Optimization Method and System" includes the following steps: obtaining logistics transportation business requirements, the logistics transportation business includes transportation time, transportation distance, transportation item type, and transportation item mass and volume; selecting logistics distribution parties that meet the logistics transportation business requirements, and selecting one according to the preset matching method; obtaining the logistics nodes that the matched logistics distribution parties must pass through; according to the logistics nodes, obtaining all paths from the starting point of the transportation route through the logistics node to the end point of the transportation route; selecting the selected path that meets the transportation time requirement from all the obtained paths; and sending the selected path to the logistics transportation equipment as a candidate path. The entire process selects a suitable logistics carrier, fully utilizes the necessary node requirements of the logistics carrier, and meets the delivery requirements of the client, so that the route selection is more optimized. However, the patent only obtains all the routes from the starting point of the delivery route through the logistics node to the end point of the delivery route, and selects the selected routes that meet the delivery time requirements from all the obtained routes. It does not quantify the transportation efficiency of each transportation route, and does not consider how to arrange the delivery order to maximize the delivery efficiency when there are multiple delivery points.

[0004] Therefore, the present invention proposes a logistics distribution path optimization method and system based on traffic flow prediction. Summary of the invention

[0005] The present invention provides a logistics distribution path optimization method and system based on traffic flow prediction, which is used to obtain the predicted efficiency values ​​of all road nodes at the current moment according to the processed values ​​of all types of traffic data of all road nodes at the current moment, that is, to quantify the degree of vehicle congestion on the road corresponding to each road node in a unit time after the current moment, to obtain a distribution node map according to the geographical location of all distribution points and the location of distribution vehicles, to obtain all first predicted distribution points according to the distribution node map, to screen out all distribution points that the distribution vehicle cannot deliver to at the current moment, to reduce the amount of invalid calculation, and to accurately obtain the transportation efficiency of all transportation paths of each first predicted distribution point according to the predicted efficiency values ​​of all first predicted distribution points and all road nodes at the current moment. The evaluation value realizes the quantification of the transportation efficiency of each transportation path from the delivery vehicle to each first predicted delivery point, accurately obtains the first delivery point and the best planned path of the first delivery point according to the transportation evaluation values ​​of all transportation paths of all first predicted delivery points, accurately selects the optimal delivery point and the best planned path that the delivery vehicle should select from all first predicted delivery points, updates the distribution node graph according to the first distribution point, obtains a new distribution node graph, and obtains the distribution order of all distribution points according to the new distribution node graph, accurately obtains the delivery order of the delivery vehicle to deliver the goods to each distribution point, obtains the logistics distribution path optimization result according to the distribution order of all distribution points and the best planned path of all distribution points, and improves the logistics distribution efficiency.

[0006] The present invention provides a method for optimizing logistics distribution paths based on traffic flow prediction, comprising:

[0007] S1: based on the geographical locations of all distribution points, all road nodes are obtained, and all types of traffic data of all road nodes at the current moment are obtained, and all types of traffic data of all road nodes at the current moment are processed to obtain the processed values ​​of all types of traffic data of all road nodes at the current moment;

[0008] S2: obtaining the predicted efficiency values ​​of all road nodes at the current moment based on the processed values ​​of all types of traffic data of all road nodes at the current moment;

[0009] S3: obtaining a distribution node graph based on the geographical locations of all distribution points and the locations of distribution vehicles, obtaining all first predicted distribution points based on the distribution node graph, obtaining transportation evaluation values ​​of all transportation paths of each first predicted distribution point based on the predicted efficiency values ​​of all first predicted distribution points and all road nodes at the current moment, and obtaining the first distribution point and the optimal planned path of the first distribution point based on the transportation evaluation values ​​of all transportation paths of all first predicted distribution points;

[0010] S4: Based on the first distribution point, the distribution node graph is updated to obtain a new distribution node graph, the distribution order of all distribution points is obtained based on the new distribution node graph, and the logistics distribution path optimization result is obtained based on the distribution order of all distribution points and the best planned paths of all distribution points.

[0011] Preferably, the logistics distribution path optimization method based on traffic flow prediction, S1: based on the geographical location of all distribution points, all road nodes are obtained, and all types of traffic data of all road nodes at the current moment are obtained, and all types of traffic data of all road nodes at the current moment are processed to obtain the processed values ​​of all types of traffic data of all road nodes at the current moment, including:

[0012] Get the geographic location of all delivery points and the location of the delivery vehicle, and use the location of the delivery vehicle as the origin and the distance between the delivery point farthest from the location of the delivery vehicle and the delivery vehicle as the radius to obtain a judgment circle. Based on the judgment circle and the preset collection point library, obtain all monitoring points within the judgment circle.

[0013] All monitoring points within the judgment circle are regarded as all road nodes, and all types of traffic data of all road nodes in a unit time before the current moment are obtained, wherein all types of traffic data include passing vehicle data and passing speed data;

[0014] Data processing is performed on all types of traffic data of all road nodes within a unit time before the current moment, and processed values ​​of all types of traffic data of all road nodes at the current moment are obtained.

[0015] Preferably, the logistics distribution path optimization method based on traffic flow prediction processes all types of traffic data of all road nodes within a unit time before the current moment to obtain the processed values ​​of all types of traffic data of all road nodes at the current moment, including:

[0016] Based on the passing vehicle data and passing speed data of each road node in the unit time before the current moment, the number of all passing vehicles and the passing speed of each passing vehicle of the corresponding road node in the unit time before the current moment are obtained;

[0017] The speed limit value of each road node is obtained based on all road nodes and the preset speed limit library. If the passing speed of the passing vehicle of each road node is not greater than the speed limit value of the corresponding road node, the corresponding passing vehicle is regarded as the statistical vehicle of the corresponding road node;

[0018] The total number of all statistical vehicles at each road node is regarded as the processing value of the passing vehicle data of the corresponding road node at the current moment;

[0019] The average value of the passing speed of all statistical vehicles at each road node is used as the processing value of the passing speed data of the corresponding road node at the current moment.

[0020] Preferably, the logistics distribution path optimization method based on traffic flow prediction, S2: based on the processed values ​​of all types of traffic data of all road nodes at the current moment, the predicted efficiency values ​​of all road nodes at the current moment are obtained, including:

[0021] Based on the processed values ​​of the passing vehicle data of each road node at the current moment, the processed values ​​of the passing speed data at the current moment and the preset efficiency prediction model, the predicted efficiency value of the corresponding road node at the current moment is obtained.

[0022] Preferably, the logistics distribution path optimization method based on traffic flow prediction, S3: based on the geographical location of all distribution points and the location of the distribution vehicle, a distribution node map is obtained, based on the distribution node map, all first predicted distribution points are obtained, based on the predicted efficiency values ​​of all first predicted distribution points and all road nodes at the current moment, the transportation evaluation values ​​of all transportation paths of each first predicted distribution point are obtained, based on the transportation evaluation values ​​of all transportation paths of all first predicted distribution points, the first distribution points and the best planned paths of the first distribution points are obtained, including:

[0023] The geographical locations of all delivery points and the locations of delivery vehicles are taken as nodes, and all nodes are connected to obtain a delivery node graph;

[0024] All nodes in the distribution node graph whose distance from the node corresponding to the distribution vehicle position is less than the preset distance are used as prediction nodes, and the distribution points corresponding to all prediction nodes are used as the first prediction distribution points;

[0025] Obtaining the transportation evaluation values ​​of all transportation paths of each first predicted delivery point based on the predicted efficiency values ​​of all first predicted delivery points and all road nodes at the current moment;

[0026] The first delivery point and the optimal planning path of the first delivery point are obtained based on the transportation evaluation values ​​of all transportation paths of all first predicted delivery points.

[0027] Preferably, the logistics distribution path optimization method based on traffic flow prediction obtains the transportation evaluation value of all transportation paths of each first predicted distribution point based on the predicted efficiency values ​​of all first predicted distribution points and all road nodes at the current moment, including:

[0028] Based on the position of the delivery vehicle and the corresponding position of each first predicted delivery point and a preset route planning model, all transportation paths of each first predicted delivery point are obtained, wherein all transportation paths of each first predicted delivery point are within the judgment circle;

[0029] Obtain the path distance of each transportation path of each first predicted delivery point, and regard all road nodes on each transportation path as transportation nodes of the corresponding transportation path, and define all transportation nodes of each transportation path in an ordinal order starting from 1 according to the order in which they are passed, to obtain an ordinal definition result;

[0030] Obtain the processed values ​​of the passing speed data of all transport nodes in each transport path at the current moment;

[0031] Based on the path distance of each transportation path of each first predicted distribution point, the predicted efficiency values ​​of all transportation nodes at the current moment, the processed values ​​of the passing speed data of all transportation nodes in each transportation path at the current moment, and the ordinal definition results, the transportation evaluation value of each transportation path of each first predicted distribution point is obtained, which is:

[0032] ;

[0033] in, is the transport evaluation value of a single transport path for the first predicted delivery point currently calculated, is the total number of transport nodes on the transport path corresponding to the first predicted delivery point, is the average value of the processed values ​​of the passing speed data of all transportation nodes in the corresponding transportation path corresponding to the first predicted delivery point at the current moment, is the sum of the path distances of all transportation paths corresponding to the first predicted delivery point, is the path distance of the corresponding transportation path corresponding to the first predicted delivery point, The ordinal number of the transportation path corresponding to the first predicted delivery point is The predicted efficiency value of the transport node at the current moment, The ordinal number of the transportation path corresponding to the first predicted delivery point is The processing value of the speed data of the transport node at the current moment, is the natural logarithm, and the value of the natural constant e is 2.718.

[0034] Preferably, the logistics distribution path optimization method based on traffic flow prediction obtains the optimal planning path between the first distribution point and the first distribution point based on the transportation evaluation values ​​of all transportation paths of all first predicted distribution points, including:

[0035] From all the transport paths of each first predicted delivery point, select the transport path with the largest transport evaluation value as the best planning path corresponding to the first predicted delivery point;

[0036] The transport evaluation values ​​of the best planned paths of all first predicted delivery points are numerically compared, and the first predicted delivery point corresponding to the best planned path with the largest transport evaluation value is selected as the first delivery point.

[0037] Preferably, the logistics distribution path optimization method based on traffic flow prediction, S4: based on the first distribution point, the distribution node map is updated to obtain a new distribution node map, based on the new distribution node map, the distribution order of all distribution points is obtained, and based on the distribution order of all distribution points and the best planned paths of all distribution points, the logistics distribution path optimization result is obtained, including:

[0038] Delete the node corresponding to the original delivery vehicle position, and use the first delivery point in the delivery node graph as the new delivery vehicle position to obtain a new delivery node graph, and continue to obtain a new first delivery point and the best planning path for the new first delivery point based on the new delivery node graph until the delivery order of all delivery points and the best planning paths for all delivery points are determined;

[0039] The logistics distribution path optimization results are obtained based on the distribution order of all distribution points and the best planned paths of all distribution points.

[0040] Preferably, the logistics distribution path optimization method based on traffic flow prediction obtains the logistics distribution path optimization result based on the distribution order of all distribution points and the best planned paths of all distribution points, including:

[0041] According to the distribution order of the distribution points, the best planned paths of all distribution points are connected to obtain the logistics distribution path, and the logistics distribution path is sent to the distribution vehicle backend;

[0042] When it is determined that the real-time trajectory of the delivery vehicle deviates from the logistics distribution path, a voice prompt is given to obtain the logistics distribution path optimization result.

[0043] The present invention provides a logistics distribution path optimization system based on traffic flow prediction, which is used to execute any one of the logistics distribution path optimization methods based on traffic flow prediction in embodiments 1 to 9, including:

[0044] A processing module is used to obtain all road nodes based on the geographical locations of all distribution points, obtain all types of traffic data of all road nodes at the current moment, perform data processing on all types of traffic data of all road nodes at the current moment, and obtain processed values ​​of all types of traffic data of all road nodes at the current moment;

[0045] A prediction module, used for obtaining the predicted efficiency values ​​of all road nodes at the current moment based on the processed values ​​of all types of traffic data of all road nodes at the current moment;

[0046] A calculation module, for obtaining a distribution node map based on the geographical locations of all distribution points and the locations of distribution vehicles, obtaining all first predicted distribution points based on the distribution node map, obtaining a transportation evaluation value of all transportation paths of each first predicted distribution point based on the predicted efficiency values ​​of all first predicted distribution points and all road nodes at the current moment, and obtaining a first distribution point and an optimal planned path of the first distribution point based on the transportation evaluation values ​​of all transportation paths of all first predicted distribution points;

[0047] The path optimization module is used to update the distribution node diagram based on the first distribution point to obtain a new distribution node diagram, obtain the distribution order of all distribution points based on the new distribution node diagram, and obtain the logistics distribution path optimization result based on the distribution order of all distribution points and the best planned path of all distribution points.

[0048] Compared with the prior art, the beneficial effects of the present invention are as follows: the predicted efficiency values ​​of all road nodes at the current moment are obtained according to the processed values ​​of all types of traffic data of all road nodes at the current moment, that is, the quantification of the vehicle congestion degree per unit time on the road corresponding to each road node after the current moment is realized, the distribution node map is obtained according to the geographical location of all distribution points and the location of the distribution vehicle, all the first predicted distribution points are obtained according to the distribution node map, all the distribution points that the distribution vehicle cannot deliver at the current moment are screened out, and the amount of invalid calculation is reduced, and the transportation evaluation values ​​of all transportation paths of each first predicted distribution point are accurately obtained according to the predicted efficiency values ​​of all first predicted distribution points and all road nodes at the current moment, that is, the transportation evaluation values ​​of all transportation paths of each first predicted distribution point are realized. The transport efficiency of each transport path from the delivery vehicle to each first predicted delivery point is quantified, the first delivery point and the best planned path of the first delivery point are accurately obtained according to the transport evaluation values ​​of all transport paths of all first predicted delivery points, the optimal delivery point and the best planned path that the delivery vehicle should select from all first predicted delivery points are accurately selected, the distribution node graph is updated according to the first distribution point to obtain a new distribution node graph, and the distribution order of all distribution points is obtained according to the new distribution node graph, the delivery order of the delivery vehicle to each distribution point is accurately obtained, and the logistics distribution path optimization result is obtained according to the distribution order of all distribution points and the best planned path of all distribution points, thereby improving the logistics distribution efficiency.

[0049] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structure specifically pointed out in the written application document.

[0050] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0052] Figure 1 This is a flow chart of a method for optimizing a logistics distribution path based on traffic flow prediction in an embodiment of the present invention;

[0053] Figure 2 Schematic diagram of a logistics distribution path optimization system based on traffic flow prediction in an embodiment of the present invention. DETAILED DESCRIPTION

[0054] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention. Embodiment 1:

[0055] The present invention provides a logistics distribution path optimization method based on traffic flow prediction. Figure 1 ,include:

[0056] S1: based on the geographical locations of all distribution points, all road nodes are obtained, and all types of traffic data of all road nodes at the current moment are obtained, and all types of traffic data of all road nodes at the current moment are processed to obtain the processed values ​​of all types of traffic data of all road nodes at the current moment;

[0057] S2: obtaining the predicted efficiency values ​​of all road nodes at the current moment based on the processed values ​​of all types of traffic data of all road nodes at the current moment;

[0058] S3: obtaining a distribution node graph based on the geographical locations of all distribution points and the locations of distribution vehicles, obtaining all first predicted distribution points based on the distribution node graph, obtaining transportation evaluation values ​​of all transportation paths of each first predicted distribution point based on the predicted efficiency values ​​of all first predicted distribution points and all road nodes at the current moment, and obtaining the first distribution point and the optimal planned path of the first distribution point based on the transportation evaluation values ​​of all transportation paths of all first predicted distribution points;

[0059] S4: Based on the first distribution point, the distribution node graph is updated to obtain a new distribution node graph, the distribution order of all distribution points is obtained based on the new distribution node graph, and the logistics distribution path optimization result is obtained based on the distribution order of all distribution points and the best planned paths of all distribution points.

[0060] In this embodiment, the geographical location of the delivery point is the actual location of all packages that need to be delivered during this logistics delivery process.

[0061] In this embodiment, the road node is the location of all road monitoring that can obtain vehicle data required to obtain the logistics distribution path optimization result.

[0062] In this embodiment, the data processing is a process of obtaining processed values ​​of all types of traffic data of all road nodes at the current moment based on all types of traffic data of all road nodes at the current moment.

[0063] In this embodiment, the processed value of the traffic data is a value of real traffic data obtained based on all types of traffic data of each road node at the current moment and can be used to obtain the predicted efficiency value of each road node at the current moment.

[0064] In this embodiment, the predicted efficiency value is a value predicted based on the processed values ​​of all types of traffic data of each road node at the current moment, which can reflect the degree of vehicle congestion on the road corresponding to each road node within a preset time (60 minutes) after the current moment.

[0065] In this embodiment, the delivery vehicle location is the actual location of the delivery vehicle using the logistics delivery path optimization system based on traffic flow prediction.

[0066] In this embodiment, the delivery node graph is a node graph that includes the geographical locations of all delivery points and the relative positions of the delivery vehicles in the actual geographical space, and that can obtain all first predicted delivery points.

[0067] In this embodiment, the first predicted delivery points are all delivery points that the delivery vehicle may deliver to at the current moment.

[0068] In this embodiment, the transportation routes are all routes that the delivery vehicle can travel to deliver the goods to each first predicted delivery point.

[0069] In this embodiment, the transport evaluation value is a numerical value obtained based on the predicted efficiency values ​​of all first predicted delivery points and all road nodes at the current moment, representing the transport efficiency of each transport path from the delivery vehicle to each first predicted delivery point.

[0070] In this embodiment, the first delivery point is the optimal delivery point that the delivery vehicle should select from among all first predicted delivery points (ie, the delivery point that should be delivered first in the current logistics delivery process).

[0071] In this embodiment, the optimal planned path for the first delivery point is the transportation path that can maximize the transportation efficiency when the delivery vehicle delivers the goods to the first delivery point among all transportation paths.

[0072] In this embodiment, the new delivery node graph is a new node graph obtained by reconstructing the delivery node graph based on the first delivery point.

[0073] In this embodiment, the delivery order is the order in which each delivery point is delivered when the delivery vehicle is delivering the goods.

[0074] In this embodiment, the logistics distribution path optimization result is to obtain the logistics distribution path based on the distribution order of all distribution points and the best planned path of all distribution points, and voice prompt this result based on the logistics distribution path.

[0075] The beneficial effects of the above technology are as follows: the predicted efficiency values ​​of all road nodes at the current moment are obtained according to the processed values ​​of all types of traffic data of all road nodes at the current moment, that is, the quantification of the vehicle congestion degree per unit time on the road corresponding to each road node after the current moment is realized, the distribution node map is obtained according to the geographical location of all distribution points and the location of the distribution vehicles, all the first predicted distribution points are obtained according to the distribution node map, all the distribution points that the distribution vehicles cannot deliver to at the current moment are screened out, and the amount of invalid calculations is reduced, and the transportation evaluation values ​​of all transportation paths of each first predicted distribution point are accurately obtained according to the predicted efficiency values ​​of all first predicted distribution points and all road nodes at the current moment, that is, the distribution evaluation of the distribution points is realized. The transport efficiency of each transport path from the delivery vehicle to each first predicted delivery point is quantified, and the first delivery point and the best planned path of the first delivery point are accurately obtained according to the transport evaluation values ​​of all transport paths of all first predicted delivery points. The optimal delivery point and the best planned path that the delivery vehicle should select from all first predicted delivery points are accurately selected, and the distribution node graph is updated according to the first distribution point to obtain a new distribution node graph, and the distribution order of all distribution points is obtained according to the new distribution node graph, and the delivery order of the delivery vehicle to each distribution point is accurately obtained. The logistics distribution path optimization result is obtained according to the distribution order of all distribution points and the best planned path of all distribution points, thereby improving the logistics distribution efficiency. Embodiment 2:

[0076] Based on Example 1, a logistics distribution path optimization method based on traffic flow prediction, S1: based on the geographical locations of all distribution points, all road nodes are obtained, and all types of traffic data of all road nodes at the current moment are obtained, and all types of traffic data of all road nodes at the current moment are processed to obtain the processed values ​​of all types of traffic data of all road nodes at the current moment, including:

[0077] Get the geographic location of all delivery points and the location of the delivery vehicle, and use the location of the delivery vehicle as the origin and the distance between the delivery point farthest from the location of the delivery vehicle and the delivery vehicle as the radius to obtain a judgment circle. Based on the judgment circle and the preset collection point library, obtain all monitoring points within the judgment circle.

[0078] All monitoring points within the judgment circle are regarded as all road nodes, and all types of traffic data of all road nodes in the unit time (1min) before the current moment are obtained, where all types of traffic data include passing vehicle data and passing speed data;

[0079] Data processing is performed on all types of traffic data of all road nodes within a unit time before the current moment, and processed values ​​of all types of traffic data of all road nodes at the current moment are obtained.

[0080] In this embodiment, the judgment circle is a circular geographical range obtained by taking the location of the delivery vehicle as the origin and the distance between the delivery point farthest from the location of the delivery vehicle and the delivery vehicle as the radius.

[0081] In this embodiment, the preset collection point library is a database containing all the installation locations of road monitoring within the areas covered by all the distribution points collected in advance.

[0082] In this embodiment, the passing vehicle data is the number of vehicles that have passed the road node within a unit time (1 minute) before the current moment.

[0083] In this embodiment, the passing speed data is the speed of each vehicle passing through the road node within a unit time (1 minute) before the current moment.

[0084] The beneficial effects of the above technology are: all road nodes are obtained according to the geographical location of all distribution points, the method of obtaining road nodes is clarified, and the specific parameter items of all types of traffic data of all road nodes at the current moment are clarified, and data processing is performed on all types of traffic data of all road nodes at the current moment to obtain the processed values ​​of all types of traffic data of all road nodes at the current moment. Embodiment 3:

[0085] On the basis of Example 2, the logistics distribution path optimization method based on traffic flow prediction processes all types of traffic data of all road nodes within a unit time before the current moment, and obtains the processed values ​​of all types of traffic data of all road nodes at the current moment, including:

[0086] Based on the passing vehicle data and passing speed data of each road node in the unit time before the current moment, the number of all passing vehicles and the passing speed of each passing vehicle of the corresponding road node in the unit time before the current moment are obtained;

[0087] The speed limit value of each road node is obtained based on all road nodes and the preset speed limit library. If the passing speed of the passing vehicle of each road node is not greater than the speed limit value of the corresponding road node, the corresponding passing vehicle is regarded as the statistical vehicle of the corresponding road node;

[0088] The total number of all statistical vehicles at each road node is regarded as the processing value of the passing vehicle data of the corresponding road node at the current moment;

[0089] The average value of the passing speed of all statistical vehicles at each road node is used as the processing value of the passing speed data of the corresponding road node at the current moment.

[0090] In this embodiment, the preset speed limit database is a database composed of pre-collected speed limit values ​​on roads corresponding to road nodes corresponding to all monitoring points.

[0091] In this embodiment, the speed limit value is the maximum travel speed allowed on the road corresponding to each road node.

[0092] In this embodiment, the counted vehicles are vehicles passing through whose passing speed is not greater than the speed limit value of the corresponding road node.

[0093] The beneficial effects of the above technology are: based on the passing vehicle data, passing speed data and preset speed limit library of each road node in a unit time before the current moment, the statistical vehicles of all road nodes are obtained, and based on the total number and passing speed of all statistical vehicles of all road nodes, the processed values ​​of all types of traffic data of all road nodes at the current moment are obtained. This embodiment specifically provides a specific method for processing all types of traffic data of all road nodes in a unit time before the current moment to obtain the processed values ​​of all types of traffic data of all road nodes at the current moment. Embodiment 4:

[0094] Based on Example 2, the logistics distribution path optimization method based on traffic flow prediction, S2: based on the processed values ​​of all types of traffic data of all road nodes at the current moment, the predicted efficiency values ​​of all road nodes at the current moment are obtained, including:

[0095] Based on the processed values ​​of the passing vehicle data of each road node at the current moment, the processed values ​​of the passing speed data at the current moment and the preset efficiency prediction model, the predicted efficiency value of the corresponding road node at the current moment is obtained, which is:

[0096] The processed values ​​of the passing vehicle data and the processed values ​​of the passing speed data of each road node at the current moment are input into the preset efficiency prediction model to obtain the predicted efficiency value of the corresponding road node at the current moment.

[0097] In this embodiment, the preset efficiency prediction model is a model that uses the processed values ​​of the passing vehicle data of a large number of road nodes at the current moment and the processed values ​​of the passing speed data at the current moment as model input in advance, and the predicted efficiency value of the corresponding road node at the current moment analyzed manually (according to the vehicle congestion level of the corresponding road node within a preset time after the current moment) as model output, and is trained to output the predicted efficiency value of the corresponding road node at the current moment based on the input processed values ​​of the passing vehicle data of the road node at the current moment and the processed values ​​of the passing speed data at the current moment.

[0098] The beneficial effects of the above technology are: obtaining the predicted efficiency values ​​of all road nodes at the current moment based on the processed values ​​of all types of traffic data of all road nodes at the current moment, quantifying the degree of vehicle congestion on the road corresponding to each road node per unit time after the current moment, and facilitating the acquisition of subsequent transportation evaluation values. Embodiment 5:

[0099] Based on Example 1, a logistics distribution path optimization method based on traffic flow prediction, S3: obtaining a distribution node map based on the geographical locations of all distribution points and the locations of distribution vehicles, obtaining all first predicted distribution points based on the distribution node map, obtaining a transportation evaluation value of all transportation paths of each first predicted distribution point based on the predicted efficiency values ​​of all first predicted distribution points and all road nodes at the current moment, and obtaining the first distribution point and the best planned path of the first distribution point based on the transportation evaluation values ​​of all transportation paths of all first predicted distribution points, including:

[0100] The geographical locations of all delivery points and the locations of delivery vehicles are taken as nodes, and all nodes are connected to obtain a delivery node graph;

[0101] All nodes in the distribution node graph whose distance from the node corresponding to the distribution vehicle position is less than the preset distance are used as prediction nodes, and the distribution points corresponding to all prediction nodes are used as the first prediction distribution points;

[0102] Obtaining the transportation evaluation values ​​of all transportation paths of each first predicted delivery point based on the predicted efficiency values ​​of all first predicted delivery points and all road nodes at the current moment;

[0103] The first delivery point and the optimal planning path of the first delivery point are obtained based on the transportation evaluation values ​​of all transportation paths of all first predicted delivery points.

[0104] In this embodiment, the preset distance is a value that the distance between the preset prediction node and the node corresponding to the delivery vehicle position should be less than, for example, 2KM.

[0105] The beneficial effects of the above technology are as follows: a distribution node diagram is obtained according to the geographical locations of all distribution points and the locations of distribution vehicles, a specific method for constructing a distribution node diagram is clearly given, all first predicted distribution points are obtained according to the distribution node diagram, all distribution points that the distribution vehicle cannot deliver to at the current moment are screened out, invalid calculations are reduced, and calculation efficiency is improved, and the transportation evaluation values ​​of all transportation paths of each first predicted distribution point are accurately obtained according to the predicted efficiency values ​​of all first predicted distribution points and all road nodes at the current moment, and the transportation efficiency of each transportation path from the distribution vehicle to each first predicted distribution point is quantified, and the first distribution points and the best planned paths of the first distribution points are accurately obtained according to the transportation evaluation values ​​of all transportation paths of all first predicted distribution points, and the optimal distribution points and the best planned paths that the delivery vehicles should select among all first predicted distribution points are accurately selected. Embodiment 6:

[0106] On the basis of Example 5, the logistics distribution path optimization method based on traffic flow prediction obtains the transportation evaluation value of all transportation paths of each first predicted distribution point based on the predicted efficiency values ​​of all first predicted distribution points and all road nodes at the current moment, including:

[0107] Based on the position of the delivery vehicle and the corresponding position of each first predicted delivery point and a preset route planning model, all transportation paths of each first predicted delivery point are obtained, wherein all transportation paths of each first predicted delivery point are within the judgment circle;

[0108] Obtain the path distance of each transportation path of each first predicted delivery point, and regard all road nodes on each transportation path as transportation nodes of the corresponding transportation path, and define all transportation nodes of each transportation path in an ordinal order starting from 1 according to the order in which they are passed, to obtain an ordinal definition result;

[0109] Obtain the processed values ​​of the passing speed data of all transport nodes in each transport path at the current moment;

[0110] Based on the path distance of each transportation path of each first predicted distribution point, the predicted efficiency values ​​of all transportation nodes at the current moment, the processed values ​​of the passing speed data of all transportation nodes in each transportation path at the current moment, and the ordinal definition results, the transportation evaluation value of each transportation path of each first predicted distribution point is obtained, which is:

[0111] ;

[0112] in, is the transport evaluation value of a single transport path for the first predicted delivery point currently calculated, is the total number of transport nodes on the transport path corresponding to the first predicted delivery point, is the average value of the processed values ​​of the passing speed data of all transportation nodes in the corresponding transportation path corresponding to the first predicted delivery point at the current moment, is the sum of the path distances of all transportation paths corresponding to the first predicted delivery point, is the path distance of the corresponding transportation path corresponding to the first predicted delivery point, The ordinal number of the transportation path corresponding to the first predicted delivery point is The predicted efficiency value of the transport node at the current moment, The ordinal number of the transportation path corresponding to the first predicted delivery point is The processing value of the speed data of the transport node at the current moment, is the natural logarithm, and the value of the natural constant e is 2.718.

[0113] In this embodiment, the preset route planning model is a model that is pre-trained with a large number of delivery vehicle locations and all first predicted delivery points corresponding to each delivery vehicle location as model input, and all transportation paths between each manually marked delivery vehicle location and each corresponding first predicted delivery point as model output. The model can output all transportation paths between the delivery vehicle location and the corresponding single first predicted delivery point based on the input delivery vehicle location and the corresponding single first predicted delivery point.

[0114] The beneficial effects of the above technology are: accurately obtaining the transportation evaluation value of all transportation paths of each first predicted delivery point according to the predicted efficiency values ​​of all first predicted delivery points and all road nodes at the current moment, quantifying the transportation efficiency of each transportation path from the delivery vehicle to each first predicted delivery point, which is conducive to the delivery vehicle selecting the most efficient transportation path and reducing driving time and cost. This embodiment provides a specific method for accurately obtaining the transportation evaluation value of all transportation paths of each first predicted delivery point according to the predicted efficiency values ​​of all first predicted delivery points and all road nodes at the current moment.

[0115] Embodiment 7:

[0116] On the basis of Example 5, the logistics distribution path optimization method based on traffic flow prediction obtains the first distribution point and the optimal planning path of the first distribution point based on the transportation evaluation values ​​of all transportation paths of all first predicted distribution points, including:

[0117] From all the transport paths of each first predicted delivery point, select the transport path with the largest transport evaluation value as the best planning path corresponding to the first predicted delivery point;

[0118] The transport evaluation values ​​of the best planned paths of all first predicted delivery points are numerically compared, and the first predicted delivery point corresponding to the best planned path with the largest transport evaluation value is selected as the first delivery point.

[0119] The beneficial effects of the above technology are: accurately obtaining the first delivery point and the best planned path of the first delivery point based on the transportation evaluation values ​​of all transportation paths of all first predicted delivery points, and accurately selecting the optimal delivery point and the best planned path that the delivery vehicle should select from all first predicted delivery points. This embodiment provides a specific method for obtaining the first delivery point and the best planned path of the first delivery point based on the transportation evaluation values ​​of all transportation paths of all first predicted delivery points.

[0120] Embodiment 8:

[0121] Based on Example 1, the logistics distribution path optimization method based on traffic flow prediction, S4: based on the first distribution point, the distribution node graph is updated to obtain a new distribution node graph, the distribution order of all distribution points is obtained based on the new distribution node graph, and the logistics distribution path optimization result is obtained based on the distribution order of all distribution points and the best planned paths of all distribution points, including:

[0122] Delete the node corresponding to the original delivery vehicle position, and use the first delivery point in the delivery node graph as the new delivery vehicle position to obtain a new delivery node graph, and continue to obtain a new first delivery point and the best planning path for the new first delivery point based on the new delivery node graph until the delivery order of all delivery points and the best planning paths for all delivery points are determined;

[0123] The logistics distribution path optimization results are obtained based on the distribution order of all distribution points and the best planned paths of all distribution points.

[0124] In this embodiment, the method of continuing to obtain a new first delivery point and an optimal planned path for the new first delivery point based on the new delivery node graph is consistent with the method of obtaining the first delivery point and an optimal planned path for the first delivery point based on the delivery node graph for the first time.

[0125] The beneficial effects of the above technology are: the distribution node map is updated according to the first distribution point to obtain a new distribution node map, the distribution order of all distribution points is obtained according to the new distribution node map, the delivery order of the delivery vehicle to each distribution point is accurately obtained, and the logistics distribution path optimization result is obtained according to the distribution order of all distribution points and the best planned path of all distribution points, thereby improving logistics efficiency.

[0126] Embodiment 9:

[0127] On the basis of Example 8, the logistics distribution path optimization method based on traffic flow prediction obtains the logistics distribution path optimization result based on the distribution order of all distribution points and the best planned paths of all distribution points, including:

[0128] According to the distribution order of the distribution points, the best planned paths of all distribution points are connected to obtain the logistics distribution path, and the logistics distribution path is sent to the distribution vehicle backend;

[0129] When it is determined that the real-time trajectory of the delivery vehicle deviates from the logistics distribution path, a voice prompt is given to obtain the logistics distribution path optimization result.

[0130] In this embodiment, the delivery vehicle backend is a program system installed on the delivery vehicle that can receive data and can also send prompt information to the logistics delivery personnel.

[0131] In this embodiment, the voice prompt is a voice alarm prompt, such as "You have deviated from the course, please enter the logistics distribution path as soon as possible" and the like.

[0132] The beneficial effects of the above technology are: obtaining the logistics distribution path optimization results based on the distribution order of all distribution points and the best planned paths of all distribution points, and timely prompting the delivery vehicles whose real-time trajectories deviate from the logistics distribution paths, thereby optimizing the logistics distribution paths and improving logistics efficiency.

[0133] Embodiment 10:

[0134] The present invention provides a logistics distribution path optimization system based on traffic flow prediction, which is used to execute any one of the logistics distribution path optimization methods based on traffic flow prediction in embodiments 1 to 9, referring to Figure 2 ,include:

[0135] A processing module is used to obtain all road nodes based on the geographical locations of all distribution points, obtain all types of traffic data of all road nodes at the current moment, perform data processing on all types of traffic data of all road nodes at the current moment, and obtain processed values ​​of all types of traffic data of all road nodes at the current moment;

[0136] A prediction module, used for obtaining the predicted efficiency values ​​of all road nodes at the current moment based on the processed values ​​of all types of traffic data of all road nodes at the current moment;

[0137] A calculation module, for obtaining a distribution node map based on the geographical locations of all distribution points and the locations of distribution vehicles, obtaining all first predicted distribution points based on the distribution node map, obtaining a transportation evaluation value of all transportation paths of each first predicted distribution point based on the predicted efficiency values ​​of all first predicted distribution points and all road nodes at the current moment, and obtaining a first distribution point and an optimal planned path of the first distribution point based on the transportation evaluation values ​​of all transportation paths of all first predicted distribution points;

[0138] The path optimization module is used to update the distribution node diagram based on the first distribution point to obtain a new distribution node diagram, obtain the distribution order of all distribution points based on the new distribution node diagram, and obtain the logistics distribution path optimization result based on the distribution order of all distribution points and the best planned path of all distribution points.

[0139] The beneficial effects of the above technology are as follows: the predicted efficiency values ​​of all road nodes at the current moment are obtained according to the processed values ​​of all types of traffic data of all road nodes at the current moment, that is, the quantification of the vehicle congestion degree per unit time on the road corresponding to each road node after the current moment is realized, the distribution node map is obtained according to the geographical location of all distribution points and the location of the distribution vehicles, all the first predicted distribution points are obtained according to the distribution node map, all the distribution points that the distribution vehicles cannot deliver to at the current moment are screened out, and the amount of invalid calculations is reduced, and the transportation evaluation values ​​of all transportation paths of each first predicted distribution point are accurately obtained according to the predicted efficiency values ​​of all first predicted distribution points and all road nodes at the current moment, that is, the distribution evaluation of the distribution points is realized. The transport efficiency of each transport path from the delivery vehicle to each first predicted delivery point is quantified, and the first delivery point and the best planned path of the first delivery point are accurately obtained according to the transport evaluation values ​​of all transport paths of all first predicted delivery points. The optimal delivery point and the best planned path that the delivery vehicle should select from all first predicted delivery points are accurately selected, and the distribution node graph is updated according to the first distribution point to obtain a new distribution node graph, and the distribution order of all distribution points is obtained according to the new distribution node graph, and the delivery order of the delivery vehicle to each distribution point is accurately obtained. The logistics distribution path optimization result is obtained according to the distribution order of all distribution points and the best planned path of all distribution points, thereby improving the logistics distribution efficiency.

[0140] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A logistics distribution path optimization method based on traffic flow prediction, characterized in that: include: S1: based on the geographical locations of all distribution points, all road nodes are obtained, and all types of traffic data of all road nodes at the current moment are obtained, and all types of traffic data of all road nodes at the current moment are processed to obtain the processed values ​​of all types of traffic data of all road nodes at the current moment; S2: obtaining the predicted efficiency values ​​of all road nodes at the current moment based on the processed values ​​of all types of traffic data of all road nodes at the current moment; S3: obtaining a distribution node graph based on the geographical locations of all distribution points and the locations of distribution vehicles, obtaining all first predicted distribution points based on the distribution node graph, obtaining transportation evaluation values ​​of all transportation paths of each first predicted distribution point based on the predicted efficiency values ​​of all first predicted distribution points and all road nodes at the current moment, and obtaining the first distribution point and the optimal planned path of the first distribution point based on the transportation evaluation values ​​of all transportation paths of all first predicted distribution points; S4: updating the distribution node graph based on the first distribution point to obtain a new distribution node graph, obtaining the distribution order of all distribution points based on the new distribution node graph, and obtaining the logistics distribution path optimization result based on the distribution order of all distribution points and the best planned paths of all distribution points; Wherein, based on the predicted efficiency values ​​of all first predicted delivery points and all road nodes at the current moment, the transportation evaluation values ​​of all transportation paths of each first predicted delivery point are obtained, including: Based on the position of the delivery vehicle and the corresponding position of each first predicted delivery point and a preset route planning model, all transportation paths of each first predicted delivery point are obtained, wherein all transportation paths of each first predicted delivery point are within the judgment circle; Obtain the path distance of each transportation path of each first predicted delivery point, and regard all road nodes on each transportation path as transportation nodes of the corresponding transportation path, and define all transportation nodes of each transportation path in an ordinal order starting from 1 according to the order in which they are passed, to obtain an ordinal definition result; Obtain the processed values ​​of the passing speed data of all transport nodes in each transport path at the current moment; Based on the path distance of each transportation path of each first predicted distribution point, the predicted efficiency values ​​of all transportation nodes at the current moment, the processed values ​​of the passing speed data of all transportation nodes in each transportation path at the current moment, and the ordinal definition results, the transportation evaluation value of each transportation path of each first predicted distribution point is obtained, which is: ； in, is the transport evaluation value of a single transport path for the first predicted delivery point currently calculated, is the total number of transport nodes on the transport path corresponding to the first predicted delivery point, is the average value of the processed values ​​of the passing speed data of all transportation nodes in the corresponding transportation path corresponding to the first predicted delivery point at the current moment, is the sum of the path distances of all transportation paths corresponding to the first predicted delivery point, is the path distance of the corresponding transportation path corresponding to the first predicted delivery point, The ordinal number of the transportation path corresponding to the first predicted delivery point is The predicted efficiency value of the transport node at the current moment, The ordinal number of the transportation path corresponding to the first predicted delivery point is The processing value of the speed data of the transport node at the current moment, is the natural logarithm, and the value of the natural constant e is 2.

718.

2. The method for optimizing logistics distribution paths based on traffic flow prediction according to claim 1 is characterized in that: S1: Based on the geographical locations of all distribution points, all road nodes are obtained, and all traffic data of all road nodes at the current moment are obtained. All traffic data of all road nodes at the current moment are processed to obtain the processed values ​​of all traffic data of all road nodes at the current moment, including: Get the geographic location of all delivery points and the location of the delivery vehicle, and use the location of the delivery vehicle as the origin and the distance between the delivery point farthest from the location of the delivery vehicle and the delivery vehicle as the radius to obtain a judgment circle. Based on the judgment circle and the preset collection point library, obtain all monitoring points within the judgment circle. All monitoring points within the judgment circle are regarded as all road nodes, and all types of traffic data of all road nodes in a unit time before the current moment are obtained, wherein all types of traffic data include passing vehicle data and passing speed data; Data processing is performed on all types of traffic data of all road nodes within a unit time before the current moment, and processed values ​​of all types of traffic data of all road nodes at the current moment are obtained.

3. The method for optimizing logistics distribution paths based on traffic flow prediction according to claim 2 is characterized in that: Data processing is performed on all types of traffic data of all road nodes within a unit time before the current moment, and the processed values ​​of all types of traffic data of all road nodes at the current moment are obtained, including: Based on the passing vehicle data and passing speed data of each road node in the unit time before the current moment, the number of all passing vehicles and the passing speed of each passing vehicle of the corresponding road node in the unit time before the current moment are obtained; The speed limit value of each road node is obtained based on all road nodes and the preset speed limit library. If the passing speed of the passing vehicle of each road node is not greater than the speed limit value of the corresponding road node, the corresponding passing vehicle is regarded as the statistical vehicle of the corresponding road node; The total number of all statistical vehicles at each road node is regarded as the processing value of the passing vehicle data of the corresponding road node at the current moment; The average value of the passing speed of all the statistical vehicles at each road node is used as the processing value of the passing speed data of the corresponding road node at the current moment.

4. The method for optimizing logistics distribution paths based on traffic flow prediction according to claim 2 is characterized in that: S2: Based on the processed values ​​of all types of traffic data of all road nodes at the current moment, the predicted efficiency values ​​of all road nodes at the current moment are obtained, including: Based on the processed values ​​of the passing vehicle data of each road node at the current moment, the processed values ​​of the passing speed data at the current moment and the preset efficiency prediction model, the predicted efficiency value of the corresponding road node at the current moment is obtained.

5. The method for optimizing logistics distribution paths based on traffic flow prediction according to claim 1 is characterized in that: S3: obtaining a distribution node graph based on the geographic locations of all distribution points and the locations of distribution vehicles, obtaining all first predicted distribution points based on the distribution node graph, obtaining a transportation evaluation value of all transportation paths of each first predicted distribution point based on the predicted efficiency values ​​of all first predicted distribution points and all road nodes at the current moment, and obtaining the first distribution point and the optimal planning path of the first distribution point based on the transportation evaluation values ​​of all transportation paths of all first predicted distribution points, including: The geographical locations of all delivery points and the locations of delivery vehicles are taken as nodes, and all nodes are connected to obtain a delivery node graph; All nodes in the distribution node graph whose distance from the node corresponding to the distribution vehicle position is less than a preset distance are used as prediction nodes, and the distribution points corresponding to all prediction nodes are used as the first prediction distribution points; Obtaining the transportation evaluation values ​​of all transportation paths of each first predicted delivery point based on the predicted efficiency values ​​of all first predicted delivery points and all road nodes at the current moment; The first delivery point and the optimal planning path of the first delivery point are obtained based on the transportation evaluation values ​​of all transportation paths of all first predicted delivery points.

6. The method for optimizing logistics distribution paths based on traffic flow prediction according to claim 5 is characterized in that: The first delivery point and the best planning path of the first delivery point are obtained based on the transportation evaluation values ​​of all transportation paths of all first predicted delivery points, including: From all the transport paths of each first predicted delivery point, select the transport path with the largest transport evaluation value as the best planning path corresponding to the first predicted delivery point; The transport evaluation values ​​of the best planned paths of all first predicted delivery points are numerically compared, and the first predicted delivery point corresponding to the best planned path with the largest transport evaluation value is selected as the first delivery point.

7. The method for optimizing logistics distribution paths based on traffic flow prediction according to claim 1 is characterized in that: S4: Based on the first distribution point, the distribution node graph is updated to obtain a new distribution node graph, the distribution order of all distribution points is obtained based on the new distribution node graph, and the logistics distribution path optimization result is obtained based on the distribution order of all distribution points and the best planning path of all distribution points, including: Delete the node corresponding to the original delivery vehicle position, and use the first delivery point in the delivery node graph as the new delivery vehicle position to obtain a new delivery node graph, and continue to obtain a new first delivery point and the best planning path for the new first delivery point based on the new delivery node graph until the delivery order of all delivery points and the best planning paths for all delivery points are determined; The logistics distribution path optimization results are obtained based on the distribution order of all distribution points and the best planned paths of all distribution points.

8. The method for optimizing logistics distribution paths based on traffic flow prediction according to claim 7 is characterized in that: Based on the distribution order of all distribution points and the best planning path of all distribution points, the logistics distribution path optimization results are obtained, including: According to the distribution order of the distribution points, the best planned paths of all distribution points are connected to obtain the logistics distribution path, and the logistics distribution path is sent to the distribution vehicle backend; When it is determined that the real-time trajectory of the delivery vehicle deviates from the logistics distribution path, a voice prompt is given to obtain the logistics distribution path optimization result.

9. A logistics distribution path optimization system based on traffic flow prediction, characterized in that: The method for optimizing a logistics distribution path based on traffic flow prediction according to any one of claims 1 to 8 comprises: A processing module is used to obtain all road nodes based on the geographical locations of all distribution points, obtain all types of traffic data of all road nodes at the current moment, perform data processing on all types of traffic data of all road nodes at the current moment, and obtain processed values ​​of all types of traffic data of all road nodes at the current moment; A prediction module, used for obtaining the predicted efficiency values ​​of all road nodes at the current moment based on the processed values ​​of all types of traffic data of all road nodes at the current moment; A calculation module, for obtaining a distribution node map based on the geographical locations of all distribution points and the locations of distribution vehicles, obtaining all first predicted distribution points based on the distribution node map, obtaining a transportation evaluation value of all transportation paths of each first predicted distribution point based on the predicted efficiency values ​​of all first predicted distribution points and all road nodes at the current moment, and obtaining a first distribution point and an optimal planned path of the first distribution point based on the transportation evaluation values ​​of all transportation paths of all first predicted distribution points; A path optimization module is used to update the distribution node graph based on the first distribution point to obtain a new distribution node graph, obtain the distribution order of all distribution points based on the new distribution node graph, and obtain the logistics distribution path optimization result based on the distribution order of all distribution points and the best planned paths of all distribution points; Wherein, based on the predicted efficiency values ​​of all first predicted delivery points and all road nodes at the current moment, the transportation evaluation values ​​of all transportation paths of each first predicted delivery point are obtained, including: Based on the position of the delivery vehicle and the corresponding position of each first predicted delivery point and a preset route planning model, all transportation paths of each first predicted delivery point are obtained, wherein all transportation paths of each first predicted delivery point are within the judgment circle; Obtain the path distance of each transportation path of each first predicted delivery point, and regard all road nodes on each transportation path as transportation nodes of the corresponding transportation path, and define all transportation nodes of each transportation path in an ordinal order starting from 1 according to the order in which they are passed, to obtain an ordinal definition result; Obtain the processed values ​​of the passing speed data of all transport nodes in each transport path at the current moment; Based on the path distance of each transportation path of each first predicted distribution point, the predicted efficiency values ​​of all transportation nodes at the current moment, the processed values ​​of the passing speed data of all transportation nodes in each transportation path at the current moment, and the ordinal definition results, the transportation evaluation value of each transportation path of each first predicted distribution point is obtained, which is: ； in, is the transport evaluation value of a single transport path for the first predicted delivery point currently calculated, is the total number of transport nodes on the transport path corresponding to the first predicted delivery point, is the average value of the processed values ​​of the passing speed data of all transportation nodes in the corresponding transportation path corresponding to the first predicted delivery point at the current moment, is the sum of the path distances of all transportation paths corresponding to the first predicted delivery point, is the path distance of the corresponding transportation path corresponding to the first predicted delivery point, The ordinal number of the transportation path corresponding to the first predicted delivery point is The predicted efficiency value of the transport node at the current moment, The ordinal number of the transportation path corresponding to the first predicted delivery point is The processing value of the speed data of the transport node at the current moment, is the natural logarithm, and the value of the natural constant e is 2.718.

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