A high-performance recall method and system for on-the-way cargo sources in a high-concurrency scenario

Abstract

The application discloses a high-performance recall method and system for on-the-way goods sources in a high-concurrency scene, relates to the technical field of goods recall, and comprises the following steps: periodically updating hot route along block caching, assigning different resolutions to different distances according to blocks and caching, and the longer the distance, the lower the resolution; converting the starting point and the destination of the goods source into a plurality of resolution blocks as index attributes; according to the starting point and the destination searched by the driver, obtaining the along-block from the cache and splitting and expanding the block, and according to the expanded block, arranging the driver to transport back the goods source meeting the recall condition. The application has high recall rate and accuracy: when recalling massive along-block goods sources, the along-block degree is calculated according to the self-developed along-block degree formula, and low along-block degree goods sources are filtered.

Description

Technical Field

[0001] This invention relates to the field of cargo recall technology, and more specifically, to a high-performance recall method and system for along-the-way cargo in high-concurrency scenarios. Background Technology

[0002] Existing freight platforms handle millions of freight orders daily. When drivers search for freight on a specific route, traditional recall solutions only recall freight that meets the criteria from the area around the origin to the destination. This often results in difficulty finding suitable freight on less popular long-distance routes. The common practice for recalling freight along the route is to query cities along the way and then piece together a route based on those cities to search for available freight. However, existing recall strategies have the following problems: a) Recalling only freight from the area around the origin to the destination misses many freight opportunities along the route in long-distance scenarios, resulting in a low recall rate; b) Querying cities along the route and calculating the Cartesian product route involves a large recall volume, and the irregular shapes of cities along the route, with some peripheral areas requiring significant detours, leads to low accuracy. Furthermore, querying cities along the route on third-party maps in high-traffic scenarios is too costly and time-consuming; querying cities along the route for distances exceeding 1000 kilometers takes about one second, which does not meet expectations. Summary of the Invention

[0003] To address the aforementioned issues, the present invention aims to provide a high-performance recall technology for along-route freight in high-concurrency scenarios, precisely meeting drivers' carpooling needs, helping drivers reduce empty runs, increase load factor, and thus increase income.

[0004] To achieve the above technical objectives, this application provides a high-performance recall method for along-the-way goods in high-concurrency scenarios, comprising the following steps: The block cache along popular routes is updated regularly. Different distances are assigned different resolutions according to the blocks and cached. The longer the distance, the lower the resolution. The origin and destination of the goods are converted into blocks of various resolutions and stored as index attributes; Based on the driver's search origin and destination, retrieve the blocks along the route from the cache, split and expand them, and arrange the driver to transport the goods that meet the recall conditions based on the expanded blocks.

[0005] Preferably, when storing index attributes, based on multiple resolution blocks, the basic information of the cargo source, cargo information, transportation plan, vehicle demand, cost information, cargo owner information, search strategy and tag information are used as index fields.

[0006] Preferably, when a driver is searching, the straight-line distance is calculated based on the latitude and longitude of the starting point and destination, the blocks along the route are retrieved from the cache, and the corresponding resolution is configured. If the cache is empty, a real-time query of a third-party map is triggered, and the cache is updated simultaneously.

[0007] Preferably, when splitting the blocks along the route, blocks with similar starting points are designated as the first half of the blocks, and blocks with similar destinations are designated as the second half of the blocks.

[0008] Preferably, when expanding the blocks along the route, blocks corresponding to the location range that are positively correlated with the straight-line distance between the origin and the destination are selected for expansion.

[0009] Preferably, when arranging drivers to transport goods that meet the recall conditions, the expanded blocks are used to arrange drivers to transport goods that meet the recall conditions based on the vehicle information of the goods demand.

[0010] Preferably, when assigning drivers, freight sources with low road accessibility are filtered out using a road accessibility formula, wherein the road accessibility formula is expressed as: [2 * A transport distance - (AB loading point distance + AB unloading point distance + min(A transport distance, B transport distance, A loading / B unloading distance, B loading / A unloading distance))] / A transport distance; Where: A represents the driver's search route, and B represents the recommended freight.

[0011] This invention discloses a high-performance recall system for along-the-way goods in high-concurrency scenarios, comprising: The cache update module is used to periodically update the cache of blocks along popular routes. Different distances are assigned different resolutions according to blocks and cached. The longer the distance, the lower the resolution. The index module is used to convert the origin and destination of the goods into blocks of various resolutions and store them as index attributes. The recall module is used to retrieve the along-route blocks from the cache based on the driver's search start point and destination, and then split and expand the blocks. Based on the expanded blocks, the module arranges for the driver to transport the cargo that meets the recall conditions.

[0012] Preferably, the recall module is used to calculate the straight-line distance based on the latitude and longitude of the search origin and destination, retrieve the blocks along the route from the cache, and configure the corresponding resolution. If the cache is empty, a real-time query of a third-party map is triggered, and the cache is updated simultaneously. Blocks with similar origins are designated as the first half of the blocks; blocks with similar destinations are designated as the second half of the blocks. Select blocks corresponding to the location range where the straight-line distance between the origin and destination is positive, and expand the blocks accordingly; Based on the expanded block and the vehicle information for cargo demand, drivers will be arranged to transport cargo that meets the recall conditions back to the area.

[0013] Preferably, the recall module is further used to filter cargo sources with low road accessibility using a road accessibility formula, wherein the road accessibility formula is expressed as: [2 * A transport distance - (AB loading point distance + AB unloading point distance + min(A transport distance, B transport distance, A loading / B unloading distance, B loading / A unloading distance))] / A transport distance; Where: A represents the driver's search route, and B represents the recommended freight.

[0014] The present invention discloses the following technical effects: This invention boasts high performance: it caches blocks of popular route waypoints. Based on route length, it adaptively generates blocks of different resolutions, avoiding real-time queries to third parties, thus improving response speed while reducing third-party query costs. It stores multiple resolution blocks for the origin and destination of the cargo source index, allowing for high-performance retrieval of massive cargo sources along the route by matching block keywords during retrieval. This invention features high recall and accuracy: when recalling a large number of goods along the route, it calculates the routeability based on a self-developed routeability formula and filters out goods with low routeability. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the method described in this invention; Figure 2 This is a schematic diagram of the route-following calculation logic described in this invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0018] like Figures 1-2As shown, this invention provides a high-performance recall method for along-the-way goods in high-concurrency scenarios, including the following steps: S1. Regularly update the block cache along popular routes, assign different resolutions to blocks according to different distances and cache them, with lower resolutions for longer distances; S2. Convert the origin and destination of the goods into blocks of various resolutions and store them as index attributes; S3. Based on the driver's search starting point and destination, retrieve the blocks along the route from the cache and split and expand them. Based on the expanded blocks, arrange for the driver to transport the goods that meet the recall conditions back.

[0019] Specifically, when storing the index attributes as described in S2, based on multiple resolution blocks, the basic information of the cargo source, cargo information, transportation plan, vehicle demand, cost information, cargo owner information, search strategy, and tag information are used as index fields.

[0020] In S3, the specific process of a driver searching for a starting point and destination and retrieving along-route blocks from the cache includes: first, calculating the straight-line distance based on the latitude and longitude of the starting point and destination; then retrieving along-route blocks from the cache and configuring the corresponding resolution; if the cache is empty, triggering a real-time query of a third-party map and updating the cache simultaneously; splitting along-route blocks specifically includes: using blocks close to the starting point as the first half of the blocks; using blocks close to the destination as the second half of the blocks; expanding along-route blocks specifically includes: selecting blocks corresponding to the location range positively correlated with the straight-line distance between the starting point and the destination for expansion; arranging for drivers to transport goods meeting the recall conditions specifically includes: based on the expanded blocks and the vehicle information of the goods demand, arranging for drivers to transport goods meeting the recall conditions back to the destination.

[0021] In some preferred embodiments, S3 further includes filtering freight sources with low routeability using a routeability formula when assigning drivers, wherein the routeability formula is expressed as: [2 * A transport distance - (AB loading point distance + AB unloading point distance + min(A transport distance, B transport distance, A loading / B unloading distance, B loading / A unloading distance))] / A transport distance; Where: A represents the driver's search route, and B represents the recommended freight.

[0022] To enable those skilled in the art to more intuitively understand the process of the present invention, a specific embodiment is described by way of example: This invention provides a high-performance recall technology for along-the-way goods in high-concurrency scenarios, including the following steps: Step 1: Before triggering the recall task, this invention periodically triggers the update of the block cache along the popular route through the form of a Job task, calls the third-party map interface to obtain the waypoints, and caches different distances according to different block resolutions. The longer the distance, the lower the resolution. The cache structure is as follows: Key is the origin_destination, and value is List<waypoints>. Step 2: When the cargo is dispatched, it is converted into multiple resolution blocks based on the origin and destination, and stored as index attributes. Index fields can include attributes related to basic information, cargo information, transportation plans, vehicle requirements, cost information, cargo owner information, search strategies, and tag information. Step 3: Drivers search for their origin and destination based on their latitude and longitude. If the origin is a city, the city center's latitude and longitude are used. The straight-line distance is calculated first, and the corresponding block resolution is obtained according to the configuration (as shown in Table 1). An origin_destination map is generated, and the corresponding roadside blocks are retrieved from the cache. If the cache is empty, a real-time query of a third-party map is triggered, and the cache is updated simultaneously.

[0023] Table 1 0，60 6 3.22 60， 200 5 8.54 200,600 4 22.60 >600 3 59.81 Step 4: Split the obtained list of blocks along the route into two parts. Place the first half of the blocks, which are close to the origin, into the origin block list. Place the second half of the blocks, which are close to the destination, into the destination block list. Specifically, for higher recall, blocks within a N-kilometer radius of the origin can also be placed into the origin block list, and blocks within a N-kilometer radius of the destination can be placed into the destination block list. N is positively correlated with the straight-line distance between the origin and destination. Step 5: Based on the origin and destination area block list, as well as other information searched by the driver, such as vehicle length and model, recall cargo that meets the freight conditions. These freight conditions are obtained by matching the origin, destination, and vehicle information with the transportation needs of the recalled cargo. Step 6: After the recall, filter out cargo sources with low roadworthiness according to the roadworthiness formula. Roadworthiness formula: [2*A transport distance - (AB loading distance + AB unloading distance + min(A transport distance, B transport distance, A loading / B unloading distance, B loading / A unloading distance))] / A transport distance. Where: A represents the driver's search route, and B represents the recommended cargo. First, roughly sort the goods according to straight-line distance, and then finely sort the top K goods according to navigation distance to reduce the cost of calling third-party navigation.

[0024] To address the aforementioned high-performance recall method for along-route goods in high-concurrency scenarios, this invention also discloses a high-performance recall system for along-route goods in high-concurrency scenarios to implement the above method, specifically including the following modules: The cache update module is used to periodically update the cache of blocks along popular routes. Different distances are assigned different resolutions according to blocks and cached. The longer the distance, the lower the resolution. The index module is used to convert the origin and destination of the goods into blocks of various resolutions and store them as index attributes. The recall module is used to retrieve the along-route blocks from the cache based on the driver's search start point and destination, and then split and expand the blocks. Based on the expanded blocks, the module arranges for the driver to transport the cargo that meets the recall conditions.

[0025] This invention presents a route-side block caching scheme suitable for scenarios requiring high-concurrency geographic computation. Its hexagonal topology enables higher recall accuracy. During cargo source index construction, multiple resolution block codes are generated based on the latitude and longitude of the origin and destination, serving as keyword-type fields. Keyword matching enables high-performance recall of massive amounts of cargo along the route. Furthermore, filtering based on route proximity after recall further improves accuracy. An improved route proximity calculation formula, tailored for the freight logistics industry, is proposed: [2*A transport distance - (AB loading distance + AB unloading distance + min(A transport distance, B transport distance, A loading / B unloading distance, B loading / A unloading distance))] / A transport distance. This reduces driver detours and helps drivers minimize empty runs.

[0026] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0027] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A high-performance recall method for along-the-way goods in high-concurrency scenarios, characterized in that, Includes the following steps: The block cache along popular routes is updated regularly. Different distances are assigned different resolutions according to the blocks and cached. The longer the distance, the lower the resolution. The origin and destination of the goods are converted into blocks of various resolutions and stored as index attributes; Based on the driver's search origin and destination, retrieve the along-route blocks from the cache and split and expand them. Based on the expanded blocks, arrange for the driver to transport the goods that meet the recall conditions. When splitting the blocks along the route, blocks with similar starting points are designated as the first half of the blocks, and blocks with similar destinations are designated as the second half of the blocks. When expanding the blocks along the route, select the blocks corresponding to the location range that is positively correlated with the straight-line distance between the origin and the destination, and expand the blocks accordingly. When arranging for drivers to transport goods that meet the recall conditions, the expanded blocks are used to arrange for drivers to transport goods that meet the recall conditions based on the vehicle information of the goods demand. When assigning drivers, freight with low road accessibility is filtered out using a road accessibility formula, which is expressed as: [2 * A transport distance - (AB loading point distance + AB unloading point distance + min(A transport distance, B transport distance, A loading / B unloading distance, B loading / A unloading distance))] / A transport distance; Where: A represents the driver's search route, and B represents the recommended freight.

2. The high-performance recall method for along-the-way goods in a high-concurrency scenario according to claim 1, characterized in that: When storing indexed attributes, based on multiple resolution blocks, the basic information of the cargo source, cargo information, transportation plan, vehicle demand, cost information, cargo owner information, search strategy, and tag information are used as index fields.

3. The high-performance recall method for along-the-way goods in a high-concurrency scenario according to claim 2, characterized in that: When a driver searches, the straight-line distance is calculated based on the latitude and longitude of the origin and destination. The system retrieves the blocks along the route from the cache and configures the corresponding resolution. If the cache is empty, a real-time query of a third-party map is triggered, and the cache is updated simultaneously.

4. A high-performance recall system for along-route goods in high-concurrency scenarios, used to execute the high-performance recall method for along-route goods in high-concurrency scenarios as described in claim 1, characterized in that, include: The cache update module is used to periodically update the cache of blocks along popular routes. Different distances are assigned different resolutions according to blocks and cached. The longer the distance, the lower the resolution. The index module is used to convert the origin and destination of the goods into blocks of various resolutions and store them as index attributes. The recall module is used to retrieve the route blocks from the cache based on the driver's search start point and destination, and then split and expand the blocks. Based on the expanded blocks, the driver is arranged to transport the cargo that meets the recall conditions back. The recall module is used to calculate the straight-line distance based on the latitude and longitude of the search origin and destination, retrieve the blocks along the route from the cache, and configure the corresponding resolution. If the cache is empty, it triggers a real-time query of a third-party map and updates the cache at the same time. Blocks with similar origins are designated as the first half of the blocks; blocks with similar destinations are designated as the second half of the blocks. Select blocks corresponding to the location range where the straight-line distance between the origin and destination is positive, and expand the blocks accordingly; Based on the expanded blocks and the vehicle information for cargo demand, drivers will be arranged to transport cargo that meets the recall conditions back to the area. The recall module is also used to filter cargo sources with low road accessibility using a road accessibility formula, wherein the road accessibility formula is expressed as: [2 * A transport distance - (AB loading point distance + AB unloading point distance + min(A transport distance, B transport distance, A loading / B unloading distance, B loading / A unloading distance))] / A transport distance; Where: A represents the driver's search route, and B represents the recommended freight.

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