A goods circulation and transportation planning management system and method based on blockchain

Abstract

The present invention discloses a blockchain-based goods circulation and transportation planning management system and method, relating to the technical field of freight planning. The present invention obtains freight vehicle information and historical driving data of corresponding freight vehicle drivers from a set of passing freight vehicles; obtains a set of freight orders within a to-be-detected area from the blockchain; screens freight vehicles based on the freight vehicle information and freight order demand characteristics; extracts freight vehicle drivers corresponding to the freight vehicles from a second screened set of freight vehicles to form a set of drivers to be evaluated; establishes an evaluation system group for freight vehicle drivers; constructs an evaluation model based on the evaluation system group for freight vehicle drivers; calculates the evaluation score for each freight vehicle driver; generates a candidate driver sequence based on the calculation results; and updates the pre-delivery route based on the results of the delivery time impact coefficient analysis. Obtaining a more optimal replacement route from the historical driving data can improve service quality.

Description

Technical Field

[0001] The present invention relates to the technical field of freight planning, and in particular to a blockchain-based goods circulation and transportation planning management system and method. Background Art

[0002] Transportation is a pioneering, basic and strategic industry in the national economy, an important service industry and an important part of the modern economic system. It is an important support for building a new development pattern and a solid guarantee for serving the people's better life and promoting common prosperity.

[0003] In the existing transport vehicle recommendations, the logistics platform does not analyze the remaining carrying capacity of freight vehicles that are transporting other freight orders, which may easily result in the remaining carrying capacity of the freight vehicles selected by users not meeting the new freight orders, reducing transportation efficiency; the navigation routes of the logistics platform are not updated for a long time, which may easily cause delays in freight orders.

[0004] Therefore, the present invention discloses a goods circulation and transportation planning management system and method based on blockchain to solve the above problems. Summary of the Invention

[0005] The purpose of the present invention is to provide a blockchain-based goods circulation and transportation planning management system and method to solve the problems raised in the prior art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a blockchain-based goods circulation and transportation planning and management method, the method comprising the following steps:

[0007] S1: The freight vehicles whose planned routes pass through the area to be inspected are grouped into a passing freight vehicle set, and the freight vehicle information and historical driving data of the corresponding freight vehicle drivers in the passing freight vehicle set are obtained; the freight order set within the area to be inspected is obtained from the blockchain;

[0008] S2: Extract freight order demand characteristics for each freight order in the freight order set within the area to be detected; screen freight vehicles based on freight vehicle information and freight order demand characteristics to form a first screened freight vehicle set; analyze the arrival time of freight vehicles in the first screened freight vehicle set to screen the first screened freight vehicle set to form a second screened freight vehicle set; extract freight vehicle drivers corresponding to the freight vehicles in the second screened freight vehicle set to form a driver set to be evaluated;

[0009] S3: Analyze the historical driving data of freight vehicle drivers in the set of drivers to be evaluated, establish an evaluation system group for freight vehicle drivers, and construct an evaluation model based on the evaluation system group for freight vehicle drivers;

[0010] S4: Substitute the evaluation system group corresponding to the freight vehicle drivers in the set of drivers to be evaluated into the evaluation model, and calculate the evaluation score of each freight vehicle driver; generate a sequence of drivers to be selected based on the calculation results; analyze the delivery time impact coefficient of the freight vehicle driver selected by the user who initiated the freight order; and update the pre-delivery route based on the analysis results of the delivery time impact coefficient.

[0011] According to the above scheme, in S1, the freight vehicle information includes the real-time position of the freight vehicle, the vehicle's planned travel route and the freight vehicle's remaining carrying capacity; the freight vehicle's remaining carrying capacity includes the freight vehicle's remaining carrying space and the freight vehicle's remaining carrying weight; the vehicle's planned travel route is a navigation route selected by the freight order initiator user corresponding to the freight order being transported from the navigation route recommendation scheme; the navigation route recommendation scheme is a collection of various navigation routes between the freight vehicle's real-time position and the corresponding destination in the historical driving data of all freight vehicle drivers; the freight order information in the blockchain is uploaded by the freight order initiator user through the user terminal.

[0012] By obtaining the remaining carrying capacity of freight vehicles, it is possible to effectively screen suitable freight vehicles for freight orders, avoid the situation where the remaining carrying capacity of the freight vehicles selected by users is insufficient, and improve overall transportation efficiency.

[0013] According to the above solution, S2 includes the following contents:

[0014] S201: Extracting freight order demand features for each freight order in the freight order set within the area to be detected; the freight order demand features include cargo weight, cargo volume, cargo location, arrival time at the cargo location, destination location, and delivery time;

[0015] S202: Based on the freight vehicle information and the freight order requirement characteristics of each freight order, select freight vehicles that simultaneously meet the freight order requirement characteristics of the freight order, namely, the freight weight and the freight volume, and record this as a first selected freight vehicle set;

[0016] S203: From the historical driving data of all freight vehicle drivers, select navigation routes that start at the real-time location of the freight vehicle, pass through the location of the goods, and end at the location of the destination, and form a set of them, which is recorded as a pre-delivery route set; from the historical vehicle operation data of all freight vehicles, extract the pre-delivery route segments from the real-time location of the freight vehicle to the location of the goods of the freight order and the estimated time of each pre-delivery route segment, calculate the average estimated time of the pre-delivery route segments, and calculate the estimated time of the freight vehicle's arrival at the location of the goods based on the average of the real-time time and the estimated time of the pre-delivery route segments;

[0017] S204: From the first filtered freight vehicle set, filter out freight vehicles whose estimated arrival time at the cargo location meets the arrival time at the cargo location in the freight order requirement characteristics, and record them as the second filtered freight vehicle set; mark and extract the freight vehicle drivers corresponding to the freight vehicles in the second filtered freight vehicle set to form a set, which is recorded as the driver set to be evaluated DE = {DE1, DE2, ..., DE i ,…,DE I}; where DE i represents the i-th freight vehicle driver in the set of drivers to be evaluated, i∈[1,I]; I represents the total number of freight vehicle drivers in the set of drivers to be evaluated.

[0018] Through the above scheme, the present invention can effectively screen freight vehicles that meet the freight order demand characteristics of the freight order, improve the accuracy of user selection, and improve the overall service experience.

[0019] According to the above solution, S3 includes the following:

[0020] S301: Extract historical driving data of freight vehicle drivers from the set of drivers to be evaluated; calculate DE of freight vehicle drivers i In each transport task, the average of the difference between the actual arrival time of the freight vehicle at the location of the goods and the arrival time at the location of the goods in the freight order demand characteristics is recorded as the arrival time offset ATO i ;

[0021] Calculating DE for freight vehicle drivers i In each transport task, the average of the difference between the actual delivery time of the freight vehicle and the delivery time in the freight order demand characteristics is recorded as the delivery time offset DTO i ;

[0022] Calculating DE for freight vehicle drivers i In each transport mission, the average value of the difference in mileage between the actual route and the vehicle's planned route is recorded as the route offset NRO. i ;

[0023] The arrival time offset, delivery time offset and driving route offset are positive, negative or zero;

[0024] S302: Deliver the freight vehicle driver i The arrival time offset, delivery time offset and driving route offset of the vehicle constitute the evaluation system group, which is recorded as ESG. i =(ATO i , DTO i , NRO i );

[0025] S303: According to the freight vehicle driver DE i The evaluation system group builds an evaluation model for freight vehicle drivers:

[0026] AS i =α1×exp(-ATO i )+α2×exp(-DTO i )+α3×exp(-NRO i );

[0027] Among them AS i Denotes freight vehicle driver DE i , α1, α2 and α3 represent evaluation proportional coefficients, and the evaluation proportional coefficients are system preset constants.

[0028] The exponential function in the above evaluation model can effectively obtain higher evaluation scores for freight vehicle drivers whose actual arrival time at the cargo location is much earlier than the arrival time at the cargo location in the freight order demand characteristics, whose actual delivery time is much earlier than the delivery time in the freight order demand characteristics, and whose actual driving route is much shorter than the mileage of the vehicle's expected driving route, thereby providing data support for the subsequent generation of a sequence of candidate drivers.

[0029] According to the above scheme, S4 includes the following contents:

[0030] S401: Substitute the evaluation system group corresponding to the freight vehicle drivers in the set of drivers to be evaluated into the evaluation model to calculate the evaluation score of each freight vehicle driver;

[0031] S402: Arrange the freight vehicle drivers in the set of drivers to be evaluated in descending order of evaluation scores to generate a sequence of drivers to be selected; send the sequence of drivers to be selected and the set of pre-delivery routes corresponding to the freight order to the user who initiated the freight order; the user who initiated the freight order selects a freight vehicle driver and a pre-delivery route;

[0032] S403: Extract the historical driving data of the freight vehicle driver selected by the freight order initiator and analyze the delivery time impact coefficient (TTIC) of the freight vehicle driver:

[0033] TTIC = exp(DTO ÷ ATO - 1);

[0034] Where ATO represents the arrival time offset of the freight vehicle driver selected by the freight order initiating user, and DTO represents the delivery time offset of the freight vehicle driver selected by the freight order initiating user;

[0035] By analyzing the delivery time impact coefficient of freight vehicle drivers, we can effectively screen freight vehicle drivers who complete orders in a timely manner, providing high-standard comparison objects for subsequent route replacements.

[0036] If the delivery time impact coefficient TTIC of the freight vehicle driver is less than or equal to 1, no action will be taken; if the delivery time impact coefficient TTIC of the freight vehicle driver is greater than 1, the pre-delivery route will be updated;

[0037] The updating of the pre-delivery route includes the following:

[0038] S411: Extracting navigation routes starting from the real-time location of the freight vehicle, passing through the location of the goods, and ending at the destination from the historical driving data of the freight vehicle driver selected by the freight order initiator, and forming a set of routes, which is recorded as a to-be-compared route set;

[0039] S412: performing an intersection operation on the pre-delivery route selected by the freight order initiating user and each of the routes to be compared in the set of routes to be compared, to generate intersection segments and non-intersection segments; the intersection segments appear in both the pre-delivery route and any of the routes to be compared, and the non-intersection segments are segments in the pre-delivery route other than the intersection segments;

[0040] S413: From the historical driving data of the freight vehicle driver selected by the freight order initiator, for each non-intersecting road segment, extract the road segment with the same endpoint as the non-intersecting road segment and the smallest mileage, and record it as the replacement road segment; and integrate the intersecting road segment and the replacement road segment according to the original driving order of the pre-delivery route to form a replacement route;

[0041] S414: The replacement route is updated to cover the pre-delivery route selected by the freight order initiating user.

[0042] By analyzing the historical driving data of the freight vehicle drivers selected by the users who initiate the freight order and obtaining better replacement routes from the historical driving data, the service quality for the users who initiate the freight order can be further improved, thereby enhancing the user experience.

[0043] Another aspect of the present application provides a blockchain-based goods circulation and transportation planning and management system, which is applied to the above-mentioned blockchain-based goods circulation and transportation planning and management method. The system includes a freight information collection module, a freight vehicle screening module, a driver evaluation model construction module, and a route update module.

[0044] The freight information collection module is used to group freight vehicles whose planned routes pass through the area to be detected into a passing freight vehicle set, obtain freight vehicle information and historical driving data of the corresponding freight vehicle drivers in the passing freight vehicle set; and obtain a freight order set within the area to be detected from the blockchain;

[0045] The freight vehicle screening module is used to extract freight order demand characteristics of each freight order in the freight order set within the area to be detected; screen freight vehicles based on freight vehicle information and freight order demand characteristics to form a first screened freight vehicle set; analyze the arrival time of freight vehicles in the first screened freight vehicle set, and screen the first screened freight vehicle set to form a second screened freight vehicle set; extract freight vehicle drivers corresponding to freight vehicles in the second screened freight vehicle set to form a set of drivers to be evaluated;

[0046] The driver evaluation model building module is used to analyze the historical driving data of freight vehicle drivers in the set of drivers to be evaluated, form an evaluation system group for freight vehicle drivers; and build an evaluation model based on the evaluation system group for freight vehicle drivers;

[0047] The route update module includes substituting the evaluation system group corresponding to the freight vehicle drivers in the set of drivers to be evaluated into the evaluation model, calculating the evaluation score of each freight vehicle driver; generating a sequence of drivers to be selected based on the calculation results; analyzing the delivery time impact coefficient of the freight vehicle driver selected by the user who initiated the freight order; and updating the pre-delivery route based on the analysis results of the delivery time impact coefficient.

[0048] According to the above solution, the freight information collection module includes a freight vehicle data collection unit and a freight order collection unit;

[0049] The freight vehicle data collection unit is used to group freight vehicles passing through the area to be detected along the vehicle's planned travel route into a passing freight vehicle set, and obtain freight vehicle information and historical driving data of the corresponding freight vehicle drivers in the passing freight vehicle set;

[0050] The freight order collection unit is used to obtain a freight order set within the area to be detected from the electronic contract of the blockchain.

[0051] According to the above solution, the freight vehicle screening module includes a freight vehicle initial screening unit and a to-be-evaluated driver screening unit;

[0052] The freight vehicle initial screening unit is used to screen freight vehicles that simultaneously meet the freight order requirement characteristics of the freight order, the freight weight and the freight volume, based on the freight vehicle information and the freight order requirement characteristics of each freight order, and record them as a first screened freight vehicle set;

[0053] The to-be-evaluated driver screening unit is used to calculate the estimated time for a freight vehicle to arrive at the cargo location, and screen out, from the first screened freight vehicle set, freight vehicles whose estimated time for arriving at the cargo location meets the arrival time at the cargo location in the freight order demand characteristics, and record them as the second screened freight vehicle set; mark and extract the freight vehicle drivers corresponding to the freight vehicles in the second screened freight vehicle set to form a set, which is recorded as the to-be-evaluated driver set.

[0054] According to the above solution, the driver evaluation model construction module includes an evaluation system group construction unit and an evaluation model construction unit;

[0055] The evaluation system group construction unit is used to calculate the arrival time offset, delivery time offset and driving route offset corresponding to the transportation task of the freight vehicle driver; the arrival time offset, delivery time offset and driving route offset of the freight vehicle driver are combined to form an evaluation system group;

[0056] The evaluation model construction unit constructs an evaluation model for the freight vehicle driver according to the evaluation system group for the freight vehicle driver.

[0057] According to the above solution, the route updating module includes a delivery time impact coefficient analysis unit and a pre-delivery route updating unit;

[0058] The delivery time impact coefficient analysis unit includes arranging freight vehicle drivers in the set of drivers to be evaluated in descending order of evaluation scores to generate a sequence of drivers to be selected; sending the sequence of drivers to be selected and a set of pre-delivery routes corresponding to the freight order to a freight order initiating user; the freight order initiating user selecting a freight vehicle driver and a pre-delivery route; extracting historical driving data of the freight vehicle driver selected by the freight order initiating user, and analyzing the delivery time impact coefficient of the freight vehicle driver;

[0059] The pre-delivery route updating unit is used to perform an intersection operation on the pre-delivery route that meets the requirements and the route set to be compared to generate intersection sections and non-intersection sections; analyze replacement sections of the non-intersection sections, and form a replacement route based on the intersection sections and the replacement sections; and update the replacement route to cover the pre-delivery route selected by the freight order initiating user.

[0060] Compared with the prior art, the beneficial effects of the present invention are: by obtaining the remaining carrying capacity of freight vehicles, it is possible to effectively screen suitable freight vehicles for freight orders, avoid the situation where the remaining carrying capacity of freight vehicles selected by users is insufficient, and improve the overall transportation efficiency; through the exponential function in the evaluation model, it is possible to effectively obtain higher evaluation scores for freight vehicle drivers whose actual arrival time at the location of the goods is much earlier than the arrival time at the location of the goods in the freight order demand characteristics, whose actual delivery time is much earlier than the delivery time in the freight order demand characteristics, and whose actual driving route is much less than the mileage of the vehicle's expected driving route, thereby providing data support for the subsequent generation of a sequence of candidate drivers; the analysis of the impact coefficient of the delivery time of freight vehicle drivers can effectively screen freight vehicle drivers who complete orders in a timely manner, and provide high-standard comparison objects for subsequent route replacement; by analyzing the historical driving data of freight vehicle drivers selected by the freight order initiating user, a better replacement route can be obtained from the historical driving data, which can further improve the service quality for the freight order initiating user and improve the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] 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:

[0062] Figure 1 This is a flowchart of a blockchain-based goods circulation and transportation planning and management method of the present invention;

[0063] Figure 2 This is a structural diagram of a blockchain-based goods circulation and transportation planning and management system of the present invention. DETAILED DESCRIPTION

[0064] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0065] See also Figure 1 The present invention provides a technical solution: a method for planning and managing goods circulation and transportation based on blockchain, the method comprising the following steps:

[0066] S1: The freight vehicles whose planned routes pass through the area to be inspected are grouped into a passing freight vehicle set, and the freight vehicle information and historical driving data of the corresponding freight vehicle drivers in the passing freight vehicle set are obtained; the freight order set within the area to be inspected is obtained from the blockchain;

[0067] S2: Extract freight order demand characteristics for each freight order in the freight order set within the area to be detected; screen freight vehicles based on freight vehicle information and freight order demand characteristics to form a first screened freight vehicle set; analyze the arrival time of freight vehicles in the first screened freight vehicle set to screen the first screened freight vehicle set to form a second screened freight vehicle set; extract freight vehicle drivers corresponding to the freight vehicles in the second screened freight vehicle set to form a driver set to be evaluated;

[0068] S3: Analyze the historical driving data of freight vehicle drivers in the set of drivers to be evaluated, establish an evaluation system group for freight vehicle drivers, and construct an evaluation model based on the evaluation system group for freight vehicle drivers;

[0069] S4: Substitute the evaluation system group corresponding to the freight vehicle drivers in the set of drivers to be evaluated into the evaluation model, and calculate the evaluation score of each freight vehicle driver; generate a sequence of drivers to be selected based on the calculation results; analyze the delivery time impact coefficient of the freight vehicle driver selected by the user who initiated the freight order; and update the pre-delivery route based on the analysis results of the delivery time impact coefficient.

[0070] In S1, the freight vehicle information includes the real-time position of the freight vehicle, the vehicle's planned route and the freight vehicle's remaining carrying capacity; the freight vehicle's remaining carrying capacity includes the freight vehicle's remaining carrying space and the freight vehicle's remaining carrying weight; the vehicle's planned route is a navigation route selected by the freight order initiator user corresponding to the freight order being transported from the navigation route recommendation plan; the navigation route recommendation plan is a collection of various navigation routes between the freight vehicle's real-time position and the corresponding destination in the historical driving data of all freight vehicle drivers; the freight order information in the blockchain is uploaded by the freight order initiator user through the user terminal.

[0071] S2 includes the following:

[0072] S201: Extracting freight order demand features for each freight order in the freight order set within the area to be detected; the freight order demand features include cargo weight, cargo volume, cargo location, arrival time at the cargo location, destination location, and delivery time;

[0073] S202: Based on the freight vehicle information and the freight order requirement characteristics of each freight order, select freight vehicles that simultaneously meet the freight order requirement characteristics of the freight order, namely, the freight weight and the freight volume, and record this as a first selected freight vehicle set;

[0074] S203: From the historical driving data of all freight vehicle drivers, select navigation routes that start at the real-time location of the freight vehicle, pass through the location of the goods, and end at the location of the destination, and form a set of them, which is recorded as a pre-delivery route set; from the historical vehicle operation data of all freight vehicles, extract the pre-delivery route segments from the real-time location of the freight vehicle to the location of the goods of the freight order and the estimated time of each pre-delivery route segment, calculate the average estimated time of the pre-delivery route segments, and calculate the estimated time of the freight vehicle's arrival at the location of the goods based on the average of the real-time time and the estimated time of the pre-delivery route segments;

[0075] S204: From the first filtered freight vehicle set, filter out freight vehicles whose estimated arrival time at the cargo location meets the arrival time at the cargo location in the freight order requirement characteristics, and record them as the second filtered freight vehicle set; mark and extract the freight vehicle drivers corresponding to the freight vehicles in the second filtered freight vehicle set to form a set, which is recorded as the driver set to be evaluated DE = {DE1, DE2, ..., DE i ,…,DE I}; where DE i represents the i-th freight vehicle driver in the set of drivers to be evaluated, i∈[1,I]; I represents the total number of freight vehicle drivers in the set of drivers to be evaluated.

[0076] In S3, include the following:

[0077] S301: Extract historical driving data of freight vehicle drivers from the set of drivers to be evaluated; calculate DE of freight vehicle drivers i In each transport task, the average of the difference between the actual arrival time of the freight vehicle at the location of the goods and the arrival time at the location of the goods in the freight order demand characteristics is recorded as the arrival time offset ATO i ;

[0078] Calculating DE for freight vehicle drivers i In each transport task, the average of the difference between the actual delivery time of the freight vehicle and the delivery time in the freight order demand characteristics is recorded as the delivery time offset DTO i ;

[0079] Calculating DE for freight vehicle drivers i In each transport mission, the average value of the difference in mileage between the actual route and the vehicle's planned route is recorded as the route offset NRO. i ;

[0080] Arrival time offset, delivery time offset, and travel route offset can be positive, negative, or zero;

[0081] S302: Deliver the freight vehicle driver iThe arrival time offset, delivery time offset and driving route offset of the vehicle constitute the evaluation system group, which is recorded as ESG. i =(ATO i , DTO i , NRO i );

[0082] S303: According to the freight vehicle driver DE i The evaluation system group builds an evaluation model for freight vehicle drivers:

[0083] AS i =α1×exp(-ATO i )+α2×exp(-DTO i )+α3×exp(-NRO i );

[0084] Among them AS i Denotes freight vehicle driver DE i The evaluation scores are α1, α2 and α3, which are evaluation proportional coefficients. The evaluation proportional coefficients are system preset constants.

[0085] In S4, include the following:

[0086] S401: Substitute the evaluation system group corresponding to the freight vehicle drivers in the set of drivers to be evaluated into the evaluation model to calculate the evaluation score of each freight vehicle driver;

[0087] S402: Arrange the freight vehicle drivers in the set of drivers to be evaluated in descending order of evaluation scores to generate a candidate driver sequence; send the candidate driver sequence and the set of pre-delivery routes corresponding to the freight order to the freight order initiator; the freight order initiator selects the freight vehicle driver and the pre-delivery route;

[0088] S403: Extract the historical driving data of the freight vehicle driver selected by the freight order initiator and analyze the delivery time impact coefficient (TTIC) of the freight vehicle driver:

[0089] TTIC = exp(DTO ÷ ATO - 1);

[0090] Where ATO represents the arrival time offset of the freight vehicle driver selected by the freight order initiating user, and DTO represents the delivery time offset of the freight vehicle driver selected by the freight order initiating user;

[0091] If the delivery time impact coefficient TTIC of the freight vehicle driver is less than or equal to 1, no action will be taken; if the delivery time impact coefficient TTIC of the freight vehicle driver is greater than 1, the pre-delivery route will be updated;

[0092] Example 1: In this example, there is only one historical freight order for freight vehicle 1, where the actual arrival time of freight vehicle 1 at the cargo location is 11:00, and the arrival time at the cargo location in the historical freight order demand characteristics is 11:30;

[0093] The actual delivery time of the freight vehicle is 14:00, which is the average difference between the delivery time and the average delivery time in the freight order demand characteristics, which is 14:30.

[0094] Therefore, the arrival time offset ATO of freight vehicle 1 is equal to -0.5H, and the delivery time offset is -0.5H;

[0095] The transport time impact coefficient of freight vehicle 1 is TTIC = exp((-0.5) ÷ (0.5) - 1) = 1;

[0096] Therefore, there is no need to update the pre-delivery route of freight vehicle 1;

[0097] Updates to pre-delivery routes include the following:

[0098] S411: Extracting navigation routes starting from the real-time location of the freight vehicle, passing through the location of the goods, and ending at the destination from the historical driving data of the freight vehicle driver selected by the freight order initiator, and forming a set of routes, which is recorded as a to-be-compared route set;

[0099] S412: performing an intersection operation on the pre-delivery route selected by the freight order initiating user and each of the routes to be compared in the set of routes to be compared, to generate intersection segments and non-intersection segments; an intersection segment is a segment that appears in both the pre-delivery route and any of the routes to be compared, and a non-intersection segment is a segment in the pre-delivery route other than the intersection segment;

[0100] S413: From the historical driving data of the freight vehicle driver selected by the freight order initiator, for each non-intersecting road segment, extract the road segment with the same endpoint as the non-intersecting road segment and the smallest mileage, and record it as the replacement road segment; and integrate the intersecting road segment and the replacement road segment according to the original driving order of the pre-delivery route to form a replacement route;

[0101] S414: The replacement route is updated to cover the pre-delivery route selected by the freight order initiating user.

[0102] See also Figure 2 , the present invention provides a technical solution: a goods circulation and transportation planning and management system based on blockchain, the system includes a freight information collection module, a freight vehicle screening module, a driver evaluation model construction module and a route update module;

[0103] The freight information collection module is used to group freight vehicles whose routes pass through the area to be detected into a passing freight vehicle set, obtain freight vehicle information and historical driving data of the corresponding freight vehicle drivers in the passing freight vehicle set; and obtain a set of freight orders within the area to be detected from the blockchain;

[0104] The freight vehicle screening module is used to extract freight order demand characteristics of each freight order in the freight order set within the area to be detected; screen freight vehicles based on freight vehicle information and freight order demand characteristics to form a first screened freight vehicle set; analyze the arrival time of freight vehicles in the first screened freight vehicle set, and screen the first screened freight vehicle set to form a second screened freight vehicle set; extract freight vehicle drivers corresponding to freight vehicles in the second screened freight vehicle set to form a set of drivers to be evaluated;

[0105] The driver evaluation model building module is used to analyze the historical driving data of freight vehicle drivers in the set of drivers to be evaluated, establish an evaluation system group for freight vehicle drivers, and build an evaluation model based on the evaluation system group for freight vehicle drivers;

[0106] The route update module includes substituting the evaluation system group corresponding to the freight vehicle drivers in the set of drivers to be evaluated into the evaluation model to calculate the evaluation score of each freight vehicle driver; generating a sequence of drivers to be selected based on the calculation results; analyzing the delivery time impact coefficient of the freight vehicle driver selected by the user who initiated the freight order; and updating the pre-delivery route based on the analysis results of the delivery time impact coefficient.

[0107] The freight information collection module includes a freight vehicle data collection unit and a freight order collection unit;

[0108] The freight vehicle data collection unit is used to group freight vehicles that pass through the area to be detected on the vehicle's pre-travel route into a passing freight vehicle set, and obtain freight vehicle information and historical driving data of the corresponding freight vehicle drivers in the passing freight vehicle set;

[0109] The freight order collection unit is used to obtain a set of freight orders within the area to be detected from the electronic contract of the blockchain.

[0110] The freight vehicle screening module includes a freight vehicle initial screening unit and a driver screening unit to be evaluated;

[0111] The freight vehicle initial screening unit is used to screen freight vehicles that simultaneously meet the freight order requirement characteristics of the freight order, the freight weight and the freight volume, based on the freight vehicle information and the freight order requirement characteristics of each freight order, and record them as the first screened freight vehicle set;

[0112] The driver screening unit to be evaluated is used to calculate the estimated time for the freight vehicle to arrive at the location of the goods, and screen out from the first screened freight vehicle set the freight vehicles whose estimated time for arriving at the location of the goods meets the arrival time at the location of the goods in the freight order demand characteristics, which are recorded as the second screened freight vehicle set; mark and extract the freight vehicle drivers corresponding to the freight vehicles in the second screened freight vehicle set to form a set, which is recorded as the driver set to be evaluated.

[0113] The driver evaluation model construction module includes an evaluation system group construction unit and an evaluation model construction unit;

[0114] The evaluation system group construction unit is used to calculate the arrival time offset, delivery time offset, and driving route offset corresponding to the transportation task of the freight vehicle driver; the arrival time offset, delivery time offset, and driving route offset of the freight vehicle driver are combined to form an evaluation system group;

[0115] The evaluation model construction unit constructs an evaluation model for the freight vehicle driver according to the evaluation system group for the freight vehicle driver.

[0116] The route update module includes a delivery time impact coefficient analysis unit and a pre-delivery route update unit;

[0117] The delivery time impact coefficient analysis unit includes the following steps: arranging the freight vehicle drivers in the set of drivers to be evaluated in descending order of evaluation scores to generate a candidate driver sequence; sending the candidate driver sequence and a set of pre-delivery routes corresponding to the freight order to a freight order initiating user; the freight order initiating user selecting a freight vehicle driver and a pre-delivery route; extracting historical driving data of the freight vehicle driver selected by the freight order initiating user, and analyzing the delivery time impact coefficient of the freight vehicle driver;

[0118] The pre-delivery route update unit is used to perform an intersection operation on the pre-delivery route that meets the requirements and the route set to be compared to generate intersection sections and non-intersection sections; analyze the replacement sections of the non-intersection sections, and form a replacement route based on the intersection sections and the replacement sections; and update the replacement route to cover the pre-delivery route selected by the user who initiated the freight order.

[0119] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0120] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

Claims

1. A method for planning and managing goods circulation and transportation based on blockchain, characterized in that: The method comprises the following steps: S1: The freight vehicles whose planned routes pass through the area to be inspected are grouped into a passing freight vehicle set, and the freight vehicle information and historical driving data of the corresponding freight vehicle drivers in the passing freight vehicle set are obtained; the freight order set within the area to be inspected is obtained from the blockchain; S2: extracting freight order demand features of each freight order in the freight order set within the area to be detected; The freight vehicles are screened according to the freight vehicle information and freight order demand characteristics to form a first screened freight vehicle set; the arrival time of the freight vehicles in the first screened freight vehicle set is analyzed to the location of the goods, and the first screened freight vehicle set is screened to form a second screened freight vehicle set; the freight vehicle drivers corresponding to the freight vehicles in the second screened freight vehicle set are extracted to form a driver set to be evaluated; S3: Analyze the historical driving data of freight vehicle drivers in the set of drivers to be evaluated, establish an evaluation system group for freight vehicle drivers, and construct an evaluation model based on the evaluation system group for freight vehicle drivers; S4: Substitute the evaluation system group corresponding to the freight vehicle drivers in the set of drivers to be evaluated into the evaluation model, calculate the evaluation score of each freight vehicle driver; generate a sequence of candidate drivers based on the calculation results; and analyze the delivery time impact coefficient of the freight vehicle driver selected by the freight order initiator; Update the planned delivery route based on the analysis results of the delivery time impact coefficient; In S2, the following contents are included: from the historical driving data of all freight vehicle drivers, the navigation routes starting from the real-time location of the freight vehicle, passing through the location of the goods, and ending at the location of the destination are selected and formed into a set, which is recorded as the pre-delivery route set; In S4, include the following: S401: Substitute the evaluation system group corresponding to the freight vehicle drivers in the set of drivers to be evaluated into the evaluation model to calculate the evaluation score of each freight vehicle driver; S402: Arrange the freight vehicle drivers in the set of drivers to be evaluated in descending order of evaluation scores to generate a sequence of drivers to be selected; send the sequence of drivers to be selected and the set of pre-delivery routes corresponding to the freight order to the user who initiated the freight order; the user who initiated the freight order selects a freight vehicle driver and a pre-delivery route; S403: Extract the historical driving data of the freight vehicle driver selected by the freight order initiator and analyze the delivery time impact coefficient (TTIC) of the freight vehicle driver: TTIC=exp(DTO÷ATO-1); Wherein, ATO represents the arrival time offset of the freight vehicle driver selected by the freight order initiating user. The arrival time offset represents the average value of the difference between the actual arrival time of the freight vehicle at the location of the goods in the freight vehicle driver's transportation task and the arrival time at the location of the goods in the freight order demand characteristics. DTO represents the delivery time offset of the freight vehicle driver selected by the freight order initiating user. The delivery time offset represents the average value of the difference between the actual delivery time of the freight vehicle in the freight vehicle driver's transportation task and the delivery time in the freight order demand characteristics. If the delivery time impact coefficient TTIC of the freight vehicle driver is less than or equal to 1, no action will be taken; if the delivery time impact coefficient TTIC of the freight vehicle driver is greater than 1, the pre-delivery route will be updated; The updating of the pre-delivery route includes the following: S411: Extracting navigation routes starting from the real-time location of the freight vehicle, passing through the location of the goods, and ending at the destination from the historical driving data of the freight vehicle driver selected by the freight order initiator, and forming a set of routes, which is recorded as a to-be-compared route set; S412: performing an intersection operation on the pre-delivery route selected by the freight order initiating user and each of the routes to be compared in the set of routes to be compared, to generate intersection segments and non-intersection segments; the intersection segments appear in both the pre-delivery route and any of the routes to be compared, and the non-intersection segments are segments in the pre-delivery route other than the intersection segments; S413: From the historical driving data of the freight vehicle driver selected by the freight order initiator, for each non-intersecting road segment, extract the road segment with the same endpoint as the non-intersecting road segment and the smallest mileage, and record it as the replacement road segment; and integrate the intersecting road segment and the replacement road segment according to the original driving order of the pre-delivery route to form a replacement route; S414: The replacement route is updated to cover the pre-delivery route selected by the freight order initiating user.

2. The method for managing goods circulation and transportation planning based on blockchain according to claim 1, characterized in that: In S1, the freight vehicle information includes the real-time position of the freight vehicle, the vehicle's planned route and the freight vehicle's remaining carrying capacity; the freight vehicle's remaining carrying capacity includes the freight vehicle's remaining carrying space and the freight vehicle's remaining carrying weight; the vehicle's planned route is a navigation route selected by the freight order initiator user who is currently transporting the freight order from the navigation route recommendation scheme; the navigation route recommendation scheme is a collection of various navigation routes between the freight vehicle's real-time position and the corresponding destination in the historical driving data of all freight vehicle drivers; the freight order information in the blockchain is uploaded by the freight order initiator user through the user terminal.

3. The method for managing goods circulation and transportation planning based on blockchain according to claim 2, characterized in that: S2 also includes the following: S201: Extracting freight order demand features for each freight order in the freight order set within the area to be detected; the freight order demand features include cargo weight, cargo volume, cargo location, arrival time at the cargo location, destination location, and delivery time; S202: Based on the freight vehicle information and the freight order requirement characteristics of each freight order, select freight vehicles that simultaneously meet the freight order requirement characteristics of the freight order, namely, the freight weight and the freight volume, and record this as a first selected freight vehicle set; S203: Extracting the pre-delivery route segments from the real-time location of the freight vehicle to the location of the goods in the freight order and the estimated time for each pre-delivery route segment from the historical vehicle operation data of all freight vehicles, calculating the average estimated time for the pre-delivery route segments, and calculating the estimated time for the freight vehicle to arrive at the location of the goods based on the real-time time and the average estimated time for the pre-delivery route segments; S204: Filter out the freight vehicles whose estimated arrival time at the cargo location meets the arrival time at the cargo location in the freight order requirement characteristics from the first filtered freight vehicle set, and record them as the second filtered freight vehicle set; mark and extract the freight vehicle drivers corresponding to the freight vehicles in the second filtered freight vehicle set, and form a set, which is recorded as the driver set to be evaluated DE = {DE1, DE2, ..., DE i ,…,DE I }; where DE i represents the i-th freight vehicle driver in the set of drivers to be evaluated, i∈[1,I]; I represents the total number of freight vehicle drivers in the set of drivers to be evaluated.

4. The method for managing goods circulation and transportation planning based on blockchain according to claim 3, characterized in that: In S3, include the following: S301: Extract historical driving data of freight vehicle drivers from the set of drivers to be evaluated; calculate DE of freight vehicle drivers i In each transport task, the average of the difference between the actual arrival time of the freight vehicle at the location of the goods and the arrival time at the location of the goods in the freight order demand characteristics is recorded as the arrival time offset ATO i ; Calculating DE for freight vehicle drivers i In each transport task, the average of the difference between the actual delivery time of the freight vehicle and the delivery time in the freight order demand characteristics is recorded as the delivery time offset DTO i ; Calculating DE for freight vehicle drivers i In each transport mission, the average value of the difference in mileage between the actual route and the vehicle's planned route is recorded as the route offset NRO. i ; The arrival time offset, delivery time offset and driving route offset are positive, negative or zero; S302: Deliver the freight vehicle driver i The arrival time offset, delivery time offset and driving route offset of the vehicle constitute the evaluation system group, which is recorded as ESG. i =(ATO i , DTO i , NRO i ); S303: According to the freight vehicle driver DE i The evaluation system group builds an evaluation model for freight vehicle drivers: AS i =α1×exp(-ATO i )+α2×exp(-DTO i )+α3×exp(-NRO i ); in AS i Denotes freight vehicle driver DE i , α1, α2 and α3 represent evaluation proportional coefficients, and the evaluation proportional coefficients are system preset constants.

5. A blockchain-based goods circulation and transportation planning and management system, wherein the system is applied to the blockchain-based goods circulation and transportation planning and management method according to any one of claims 1 to 4, and is characterized in that: The system includes a freight information collection module, a freight vehicle screening module, a driver evaluation model building module and a route update module; The freight information collection module is used to group freight vehicles whose planned routes pass through the area to be detected into a passing freight vehicle set, obtain freight vehicle information and historical driving data of the corresponding freight vehicle drivers in the passing freight vehicle set; and obtain a freight order set within the area to be detected from the blockchain; The freight vehicle screening module is used to extract freight order demand characteristics of each freight order in the freight order set within the area to be detected; The freight vehicles are screened according to the freight vehicle information and freight order demand characteristics to form a first screened freight vehicle set; the arrival time of the freight vehicles in the first screened freight vehicle set is analyzed, and the first screened freight vehicle set is screened to form a second screened freight vehicle set; the freight vehicle drivers corresponding to the freight vehicles in the second screened freight vehicle set are extracted to form a driver set to be evaluated; The driver evaluation model building module is used to analyze the historical driving data of freight vehicle drivers in the set of drivers to be evaluated, form an evaluation system group for freight vehicle drivers; and build an evaluation model based on the evaluation system group for freight vehicle drivers; The route update module includes substituting the evaluation system group corresponding to the freight vehicle drivers in the set of drivers to be evaluated into the evaluation model, calculating the evaluation score of each freight vehicle driver; generating a sequence of drivers to be selected based on the calculation results; and analyzing the delivery time impact coefficient of the freight vehicle driver selected by the freight order initiator; Update the planned delivery route based on the analysis results of the delivery time impact coefficient.

6. The blockchain-based goods circulation and transportation planning and management system according to claim 5, characterized in that: The freight information collection module includes a freight vehicle data collection unit and a freight order collection unit; The freight vehicle data collection unit is used to group freight vehicles passing through the area to be detected along the vehicle's planned travel route into a passing freight vehicle set, and obtain freight vehicle information and historical driving data of the corresponding freight vehicle drivers in the passing freight vehicle set; The freight order collection unit is used to obtain a freight order set within the area to be detected from the electronic contract of the blockchain.

7. The blockchain-based goods circulation and transportation planning and management system according to claim 5, characterized in that: The freight vehicle screening module includes a freight vehicle initial screening unit and a to-be-assessed driver screening unit; The freight vehicle initial screening unit is used to screen freight vehicles that simultaneously meet the freight order requirement characteristics of the freight order, the freight weight and the freight volume, based on the freight vehicle information and the freight order requirement characteristics of each freight order, and record them as a first screened freight vehicle set; The to-be-evaluated driver screening unit is used to calculate the estimated time for a freight vehicle to arrive at the cargo location, and screen out, from the first screened freight vehicle set, freight vehicles whose estimated time for arriving at the cargo location meets the arrival time at the cargo location in the freight order demand characteristics, and record them as the second screened freight vehicle set; mark and extract the freight vehicle drivers corresponding to the freight vehicles in the second screened freight vehicle set to form a set, which is recorded as the to-be-evaluated driver set.

8. The blockchain-based goods circulation and transportation planning and management system according to claim 5, characterized in that: The driver evaluation model construction module includes an evaluation system group construction unit and an evaluation model construction unit; The evaluation system group construction unit is used to calculate the arrival time offset, delivery time offset and driving route offset corresponding to the transportation task of the freight vehicle driver; the arrival time offset, delivery time offset and driving route offset of the freight vehicle driver are combined to form an evaluation system group; The evaluation model construction unit constructs an evaluation model for the freight vehicle driver according to the evaluation system group for the freight vehicle driver.

9. The blockchain-based goods circulation and transportation planning and management system according to claim 5, characterized in that: The route updating module includes a delivery time impact coefficient analysis unit and a pre-delivery route updating unit; The delivery time impact coefficient analysis unit comprises: arranging the freight vehicle drivers in the set of drivers to be evaluated in descending order of evaluation scores to generate a sequence of drivers to be selected; and sending the sequence of drivers to be selected and the set of pre-delivery routes corresponding to the freight order to the user who initiated the freight order; The user who initiates the freight order selects the freight vehicle driver and the expected delivery route; Extract the historical driving data of the freight vehicle driver selected by the freight order initiator and analyze the impact coefficient of the freight vehicle driver's delivery time; The pre-delivery route updating unit is used to perform an intersection operation on the pre-delivery route that meets the requirements and the route set to be compared to generate intersection sections and non-intersection sections; analyze replacement sections of the non-intersection sections, and form a replacement route based on the intersection sections and the replacement sections; and update the replacement route to cover the pre-delivery route selected by the freight order initiating user.

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