Goods circulation and transportation planning management system and method based on block chain

Abstract

The invention discloses a cargo circulation and transportation planning management system and method based on a block chain, and relates to the technical field of freight planning, and the method comprises the steps: obtaining the information of freight vehicles in a passing freight vehicle set and the historical driving data of corresponding freight vehicle drivers; acquiring a freight order set in the to-be-detected area from the block chain; the freight vehicles are screened according to the freight vehicle information and the freight order demand characteristics; freight vehicle drivers corresponding to freight vehicles in the second screened freight vehicle set are extracted to form a to-be-evaluated driver set; establishing an evaluation system group of freight vehicle drivers; constructing an evaluation model according to the evaluation system group of the freight vehicle driver; calculating an evaluation score of each freight vehicle driver; generating a to-be-selected driver sequence according to a calculation result; and updating the pre-delivery route according to a delivery time influence coefficient analysis result. A better alternative route is obtained from historical driving data, and the service quality can be improved.

Description

Technical Field

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

[0002] Transportation is a pioneering, basic and strategic industry in the national economy, an important service industry and an important component 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, thereby 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 goods circulation and transportation planning management system and method based on blockchain to solve the problems raised in the prior art.

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

[0007] S1: The freight vehicles whose pre-travel routes pass through the area to be detected 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; and the freight order set in the area to be detected is obtained from the blockchain;

[0008] S2: extracting freight order demand characteristics of each freight order in the freight order set within the area to be detected; screening freight vehicles according to freight vehicle information and freight order demand characteristics to form a first screened freight vehicle set; analyzing the arrival time of freight vehicles in the first screened freight vehicle set, screening the first screened freight vehicle set to form a second screened freight vehicle set; extracting freight vehicle drivers corresponding to 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 the freight vehicle drivers in the set of drivers to be evaluated, and form an evaluation system group for the freight vehicle drivers; and construct an evaluation model based on the evaluation system group for the 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 driving route and the remaining carrying capacity of the freight vehicle; the remaining carrying capacity of the freight vehicle includes the remaining carrying space of the freight vehicle and the remaining carrying weight of the freight vehicle; the vehicle's planned driving route is a navigation route selected by the freight order initiating 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 real-time position of the freight vehicle 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 initiating user through the user end.

[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 the overall transportation efficiency.

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

[0014] S201: extracting freight order demand features of 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 cargo location, destination location and delivery time;

[0015] S202: According to the freight vehicle information and the freight order demand characteristics of each freight order, a freight vehicle that satisfies both the freight weight and the freight volume in the freight order demand characteristics of the freight order is selected, and recorded as a first selected freight vehicle set;

[0016] S203: from the historical driving data of all freight vehicle drivers, select navigation routes that start from the real-time position of the freight vehicle, pass through the location of the goods, and end at the location of the destination, and form a set, which is recorded as a pre-delivery route set; from the historical vehicle operation data of all freight vehicles, extract the pre-delivery route sections from the real-time position of the freight vehicle to the location of the goods of the freight order and the estimated time of each pre-delivery route section, calculate the average value of the estimated time of the pre-delivery route sections, and calculate the estimated time of the freight vehicle arriving at the location of the goods according to the real-time time and the average value of the estimated time of the pre-delivery route sections;

[0017] S204: Filter out the freight vehicles whose estimated arrival time at the location of the goods meets the arrival time at the location of the goods in the freight order demand 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 to form a set, and record them as the driver set to be evaluated DE = {DE 1 ,DE 2 , …, 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 scheme, 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 transportation 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 transportation task, the average value 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 expected 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: Determine the driver of the freight vehicle i The arrival time offset, delivery time offset and driving route offset of the vehicle constitute the evaluation system group, denoted 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 =α 1 ×exp(-ATO i )+α 2 ×exp(-DTO i )+α 3 ×exp(-NRO i );

[0027] Among them AS i Denotes a freight vehicle driver DE i The evaluation score, α 1 , α 2 and α 3 Represents the evaluation proportional coefficient, which is a system preset constant.

[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 driver 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 freight order initiating user; the freight order initiating user selects the freight vehicle driver and the pre-delivery route;

[0032] S403: extract the historical driving data of the freight vehicle driver selected by the freight order initiating user, 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 impact coefficient of freight vehicle drivers' delivery time, 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 ≤1, no processing will be done; if the delivery time impact coefficient TTIC of the freight vehicle driver is >1, the pre-delivery route will be updated;

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

[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 location of the destination from the historical driving data of the freight vehicle driver selected by the freight order initiating user, and forming a set, which is recorded as a route set to be compared;

[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 sections and non-intersection sections; the intersection section appears in both the pre-delivery route and any of the routes to be compared, and the non-intersection section is a section in the pre-delivery route other than the intersection section;

[0040] S413: From the historical driving data of the freight vehicle driver selected by the freight order initiating user, for each non-intersecting road section, extract the road section with the same endpoint as the non-intersecting road section and the smallest mileage, and record it as the replacement road section; according to the original driving order of the pre-delivery route, integrate the intersection road section and the replacement road section 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 improving the user experience.

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

[0044] The freight information collection module is used to group freight vehicles whose planned travel routes pass through the area to be detected into a passing freight vehicle set, obtain freight vehicle information in the passing freight vehicle set and historical driving data of the corresponding freight vehicle drivers; and obtain a freight order set in 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 according to 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, 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 driver set 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 according to the calculation results; analyzing the delivery time impact coefficient of the freight vehicle driver selected by the freight order initiator user; and updating the pre-delivery route according to the analysis results of the delivery time impact coefficient.

[0048] According to the above scheme, 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 on the vehicle's pre-travel route into a passing freight vehicle set, and obtain freight vehicle information in the passing freight vehicle set and historical driving data of the corresponding freight vehicle drivers;

[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 scheme, 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 demand characteristics of the freight order, the freight weight and the freight volume, according to the freight vehicle information and the freight order demand characteristics of each freight order, and record them as the first screened freight vehicle set;

[0053] The to-be-evaluated driver screening unit 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, 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 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 into an evaluation system group;

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

[0057] According to the above scheme, 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 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; sending the sequence of drivers to be selected and the set of pre-delivery routes corresponding to the freight order to the freight order initiating user; the freight order initiating user selecting the freight vehicle driver and the pre-delivery route; extracting the 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 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 freight order initiating user.

[0060] Compared with the prior art, the beneficial effects of the present invention are as follows: 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 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 drivers to be selected; 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 the freight vehicle drivers selected by the freight order initiating user, a better replacement route can be obtained from the historical driving data, thereby further improving the service quality for the freight order initiating user and improving 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 method for planning and managing goods circulation and transportation based on blockchain in the present invention;

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

[0064] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work 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 pre-travel routes pass through the area to be detected 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; and the freight order set in the area to be detected is obtained from the blockchain;

[0067] S2: extracting freight order demand characteristics of each freight order in the freight order set within the area to be detected; screening freight vehicles according to freight vehicle information and freight order demand characteristics to form a first screened freight vehicle set; analyzing the arrival time of freight vehicles in the first screened freight vehicle set, screening the first screened freight vehicle set to form a second screened freight vehicle set; extracting freight vehicle drivers corresponding to 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 the freight vehicle drivers in the set of drivers to be evaluated, and form an evaluation system group for the freight vehicle drivers; and construct an evaluation model based on the evaluation system group for the 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 driving route and the remaining carrying capacity of the freight vehicle; the remaining carrying capacity of the freight vehicle includes the remaining carrying space of the freight vehicle and the remaining carrying weight of the freight vehicle; the vehicle's planned driving route is a navigation route selected by the freight order initiating 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 real-time position of the freight vehicle 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 initiating user through the user terminal.

[0071] S2 includes the following:

[0072] S201: extracting freight order demand features of 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, time of arrival at cargo location, destination location and delivery time;

[0073] S202: According to the freight vehicle information and the freight order demand characteristics of each freight order, a freight vehicle that satisfies both the freight weight and the freight volume in the freight order demand characteristics of the freight order is selected, and recorded as a first selected freight vehicle set;

[0074] S203: from the historical driving data of all freight vehicle drivers, select navigation routes that start from the real-time position of the freight vehicle, pass through the location of the goods, and end at the location of the destination, and form a set, which is recorded as a pre-delivery route set; from the historical vehicle operation data of all freight vehicles, extract the pre-delivery route sections from the real-time position of the freight vehicle to the location of the goods of the freight order and the estimated time of each pre-delivery route section, calculate the average value of the estimated time of the pre-delivery route sections, and calculate the estimated time of the freight vehicle arriving at the location of the goods according to the real-time time and the average value of the estimated time of the pre-delivery route sections;

[0075] S204: Filter out the freight vehicles whose estimated arrival time at the location of the goods meets the arrival time at the location of the goods in the freight order demand 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 to form a set, and record them as the driver set to be evaluated DE = {DE 1 ,DE 2 , …, 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 transportation 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 transportation task, the average value 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 expected route is recorded as the route offset NRO. i ;

[0080] The arrival time offset, delivery time offset, and travel route offset are positive, negative, or zero;

[0081] S302: Determine the driver of the freight vehicle i The arrival time offset, delivery time offset and driving route offset of the vehicle constitute the evaluation system group, denoted 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 =α 1 ×exp(-ATO i )+α 2 ×exp(-DTO i )+α 3 ×exp(-NRO i );

[0084] Among them AS i Denotes a freight vehicle driver DE i The evaluation score, α 1 , α 2 and α 3 Represents the evaluation proportional coefficient, which is a system preset constant.

[0085] In S4, the following are included:

[0086] S401: Substitute the evaluation system group corresponding to the freight vehicle driver 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 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 freight order initiating user; the freight order initiating user 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 initiating user, 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 ≤1, no processing will be done; if the delivery time impact coefficient TTIC of the freight vehicle driver is >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, in which the actual arrival time of freight vehicle 1 at the location of the goods is 11:00, and the arrival time at the location of the goods 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 of the delivery time differences in the freight order demand characteristics, 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 influence coefficient TTIC of freight vehicle 1 = 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 location of the destination from the historical driving data of the freight vehicle driver selected by the freight order initiating user, and forming a set, which is recorded as a route set to be compared;

[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 sections and non-intersection sections; the intersection section appears in both the pre-delivery route and any of the routes to be compared, and the non-intersection section is a section in the pre-delivery route other than the intersection section;

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

[0103] The freight information collection module is used to group the freight vehicles that pass through the area to be detected on the vehicle's pre-travel route into a passing freight vehicle set, obtain the freight vehicle information in the passing freight vehicle set and the historical driving data of the corresponding freight vehicle drivers; obtain the freight order set in the area to be detected from the blockchain;

[0104] The freight vehicle screening module is used to extract the freight order demand characteristics of each freight order in the freight order set within the area to be detected; screen the freight vehicles according to the freight vehicle information and the freight order demand characteristics to form a first screened freight vehicle set; analyze the arrival time of the 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 the freight vehicle drivers corresponding to the freight vehicles in the second screened freight vehicle set to form a driver set 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, and to form an evaluation system group for freight vehicle drivers; and to 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, 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.

[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 the 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 in the passing freight vehicle set and historical driving data of the corresponding freight vehicle drivers;

[0109] 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.

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

[0111] The freight vehicle initial screening unit is used to screen freight vehicles that simultaneously meet the freight order demand characteristics of the freight order, the freight weight and the freight volume, according to the freight vehicle information and the freight order demand 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 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 from the first screened freight vehicle set, which is 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 into an evaluation system group;

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

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

[0117] The delivery time impact coefficient analysis unit includes 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; sending the sequence of drivers to be selected and the set of pre-delivery routes corresponding to the freight order to the freight order initiating user; the freight order initiating user selecting the freight vehicle driver and the pre-delivery route; extracting the 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 article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0120] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered 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 pre-travel routes pass through the area to be detected 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; and the freight order set in the area to be detected 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, 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 the freight vehicle drivers in the set of drivers to be evaluated, and form an evaluation system group for the freight vehicle drivers; and construct an evaluation model based on the evaluation system group for the 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 drivers to be selected according to the calculation results; analyze the delivery time impact coefficient of the freight vehicle driver selected by the freight order initiator; The planned delivery route is updated based on the analysis results of the delivery time impact coefficient.

2. According to a blockchain-based goods circulation and transportation planning and management method according to claim 1, it is characterized by: In S1, the freight vehicle information includes the real-time position of the freight vehicle, the vehicle's planned driving route and the remaining carrying capacity of the freight vehicle; the remaining carrying capacity of the freight vehicle includes the remaining carrying space of the freight vehicle and the remaining carrying weight of the freight vehicle; the vehicle's planned driving route is a navigation route selected by the freight order initiating 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 real-time position of the freight vehicle 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 initiating user through the user terminal.

3. According to a blockchain-based goods circulation and transportation planning and management method according to claim 2, it is characterized by: S2 includes the following: S201: extracting freight order demand features of 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 cargo location, destination location and delivery time; S202: According to the freight vehicle information and the freight order demand characteristics of each freight order, a freight vehicle that satisfies both the freight weight and the freight volume in the freight order demand characteristics of the freight order is selected, and recorded as a first selected freight vehicle set; S203: from the historical driving data of all freight vehicle drivers, select navigation routes that start from the real-time position of the freight vehicle, pass through the location of the goods, and end at the location of the destination, and form a set, which is recorded as a pre-delivery route set; from the historical vehicle operation data of all freight vehicles, extract the pre-delivery route sections from the real-time position of the freight vehicle to the location of the goods of the freight order and the estimated time of each pre-delivery route section, calculate the average value of the estimated time of the pre-delivery route sections, and calculate the estimated time of the freight vehicle arriving at the location of the goods according to the real-time time and the average value of the estimated time of the pre-delivery route sections; S204: From the first filtered freight vehicle set, filter out the freight vehicles whose estimated arrival time at the location of the goods meets the arrival time at the location of the goods in the freight order demand 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.

4. According to a blockchain-based goods circulation and transportation planning and management method according to claim 3, it is characterized by: 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 transportation 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 transportation task, the average value 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 expected 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: Determine the driver of the freight vehicle i The arrival time offset, delivery time offset and driving route offset of the vehicle constitute the evaluation system group, denoted 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 a freight vehicle driver DE i , α1, α2 and α3 represent evaluation proportional coefficients, and the evaluation proportional coefficients are system preset constants.

5. According to a blockchain-based goods circulation and transportation planning and management method according to claim 4, it is characterized by: In S4, the following are included: S401: Substitute the evaluation system group corresponding to the freight vehicle driver 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 freight order initiating user; the freight order initiating user selects the freight vehicle driver and the pre-delivery route; S403: extract the historical driving data of the freight vehicle driver selected by the freight order initiating user, and analyze the delivery time impact coefficient TTIC of the freight vehicle driver: TTIC = exp(DTO÷ATO-1); 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; If the delivery time impact coefficient TTIC of the freight vehicle driver is ≤1, no processing will be done; if the delivery time impact coefficient TTIC of the freight vehicle driver is >1, the pre-delivery route will be updated; The updating of the pre-delivery route includes the following contents: 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 location of the destination from the historical driving data of the freight vehicle driver selected by the freight order initiating user, and forming a set, which is recorded as a route set to be compared; 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 sections and non-intersection sections; the intersection section appears in both the pre-delivery route and any of the routes to be compared, and the non-intersection section is a section in the pre-delivery route other than the intersection section; S413: From the historical driving data of the freight vehicle driver selected by the freight order initiating user, for each non-intersecting road section, extract the road section with the same endpoint as the non-intersecting road section and the smallest mileage, and record it as the replacement road section; according to the original driving order of the pre-delivery route, integrate the intersection road section and the replacement road section to form a replacement route; S414: The replacement route is updated to cover the pre-delivery route selected by the freight order initiating user.

6. A goods circulation and transportation planning and management system based on blockchain, the system is applied to the goods circulation and transportation planning and management method based on blockchain as described in any one of claims 1-5, 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 travel routes pass through the area to be detected into a passing freight vehicle set, obtain freight vehicle information in the passing freight vehicle set and historical driving data of the corresponding freight vehicle drivers; and obtain a freight order set in 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 according to the calculation results; analyzing the delivery time influence coefficient of the freight vehicle driver selected by the freight order initiator user; The planned delivery route is updated based on the analysis results of the delivery time impact coefficient.

7. According to claim 6, a blockchain-based goods circulation and transportation planning and management system is characterized by: 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 on the vehicle's pre-travel route into a passing freight vehicle set, and obtain freight vehicle information in the passing freight vehicle set and historical driving data of the corresponding freight vehicle drivers; 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.

8. According to claim 6, a blockchain-based goods circulation and transportation planning and management system is characterized by: The freight vehicle screening module includes a freight vehicle initial screening unit and a to-be-evaluated driver screening unit; The freight vehicle initial screening unit is used to screen freight vehicles that simultaneously meet the freight order demand characteristics of the freight order, the freight weight and the freight volume, according to the freight vehicle information and the freight order demand characteristics of each freight order, and record them as the first screened freight vehicle set; The to-be-evaluated driver screening unit 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, 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 to-be-evaluated driver set.

9. According to claim 6, a blockchain-based goods circulation and transportation planning and management system, 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 into an evaluation system group; The evaluation model construction unit constructs an evaluation model for a freight vehicle driver according to the evaluation system group for the freight vehicle driver.

10. According to claim 6, a blockchain-based goods circulation and transportation planning and management system, 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 includes 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; sending the sequence of drivers to be selected and the set of pre-delivery routes corresponding to the freight order to the freight order initiator user; 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 delivery time influence coefficient of the freight vehicle driver; 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 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 freight order initiating user.

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