Method, device and equipment for measuring and calculating cargo transportation volume of common road and medium

Abstract

The invention relates to the technical field of highway freight statistics, and discloses a method, a device and equipment for measuring and calculating the cargo transportation volume of a common highway and a medium. The method comprises the following steps: preprocessing a basic information database of a commercial freight vehicle to obtain a preprocessed basic information database; determining a final transportation trip according to the satellite track point location data; according to the vector map data of the expressway network, determining a common road trip in the final transportation trip; correcting the overload control truck data to obtain corrected overload control truck data; according to the corrected overload control truck data, the preprocessed basic information database and the final transportation trip, calculating the average cargo weight of each commercial freight vehicle on a common road; and calculating the total cargo transportation volume of the common road according to the common road trip, the total mileage of the common road trip and the average cargo weight of the common road. By integrating multi-source big data, the accuracy of the data is remarkably improved, and meanwhile, the normalization and scientificity of the statistical process are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of highway freight statistics, and in particular to a method, device, equipment and medium for calculating the amount of freight transported by ordinary highways. Background Art

[0002] Highway freight transport volume includes two indicators: freight volume and freight turnover. It is a key indicator to characterize the service results of the highway freight transport industry, the core statistical content in the statistical work of transportation authorities at all levels, and an important reference indicator for the calculation of road transport added value in the calculation of regional GDP.

[0003] The current statistical method for ordinary highway freight transport volume adopts a combination of "comprehensive statistics of large-scale enterprises + fluctuation estimation of small-scale businesses". However, the data information used in this method is not authentic and representative, long-term estimation may lead to deviations, and the statistical frequency is low, which makes it difficult to meet the needs of daily management and decision-making. Summary of the invention

[0004] In view of this, the purpose of the present invention is to overcome the deficiencies in the prior art and to provide a method, device, equipment and medium for calculating the freight transport volume on ordinary roads.

[0005] The present invention provides the following technical solutions:

[0006] In a first aspect, an embodiment of the present disclosure provides a method for calculating the freight transport volume of ordinary roads, the method comprising:

[0007] Obtaining a basic information database of commercial freight vehicles in the measurement area, and preprocessing the basic information database to obtain a preprocessed basic information database;

[0008] Obtain satellite trajectory point data of commercial freight vehicles in the measurement area during the measurement period, and determine the final transportation trips based on the satellite trajectory point data;

[0009] Obtaining vector map data of the expressway network in the measurement area, and determining the number of ordinary highway trips in the final transportation trips based on the vector map data;

[0010] Obtain overweight truck data of commercial freight vehicles collected by off-site overweight truck enforcement equipment in the measurement area during the measurement period, and correct the overweight truck data to obtain corrected overweight truck data;

[0011] Match the corrected overweight truck data with the pre-processed basic information database to obtain the hierarchical information of each commercial freight vehicle, and calculate the average freight weight of each commercial freight vehicle on ordinary roads based on the hierarchical information and the final transport trips;

[0012] Obtain the total mileage of ordinary highway trips, and calculate the total freight transport volume of ordinary highways based on the number of ordinary highway trips, the total mileage of ordinary highway trips and the average freight weight of ordinary highways.

[0013] Optionally, the basic information database includes a plurality of vehicle records, each vehicle record includes at least one of a license plate number, a license plate color, a vehicle type, a total mass, a curb weight, and an annual inspection time. The basic information database is preprocessed to obtain a preprocessed basic information database, including:

[0014] According to the annual inspection time, delete the vehicle records whose time from the current time is greater than the preset age threshold, delete the vehicle records of the vehicle type being trailers, delete the vehicle records with missing curb weight and outside the preset weight range, and supplement the vehicle records with missing curb weight to obtain the cleaned basic information database;

[0015] Each vehicle record in the cleaned basic information database is divided into a plurality of basic layers according to the vehicle type and the total mass, so as to obtain a preprocessed basic information database.

[0016] Optionally, the satellite trajectory point data includes at least one of time information, longitude and latitude information, speed information, and direction information. Determining the final transportation trip according to the satellite trajectory point data includes:

[0017] According to the time information and speed information, the stop points of each satellite trajectory point data are identified to obtain the stop points of commercial freight vehicles, and the basic trips of commercial freight vehicles are determined according to the stop time of the stop points;

[0018] Traverse the basic trips, merge the non-transportation loading and unloading trips, and obtain the initial transportation trips of commercial freight vehicles;

[0019] Determine the long-distance transport trips in the initial transport trips, traverse the long-distance transport trips, merge the non-long-distance transport loading and unloading trips according to the time information and direction information, and obtain the final transport trips.

[0020] Optionally, determining the number of ordinary highway trips in the final transportation trips according to the vector map data includes:

[0021] Matching the information of each trip in the final transport trip with the vector map data to determine whether the vehicle trajectory of each trip information matches on the highway;

[0022] The trip information without vehicle trajectory matching on the expressway is determined as the ordinary road trip, and the ordinary road trips of each layer are summarized according to the basic layer.

[0023] Optionally, the overweight truck data includes at least one of a license plate number, a license plate color, axle number, and weighing data. The overweight truck data is corrected to obtain the corrected overweight truck data, including:

[0024] Match the overload truck data with the pre-processed basic information database according to the license plate number and license plate color, and filter out the traction vehicles among the commercial freight vehicles;

[0025] According to the frequency distribution of the weighing data of the towing vehicle, the no-load weighing value and the full-load weighing value of the towing vehicle are determined respectively;

[0026] Calculate the deadweight and full-load weighing value of the traction vehicle according to the pre-processed basic information database;

[0027] The linear correction method is adopted and the overload truck data is corrected according to the deadweight, full load weighing value, empty load weighing value and actual load weighing value of the towing vehicle to obtain the corrected overload truck data.

[0028] Optionally, the corrected overweight truck data is matched with the preprocessed basic information database to obtain the hierarchical information of each commercial freight vehicle, and the average freight weight of each commercial freight vehicle on ordinary roads is calculated based on the hierarchical information and the final transport trips, including:

[0029] The number of ordinary highway trips is layered according to the total mileage to obtain a plurality of first distance layers, each first distance layer is cross-grouped with each basic layer to obtain a plurality of first sub-groups, and the number of trips in each first sub-group is calculated;

[0030] The difference between the weighing data and the curb weight of each commercial freight vehicle is used as the freight volume of the corresponding commercial freight vehicle;

[0031] Match the corrected overload truck data with the preprocessed basic information database according to the license plate number and license plate color, stratify the successfully matched trips according to the total mileage to obtain multiple second distance layers, cross-group each second distance layer with each basic layer to obtain multiple second sub-groups, and calculate the trip weight average of each second sub-group;

[0032] The average cargo weight of each commercial freight vehicle on ordinary roads is calculated based on the number of trips of each first subgroup and the average weighing value of the trips of each second subgroup.

[0033] Optionally, the total freight transport volume of ordinary roads is calculated based on the number of ordinary road trips, the total mileage of ordinary road trips and the average freight weight of ordinary roads, including:

[0034] Calculate the total freight volume of ordinary roads based on the number of trips and average freight weight of ordinary roads;

[0035] The total turnover of ordinary roads is calculated based on the total mileage of ordinary road trips and the average cargo weight of ordinary roads.

[0036] In a second aspect, an embodiment of the present disclosure provides a device for calculating the amount of freight transported by ordinary roads, the device comprising:

[0037] A preprocessing module is used to obtain a basic information database of commercial freight vehicles in the measurement area, and preprocess the basic information database to obtain a preprocessed basic information database;

[0038] The first determination module is used to obtain satellite trajectory point data of commercial freight vehicles in the measurement area within the measurement time period, and determine the final transportation trip according to the satellite trajectory point data;

[0039] The second determination module is used to obtain vector map data of the expressway network in the measurement area, and determine the number of ordinary highway trips in the final transportation trips according to the vector map data;

[0040] The correction module is used to obtain the overweight truck data of commercial freight vehicles collected by the off-site overweight truck enforcement equipment in the measurement area during the measurement period, and correct the overweight truck data to obtain the corrected overweight truck data;

[0041] The first calculation module is used to match the corrected overweight truck data with the pre-processed basic information database to obtain the hierarchical information of each commercial freight vehicle, and calculate the average freight weight of each commercial freight vehicle on ordinary roads based on the hierarchical information and the final transportation trips;

[0042] The second calculation module is used to obtain the total mileage of ordinary highway trips, and calculate the total cargo transportation volume of ordinary highways based on the number of ordinary highway trips, the total mileage of ordinary highway trips and the average cargo weight of ordinary highways.

[0043] In a third aspect, a computer device is provided in an embodiment of the present disclosure, the computer device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the steps of the method for calculating the ordinary highway freight transport volume in the first aspect when executing the computer program.

[0044] In a fourth aspect, a computer-readable storage medium is provided in an embodiment of the present disclosure, and the computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for calculating the ordinary highway freight transport volume in the first aspect.

[0045] Beneficial effects of this application:

[0046] The method for calculating the ordinary highway freight transport volume provided in the embodiment of the present application includes: obtaining a basic information database of commercial freight vehicles in the measurement area, and preprocessing the basic information database to obtain a preprocessed basic information database; obtaining satellite trajectory point data of commercial freight vehicles in the measurement area within the measurement time period, and determining the final transport trips according to the satellite trajectory point data; obtaining vector map data of the expressway network in the measurement area, and determining the ordinary highway trips in the final transport trips according to the vector map data; obtaining overweight truck data of commercial freight vehicles collected by non-site overweight truck control law enforcement equipment in the measurement area within the measurement time period, and correcting the overweight truck data to obtain corrected overweight truck data; matching the corrected overweight truck data with the preprocessed basic information database to obtain layered information of each commercial freight vehicle, and calculating the average freight weight of each commercial freight vehicle on ordinary highways according to the layered information and the final transport trips; obtaining the total mileage of ordinary highway trips, and calculating the total freight transport volume of ordinary highways according to the ordinary highway trips, the total mileage of ordinary highway trips and the average freight weight of ordinary highways. This application significantly improves the accuracy of data by integrating multi-source big data, while ensuring the standardization and scientific nature of the statistical process.

[0047] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and understandable, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work. In each of the drawings, similar components are numbered similarly.

[0049] Figure 1 A flow chart of a method for calculating the freight transport volume of ordinary roads provided in an embodiment of the present application is shown;

[0050] Figure 2 A frequency peak diagram of weighing data provided by an embodiment of the present application is shown;

[0051] Figure 3 A schematic diagram of the structure of a device for calculating the amount of freight transported by ordinary roads provided in an embodiment of the present application is shown;

[0052] Figure 4 A schematic diagram of the structure of a computer device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0053] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0054] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. In contrast, when an element is referred to as being "directly on" another element, there is no intermediate element. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0055] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0056] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein in the specification of the template are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0058] Example 1

[0059] like Figure 1 , which is a flow chart of a method for calculating the freight transport volume of ordinary roads in an embodiment of the present application. The method for calculating the freight transport volume of ordinary roads provided in an embodiment of the present application includes the following steps:

[0060] Step S110, obtaining a basic information database of commercial freight vehicles in the measurement area, and preprocessing the basic information database to obtain a preprocessed basic information database.

[0061] In this embodiment, the basic information database of commercial freight vehicles in the measurement area X is first obtained. The basic information database includes multiple vehicle records, each of which includes but is not limited to the license plate number, license plate color, vehicle type, gross weight, curb weight, annual inspection time, marked tonnage and other data of the commercial freight vehicle.

[0062] Specifically, the basic information database needs to be cleaned. First, the vehicle records whose time from the current annual inspection is greater than the preset age threshold (such as 2 years) are deleted, and then all vehicle records of the trailer type are deleted. At the same time, the vehicle records with missing curb weight, curb weight of 0 and exceeding the upper limit of abnormal value (such as 40,000 kg) are kept as vehicle curb weight to be supplemented.

[0063] Next, a curb weight reference library for vehicle brands and models is constructed. First, vehicle records with complete curb weight records and a curb weight within a preset weight range (such as 0 to 40,000 kg) are screened out from the basic information database. Then, these vehicle records are summarized according to the brand model field. During the summary process, the vehicle records with a preset percentage of curb weight before and after (such as the first 5% and the last 5%) of each brand model are first deleted, and then the remaining vehicle records of each brand model are ensured to be no less than the preset number (such as 3), and then the curb weight mode of the brand model is calculated as the curb weight reference value of the brand model. Finally, the vehicle records with a curb weight less than the preset weight (such as 920 kg) in the calculation results are eliminated to form the final vehicle brand model curb weight reference library.

[0064] Furthermore, the vehicle curb weight to be supplemented library is matched with the vehicle curb weight reference library according to the brand model, and the vehicle records of the vehicle with missing curb weight, curb weight of 0 and exceeding the upper limit of abnormal value (such as 40000kg) are supplemented.

[0065] For vehicle records that are still incomplete in the above steps, further methods are used to supplement them: (1) For records of non-towing vehicles with missing curb mass, first, the difference between the total mass and the marked tonnage of the vehicle record is used as the curb mass to supplement the database. Secondly, when the total mass record is incomplete, the marked tonnage is directly used as the curb mass to supplement; (2) For records of towing vehicles with missing curb mass, the existing completed records are used to calculate the mode of the curb mass of all tractor vehicles, and then this value is used as the curb mass of the remaining tractor vehicles to supplement.

[0066] Furthermore, the curb weight of the towing vehicle is converted into the deadweight of the vehicle when towing the trailer as a whole. The calculation method is: select vehicle records whose vehicle type is trailer and whose curb weight is within a preset weight range (such as greater than 0 and less than 40,000 kg) in the original basic information database, calculate the average curb weight of all trailer vehicle records, and then convert the curb weight of each towing vehicle into the original curb weight + the average curb weight of the trailer as the final curb weight of the towing vehicle, and finally form a cleaned basic information database.

[0067] Preferably, each vehicle record in the basic information database after cleaning is layered and marked, and the layering is performed according to the two indicators of vehicle type and total mass. First, for vehicle records with incomplete total mass records, data supplementation is required. The supplementation method is: first calculate and supplement according to the total mass of vehicles of the same brand model; if it is still not possible to complete the supplement, then supplement according to the total mass of vehicles of the same length, width and height. When layering, the vehicle type index is divided into six categories: tractor, special structure vehicle, tank truck, dump truck, van and ordinary vehicle. The total mass index is divided into four levels: less than 12 tons, 12-20 tons, 20-30 tons and greater than 30 tons. Then, the vehicle type index and the total mass index are cross-layered. On this basis, for the layer with a small number of vehicle records, it is merged with the adjacent layer to obtain multiple basic layers to form a pre-processed basic information database. In this embodiment, 13 basic layers are finally formed as an example, as shown in Table 1.

[0068] Table 1: Basic layer division

[0069]

[0070]

[0071] The above method improves the accuracy, completeness and classification clarity of the data by preprocessing the basic information database, while also improving the efficiency of measurement, providing a solid foundation for subsequent transportation volume measurement work.

[0072] Step S120, obtaining satellite trajectory point data of commercial freight vehicles in the measurement area within the measurement time period, and determining the final transportation trips based on the satellite trajectory point data.

[0073] Specifically, the satellite trajectory point data of commercial freight vehicles in the measurement area X within the measurement time period Y is obtained, including but not limited to time information, longitude and latitude information, speed information, direction information, etc., and duplicate or abnormal data is deleted.

[0074] Furthermore, according to the time information, the continuous satellite trajectory point data are identified as stop points in chronological order, that is, the vehicle speed threshold (such as 1m / s) is preset to preliminarily determine whether the vehicle is in a stop state. When the vehicle speed is greater than a certain preset vehicle speed threshold, it is determined to be in a driving state, otherwise it is determined to be in a stopped state, that is, a stop point. Then, according to the stay time of the stop point, it is determined whether the corresponding transport trip is divided into a valid trip, that is, when the stay time of the stop point is less than the preset stop time threshold (such as 3 minutes), it is judged as an invalid stop point; when the stay time of the stop point exceeds the preset stop time threshold, it is marked as the end of the transport trip; if the moving distance between the previous stop point and the next stop point is within the preset moving distance threshold (such as 50 meters), the trip between the two stop points is recorded as an invalid trip, and the stop point time is recorded as the start of the previous stop point to the end of the next stop point. According to the above rules, the basic trips of all commercial freight vehicles are obtained.

[0075] Then, all basic trips are traversed, and the non-transportation loading and unloading trips are merged to obtain the initial transportation trips of commercial freight vehicles. Among them, the merging rules are: different time thresholds are designed according to the location of the stop point. For example, if the stop point is located on a highway, the previous trip and the next trip of the stop point are merged; when the stop point is located at other locations, when the stop point time is less than the corresponding time threshold (such as 40 minutes), the previous trip and the next trip of the stop point are merged.

[0076] Furthermore, it is necessary to screen the long-distance transport trips in the initial transport trips. First, the traction vehicles and vehicles with a total mass above the preset total mass threshold (such as 30 tons) are screened out according to the vehicle type, and then the number of districts and counties passed during the measurement time period Y is summarized. The trips that pass through the preset number of districts and counties (such as 10) or more are defined as long-distance transport trips.

[0077] Finally, the long-distance transport trips are traversed again, and the non-long-distance transport loading and unloading trips are merged. The basis for the merging judgment is the vehicle driving time period and the trip direction angle. The specific rule is that when driving at night (generally defined as the end time of the previous trip between 9 pm and 3 am), if the parking time exceeds the first preset parking time upper limit threshold (such as 8 hours), the trips will not be merged; if the parking time is between the first preset parking time lower limit threshold and the first preset parking time upper limit threshold (such as 1 to 8 hours), and the difference between the direction angle of the next trip and the direction angle of the previous trip is within the first preset angle range (such as plus or minus 60 degrees), the previous trip and the next trip of the stop point are merged; if the parking time is less than the first preset parking time lower limit threshold (such as 1 hour), the previous trip and the next trip of the stop point are merged. When driving during the day (generally defined as the end time of the previous trip being between 3 a.m. and 9 p.m.), if the parking time exceeds the second preset parking time upper limit threshold (such as 4 hours), the trips will not be merged; if the parking time is between the second preset parking time lower limit threshold and the second preset parking time upper limit threshold (such as 1 to 4 hours), and the difference between the direction angle of the next trip and the direction angle of the previous trip is within the second preset angle range (such as plus or minus 60 degrees), the previous trip and the next trip of the stop point will be merged; if the parking time is less than the second preset parking time lower limit threshold (such as 1 hour), the previous trip and the next trip of the stop point will be merged. The final transport trips are formed according to the above rules, and the basic vehicle information, starting and ending time, starting and ending longitude and latitude, total mileage of each final transport trip, and the longitude and latitude information of all track points under the final transport trip are recorded.

[0078] The above method identifies the stop points and divides the trips of long-distance vehicles by combining the driving time period and direction angle factors to obtain the final transport trips, which improves the accuracy of long-distance transport trip identification and reduces redundant records in long-distance transport, thereby improving the accuracy of transport volume calculation.

[0079] Step S130, obtaining vector map data of the expressway network in the measurement area, and determining the number of ordinary highway trips in the final transportation trips based on the vector map data.

[0080] Specifically, the vector map data of the highway network in the measurement area X is obtained, and then each trip information of the final transportation trip in step S120 is matched with the vector map data, and the map matching method based on the hidden Markov model is used to match whether the vehicle trajectory of each trip information passes through the highway.

[0081] If some trajectories in the trip information match on the highway, it is recorded as a highway trip. If no trajectory matches on the highway, it is recorded as an ordinary road trip, and the number of ordinary road trips in each layer is summarized according to the basic layer.

[0082] The above method obtains more accurate transportation volume measurement results by accurately classifying transportation trips.

[0083] Step S140, obtaining the overweight truck data of commercial freight vehicles collected by the off-site overweight truck enforcement equipment in the measurement area during the measurement time period, and correcting the overweight truck data to obtain the corrected overweight truck data.

[0084] Specifically, the overweight truck data of commercial freight vehicles collected by the off-site overweight law enforcement equipment in the measurement area X during the measurement time period Y is obtained, including but not limited to the license plate number, license plate color, number of axles, weighing data and other information. In view of the inaccurate weighing data collected by the off-site overweight law enforcement equipment, the weighing data of each station needs to be corrected. The correction method is:

[0085] (1) First, the overload truck data is matched with the preprocessed basic information database according to the license plate number and license plate color, and the towing vehicle is selected according to the matched vehicle type;

[0086] (2) Figure 2 As shown in the figure, the weighing data of the selected tractor vehicles are grouped according to the preset weight (such as 2 tons) as a group interval, and the data of each site are grouped, and the frequency value of each group is calculated; then, the frequency of each group of each site is traversed, and the peak with the highest frequency is first found, which is recorded as A i , then at distance A i Find the second frequency peak within the range above the preset group interval (such as at least 5 group intervals), record it as B i ; Further compare the load values ​​corresponding to these two peaks, the larger value is taken as the actual load peak value, and the corresponding group record weighing average is the actual load weighing value a i The smaller value is taken as the no-load peak value, and the corresponding average weighing value in the group is the no-load weighing value b i ;

[0087] (3) Based on the preprocessed basic information database, calculate the mode of the curb weight of the tractor vehicle, recorded as its own weight p, and calculate the mode of the curb weight of the tractor and trailer, recorded as the fully loaded weight value q;

[0088] (4) Finally, the linear correction method is used to correct the weighing data of each station. The formula is as follows:

[0089] t kc =α k t km +β k

[0090] Where, t kcis the corrected weighing value of the kth station, t km is the weight value observed at the kth station, and the correction coefficient α of the kth station k and β k Calculated by the following formula:

[0091]

[0092] β k =p-α k *b k

[0093] The above formula is used to correct the weighing data observed at each station, and finally the corrected overweight truck data is obtained.

[0094] The above method accurately corrects the problem of inaccurate weighing data collected by off-site overweight control law enforcement equipment, ensuring that the weighing data of each transport trip is accurate and reliable, thereby improving the accuracy and reliability of the data.

[0095] Step S150, matching the corrected overweight truck data with the preprocessed basic information database to obtain the hierarchical information of each commercial freight vehicle, and calculating the average cargo weight of each commercial freight vehicle on ordinary roads based on the hierarchical information and the final transport trips.

[0096] Understandably, first, the ordinary highway trips in step S130 are stratified according to the total mileage to obtain multiple first distance layers. Exemplarily, the stratification method can be grouped according to 8 distance categories, such as 0-10 kilometers, 10-20 kilometers, 20-50 kilometers, 50-100 kilometers, 100-200 kilometers, 200-500 kilometers, 500-800 kilometers, and more than 800 kilometers. Each first distance layer is cross-grouped with each basic layer to form multiple first sub-groups, which are included in the overall set of trip divisions, and the number of trips in each first sub-group is calculated.

[0097] Furthermore, the corrected overweight truck data in step S140 is matched with the preprocessed basic information database according to the license plate number and license plate color, and the difference between the weighing data and the curb weight of each vehicle is used as the corresponding freight volume, and then the successfully matched trip samples are included in the calculation trip matching set C of the average freight weight.

[0098] The samples in set C are stratified according to the total mileage of each trip to obtain multiple second distance layers. For example, the stratification method can be grouped according to 8 distance categories, namely, 0-10 km, 10-20 km, 20-50 km, 50-100 km, 100-200 km, 200-500 km, 500-800 km, and above 800 km. Each second distance layer is cross-grouped with each basic layer to obtain multiple second sub-groups, and the trip weight average of each second sub-group is calculated.

[0099] Since most of the overweight control stations are distributed on ordinary national and provincial roads, most of the observed transportation is long-distance transportation, so there is a certain difference from the trip distance distribution in the satellite positioning data, and the actual load of the vehicle under different transportation distances is also different. Therefore, it is necessary to calculate the average cargo weight based on the overall trip set distribution. The specific method is to adjust the average trip weighing value of each second subgroup according to the number of trips of each first subgroup, and finally obtain the average cargo weight of ordinary roads for each basic layer of commercial freight vehicles. The adjustment formula is as follows:

[0100]

[0101] In the formula, is the average freight weight of commercial freight vehicles on ordinary roads at the ith basic level, n ij is the number of passes in the total set of passes partitioned in the jth distance layer of the basic layer of the i-th pass sample, It is the weighted average of the trip matching set C in the jth distance layer of the basic layer of the i-th trip sample.

[0102] The above method ensures the accuracy and consistency of the data, and the calculated average cargo weight of each commercial freight vehicle on ordinary roads provides strong support for subsequent transportation volume calculations.

[0103] Step S160, obtaining the total mileage of ordinary highway trips, and calculating the total cargo transportation volume of ordinary highways according to the number of ordinary highway trips, the total mileage of ordinary highway trips and the average cargo weight of ordinary highways.

[0104] It can be understood that the total freight volume of ordinary roads includes two indicators: freight volume and turnover volume. The total freight volume of ordinary roads is obtained by multiplying the number of ordinary road trips in step S130 by the average freight weight of ordinary roads in step S150. The specific calculation formula is as follows:

[0105]

[0106] Where H is the total freight volume of ordinary roads, N i is the number of ordinary road trips.

[0107] Then, the total mileage of each ordinary highway trip is summed up and multiplied by the average cargo weight of ordinary highways of each basic layer to obtain the total turnover of ordinary highways. The specific calculation formula is as follows:

[0108]

[0109] Where, L i is the total mileage of the ith basic layer of ordinary highway trips, l ik is the mileage of the kth trip on the i-th basic layer on the ordinary highway calculated in step S130, and Z is the total turnover of the ordinary highway.

[0110] The above method realizes comprehensive and dynamic monitoring of the freight industry by integrating multi-source big data. The entire measurement process is standardized and scientific, which enhances the multidimensionality of the statistical results and significantly improves the accuracy of freight volume data. It overcomes the shortcomings of traditional statistical methods such as low precision, slow update frequency, and inability to comprehensively, dynamically and objectively reflect the changing trends and degree of the road freight industry, and provides reliable data support for transportation development and policy formulation.

[0111] The method for calculating the freight transport volume on ordinary roads provided in the embodiment of the present application obtains a basic information database of commercial freight vehicles in the measurement area, and preprocesses the basic information database to obtain the preprocessed basic information database; obtains satellite trajectory point data of commercial freight vehicles in the measurement area within the measurement time period, and determines the final transportation trips according to the satellite trajectory point data; obtains vector map data of the expressway network in the measurement area, and determines the number of ordinary road trips in the final transportation trips according to the vector map data; obtains overweight truck data of commercial freight vehicles collected by non-site overweight truck control law enforcement equipment in the measurement area within the measurement time period, and corrects the overweight truck data to obtain corrected overweight truck data; matches the corrected overweight truck data with the preprocessed basic information database to obtain layered information of each commercial freight vehicle, and calculates the average freight weight of ordinary roads for each commercial freight vehicle according to the layered information and the final transportation trips; obtains the total mileage of ordinary road trips, and calculates the total freight transport volume of ordinary roads according to the ordinary road trips, the total mileage of ordinary road trips and the average freight weight of ordinary roads. This application significantly improves the accuracy of data by integrating multi-source big data, while ensuring the standardization and scientific nature of the statistical process.

[0112] Example 2

[0113] like Figure 3 FIG. 1 is a schematic diagram of a common highway freight transport volume calculation device 300 in an embodiment of the present application, and the device includes:

[0114] The preprocessing module 310 is used to obtain a basic information database of commercial freight vehicles in the measurement area, and preprocess the basic information database to obtain a preprocessed basic information database;

[0115] The first determination module 320 is used to obtain satellite trajectory point data of commercial freight vehicles in the measurement area within the measurement time period, and determine the final transportation trip according to the satellite trajectory point data;

[0116] The second determination module 330 is used to obtain vector map data of the highway network in the measurement area, and determine the number of ordinary highway trips in the final transportation trips according to the vector map data;

[0117] The correction module 340 is used to obtain the overweight truck data of commercial freight vehicles collected by the off-site overweight truck enforcement equipment in the measurement area during the measurement period, and correct the overweight truck data to obtain the corrected overweight truck data;

[0118] The first calculation module 350 is used to match the corrected overweight truck data with the pre-processed basic information database to obtain the hierarchical information of each commercial freight vehicle, and calculate the average freight weight of each commercial freight vehicle on ordinary roads according to the hierarchical information and the final transportation trips;

[0119] The second calculation module 360 ​​is used to obtain the total mileage of ordinary highway trips, and calculate the total cargo transportation volume of ordinary highways according to the number of ordinary highway trips, the total mileage of ordinary highway trips and the average cargo weight of ordinary highways.

[0120] The ordinary highway freight transport volume calculation device provided in the embodiment of the present application significantly improves the accuracy of data by integrating multi-source big data, while ensuring the standardization and scientificity of the statistical process.

[0121] Example 3

[0122] The present application also provides a computer device. Figure 4 , Figure 4 This is a basic structural block diagram of the computer device in this embodiment.

[0123] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are interconnected and communicated through a system bus. It should be noted that the figure only shows a computer device 4 with a memory 41, a processor 42, and a network interface 43, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable gate arrays (Field-Programmable Gate Array, FPGA), digital processors (Digital Signal Processor, DSP), embedded devices, etc.

[0124] The computer device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device may interact with a user through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device.

[0125] The memory 41 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or D slot compatibility test memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 41 can be an internal storage unit of the computer device 4, such as a hard disk or memory of the computer device 4. In other embodiments, the memory 41 can also be an external storage device of the computer device 4, such as a plug-in hard disk equipped on the computer device 4, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. Of course, the memory 41 can also include both the internal storage unit of the computer device 4 and its external storage device. In this embodiment, the memory 41 is generally used to store the operating system and various application software installed on the computer device 4, such as computer-readable instructions of the slot compatibility test method, etc. In addition, the memory 41 can also be used to temporarily store various types of data that have been output or are to be output.

[0126] The processor 42 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other common highway freight transport volume measurement chips in some embodiments. The processor 42 is generally used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to run computer-readable instructions or process data stored in the memory 41, such as computer-readable instructions for running the slot compatibility test method.

[0127] The network interface 43 may include a wireless network interface or a wired network interface. The network interface 43 is generally used to establish a communication connection between the computer device 4 and other electronic devices.

[0128] The computer device provided in this embodiment can execute the above-mentioned method for calculating the freight transport volume of ordinary roads. The method for calculating the freight transport volume of ordinary roads here can be the method for calculating the freight transport volume of ordinary roads in each of the above-mentioned embodiments.

[0129] Example 4

[0130] This embodiment also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method for calculating the ordinary highway freight transportation volume in the embodiment are implemented.

[0131] In this embodiment, the computer-readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the computer-readable storage medium can be an internal storage unit of a computer device, such as a hard disk or memory of the computer device. In other embodiments, the computer-readable storage medium can also be an external storage device of a computer device, such as a plug-in hard disk equipped on the computer device, a smart memory card (Smart Media Card, referred to as SMC), a secure digital (Secure Digital, referred to as SD) card, a flash card, etc. Of course, the computer-readable storage medium can also include both the internal storage unit of the computer device and its external storage device. In this embodiment, the computer-readable storage medium is generally used to store an operating system and various application software installed on the computer device. In addition, the computer-readable storage medium can also be used to temporarily store various types of data that have been output or are to be output.

[0132] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and structure diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in an alternative implementation, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the structure diagram and / or the flow chart, and the combination of boxes in the structure diagram and / or the flow chart, can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0133] In addition, the functional modules or units in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0134] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or partly contributed to the prior art or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a smart phone, a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium can be a non-volatile storage medium or a volatile storage medium. For example, the storage medium can be: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a disk or an optical disk, and other media that can store program codes.

[0135] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for calculating the volume of freight transported on ordinary roads, characterized in that: The method comprises: Acquire a basic information database of commercial freight vehicles in the measurement area, and preprocess the basic information database to obtain a preprocessed basic information database; Obtain satellite trajectory point data of commercial freight vehicles in the measurement area within the measurement time period, and determine the final transportation trips according to the satellite trajectory point data; Acquire vector map data of the expressway network in the measurement area, and determine the number of ordinary highway trips in the final transportation trips according to the vector map data; Obtaining overweight truck data of commercial freight vehicles collected by off-site overweight truck enforcement equipment in the measurement area during the measurement time period, and correcting the overweight truck data to obtain corrected overweight truck data; Matching the corrected overweight truck data with the pre-processed basic information database to obtain the hierarchical information of each commercial freight vehicle, and calculating the average freight weight of each commercial freight vehicle on ordinary roads based on the hierarchical information and the final transport trips; The total mileage of the ordinary highway trips is obtained, and the total cargo transportation volume of the ordinary highway is calculated according to the ordinary highway trips, the total mileage of the ordinary highway trips and the average cargo weight of the ordinary highway.

2. The method for calculating the freight transport volume of ordinary roads according to claim 1 is characterized in that: The basic information database includes a plurality of vehicle records, each of which includes at least one of a license plate number, a license plate color, a vehicle type, a total mass, a curb weight, and an annual inspection time. The basic information database is preprocessed to obtain a preprocessed basic information database, including: According to the annual inspection time, delete the vehicle records whose time from the current time is greater than the preset age threshold, delete the vehicle records whose vehicle type is a trailer, delete the vehicle records whose curb weight is missing and outside the preset weight range, and supplement the vehicle records whose curb weight is missing to obtain a cleaned basic information database; Each vehicle record in the cleaned basic information database is divided into a plurality of basic layers according to vehicle type and total mass, so as to obtain the preprocessed basic information database.

3. The method for calculating the freight transport volume of ordinary roads according to claim 1 is characterized in that: The satellite trajectory point data includes at least one of time information, longitude and latitude information, speed information, and direction information. The determining of the final transportation trip according to the satellite trajectory point data includes: Identify the stop points of each satellite trajectory point data according to the time information and speed information to obtain the stop points of the commercial freight vehicle, and determine the basic trips of the commercial freight vehicle according to the stop time of the stop points; Traversing the basic trips, merging the non-transportation loading and unloading trips, and obtaining the initial transportation trips of the commercial freight vehicle; Determine the long-distance transport trips in the initial transport trips, traverse the long-distance transport trips, merge the non-long-distance transport loading and unloading trips according to the time information and the direction information, and obtain the final transport trips.

4. The method for calculating the freight transport volume of ordinary roads according to claim 2 is characterized in that: The determining, according to the vector map data, the number of ordinary highway trips in the final transportation trips comprises: Matching the trip information of each final transport trip with the vector map data to determine whether the vehicle track of each trip information matches on the highway; The trip information without vehicle track matching on the expressway is determined as the ordinary highway trip information, and the ordinary highway trip information of each layer is summarized according to the basic layer.

5. The method for calculating the freight transport volume of ordinary roads according to claim 1, characterized in that: The overweight truck data includes at least one of the license plate number, license plate color, number of axles, and weighing data. The overweight truck data is corrected to obtain the corrected overweight truck data, including: Matching the overweight truck data with the pre-processed basic information database according to the license plate number and license plate color, and screening out the traction vehicles among the commercial freight vehicles; Determining the no-load weighing value and the loaded weighing value of the tractor vehicle respectively according to the frequency distribution of the weighing data of the tractor vehicle; Calculating the deadweight and fully loaded weight of the tractor vehicle according to the pre-processed basic information database; The overload truck data is corrected by adopting a linear correction method according to the deadweight, full-load weighing value, empty-load weighing value and actual-load weighing value of the tractor vehicle to obtain the corrected overload truck data.

6. The method for calculating the freight transport volume on ordinary roads according to claim 2, characterized in that: The corrected overweight truck data is matched with the pre-processed basic information database to obtain the hierarchical information of each commercial freight vehicle, and the average freight weight of each commercial freight vehicle on ordinary roads is calculated according to the hierarchical information and the final transport trips, including: Layering the ordinary highway trips according to the total mileage to obtain a plurality of first distance layers, cross-grouping each of the first distance layers and each of the basic layers to obtain a plurality of first sub-groups, and calculating the number of trips in each of the first sub-groups; The difference between the weighing data and the curb weight of each commercial freight vehicle is used as the freight volume of the corresponding commercial freight vehicle; Matching the corrected overload truck data with the preprocessed basic information database according to the license plate number and license plate color, stratifying the successfully matched trips according to the total mileage to obtain a plurality of second distance layers, cross-grouping each of the second distance layers with each of the basic layers to obtain a plurality of second sub-groups, and calculating the trip weighing average of each of the second sub-groups; The average cargo weight of each of the commercial freight vehicles on ordinary roads is calculated based on the number of trips of each of the first subgroups and the average weighing value of the trips of each of the second subgroups.

7. The method for calculating the freight transport volume on ordinary roads according to claim 1, characterized in that: The calculating of the total freight transport volume of the ordinary highway according to the ordinary highway trip number, the total mileage of the ordinary highway trip number and the average freight weight of the ordinary highway comprises: Calculate the total freight volume of the ordinary highway according to the number of ordinary highway trips and the average freight weight of the ordinary highway; The total turnover of the ordinary highway is calculated based on the total mileage of the ordinary highway trips and the average cargo weight of the ordinary highway.

8. A device for calculating the amount of freight transported on ordinary roads, characterized in that: The device comprises: A preprocessing module is used to obtain a basic information database of commercial freight vehicles in the measurement area, and preprocess the basic information database to obtain a preprocessed basic information database; A first determination module is used to obtain satellite trajectory point data of commercial freight vehicles in the measurement area within the measurement time period, and determine the final transportation trip according to the satellite trajectory point data; A second determination module is used to obtain vector map data of the expressway network in the measurement area, and determine the number of ordinary highway trips in the final transportation trips according to the vector map data; A correction module is used to obtain the overweight truck data of commercial freight vehicles collected by the off-site overweight truck enforcement equipment in the measurement area within the measurement time period, and correct the overweight truck data to obtain the corrected overweight truck data; A first calculation module is used to match the corrected overweight truck data with the pre-processed basic information database to obtain the hierarchical information of each of the commercial freight vehicles, and calculate the average freight weight of each of the commercial freight vehicles on ordinary roads according to the hierarchical information and the final transport trips; The second calculation module is used to obtain the total mileage of the ordinary highway trips, and calculate the total cargo transportation volume of the ordinary highway according to the ordinary highway trips, the total mileage of the ordinary highway trips and the average cargo weight of the ordinary highway.

9. A computer device, characterized in that: It comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the ordinary highway freight transport volume calculation method described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for calculating the ordinary highway freight transportation volume described in any one of claims 1 to 7 are implemented.

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