CN114973671B - Highway network OD data processing method, device, equipment and storage medium - Google Patents
Highway network OD data processing method, device, equipment and storage medium Download PDFInfo
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Abstract
The application provides a highway network OD data processing method, device, equipment and storage medium, wherein the method comprises the following steps: firstly, generating an initial OD data matrix based on-site OD investigation data of an ordinary highway network and charging flow data of the highway network; then, based on expressway bayonet data, performing sample expansion calculation on the initial OD data matrix to generate an investigation point-level real-time dynamic OD data matrix; and finally, displaying the initial OD data matrix and the real-time dynamic OD data matrix by taking the vehicle trip information as a screening condition. The characteristics of wide coverage and sufficient samples are brought into play by taking regular road network OD investigation as a basis, the real-time property and the accuracy of expressway bayonet data are fully utilized, the three are subjected to data fusion, and the real-time updating and the convenient utilization of the road network OD data are realized at lower cost.
Description
Technical Field
The application relates to the technical field of intelligent transportation, in particular to a highway network OD data processing method, device and equipment and a storage medium.
Background
The road network OD (Origin Destination: travel starting and ending point) data are generally used for representing the total travel amount of various vehicles from different starting points to different ending points in a specific area and a specific period, and a two-dimensional table or matrix is generally used for reflecting the space-time distribution condition of road traffic travel in the area, so that the road network OD (Origin Destination: travel starting and ending point) data have important reference values in the aspects of regional road network planning, operation management, project construction, policy formulation and the like.
At present, the update frequency and the data utilization mode of the traditional road network OD data investigation are difficult to meet the current development requirements, the expressway charging flow data and the road section high-definition bayonet data are usually managed by different units in actual operation, the data fusion accuracy is low, the practicability is poor, and the whole coverage cost of related equipment and systems on a common road is high. Therefore, a large technical bottleneck exists in order to realize the real-time dynamic update and display of the road network OD data.
Disclosure of Invention
In view of this, an object of the embodiments of the present application is to provide a method, an apparatus, a device, and a storage medium for processing highway network OD data, which generate a real-time dynamic OD data matrix of a whole vehicle type inspection point level of a regional highway network by combining conventional periodic regional highway network OD inspection data, highway network charging flow data, and highway network interface real-time monitoring data, and perform visual display of the matrix based on screening conditions, so as to fully integrate three data, improve instantaneity and accuracy, and realize real-time update and convenient use of the regional highway network OD data with lower cost, thereby solving the technical problems of low accuracy, poor practicality, and high cost.
In a first aspect, an embodiment of the present application provides a highway network OD data processing method, where the method includes: generating an initial OD data matrix based on the on-site OD investigation data of the common highway network and the charging flow data of the highway network; based on expressway bayonet data, performing sample expansion calculation on the initial OD data matrix to generate a real-time dynamic OD data matrix; and based on the vehicle trip information as a screening condition, performing visual display on the initial OD data matrix and the real-time dynamic OD data matrix.
In the implementation process, three types of data including the traditional regular regional highway network OD investigation data, the highway network charging flow data and the highway network gate real-time monitoring data are fully integrated, so that the real-time performance and the accuracy are improved, and the regional highway network OD data is updated in real time and conveniently utilized at lower cost.
Optionally, the generating an initial OD data matrix based on the on-site OD survey data of the common highway network and the highway network charging flow data includes: processing the on-site OD investigation data of the common highway network to obtain a travel investigation database of the common highway vehicles; processing the highway network charging running water data to obtain a highway vehicle trip investigation database; searching in the common highway vehicle trip investigation database and the expressway vehicle trip investigation database according to the license plate number of the vehicle, and performing time sequencing according to the search records to obtain a vehicle trip time sequence; and counting the vehicle travel time sequence based on the starting and ending point of each travel of the vehicle to generate the initial OD data matrix.
In the implementation process, the toll station information of vehicles entering the expressway network is judged in real time by using expressway bayonet data, and real-time dynamic OD data calculation covering all the expressway network is carried out by combining historical OD data characteristics.
Optionally, the processing the on-site OD survey data of the common road network to obtain a common road vehicle trip survey database includes: collecting OD video data continuously shot by a plurality of investigation points of a common highway network; analyzing the OD video data through an image recognition technology to obtain investigation data of a plurality of vehicles; wherein the survey data comprises: license plate number, vehicle type, photographed time and driving direction; and counting the investigation data of the vehicles to obtain the common road vehicle travel investigation database.
In the implementation process, the mode of adding the temporary check points is adopted to collect the OD data of the common road network, so that a great deal of complicated and laborious manual investigation is avoided, and the timeliness of using the OD data of the road network is improved.
Optionally, the performing sample expansion calculation on the initial OD data matrix based on highway bayonet data to generate a real-time dynamic OD data matrix includes: calculating real-time travel records of vehicles passing through each expressway toll gate based on expressway gate data; judging whether the behavior of the vehicle entering the expressway network exists in each expressway toll station, and extracting the OD data entering and exiting the toll station from the initial OD data matrix according to a judging result; and performing classification sample expansion calculation based on the extraction result to generate a real-time dynamic OD data matrix.
In the implementation process, only two types of vehicles exist in all highway networks, and the vehicles taking a certain toll station of the highway as a starting point and the vehicles not taking a certain toll station of the highway as a starting point are classified, expanded and calculated, so that the effect of real-time OD prediction is improved.
Optionally, the determining whether the behavior of the vehicle entering the expressway network exists in each expressway toll station, and extracting the OD data entering and exiting the toll station from the initial OD data matrix according to the determination result includes: judging whether the behavior of the vehicle entering the expressway network exists in each expressway toll gate according to the topological relation among the expressway network gate equipment, the toll gate and the expressway network and the real-time travel record; if the vehicle number and the vehicle identification rate of each vehicle type entering the expressway network from the toll station in real time are counted according to fixed time intervals by taking the toll station which is currently and correspondingly monitored by the toll station as a point of reentering the expressway; and extracting the total number of vehicles of each vehicle type taking each expressway toll station as a single trip starting point, the proportion of the total number of vehicles of each vehicle type to the total number of vehicles of each vehicle type passing through the same expressway toll station and the quantity proportion of vehicles of each vehicle type taking each expressway toll station or investigation point as an end point in the fixed time interval from the initial OD data matrix.
In the implementation process, the real-time number of vehicles taking the expressway toll station as a starting point is estimated by the proportion of the historical data, and then the vehicles can be distributed to each end point according to the sample expansion of the historical proportion, so that the vehicles do not need to wait for the vehicles to finish traveling, the effect of real-time OD prediction is realized, and the instantaneity and the accuracy are improved.
Optionally, after determining whether there is a behavior of the vehicle entering the expressway network in each expressway toll station according to the topological relation among the expressway network gate device, the toll station and the expressway network, the method further includes: and if the behavior of the vehicles entering the expressway network does not exist in each expressway toll station, extracting the total number of vehicles and the vehicle identification rate of each vehicle type passing through each expressway toll station in the fixed time interval from the initial OD data matrix.
In the implementation process, the sample expansion is carried out according to the average ratio of the total number of vehicles counted in real time in the expressway network to the historical data, so that simple real-time OD data prediction can be realized, the sample expansion coefficient is the average number of the whole expressway network collected in real time, and the system such as equipment, communication and calculation similar to a high-definition bayonet is not required to be distributed on a common expressway with huge mileage, so that the cost is saved, and the practicability is improved.
Optionally, the displaying the initial OD data matrix and the real-time dynamic OD data matrix based on the vehicle trip information as a screening condition includes: setting a travel starting point, a travel ending point, a vehicle type, a starting time and a stopping time as screening conditions, and generating a road network OD data table and an OD data space distribution graph corresponding to the screening conditions; and displaying the initial OD data matrix and the real-time dynamic OD data matrix according to the OD data table and the OD data space distribution graph of the highway network.
In the implementation process, the visual data table and the data space distribution graph enable the OD data of the regional highway network to be real, sensible and easy to use, and the technical threshold for processing, analyzing and utilizing the OD investigation data of the regional highway network is reduced.
In a second aspect, an embodiment of the present application provides a highway network OD data processing device, where the device includes: the first generation module is used for generating an initial OD data matrix based on the on-site survey data of the common road network OD and the charging flow data of the expressway network; the second generation module is used for carrying out sample expansion calculation on the initial OD data matrix based on expressway bayonet data to generate a real-time dynamic OD data matrix; and the screening display module is used for displaying the initial OD data matrix and the real-time dynamic OD data matrix based on the vehicle trip information as a screening condition.
In a third aspect, embodiments of the present application further provide an electronic device, including: a processor, a memory storing machine-readable instructions executable by the processor, which when executed by the processor perform the steps of the method described above when the electronic device is run.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method described above.
In order to make the above objects, features and advantages of the present application more comprehensible, embodiments accompanied with figures are described in detail below.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a highway network OD data processing method provided in an embodiment of the present application;
fig. 2 is a schematic diagram of an OD data space distribution diagram of a road network according to an embodiment of the present application;
fig. 3 is a schematic diagram of a topological relation between a highway network bayonet device and a toll station according to an embodiment of the present application;
FIG. 4 is a system block diagram of a preferred road network OD data processing method according to an embodiment of the present application;
fig. 5 is a schematic functional block diagram of a highway network OD data processing device according to an embodiment of the present application; and
fig. 6 is a block schematic diagram of an electronic device for providing an OD data processing device for road network according to an embodiment of the present application.
Icon: 210-a first generation module; 220-a second generation module; 230-screening display module; 300-an electronic device; 311-memory; 312-a storage controller; 313-processor; 314-peripheral interface; 315-an input-output unit; 316-display unit.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. The components of the embodiments of the present application, which are generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, as provided in the accompanying drawings, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, are intended to be within the scope of the present application.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures. The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element. The terms "first," "second," and the like are used merely to distinguish between descriptions and are not to be construed as indicating or implying relative importance.
The inventor of the application notes that a great deal of manpower and material resources are required to acquire the OD data of the regional highway network, special investigation stations are arranged along the lines of each level of highway, investigation is carried out by sampling questionnaire investigation or license plate method and other modes, and global investigation is usually carried out with a period of 5-10 years, so that the update frequency and the data utilization mode of the OD data of the traditional regional highway network are difficult to meet the current development requirements. In recent years, new technologies such as image recognition, artificial intelligence and the like are continuously and deeply applied in the traffic field, and the popularization of highway ETC equipment and the upgrading of a charging system are realized, so that the arrangement density of highway section bayonet equipment is increased, and the beneficial conditions provide possibility for counting the starting and ending points of vehicles in a highway network in real time.
Based on the above study, the embodiment of the application provides a highway network OD data processing method, which includes: firstly, generating an initial OD data matrix based on-site OD investigation data of an ordinary highway network and charging flow data of the highway network; then, based on expressway bayonet data, performing sample expansion calculation on the initial OD data matrix to generate a real-time dynamic OD data matrix; and finally, displaying the initial OD data matrix and the real-time dynamic OD data matrix based on the vehicle trip information as screening conditions. The characteristics of wide coverage and sufficient samples are brought into play by taking regular road network OD investigation as a basis, the real-time performance and the accuracy of expressway bayonet data are fully utilized, the three are subjected to data fusion, and the real-time updating and the convenient utilization of the road network OD data are realized at lower cost.
Referring to fig. 1, fig. 1 is a flowchart of a first road network OD data processing method according to an embodiment of the present application, and the specific flow of the method is described in detail below, and the method may specifically include: step 100, step 120, step 140.
Wherein, step 100: generating an initial OD data matrix based on the on-site OD investigation data of the common highway network and the charging flow data of the highway network;
Step 120: based on expressway bayonet data, performing sample expansion calculation on the initial OD data matrix to generate a real-time dynamic OD data matrix; and
step 140: and displaying the initial OD data matrix and the real-time dynamic OD data matrix based on the vehicle trip information as screening conditions.
For step 100:
the on-site OD investigation data of the common highway network can be derived from a high-definition camera, a storage unit, auxiliary power supply equipment and auxiliary lighting equipment which are arranged at an OD data investigation point of the common highway network and can be used for continuously photographing and recording the bidirectional traffic flow of the common highway section for 24 hours, wherein the OD data investigation point of the common highway network covers all roads with more than one grade in a specified investigation area, the arrangement interval can be 10-20 km, and if the intersecting roads are all roads with more than two grades, one OD data investigation point of the common highway network is arranged at each inlet direction of an intersection; the highway network tolling pipeline data may be derived from the highway historical tolling pipeline database data which may include license plate numbers of all vehicles entering the highway network, vehicle type, time of entry into the highway, number of tolls entering the highway, time of departure from the highway, number of tolls leaving the highway and route information.
Since the OD data of the whole highway network needs to be generated in real time, and the distribution rule of the OD data in each time period is different, the time when the vehicle enters and exits the highway network must be acquired so as to perform the segment statistics on the OD data in different time periods. And (3) performing targeted fusion on the two types of vehicle travel history data with different sources to form a time sequence of all vehicle travel places, and generating an initial OD data matrix covering the whole highway network.
For step 120, step 140:
for example, highway bayonet data may originate from a set of highway section high definition bayonet devices that cover bi-directional traffic disposed between every two adjacent highway intercommunications. And combining expressway gate data, identifying vehicles entering an expressway network in real time, carrying out real-time statistics and summarization on the total number of vehicles entering each expressway toll gate, comparing the total number of vehicles with corresponding data of an initial OD data matrix, carrying out classified sample expansion calculation and prediction to generate a real-time dynamic OD data matrix, and finally carrying out joint screening and inquiring according to key information such as random combination travel time, vehicle types, starting and ending points and the like to display a real-time dynamic OD data table and a data space distribution graph.
By fully utilizing the existing highway traffic investigation and observation equipment and related data, particularly the highway network charging flow data and the highway high-definition bayonet equipment and data which are widely popularized at present, the fixed traffic investigation and observation equipment and auxiliary facilities are not required to be installed on a large scale along all roads, and the investment, land resources and energy sources are greatly saved; in a longer period, the OD data of the whole road network can be dynamically updated in real time generally only by carrying out one-time large-scale road OD data investigation, so that the latest and effective reference data is provided for traffic managers and policy makers to carry out on-site decision making, a large amount of tedious and laborious manual investigation is avoided, and the timeliness of the use of the OD data of the road network is improved.
In one embodiment, step 100 may specifically include: step 101, step 102, step 103, step 104.
Wherein, step 101: processing the on-site OD investigation data of the common highway network to obtain a travel investigation database of the common highway vehicles;
step 102: processing the highway network charging running water data to obtain a highway vehicle trip investigation database;
step 103: searching in a common highway vehicle trip investigation database and a highway vehicle trip investigation database according to the license plate numbers of the vehicles, and performing time sequencing according to search records to obtain a vehicle trip time sequence; and
Step 104: and counting the vehicle travel time sequence based on the starting and ending point of each travel of the vehicle, and generating an initial OD data matrix.
The storage unit of each survey point of the common highway network is responsible for storing video files of bidirectional traffic of all vehicles continuously for 24 hours on the corresponding road section shot in the appointed survey time, and forms a common highway vehicle trip survey database, which is set as P after relevant processing. The method comprises the steps of accessing a highway network charging system in a survey area through a special interface, extracting travel records of all vehicles entering the highway network from a 24-hour continuous historical charging flow database of the highway network in a specified survey time, wherein each record comprises license plate numbers, vehicle types, highway entering time, highway entering toll gate numbers, highway leaving time, highway leaving toll gate number information and route path information as fields, forming a highway vehicle travel survey database, and setting G.
The license plate number is a unified identity representation of each vehicle running in the road network and is used for connecting two databases of the expressway network and the common highway network, and only if the two databases are connected in series, the starting and ending points of the vehicles in the whole road network, namely the OD points, can be known. According to the selected license plate number, in the common highway vehicle travel survey database P and the highway vehicle travel survey database G= { gi } (i=1, 2, … … k, k is the number of highway toll booths in the survey area), wherein gi is a vehicle travel survey database sub-database corresponding to the ith highway toll booths, and m records gi ,j The composition is formed. gi ,j Is the travel record of the jth train number of the ith expressway toll station, and is recorded by a license plate numberVehicle type->Time of entering expressway->Number of tollgate entering expressway>Departure from expressway time->Toll station number leaving highway->Route information->The data records which are consistent with the license plate number and not yet searched are searched in the database P and the database G. If the travel records corresponding to the license plate number are not stored in the database P and the database G, all travel records of the vehicle which are searched in the database P and the database G are arranged according to the time sequence, and the corresponding check point or the expressway toll gate which appears for the first time after the sorting is used as the first travel starting point, namely the point O. If the two databases also have the travel records corresponding to the license plate number, the current license plate number is still selected, and the retrieval is repeated until all the travel records corresponding to the license plate number are retrieved.
In order to address the situation that one vehicle travels for a plurality of times, the travel records of the vehicles with the license plate numbers in the database P and the investigation database G are continuously searched according to the time sequence after arrangement. If the vehicle meets one of the following conditions: (1) Two consecutive times occur at the same check point and the traveling directions are opposite; (2) Two consecutive occurrences occur at the same highway toll station and are in time sequence of first leaving the toll station and then entering the toll station. And taking the check point or the expressway toll station as the final point of the current trip, namely, the point D, namely, indicating that the next trip is not the last trip of the vehicle in the investigation period, and taking the final point of the current trip as the starting point of the next trip, and repeatedly determining and searching the final point of the trip until the corresponding check point or the expressway toll station is taken as the final point of the last trip of the vehicle when the travel record of the vehicle with the license plate number in the database P and the database G is completely searched according to time sequence.
As shown in FIG. 2, FIG. 2 is a schematic diagram showing the OD data spatial distribution of road network in investigation region, wherein the dotted line in the diagram shows road network in investigation region, the solid dot shows the OD investigation point and expressway toll station in investigation region, the solid curve shows the OD data spatial distribution expected curve between each of the regular road OD investigation point and expressway toll station, the thicker the curve shows the larger the OD data between the two points, the actual OD data between the two points is displayed on each curve, such as Flow AB The OD data of the vehicles between the point a and the point B, that is, the total number of vehicles traveling with the point a as the start point and the point B as the end point is shown.
According to all travel records searched in the process, counting initial OD data matrixes of investigation point levels of different time periods and different vehicle types of current situations in the investigation regionIs the number of x-th period y-type vehicles (s=1, 2, … …, n+k) starting from the normal road OD check point or the highway toll station r (r=1, 2, … …, n+k) ending at the normal road OD check point or the highway toll station s.
By comprehensively counting historical OD data in the two databases, whether one trip is finished or not is deduced through direction judgment for a plurality of trips of a vehicle, starting and ending points of each trip are established to search all trip records of the vehicle, and the search records are ordered according to the time of the earliest record in the two databases, so that toll station information of the vehicle entering the expressway network can be judged in real time by using expressway bayonet data, real-time dynamic OD data estimation covering all the expressway network is carried out by combining the historical OD data characteristics, and the statistics is carried out without waiting for completion of the vehicle trip. Compared with other common prior art in the field, the method avoids interference of model selection and parameter setting on OD data calculation reliability in the real-time OD data calculation process.
In one embodiment, step 101 may specifically include: step 101a, step 101b, step 101c.
Wherein, step 101a: collecting OD video data continuously shot by a plurality of investigation points of a common highway network;
step 101b: analyzing the OD video data through an image recognition technology to obtain investigation data of a plurality of vehicles; wherein, survey data includes: license plate number, vehicle type, photographed time and driving direction; and
step 101c: and counting survey data of a plurality of vehicles to obtain a common road vehicle trip survey database.
Illustratively, since the statistical object is the full road network OD data, not just the expressway, it is necessary to lay the regular road OD data check points on the regular road network. N regular ordinary highway OD data investigation points of regional highway network can be set up in investigation region, every investigation point needs to set up the camera equipment that can satisfy 24 hours continuous record ordinary highway section two-way traffic flow. Optionally, the regular ordinary highway OD data check points of the regional highway network cover all the roads with more than one grade in the appointed investigation region, the set interval is 10-20 km, and if the intersecting roads are all roads with more than two grades, one regular ordinary highway OD data check point of the regional highway network is set at each inlet direction of the intersection.
And analyzing all 24-hour continuous video files obtained from the OD investigation points of the common highway in the OD data investigation region by using a common image recognition technology, and extracting the related information of each train number. For the jth train number of the ith common road OD check point, extracting the license plate numberVehicle type->Shooting time +.>Travel direction->Forming a corresponding travel record p i,j After information extraction of the i-th common road OD investigation point is completed, a database p corresponding to the investigation point is formed i The common highway vehicle travel survey database P= { P in all survey areas is formed in a summarizing way 1 ，p 2 ，……，p n And the total vehicle quantity PT and the license plate recognition rate PR obtained by investigation of the OD of the common highway are obtained through statistics, so that the subsequent sample expansion operation is convenient.
The conventional common highway investigation point coverage density is lower, the coverage density requirement of the application cannot be met, the technical performance cannot fully meet the related requirement provided by the application, temporary equipment meeting the requirement is required to be installed during each investigation, the equipment installed in the highway toll station is fixed long-term equipment, and the related performance meets the requirement but cannot cover the common highway investigation. Therefore, the method for collecting the OD data of the common road network by adding the temporary check points avoids a great deal of complicated and laborious manual investigation and improves the timeliness of the OD data of the road network.
In one embodiment, step 120 may specifically include: step 121, step 122, step 123.
Wherein, step 121: based on expressway gate data, acquiring real-time travel records of vehicles passing through each expressway toll gate;
step 122: judging whether the behavior of the vehicle entering the expressway network exists in each expressway toll station, and extracting OD data entering and exiting the toll station from an initial OD data matrix according to a judging result; and
step 123: and carrying out classification sample expansion calculation based on the extraction result to generate a real-time dynamic OD data matrix.
For example, a set of highway section high-definition bayonet equipment covering bidirectional traffic flow can be arranged between every two adjacent highways, toll stations and time corresponding to vehicles entering and exiting the highways are identified according to records extracted by the highway section bayonet equipment in real time, and the number of vehicles entering the highways from each toll station and the vehicle identification rate in the time interval are counted according to fixed time intervals. According to the two conditions that each expressway toll station is taken as a travel starting point and only the expressway toll station is passed through (each expressway toll station is not taken as a travel starting point), the OD data of the toll station in and out under the two conditions is extracted from an initial OD data matrix of the current area highway network full-vehicle type inspection point level, namely, the corresponding travel number and OD data distribution conditions, and the real-time dynamic OD data matrix of the area highway network is calculated and generated by classifying and sample expanding.
Since the regular historical survey data covers the entire highway network, the real-time data is only highway traffic data. In fact, there are only two types of vehicles in the overall highway network, vehicles starting at a highway toll station and vehicles not starting at a highway toll station. Because the vehicles entering the expressway can only be captured in real time by the bayonet, whether the travel starting point of the vehicles is not on the common expressway or not can not be judged, for the first class of vehicles, the real-time number of the vehicles taking the expressway toll gate as the starting point can be estimated through the proportion of the historical data after the proportion is multiplied in the sample expansion calculation, and then the vehicles can be distributed to all the end points according to the historical proportion for sample expansion without waiting for the vehicles to complete travel, so that the effect of real-time OD prediction is realized; aiming at the second class of vehicles, the system such as equipment, communication, calculation and the like which are similar to a high-definition bayonet are not required to be distributed on a common highway with huge mileage, and simple real-time OD data prediction can be performed only by expanding samples according to the average ratio of the total number of vehicles counted in real time in a highway network to historical data. Compared with the first class of vehicles, the second class of vehicles has the sample expansion coefficient which is the average number of the whole highway network acquired in real time, is not as accurate as the coefficient of the first class of vehicles, and is accurate to a single toll station, so that the sample expansion calculation is carried out separately.
In one embodiment, step 122 may specifically include: step 1221, step 1222.
Wherein, step 1221: judging whether the behavior of the vehicle entering the expressway network exists in each expressway toll gate according to the topological relation among the expressway network gate equipment, the toll gate and the expressway network and the real-time travel record;
step 1222: if the vehicle number and the vehicle identification rate of each vehicle type entering the expressway network from the toll station in real time are counted according to fixed time intervals by taking the toll station currently monitored by the toll station as a point of reentering the expressway;
and extracting the total number of vehicles of each vehicle type taking each expressway toll station as a starting point, the proportion of the total number of vehicles of each vehicle type to the total number of vehicles of each vehicle type passing through the same expressway toll station and the quantity proportion of vehicles of each vehicle type taking each expressway toll station or investigation point as an end point in a fixed time interval from the initial OD data matrix.
For example, referring to fig. 3, when each vehicle is recorded by the highway gate apparatus for the first time after entering the highway network, the highway toll station closest to the apparatus in the upstream direction of the vehicle is the start point of the vehicle entering the highway network, and the time of entering the highway network in real time is as follows:
Wherein,the time of the j-th train number recorded by the high-definition highway bayonet equipment corresponding to the i-th toll station to appear in the bayonet in real time, i i V is the distance from the ith toll station to the corresponding high definition bayonet device position i And the real-time average speed from the ith toll station to the corresponding high-definition bayonet equipment position interval is obtained.
The method comprises the steps that the positions of sections where vehicles pass through in an expressway network are recorded in real time by a bayonet device, whether a vehicle travel starting point exists in each expressway toll station is judged according to the topological relation of the expressway network, namely if two sections where the vehicles continuously pass through are monitored and can not be directly communicated through the expressway network, the behavior that the vehicles enter the expressway network is indicated in the toll stations, the upstream direction of the bayonet device which is monitored the latest time, the toll station closest to the device is taken as the point where the vehicles enter the expressway network again, and meanwhile, the downstream direction of the bayonet device which is monitored the last time, and the toll station closest to the device are taken as the toll station where the vehicles leave the expressway last time.
According to the fixed time interval, counting the number of each vehicle model entering the expressway network from each expressway toll station in real time in the time interval:
Vehicle identification rate:
GTR＝{gtr i }(i＝1，2，……，k)。
wherein,the number of the y-type vehicles entering the ith toll station in real time for the xth period; GTR (GTR) i And the vehicle identification rate of the ith toll station is real-time entered in a fixed time interval.
Initial OD data matrix T of full-vehicle type inspection point level of current area highway network x,y Extracting the total number of all vehicle types taking each expressway toll station as O point in the same time interval as(i=1, 2, … …, k), wherein,the total number of y-type vehicles taking the ith toll station as an O point in the x-th period and the number proportion of each vehicle type to each D point (taking each expressway toll station or investigation point as an end point) are respectively calculated:
wherein xyid is n+k Representing the point O of the ith toll station in the x-th periodThe proportion of vehicles traveling to the n+k endpoint for the type y vehicle.
The proportion of vehicles of each type taking each highway toll station as a travel starting point (O point) in the time interval to vehicles of each type passing through the same highway toll station is counted in a database P and a database G as follows:
wherein,for the x-th period in the database P and the database G, the y-type vehicles taking the i-th toll station as the travel start point account for the proportion of all the y-type vehicles passing through the i-th toll station.
Further, for the initial OD data matrix T x,y If the O point corresponding to the data is the expressway toll station, the x-th period y-type vehicle takes the common road OD investigation point or the expressway toll station r (r=1, 2, … …, n+k) as the starting point, and the common road OD investigation point or the expressway toll station s as the real-time quantity of the vehicles at the end pointAnd performing sample expansion adjustment calculation of the real-time dynamic OD data matrix according to the following steps:
the real-time number of vehicles taking the expressway toll station as a starting point is estimated by the proportion of the historical data, and then the vehicles can be distributed to all the end points according to the historical proportion, so that the vehicles do not need to wait for the vehicles to finish traveling, the effect of real-time OD prediction is realized, and the instantaneity and the accuracy are improved.
In one embodiment, step 1221 may be followed by specifically including: step 1223.
Wherein, step 1223: if the behavior of the vehicles entering the expressway network does not exist in each expressway toll station, the total number of vehicles passing through each expressway toll station in a fixed time interval and the vehicle identification rate are extracted from the initial OD data matrix.
Illustratively, for the case where the O-point is not a highway toll gate,and performing sample expansion adjustment calculation of the real-time dynamic OD data matrix according to the following steps:
Wherein,for the x-th period counted from the highway vehicle trip survey database G, the number of y-type vehicles entering the r-th toll station in real time, gor r The vehicle identification rate of entering the toll station No. r in the database G is investigated for the travel of the expressway vehicle.
The sample expansion is carried out according to the average ratio of the total number of vehicles counted in real time in the expressway network to the historical data, so that simple real-time OD data prediction can be realized, the sample expansion coefficient is the average number of the whole expressway network collected in real time, and the system such as equipment, communication, calculation and the like similar to a high-definition bayonet is not required to be distributed on a common expressway with huge mileage, so that the cost is saved, and the practicability is improved.
In one embodiment, step 140 may specifically include: step 141, step 142.
Wherein, step 141: setting a travel starting point, a travel ending point, a vehicle type, a starting time and a stopping time as screening conditions, and generating a road network OD data table and an OD data space distribution graph corresponding to the screening conditions; and
step 142: and displaying the initial OD data matrix and the real-time dynamic OD data matrix according to the OD data table and the OD data space distribution graph of the road network.
The visual data query and graphic display are performed on the initial OD data matrix and the road network real-time dynamic OD data matrix, and after the travel start point, the travel end point, the vehicle type, the start time and the end time are set independently as screening conditions for data query, a road network OD data table and an OD data space distribution graph corresponding to the screening conditions are generated.
By providing friendly and convenient road network OD data inquiry and use channels, a data user can call relevant area road OD data history information and real-time information according to factors such as an area, a period, a vehicle type and the like which are concerned by the user, so that the flexibility and coverage of using road network OD data in different levels and different fields are improved. Meanwhile, the visual data table and the data space distribution graph enable the OD data of the regional highway network to be real, sensible and easy to use, and reduce the technical threshold for processing, analyzing and utilizing the OD investigation data of the regional highway network.
Referring to fig. 4, fig. 4 is a system block diagram of a preferred OD data processing method for highway network according to the embodiment of the present application. The contents of the method are explained below.
Preferably, the method can be executed by a highway network real-time dynamic OD data analysis system, and the system can be composed of a common highway traffic on-site observation module, a highway charging information management module, a highway section high-definition bayonet information management module, a real-time OD data analysis deduction module and an OD data visualization management module.
The on-site observation module for the traffic volume of the common highway comprises a high-definition camera, a storage unit, auxiliary power supply equipment and auxiliary lighting equipment, wherein the high-definition camera, the storage unit, the auxiliary power supply equipment and the auxiliary lighting equipment are arranged at n investigation points of OD data of the common highway in a regional highway network and can be used for continuously shooting and recording the bidirectional traffic flow of the road section of the common highway for 24 hours; the expressway charging information management module can extract license plate numbers, vehicle types, expressway entering time, expressway entering toll gate numbers, expressway exiting time, expressway exiting toll gate number information and route information of all vehicles entering an expressway network from an expressway history charging flow database to form an expressway vehicle travel investigation database; the expressway section high-definition bayonet information management module can access information from expressway section high-definition bayonet equipment in real time to acquire license plate number, vehicle type, passing time and vehicle identification rate information of an expressway section. The real-time OD data analysis deduction module can conduct regular regional highway network OD data investigation analysis and real-time dynamic OD data adjustment calculation analysis.
(1) Regular regional highway network OD data survey analysis: analyzing all 24-hour continuous video files obtained from the OD investigation points of the common highway in the OD data investigation region, extracting license plate numbers, vehicle types, photographed time and driving direction information of photographed vehicles by adopting an image recognition technology, and counting the number of the photographed vehicles and vehicle recognition rate information to form a travel investigation database of the common highway vehicles. And (3) taking the license plate number as a retrieval mark, inquiring all the investigation points and expressway toll station information which are passed by the same vehicle in an ordinary expressway vehicle travel investigation database and an expressway vehicle travel investigation database, arranging according to time sequence, judging the vehicle travel OD points, and automatically counting to form an initial OD data matrix of the full-vehicle type investigation point level of the current area highway network.
(2) Real-time dynamic OD data adjustment calculation analysis: and the corresponding relation between the position of the expressway high definition bayonet equipment and the position of the expressway toll gate and the topological relation of the expressway network are built, and the toll gate and the time corresponding to the vehicle entering and exiting the expressway are identified according to the record extracted by the expressway section high definition bayonet information management module in real time. And counting the number of each vehicle model and the vehicle identification rate of each vehicle model entering the expressway network from each expressway toll station in the time interval according to the fixed time interval. According to the two conditions that each expressway toll station is taken as a travel starting point and each expressway toll station is not taken as a travel starting point (only by way), the vehicle travel quantity and the OD data distribution conditions of the two conditions are extracted in the current-situation-area expressway network all-vehicle-type investigation point-level initial OD data matrix in a classified mode, and the real-time dynamic OD data matrix of the area expressway network is generated by classified sample expansion calculation.
Furthermore, the OD data visual management module is responsible for carrying out visual data query and graphic display on the current situation area highway network full-vehicle type investigation point-level initial OD data matrix and the area highway network real-time dynamic OD data matrix.
The method comprises the steps of respectively carrying out road section video information acquisition, expressway charging flow data processing and expressway vehicle real-time operation information processing by using an ordinary highway traffic volume on-site observation module, an expressway charging information management module and an expressway section high-definition bayonet information management module, integrating regular regional highway network OD investigation data, expressway network charging data and expressway network bayonet real-time monitoring data by taking a real-time OD data analysis deduction module as a core, automatically generating a regional highway network full-vehicle type investigation point-level real-time OD data matrix, and realizing on-line inquiry and visual management of a regional highway network real-time dynamic OD data table and a data space distribution graph by an OD data visual management module.
Referring to fig. 5, fig. 5 is a schematic functional block diagram of a highway network OD data processing device according to an embodiment of the present application, where the device may include: a first generation module 210, a second generation module 220, and a screening presentation module 230.
The first generation module 210 is configured to generate an initial OD data matrix based on the common highway network OD field survey data and the highway network charging flow data;
the second generating module 220 is configured to perform sample expansion calculation on the initial OD data matrix based on highway bayonet data, and generate a real-time dynamic OD data matrix;
the screening display module 230 is configured to display the initial OD data matrix and the real-time dynamic OD data matrix based on the vehicle trip information as a screening condition.
Alternatively, the first generation module 210 may be configured to:
processing the on-site survey data of the common road network OD to obtain a travel survey database of the common road vehicles;
processing the highway network charging running water data to obtain a highway vehicle trip investigation database;
searching in the common highway vehicle trip investigation database and the expressway vehicle trip investigation database according to the license plate number of the vehicle, and performing time sequencing according to the search records to obtain a vehicle trip time sequence; and
and counting the vehicle travel time sequence based on the starting and ending point of each travel of the vehicle, and generating the initial OD data matrix.
Alternatively, the first generation module 210 may be configured to:
collecting OD video data continuously shot by a plurality of investigation points of a common highway network;
analyzing the OD video data through an image recognition technology to obtain investigation data of a plurality of vehicles; wherein the survey data comprises: license plate number, vehicle type, photographed time and driving direction; and
and counting the investigation data of the vehicles to obtain the common road vehicle travel investigation database.
Alternatively, the second generating module 220 may be configured to:
based on expressway gate data, acquiring real-time travel records of vehicles passing through each expressway toll gate;
judging whether the behavior of the vehicle entering the expressway network exists in each expressway toll station, and extracting the OD data entering and exiting the toll station from the initial OD data matrix according to a judging result; and
and carrying out classification sample expansion calculation based on the extraction result to generate a real-time dynamic OD data matrix.
Alternatively, the second generating module 220 may be configured to:
judging whether the behavior of the vehicle entering the expressway network exists in each expressway toll gate according to the topological relation among the expressway network gate equipment, the toll gate and the expressway network and the real-time travel record;
If the vehicle number and the vehicle identification rate of each vehicle type entering the expressway network from the toll station in real time are counted according to fixed time intervals by taking the toll station currently monitored by the toll station as a point of reentering the expressway;
and extracting the total number of vehicles of each vehicle type taking each expressway toll station as a starting point, the proportion of the total number of vehicles of each vehicle type to the total number of vehicles of each vehicle type passing through the same expressway toll station and the quantity proportion of vehicles of each vehicle type taking each expressway toll station or investigation point as an end point in the fixed time interval from the initial OD data matrix.
Alternatively, the second generating module 220 may be configured to:
and if the behavior of the vehicles entering the expressway network does not exist in each expressway toll station, extracting the total number of vehicles and the vehicle identification rate of each vehicle type passing through each expressway toll station in the fixed time interval from the initial OD data matrix.
Optionally, the screening presentation module 230 may be configured to:
setting a travel starting point, a travel ending point, a vehicle type, a starting time and a stopping time as screening conditions, and generating a road network OD data table and an OD data space distribution graph corresponding to the screening conditions; and
And displaying the initial OD data matrix and the real-time dynamic OD data matrix according to the OD data table and the OD data space distribution graph of the highway network.
Referring to fig. 6, fig. 6 is a block schematic diagram of an electronic device. The electronic device 300 may include a memory 311, a memory controller 312, a processor 313, a peripheral interface 314, an input output unit 315, a display unit 316. It will be appreciated by those of ordinary skill in the art that the configuration shown in fig. 6 is merely illustrative and is not limiting of the configuration of the electronic device 300. For example, electronic device 300 may also include more or fewer components than shown in FIG. 6, or have a different configuration than shown in FIG. 6.
The above-mentioned memory 311, memory controller 312, processor 313, peripheral interface 314, input/output unit 315, and display unit 316 are electrically connected directly or indirectly to each other to realize data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The processor 313 is used to execute executable modules stored in the memory.
The Memory 311 may be, but is not limited to, a random access Memory (Random Access Memory, RAM), a Read Only Memory (ROM), a programmable Read Only Memory (Programmable Read-Only Memory, PROM), an erasable Read Only Memory (Erasable Programmable Read-Only Memory, EPROM), an electrically erasable Read Only Memory (Electric Erasable Programmable Read-Only Memory, EEPROM), etc. The memory 311 is configured to store a program, and the processor 313 executes the program after receiving an execution instruction, and a method executed by the electronic device 300 defined by the process disclosed in any embodiment of the present application may be applied to the processor 313 or implemented by the processor 313.
The processor 313 may be an integrated circuit chip having signal processing capabilities. The processor 313 may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; but also digital signal processors (digital signal processor, DSP for short), application specific integrated circuits (Application Specific Integrated Circuit, ASIC for short), field Programmable Gate Arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The peripheral interface 314 couples various input/output devices to the processor 313 and the memory 311. In some embodiments, the peripheral interface 314, the processor 313, and the memory controller 312 may be implemented in a single chip. In other examples, they may be implemented by separate chips.
The input/output unit 315 is used for providing input data to a user. The input/output unit 315 may be, but is not limited to, a mouse, a keyboard, and the like.
The display unit 316 provides an interactive interface (e.g., a user interface) between the electronic device 300 and a user for reference. In this embodiment, the display unit 316 may be a liquid crystal display or a touch display. The liquid crystal display or the touch display may display a process of executing the program by the processor.
The electronic device 300 in the present embodiment may be used to perform each step in each method provided in the embodiments of the present application.
Furthermore, the embodiments of the present application also provide a computer readable storage medium, on which a computer program is stored, which when being executed by a processor performs the steps in the above-described method embodiments.
The computer program product of the above method provided in the embodiments of the present application includes a computer readable storage medium storing a program code, where instructions included in the program code may be used to perform steps in the above method embodiment, and specifically, reference may be made to the above method embodiment, which is not described herein.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, and the division of the modules is merely a logical function division, and there may be additional divisions when actually implemented, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form. The functional modules in the embodiments of the present application may be integrated together to form a single part, or each module may exist alone, or two or more modules may be integrated to form a single part.
It should be noted that the functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM) random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The foregoing is merely exemplary embodiments of the present application and is not intended to limit the scope of the present application, and various modifications and variations may be suggested to one skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.
Claims (7)
1. A highway network OD data processing method, the method comprising:
generating an initial OD data matrix based on the on-site OD investigation data of the common highway network and the charging flow data of the highway network;
based on expressway bayonet data, performing sample expansion calculation on the initial OD data matrix to generate a real-time dynamic OD data matrix; and
based on the vehicle travel information as a screening condition, displaying the initial OD data matrix and the real-time dynamic OD data matrix;
the method for generating the real-time dynamic OD data matrix based on the expressway bayonet data comprises the steps of:
calculating real-time travel records of vehicles passing through each expressway toll gate based on expressway gate data; judging whether the behavior of the vehicle entering the expressway network exists in each expressway toll station, and extracting the OD data entering and exiting the toll station from the initial OD data matrix according to a judging result; performing classification sample expansion calculation based on the extraction result to generate a real-time dynamic OD data matrix;
Judging whether the behavior of the vehicle entering the expressway network exists in each expressway toll station, and extracting the OD data entering and exiting the toll station from the initial OD data matrix according to the judging result, wherein the method comprises the following steps: judging whether the behavior of the vehicle entering the expressway network exists in each expressway toll gate according to the topological relation among the expressway network gate equipment, the toll gate and the expressway network and the real-time travel record; if the vehicle number and the vehicle identification rate of each vehicle type entering the expressway network from the toll station in real time are counted according to fixed time intervals by taking the toll station which is currently and correspondingly monitored by the toll station as a point of reentering the expressway; extracting the total number of vehicles of each vehicle type taking each expressway toll station as a single trip starting point, the proportion of the total number of vehicles of each vehicle type accounting for the total number of vehicles of each vehicle type passing through the same expressway toll station and the quantity proportion of vehicles of each vehicle type taking each expressway toll station or investigation point as an end point in the fixed time interval from the initial OD data matrix;
after judging whether the behavior of the vehicle entering the expressway network exists in each expressway toll gate according to the topological relation among the expressway network gate equipment, the toll gate and the expressway network, the method further comprises the following steps: and if the behavior of the vehicles entering the expressway network does not exist in each expressway toll station, extracting the total number of vehicles and the vehicle identification rate of each vehicle type passing through each expressway toll station in the fixed time interval from the initial OD data matrix.
2. The method of claim 1, wherein generating the initial OD data matrix based on the common highway network site OD survey data and highway network toll flow data comprises:
processing the on-site OD investigation data of the common highway network to obtain a travel investigation database of the common highway vehicles;
processing the highway network charging running water data to obtain a highway vehicle trip investigation database;
searching in the common highway vehicle trip investigation database and the expressway vehicle trip investigation database according to the license plate number of the vehicle, and performing time sequencing according to the search records to obtain a vehicle trip time sequence; and
and counting the vehicle travel time sequence based on the starting and ending point of each travel of the vehicle, and generating the initial OD data matrix.
3. The method according to claim 2, wherein the processing the on-site OD survey data of the common road network to obtain the common road vehicle trip survey database comprises:
collecting OD video data continuously shot by a plurality of investigation points of a common highway network;
analyzing the OD video data through an image recognition technology to obtain investigation data of a plurality of vehicles; wherein the survey data comprises: license plate number, vehicle type, photographed time and driving direction; and
And counting the investigation data of the vehicles to obtain the common road vehicle travel investigation database.
4. The method of claim 1, wherein the presenting the initial OD data matrix and the real-time dynamic OD data matrix based on the vehicle trip information as a screening condition comprises:
setting a travel starting point, a travel ending point, a vehicle type, a starting time and a stopping time as screening conditions, and generating a road network OD data table and an OD data space distribution graph corresponding to the screening conditions; and
and displaying the initial OD data matrix and the real-time dynamic OD data matrix according to the OD data table and the OD data space distribution graph of the highway network.
5. A highway network OD data processing device, the device comprising:
the first generation module is used for generating an initial OD data matrix based on-site OD investigation data of the common highway network and charging flow data of the highway network;
the second generation module is used for carrying out sample expansion calculation on the initial OD data matrix based on expressway bayonet data to generate a real-time dynamic OD data matrix; the second generating module is specifically configured to: calculating real-time travel records of vehicles passing through each expressway toll gate based on expressway gate data; judging whether the behavior of the vehicle entering the expressway network exists in each expressway toll station, and extracting the OD data entering and exiting the toll station from the initial OD data matrix according to a judging result; performing classification sample expansion calculation based on the extraction result to generate a real-time dynamic OD data matrix; judging whether the behavior of the vehicle entering the expressway network exists in each expressway toll station, and extracting the OD data entering and exiting the toll station from the initial OD data matrix according to the judging result, wherein the method comprises the following steps: judging whether the behavior of the vehicle entering the expressway network exists in each expressway toll gate according to the topological relation among the expressway network gate equipment, the toll gate and the expressway network and the real-time travel record; if the vehicle number and the vehicle identification rate of each vehicle type entering the expressway network from the toll station in real time are counted according to fixed time intervals by taking the toll station which is currently and correspondingly monitored by the toll station as a point of reentering the expressway; extracting the total number of vehicles of each vehicle type taking each expressway toll station as a single trip starting point, the proportion of the total number of vehicles of each vehicle type accounting for the total number of vehicles of each vehicle type passing through the same expressway toll station and the quantity proportion of vehicles of each vehicle type taking each expressway toll station or investigation point as an end point in the fixed time interval from the initial OD data matrix; after judging whether the behavior of the vehicle entering the expressway network exists in each expressway toll gate according to the topological relation among the expressway network gate equipment, the toll gate and the expressway network, the method further comprises the following steps: if the behavior of the vehicles entering the expressway network does not exist in each expressway toll station, extracting the total number of vehicles and the vehicle identification rate of each vehicle type passing through each expressway toll station in the fixed time interval from the initial OD data matrix; and
And the screening display module is used for displaying the initial OD data matrix and the real-time dynamic OD data matrix based on the vehicle trip information as a screening condition.
6. An electronic device, comprising: a processor, a memory storing machine-readable instructions executable by the processor, which when executed by the processor perform the steps of the method of any of claims 1 to 4 when the electronic device is run.
7. A computer-readable storage medium, characterized in that it has stored thereon a computer program which, when executed by a processor, performs the steps of the method according to any of claims 1 to 4.
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