CN113823081A - Space positioning method based on commercial vehicle travel starting and ending point - Google Patents
Space positioning method based on commercial vehicle travel starting and ending point Download PDFInfo
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- G—PHYSICS
- G08—SIGNALLING
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- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
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- H—ELECTRICITY
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- H04W4/02—Services making use of location information
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W4/42—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for mass transport vehicles, e.g. buses, trains or aircraft
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/02—Hierarchically pre-organised networks, e.g. paging networks, cellular networks, WLAN [Wireless Local Area Network] or WLL [Wireless Local Loop]
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Abstract
The invention discloses a space positioning method based on a commercial vehicle travel starting and ending point, which comprises the steps of obtaining vehicle networking data reported by a vehicle; judging the starting point and the ending point of the positioning stroke; positioning a starting and ending point city; and (4) screening and merging data. The invention has the beneficial effects that: compared with railway transportation, the commercial vehicle can realize point-to-point direct transportation and reflect the inter-city contact better. While railway transportation is completely dependent on whether there is a railway connection, it is difficult, if not impossible, to count the flow of goods. The starting and ending point of the commercial vehicle travel is defined, then the city where the starting and ending point is located is found through space positioning, traffic flow direction data among different cities can be obtained, the relation between 'cargo flow' and 'economy' among cities is further analyzed, and the method has a wide application prospect.
Description
Technical Field
The invention relates to a method for positioning a starting point and a finishing point of a commercial vehicle travel, in particular to a method for identifying the flow and the space positioning of a commercial vehicle based on vehicle networking big data, and belongs to the field of economic index research.
Background
Cities are mobile, varying, and governed by some laws. The big data can help us to observe the fineness of the city block and look down the macro of the city system. When we try to evaluate the economic traffic between cities, or inside or outside the city group, or between regions, we need to calculate and evaluate "flow" data that can represent the economic traffic. While "flow" data is lacking in China.
More than 70% of freight in China is transported by trucks, namely commercial vehicles, and more than 3000 tens of thousands of trucks connect cities and areas together, so that the traffic flow big data of the commercial vehicles is one of the best data for capturing the connection between the cities and the areas.
Disclosure of Invention
The invention aims to provide a space positioning method based on a commercial vehicle travel starting and ending point, aiming at solving the problems.
The invention realizes the purpose through the following technical scheme: a space positioning method based on a commercial vehicle travel starting and ending point comprises the following steps:
(1) acquiring Internet of vehicles data reported by vehicles;
(2) judging the starting point and the ending point of the positioning stroke;
(3) positioning a starting and ending point city;
(4) screening and merging data;
as a further scheme of the invention: the Internet of vehicles data comprises:
for providing service better and faster, the system does not need detailed satellite positioning data, and only needs to provide necessary data, wherein the necessary data comprises a vehicle license plate number, a vehicle identification code/vehicle frame number, longitude, latitude and time.
As a further scheme of the invention: the feature data obtained according to the reported data includes:
according to the time reported by the Internet of vehicles data, the travel data of the vehicle lasting for one year is obtained, the obtained satellite positioning data is analyzed, and the satellite positioning time and the satellite positioning longitude and latitude of the data point are mainly analyzed.
As a further scheme of the invention: the step of extracting the event features comprises the following steps:
the extraction of the event characteristics refers to the fact that a commercial vehicle extracts the characteristics capable of representing the driving behavior of the vehicle from satellite positioning data of continuous year at least. The behavior event characteristics include: travel mark, travel start point, travel end point and characteristics of the start and end city of location.
As a further scheme of the invention: the data processing step of identifying spatial localization comprises:
based on the satellite positioning data, the processing step includes:
according to the satellite positioning data, the journey of ' duration) <20 (minutes) × 60 × 1000 ', the journey of ' distance (500 meters) and other unnecessary indexes are deleted, the starting and ending points of all the large journeys are defined, the samples of the same city are deleted, only the samples across the city are reserved, and the samples of the same city are merged.
The invention has the beneficial effects that: the space positioning method based on the commercial vehicle travel starting and ending point is reasonable in design, and compared with railway transportation, the commercial vehicle can be directly transported from point to point, and the city relation is reflected. While railway transportation is completely dependent on whether there is a railway connection, it is difficult, if not impossible, to count the flow of goods. The starting and ending point of the commercial vehicle travel is defined, then the city where the starting and ending point is located is found through space positioning, traffic flow direction data among different cities can be obtained, the relation between 'cargo flow' and 'economy' among cities is further analyzed, and the method has a wide application prospect.
Drawings
FIG. 1 is a schematic flow diagram of the present invention;
FIG. 2 is a diagram of the correlation between city traffic flow and city GDP;
FIG. 3 is a graph comparing national traffic flow in 2020 with traffic flow in 2019;
FIG. 4 is a contact diagram of traffic flow between cities across the country;
FIG. 5 is a layout view of a heavy truck on a truck bed of the transportation department;
FIG. 6 is a national license plate distribution map;
FIG. 7 is a Chinese truck driver distribution plot;
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
Referring to fig. 1, a space positioning method based on a commercial vehicle travel starting and ending point includes the following steps:
(1) acquiring Internet of vehicles data reported by vehicles;
(2) judging the starting point and the ending point of the positioning stroke;
(3) positioning a starting and ending point city;
(4) screening and merging data;
further, in an embodiment of the present invention, the car networking data includes:
for providing service better and faster, the system does not need detailed satellite positioning data, and only needs to provide necessary data, wherein the necessary data comprises a vehicle license plate number, a vehicle identification code/vehicle frame number, longitude, latitude and time.
Further, in the embodiment of the present invention, the feature data obtained according to the reported data includes:
according to the time reported by the Internet of vehicles data, the travel data of the vehicle lasting for one year is obtained, the obtained satellite positioning data is analyzed, and the satellite positioning time and the satellite positioning longitude and latitude of the data point are mainly analyzed.
Further, in an embodiment of the present invention, the step of extracting the event feature includes:
the extraction of the event characteristics refers to the fact that a commercial vehicle extracts the characteristics capable of representing the driving behavior of the vehicle from satellite positioning data of continuous year at least. The behavior event characteristics include: travel mark, travel start point, travel end point and characteristics of the start and end city of location.
Further, in the embodiment of the present invention, the data processing step of identifying spatial localization includes:
based on the satellite positioning data, the processing step includes:
according to the satellite positioning data, the journey of ' duration) <20 (minutes) × 60 × 1000 ', the journey of ' distance (500 meters) and other unnecessary indexes are deleted, the starting and ending points of all the large journeys are defined, the samples of the same city are deleted, only the samples across the city are reserved, and the samples of the same city are merged.
Example two
Referring to fig. 2 to 7, a method for spatially positioning a commercial vehicle based on a starting point and a finishing point of a travel includes the following steps:
the method comprises the following steps: positioning starting and ending point
1. Using a big data framework, calling a Scale or Java program to calculate and filter data:
1.1, removing vehicles of passenger cars and dangerous goods types, and storing a vehicle list;
1.2 delete duplicate value trimid (trimid only guarantees uid + startTime not duplicate)
Deleting strokes of "duration" <20 (minutes) × 60 × 1000 ";
deleting a journey of 'distance (running distance) < ═ 500 m';
1.3 deleting unnecessary indexes, and finally keeping indexes: uid, trim, starttime, startlon startlat, endlon, endlat, duration, distance (license plate number, trip number, start time, start longitude, start latitude, end longitude, end latitude, travel time, travel distance);
2. defining a true starting point for a vehicle
2.1 calculate data for one year
Note:
(1) if short-time strokes are put together, such as one month, because many strokes are half a month or even nearly one month long, many strokes at the end of the month are ignored, and finally, the condition that the stroke is more at the beginning of each month and the stroke is less at the end of each month occurs;
(2) if too long strokes are put together for calculation, a plurality of vehicles can change areas for business, quit the business industry and newly join the business industry during the calculation period, although the proportion is not high, certain errors can be caused;
2.2 the starting point of the travel data is taken for clustering analysis, a Geohash algorithm is adopted, and the size of the grid is selected from 5km by 5 km. And selecting the grid with the largest number in the grids, and taking the coordinate of the middle value of the grid as the starting point coordinate. All starting points within the range of radius 3.5km calculate the real starting point of the vehicle by taking the coordinate as the center;
note: there is no screening data because trucks rarely stop frequently in a fixed service area or transfer station, and the number of stops even exceeds the city where the origin is located.
3. Defining a large trip end point
3.1 in all the strokes, the stroke between the real starting points is defined as a large stroke;
3.2, recording the longitude and latitude of a stroke end point of all strokes which are farthest from the real starting point in the large stroke as a real terminal point of the large stroke;
step two: positioning start-end city, and performing batch calculation by using ArcGIS10.2 spatial database model
1. Positioning starting point city
1.1 converting data;
1.2 drawing a diagram of the starting point;
1.3, carrying out 'spatial connection' on the graph of the starting point and the base graph, and matching the county, the city and the province where the starting point is located;
2. positioning terminal city
2.1 exporting the data file;
2.2 plot the endpoint;
2.3, carrying out 'spatial connection' on the graph of the terminal point and the base graph, and matching out the county, the city and the province where the terminal point is located;
2.4 outputting a result data file;
step three: screening and merging of data
1. Deleting samples of the same city at the starting point and the ending point, and only keeping samples across cities;
2. combining the samples of the same start and end point cities, and calculating the traffic flow between the two cities;
step four: data verification
Checking one:
because the commercial vehicles represent the logistics connection between cities, and the large data quantity of the traffic flow is large, the traffic flow of the commercial vehicles can well correspond to the economy on the city level or the national level. From the results, on the urban level, the urban summed traffic flow can well correspond to the urban GDP, and the result R of univariate fitting2The total traffic flow can reach 0.63, namely the change of the total traffic flow among cities can explain the change of GDP of 63% of cities, and the fitting effect is very good;
checking two,
Because the commercial vehicles represent the logistics connection between cities, the good correspondence between the traffic flow of the commercial vehicles and the economic connection between the cities can be seen not only on the summation level but also on the connection between the cities. However, the 'stream' data of the economic connection between cities is very lack, direct verification cannot be carried out, and only indirect verification can be carried out.
Images presented on the map after urban level summing. This connection is very similar to the connection between cities represented by a city group, and a place different from intuition is that the traffic flow is more in north China. Through analysis, the phenomenon is found to be highly consistent with the distribution of heavy trucks displayed by a truck platform of a transportation department, license plates, namely the distribution of commercial vehicles at home, and the distribution of truck drivers. Meanwhile, heavy trucks are also used for transporting bulk commodities such as coal and the like in large quantities, and the traffic flow calculated by the method is also consistent with the distribution of coal and petroleum in China. Therefore, the traffic flow is more in north China, and the positioning method can be more effective.
The working principle is as follows: when the space positioning method based on the commercial vehicle journey starting and ending point is used, the economic communication density between cities is defined by calculating the number of truck flows between the cities, the method can be expanded to between provinces and between county-level cities and county-level cities, and only the level of the positioned cities needs to be switched.
The starting point and the ending point of each trip of the commercial vehicle are firstly determined, and then the economic traffic density between two cities is defined by the sum of the number of the trips between the two cities (namely the number of traffic), wherein the more the number of the traffic represents the more frequent the economic traffic. The starting point and the ending point of the journey are defined as the starting point and the ending point of one round trip in the economic activity sense, but not the starting point and the ending point of vehicle attribution (such as a license plate), driving and stopping (such as short stop) and the like. Through screening, points of short-time economic activities such as short-time stay, service area stay and the like can be eliminated, and then the area with the most times and the most dense is selected as a starting point. Meanwhile, starting from a starting point and then returning to the starting point are taken as a large stroke. And the location of the stopping point farthest from the starting point in a large journey is defined as the end point. The method is more accurate by ArcGIS journey analysis, and the city where the point farthest away from the starting point is located is taken as the end point.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.
Claims (5)
1. A space positioning method based on a commercial vehicle travel starting and ending point is characterized by comprising the following steps:
(1) acquiring Internet of vehicles data reported by vehicles;
(2) judging the starting point and the ending point of the positioning stroke;
(3) positioning a starting and ending point city;
(4) and (4) screening and merging data.
2. The commercial vehicle travel starting and ending point-based spatial positioning method according to claim 1, characterized in that: the Internet of vehicles data comprises:
in order to provide service more quickly, only necessary data need to be provided, wherein the necessary data includes license plate number, journey number, starting time, starting point longitude, starting point latitude, ending point longitude and ending point latitude.
3. The method for positioning the starting point and the ending point of a commercial vehicle according to claim 1, characterized in that: the feature data obtained according to the reported data includes:
according to the time reported by the Internet of vehicles data, the travel data of the vehicle lasting for one year is obtained, the obtained satellite positioning data is analyzed, and the satellite positioning time and the satellite positioning longitude and latitude of the data point are mainly analyzed.
4. The method for positioning the starting point and the ending point of a commercial vehicle according to claim 1, characterized in that: the step of extracting the event features comprises the following steps:
the extraction of the event characteristics refers to the fact that a commercial vehicle extracts the characteristics capable of representing the driving behavior of the vehicle from satellite positioning data of continuous year at least. The behavior event characteristics include: the characteristics of the travel mark, the large travel starting point, the large travel end point and the start and end city positioning city.
5. The method of claim 1, wherein the step of processing the data identifying the spatial location comprises:
according to the satellite positioning data, the journey of ' duration) <20 (minutes) × 60 × 1000 ', the journey of ' distance (500 meters) and other unnecessary indexes are deleted, the starting and ending points of all the large journeys are defined, the samples of the same city are deleted, only the samples across the city are reserved, and the samples of the same city are merged.
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2021
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