CN112487309A - Uncertain medical reachability calculation method based on trajectory data - Google Patents

Uncertain medical reachability calculation method based on trajectory data Download PDF

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CN112487309A
CN112487309A CN202011138071.XA CN202011138071A CN112487309A CN 112487309 A CN112487309 A CN 112487309A CN 202011138071 A CN202011138071 A CN 202011138071A CN 112487309 A CN112487309 A CN 112487309A
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track
time
medical
grid
formula
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吕莹
董鲁祺
孙会君
吴建军
支丹月
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Beijing Jiaotong University
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
    • 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
    • G08G1/0125—Traffic data processing
    • G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
    • 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

Abstract

The invention relates to an uncertain medical reachability calculation method based on trajectory data, which specifically comprises the following steps: step 1, data acquisition and pretreatment; step 2, spatial processing and grid generation; step 3, extracting historical travel time; step 4, constructing an OD matrix; step 5, calculating the trip completion probability; step 6, calculating the accessibility under the reliability constraint; the method provided by the invention has the following advantages: (1) medical accessibility which is more in line with the actual situation is obtained; (2) the model is simple, easy to understand and calculate, and strong in application; (3) compared to a square, a hexagon has fewer adjacent patterns, smaller side-to-area ratio; meanwhile, the method has isotropic geometric properties, and can reduce errors in reachability calculation.

Description

Uncertain medical reachability calculation method based on trajectory data
Technical Field
The invention belongs to the technical field of geographic information technology and the like, and relates to an uncertain medical reachability measurement method based on floating car track data.
Background
Reachability is a basic concept in traffic geography and urban planning, and has been widely applied to traffic evaluation and facility location. And the medical accessibility is an important index for measuring the construction of medical infrastructure and plays an important role in policy making. Common spatial reachability metric models include: the system comprises a gravity model, a two-step mobile search model, an accumulative chance model, a space-time constraint model and a space obstruction model. The accumulative opportunity model mainly studies the difficulty degree of the nodes approaching the opportunity. The number of all opportunities that are contacted within the threshold range is defined as the reachability of a particular node by a given threshold. The accumulative chance model has better interpretability and simple and convenient calculation, and is widely applied to reachability research.
With the development and popularization of network communication technology, vehicle-mounted positioning navigation and satellite remote sensing technology, it becomes easier to acquire massive space-time trajectory data. The use of trajectory data for reachability research is becoming a new trend in reachability research. In a large and medium-sized city crowded in China, due to frequent occurrence of random phenomena such as traffic jam and the like, uncertainty exists in travel time of trips between the same ODs. Previous studies have generally used a fixed time threshold to measure the reachability of a certain place, ignoring the influence of uncertainty of travel time on the reachability. Introducing reliability constraints in the conventional reachability model can result in more accurate reachability results.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a method for calculating uncertain medical reachability based on trajectory data, which comprises the following steps: reliability constraint is introduced into a traditional reachability model by calculating a trip completion probability, and reachability calculation is popularized from certainty to uncertainty. The method can obtain the space accessibility which is more consistent with the real situation.
The purpose of the invention is realized by the following technical scheme:
an uncertain medical accessibility calculation method based on track data, which considers the reliability of travel time, comprises the following steps:
step 1, data acquisition and pretreatment;
first, the medical facility POI data is crawled by using an API (application program interface) provided by an Internet map company; the original track data is often a GB-level large file and contains data information of 1 week or even several weeks, so that the file needs to be extracted by taking day/hour as a unit as required;
then, abnormal information generated by architectural shading and GPS signal loss is eliminated, and the time field is standardized. Meanwhile, by taking the track as a unit, calculating the time difference between adjacent track points, the time difference between the track point and the starting point, the running distance and the average speed of the track, and finishing the preprocessing of track data; the time difference between the track point and the starting point is the travel time.
Step 2, spatial processing and grid generation;
in ArcGIS, setting a geographical coordinate system and a spatial projection of a newly-built data frame, adding an administrative division diagram and a main urban road of a research area, and dividing the research area into a plurality of hexagonal grids with determined side lengths by utilizing a Thiessen Polygon tool box;
and (3) adding the track data processed in the step (1), and spatially connecting the hexagonal grids with the track data according to positions.
Adding medical facility POI and connecting with the hexagonal grids in space, setting the weights of different types of medical facilities by referring to the number of beds of the medical facilities, and calculating to obtain the score of the medical facilities of each grid to obtain a formula (1):
let GjIs the medical facility score of the grid j,
Figure BDA0002737390670000034
the weight of facility h in grid j is:
Figure BDA0002737390670000031
wherein s is the total number of medical facilities in the lattice j;
step 3, extracting historical travel time;
on the basis of the track data obtained by processing in the step 2, extracting all OD trips on each track, which are expressed as (i, j), and assuming that the track tau is composed of k track points, QτFormula (2) is obtained by representing a set of lattice numbers through which the track τ passes, and m represents the number of lattices through which the track τ passes:
Figure BDA0002737390670000032
in the formula (I), the compound is shown in the specification,
Figure BDA0002737390670000035
the number of the OD pairs contained in the track is
Figure BDA0002737390670000033
t1，t2，t3，…，tk-1，tkRepresenting the dotting time of track points 1, 2, 3, …, k-1, k;
let the number of trace points of the trace τ in the grid i be niTo obtain formula (3):
Figure BDA0002737390670000041
then
Figure BDA0002737390670000044
The starting time of the grid i is represented, and the value of the starting time is the dotting time of the last point of the track tau in the grid i;
thus, the time of flight between the grids (i, j) is denoted as Tdj-TdiAnd Tdj-Tdi＞0；
Step 4, constructing an OD matrix;
on the basis of the step 3, travel time of the same OD is combined to obtain a historical travel time matrix of the travel of the OD:
ODij＝{Tdj-Tdi|i＝0，1，2…，1101，j＝0，1，2，…，1101，i≠j} (4)
wherein, ODijFor the set of historical travel times between ij, 0, 1, 2 …, 1101 is the hexagonal grid number;
step 5, calculating the trip completion probability;
assuming that the travel time follows normal distribution, the trip completion probability is shown as formula (5):
Figure BDA0002737390670000042
in the formula, CDFij(T) is a cumulative distribution function of travel times between ij, ijσis the sample standard deviation of the travel time between ij, ijμis the sample mean of the travel times between ij;
step 6, calculating the accessibility under the reliability constraint;
the cumulative chance model is expressed as shown in equation (6):
Figure BDA0002737390670000043
in the formula, CUMiThe spatial accessibility for the trellis i does not take reliability into account,
Figure BDA0002737390670000056
the number of opportunities for a trellis is a variable from 0 to 1, as the time of flight Td between the trellis (i, j)j-TdiWhen the time is less than or equal to the set time threshold T,
Figure BDA0002737390670000051
otherwise
Figure BDA0002737390670000052
Introducing a reliability constraint in (6), then obtaining (7):
Figure BDA0002737390670000053
in the formula, PCUMi(T，r0) The requirement for reliability is r0The time threshold is the reachability at T,
Figure BDA0002737390670000057
the number of opportunities of the trellis is 0 or 1, when the travel time between (i, j)
Figure BDA0002737390670000058
When the time is less than or equal to the time threshold T,
Figure BDA0002737390670000054
the resident at i gets the chance to get the j cell, otherwise,
Figure BDA0002737390670000055
under the time threshold and reliability constraints, the total number of opportunities that the residents can obtain is the reachability of the grid i.
On the basis of the scheme, the internet map company in the step 1 comprises a Baidu map and a Gagde map.
On the basis of the scheme, the side length in the step 2 is 500 m.
On the basis of the scheme, the different types of medical facilities in the step 2 are as follows: primary hospitals, secondary hospitals and tertiary hospitals;
the invention has the beneficial effects that:
the invention provides a method for calculating medical accessibility, which utilizes track data and considers the influence of uncertain travel time and has the following advantages:
(1) the medical accessibility which is more in accordance with the actual situation can be obtained;
(2) the model is simple, easy to understand and calculate, and strong in application;
(3) compared to a square, a hexagon has fewer adjacent patterns, smaller side-to-area ratio; meanwhile, the method has isotropic geometric properties, and can reduce errors in reachability calculation.
Drawings
The invention has the following drawings:
FIG. 1 is a flow chart of a calculation method of the present invention.
Fig. 2 is a schematic view of a medical facility distribution.
FIG. 3 is a schematic diagram of the study area and grid division.
Fig. 4 is a schematic diagram of a medical score distribution.
Fig. 5 is a schematic diagram of the spatial distribution of medical reachability with reliability requirement of 0.1.
Fig. 6 is a schematic diagram of the spatial distribution of medical reachability with reliability requirement of 0.5.
Fig. 7 is a schematic diagram of the spatial distribution of medical reachability with reliability requirement of 0.9.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings 1 to 7, but is not limited thereto.
The invention provides a method for calculating medical accessibility by using track data, and a mathematical model is established.
The existing track data is the track data of the Gaode floating car in 2015 and 9 months, and the data field comprises acquisition time, a car number, an instantaneous speed, longitude and latitude and a road number; in the processing process, 2015.9.1-2015.9.7 data are extracted, track points with abnormal longitude and latitude fields are removed, time difference between adjacent track points, time difference (namely travel time) between a track point and a starting point, travel distance and average speed of the track are calculated by taking the track as a unit, and the data are stored by taking hours as a unit. Through API interface provided by Gaode, 2248 pieces of medical facility data of Beijing city are crawled, and the fields comprise: name, address, longitude, latitude, category. Then, the medical facilities are classified into three types, i.e., a third-level hospital, a second-level hospital and a first-level hospital according to medical resources, and the distribution of the medical facilities in each type is shown in fig. 2:
within the five rings of Beijing city is selected as a research area, and the research area is divided into 1102 hexagonal grids with the side length of 500m (as shown in FIG. 3).
Statistical analysis was performed on different categories of hospital information, with the results shown in the following table:
TABLE 1 medical facility information
Figure BDA0002737390670000071
The medical score for each grid can be obtained according to equation (1), as shown in fig. 4;
and setting the time threshold value to be 30min, and calculating to obtain medical reachability results under different reliability requirements.
As shown in fig. 5 to 7, fig. 5 is a schematic diagram of the spatial distribution of medical reachability with reliability requirement of 0.1, fig. 6 is a schematic diagram of the spatial distribution of medical reachability with reliability requirement of 0.5, and fig. 7 is a schematic diagram of the spatial distribution of medical reachability with reliability requirement of 0.9.
It can be seen that: the spatial distribution of medical accessibility has significant differences under different reliability constraints. As reliability requirements increase, medical accessibility shows a decreasing trend; while the central urban area has relatively high medical accessibility.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes will occur to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Those not described in detail in this specification are within the skill of the art.

Claims (4)

1. An uncertain medical reachability calculation method based on trajectory data is characterized by comprising the following steps:
step 1, data acquisition and pretreatment;
first, the medical facility POI data is crawled by using an API (application program interface) provided by an Internet map company;
then, eliminating abnormal information generated by building shielding and GPS signal loss, and carrying out standardized processing on the time field; meanwhile, calculating the time difference between adjacent track points, the time difference between the track point and the starting point, the running distance and the average speed of the track by taking the track as a unit to finish the preprocessing work of track data, wherein the time difference between the track point and the starting point is the travel time;
step 2, spatial processing and grid generation;
in ArcGIS, setting a geographical coordinate system and a spatial projection of a newly-built data frame, adding an administrative division diagram and a main urban road of a research area, and dividing the research area into a plurality of hexagonal grids with determined side lengths by utilizing a Thiessen Polygon tool box;
adding the track data processed in the step 1, and spatially connecting the hexagonal grids with the track data according to positions;
adding medical facility POI and connecting with the hexagonal grids in space, setting the weights of different types of medical facilities by referring to the number of beds of the medical facilities, and calculating to obtain the score of the medical facilities of each grid to obtain a formula (1):
let GjIs the medical facility score of the grid j,
Figure FDA0002737390660000011
the weight of facility h in grid j is:
Figure FDA0002737390660000021
wherein s is the total number of medical facilities in the lattice j;
step 3, extracting historical travel time;
on the basis of the track data obtained by processing in the step 2, extracting all OD trips on each track, which are expressed as (i, j), and assuming that the track tau is composed of k track points, QτIndicating railA set of lattice numbers through which the track τ passes, and m represents the number of lattices through which the track τ passes, to obtain formula (2):
Figure FDA0002737390660000022
in the formula (I), the compound is shown in the specification,
Figure FDA0002737390660000023
the number of the OD pairs contained in the track is
Figure FDA0002737390660000024
t1，t2，t3，…，tk-1，tkRepresenting the dotting time of track points 1, 2, 3, …, k-1, k;
let the number of trace points of the trace τ in the grid i be niTo obtain formula (3):
Figure FDA0002737390660000025
then
Figure FDA0002737390660000026
The starting time of the grid i is represented, and the value of the starting time is the dotting time of the last point of the track tau in the grid i;
thus, the time of flight between the grids (i, j) is denoted as Tdj-TdiAnd Tdj-Tdi＞0；
Step 4, constructing an OD matrix;
on the basis of the step 3, travel time of the same OD is combined to obtain a historical travel time matrix of the travel of the OD:
ODij＝{Tdj-Tdi|i＝0，1，2…，1101，j＝0.1.2，…，1101，i≠j} (4)
wherein oDijAs calendars between ijHistory travel time set, 0, 1, 2 …, 1101 is hexagonal grid number;
step 5, calculating the trip completion probability;
assuming that the travel time follows normal distribution, the trip completion probability is shown as formula (5):
Figure FDA0002737390660000031
in the formula, CDFij(T) is the cumulative distribution function σ of travel time between ijsijIs the sample standard deviation of the travel time between ij, muijIs the sample mean of the travel times between ij;
step 6, calculating the accessibility under the reliability constraint;
the cumulative chance model is expressed as shown in equation (6):
Figure FDA0002737390660000032
in the formula, CUMiThe spatial accessibility for the trellis i does not take reliability into account,
Figure FDA0002737390660000033
the number of opportunities for a trellis is a variable from 0 to 1, as the time of flight Td between the trellis (i, j)j-TdiWhen the time is less than or equal to the set time threshold T,
Figure FDA0002737390660000034
otherwise
Figure FDA0002737390660000035
Introducing a reliability constraint in (6), then obtaining (7):
Figure FDA0002737390660000036
in the formula, PCUMi(T，r0) The requirement for reliability is r0The time threshold is the reachability at T,
Figure FDA0002737390660000037
the number of opportunities of the trellis is 0 or 1, when the travel time between (i, j)
Figure FDA0002737390660000041
When the time is less than or equal to the time threshold T,
Figure FDA0002737390660000042
the resident at i gets the chance to get the j cell, otherwise,
Figure FDA0002737390660000043
under the time threshold and reliability constraints, the total number of opportunities that the resident can obtain is the reachability of the grid i.
2. The method of claim 1 wherein said internet map company of step 1 comprises a Baidu map and a Gade map.
3. The method of claim 1 wherein said step 2 is 500m on a side.
4. The method of claim 1 wherein said different types of medical facilities of step 2 are: primary hospitals, secondary hospitals and tertiary hospitals.
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