Bus passenger flow coefficient algorithm constructed based on bus related characteristics
1. A public transport passenger flow coefficient algorithm constructed based on public transport related characteristics is characterized by comprising the following steps:
step one, counting public transport passenger flow characteristics: the bus passenger flow characteristics are divided into 6 dimensions, namely passenger capacity, an operating ratio, a full load rate, a departure interval, an average running speed and a nonlinear coefficient;
and step two, calculating a line passenger flow coefficient, after the 6 dimensional data are obtained, firstly, standardizing the data, and then, weighting and summing according to the weight corresponding to each dimension to obtain the passenger flow coefficient of the line.
2. The bus passenger flow coefficient algorithm constructed based on bus-related features as claimed in claim 1, wherein the passenger volume is an average value of the number of passengers on the same type of line within 30 days.
3. The bus passenger flow coefficient algorithm constructed based on bus-related features as claimed in claim 1, wherein the revenue ratio is an average value of "profit/cost" of the same kind of lines within 30 days.
4. The bus passenger flow coefficient algorithm constructed based on bus related features as claimed in claim 1, wherein the full load rate is an average value of 'actual passenger load/number of passengers loaded' on the same kind of line within 30 days.
5. The bus passenger flow coefficient algorithm constructed based on the bus-related features as claimed in claim 1, wherein the issue interval is an average value of the issue interval time of the same kind of lines within 30 days.
6. The bus passenger flow coefficient algorithm constructed based on bus-related features as claimed in claim 1, wherein the average running speed is an average of "kilometers per running time" on the same type of line within 30 days.
7. The bus passenger flow coefficient algorithm constructed based on bus-related features as claimed in any one of claims 1 to 6, wherein the non-linear coefficient is a ratio of an actual mileage between a driving route and a destination to a spatial distance between two points, and a flow of calculating the non-linear coefficient is as follows:
(1) calculating loop
The distance between the first station and the last station of the line is less than 1000 meters, the line can be considered as a circular line by short sight, and the nonlinear coefficient is set to be 1;
(2) calculating non-circular line
The distance between the first station and the last station of the line is more than or equal to 1000 meters, and the calculation rule is as follows:
suppose that the lengths of a certain bus line in the uplink and downlink directions are luAnd ldAnd if the space linear distance between the first station and the last station is d, the nonlinear coefficient r of the line is as follows:
(3) after (1) and (2) are calculated, if the nonlinear coefficient is greater than 10, the average value of the nonlinear coefficients of all the lines except the line is used as the nonlinear coefficient of the line.
8. The bus passenger flow coefficient algorithm constructed based on bus-related features as claimed in claim 7, wherein the line passenger flow coefficient is calculated as follows:
(1) respectively carrying out (0,1) normalization on each dimension of the same type of lines, wherein the specific calculation mode is as follows:
(2) then calculating the bus passenger flow coefficient score of the line:
the bus passenger flow coefficient score is w1+ w2+ w3+ w4+ w5+ w6 + w6,
wherein, w1, w2, w3, w4, w5 and w6 are respectively the weight occupied by the passenger capacity, the revenue ratio, the full load rate, the departure interval, the average running speed and the nonlinear coefficient; the characteristic 1, the characteristic 2, the characteristic 3, the characteristic 4, the characteristic 5 and the characteristic 6 are respectively values of normalized passenger capacity, revenue ratio, full load rate, departure interval, average running speed and nonlinear coefficient;
(3) the bus passenger flow coefficient score of the line is standardized, and the specific calculation mode is as follows:
Background
Bus passenger flow coefficient: i.e. the actual value of public enjoyment of public transit services. The method covers the coefficients constructed from multiple dimensions such as passenger capacity, operating ratio, full load rate, departure interval, average running speed, nonlinear coefficients and the like, and accurately describes the passenger flow condition of the bus line. At present, technologies for constructing bus passenger flow characteristics are not abundant in the market, and accurate bus passenger flow characteristics are obtained through real bus related data through a big data technology, so that a bus passenger flow coefficient is constructed, and the passenger flow condition of a bus line is accurately described.
Disclosure of Invention
The invention aims to provide a bus passenger flow coefficient algorithm constructed based on bus related characteristics so as to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
a public transport passenger flow coefficient algorithm constructed based on public transport related characteristics is characterized by comprising the following steps:
step one, counting public transport passenger flow characteristics: the bus passenger flow characteristics are divided into 6 dimensions, namely passenger capacity, an operating ratio, a full load rate, a departure interval, an average running speed and a nonlinear coefficient;
and step two, calculating a line passenger flow coefficient, after the 6 dimensional data are obtained, firstly, standardizing the data, and then, weighting and summing according to the weight corresponding to each dimension to obtain the passenger flow coefficient of the line.
As a still further scheme of the invention: the passenger capacity is the average value of the number of passengers on the same line in 30 days.
As a still further scheme of the invention: the revenue-to-profit ratio is the average of the "profit/cost" of the same type of line over 30 days.
As a still further scheme of the invention: the full load rate is the average value of 'actual passenger load/load number' on the same type of line within 30 days.
As a still further scheme of the invention: the departure interval is the average value of departure interval time of the same line within 30 days.
As a still further scheme of the invention: the average running speed is the average value of 'kilometers per running time' on the same type of line within 30 days.
As a still further scheme of the invention: the non-linear coefficient refers to the ratio of the actual mileage between the driving route and the destination to the space distance between the two points, and the calculation process of the non-linear coefficient is as follows:
(1) calculating loop
The distance between the first station and the last station of the line is less than 1000 meters, the line can be considered as a circular line by short sight, and the nonlinear coefficient is set to be 1;
(2) calculating non-circular line
The distance between the first station and the last station of the line is more than or equal to 1000 meters, and the calculation rule is as follows:
suppose that the lengths of a certain bus line in the uplink and downlink directions are luAnd ldAnd if the space linear distance between the first station and the last station is d, the nonlinear coefficient r of the line is as follows:
(3) after (1) and (2) are calculated, if the nonlinear coefficient is greater than 10, the average value of the nonlinear coefficients of all the lines except the line is used as the nonlinear coefficient of the line.
As a still further scheme of the invention: calculating a line passenger flow coefficient:
(1) respectively carrying out (0,1) normalization on each dimension of the same type of lines, wherein the specific calculation mode is as follows:
(2) then calculating the bus passenger flow coefficient score of the line:
the bus passenger flow coefficient score is w1+ w2+ w3+ w4+ w5+ w6 + w6,
wherein, w1, w2, w3, w4, w5 and w6 are respectively the weight occupied by the passenger capacity, the revenue ratio, the full load rate, the departure interval, the average running speed and the nonlinear coefficient; the characteristic 1, the characteristic 2, the characteristic 3, the characteristic 4, the characteristic 5 and the characteristic 6 are respectively values of normalized passenger capacity, revenue ratio, full load rate, departure interval, average running speed and nonlinear coefficient;
(3) the bus passenger flow coefficient score of the line is standardized, and the specific calculation mode is as follows:
compared with the prior art, the invention has the beneficial effects that: through the coefficient construction, the travel passenger flow coefficient of each line in a period of time can be obtained, so that the passenger flow distribution condition of each line every day is analyzed, and the bus lines, the bus dispatching and the like can be optimized conveniently by related public transportation departments.
Drawings
Fig. 1 is an overall flow chart of a bus passenger flow coefficient algorithm constructed based on bus-related features.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
The following disclosure provides many different embodiments, or examples, for implementing different features of the invention. To simplify the disclosure of the present invention, the components and arrangements of specific examples are described below. Of course, they are merely examples and are not intended to limit the present invention. Furthermore, the present invention may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed.
Referring to fig. 1, in the embodiment of the present invention, a bus passenger flow coefficient algorithm constructed based on bus-related features is characterized by including the following steps:
step one, counting public transport passenger flow characteristics: the bus passenger flow characteristics are divided into 6 dimensions, namely passenger capacity, an operating ratio, a full load rate, a departure interval, an average running speed and a nonlinear coefficient;
and step two, calculating a line passenger flow coefficient, after the 6 dimensional data are obtained, firstly, standardizing the data, and then, weighting and summing according to the weight corresponding to each dimension to obtain the passenger flow coefficient of the line.
The passenger capacity is the average value of the number of passengers on the same line in 30 days.
The revenue-to-profit ratio is the average of the "profit/cost" of the same type of line over 30 days.
The full load rate is the average value of 'actual passenger load/load number' on the same type of line within 30 days.
The departure interval is the average value of departure interval time of the same line within 30 days.
The average running speed is the average value of 'kilometers per running time' on the same type of line within 30 days.
The non-linear coefficient refers to the ratio of the actual mileage between the driving route and the destination to the spatial distance between the two points, and it should be particularly noted that some cases of particularly large non-linear coefficients of the line may occur when the "non-linear coefficient" is actually calculated, and the reasons of the abnormal values may be checked by checking the actual trend of the line in combination with a map,
the flow of nonlinear coefficient calculation is as follows:
(1) calculating loop
The distance between the first station and the last station of the line is less than 1000 meters, the line can be considered as a circular line by short sight, and the nonlinear coefficient is set to be 1;
(2) calculating non-circular line
The distance between the first station and the last station of the line is more than or equal to 1000 meters, and the calculation rule is as follows:
suppose that the lengths of a certain bus line in the uplink and downlink directions are luAnd ldAnd if the space linear distance between the first station and the last station is d, the nonlinear coefficient r of the line is as follows:
in a specific example, the nonlinear coefficient of the loop is the ratio of the solid-to-space distance between the main scatterers (the processing method of (1) is used).
The improvement is that the shortest road distance d between the first station and the last station is usedm，dmInstead of the spatial straight-line distance between the two, namely:
the nonlinear coefficient calculated by adopting the improved formula reflects the degree of the deviation of the bus route from the shortest path of the road network, and is more reasonable than that before the improvement.
(3) After (1) and (2) are calculated, if the nonlinear coefficient is greater than 10, the average value of the nonlinear coefficients of all the lines except the line is used as the nonlinear coefficient of the line.
Calculating a line passenger flow coefficient:
(1) respectively carrying out (0,1) normalization on each dimension of the same type of lines, wherein the specific calculation mode is as follows:
(2) then calculating the bus passenger flow coefficient score of the line:
the bus passenger flow coefficient score is w1+ w2+ w3+ w4+ w5+ w6 + w6,
wherein, w1, w2, w3, w4, w5 and w6 are respectively the weight occupied by the passenger capacity, the revenue ratio, the full load rate, the departure interval, the average running speed and the nonlinear coefficient; the characteristic 1, the characteristic 2, the characteristic 3, the characteristic 4, the characteristic 5 and the characteristic 6 are respectively values of normalized passenger capacity, revenue ratio, full load rate, departure interval, average running speed and nonlinear coefficient;
(3) the bus passenger flow coefficient score of the line is standardized, and the specific calculation mode is as follows:
the weights w1, w2, w3, w4, w5 and w6 are more specific, and can be set by using a subjective and objective weight setting method according to the strength of the passenger flow represented by the above 6 characteristics. The method comprises the following steps:
let w1+ w2+ w3+ w4+ w5+ w6 be 100
Subjective: the industry experts give empirical values for the weights, E1, E2, E3, E4, E5, E6;
objectivity: analyzing the distribution of the features by using a series of methods such as an entropy method and the like, thereby obtaining weights P1, P2, P3, P4, P5 and P6 corresponding to the features;
combining the subjective weight and the objective weight, and obtaining a final weight through a fusion operation, where the final weight obtained here is w 1-35, w 2-30, w 3-15, w 4-10, w 5-5, and w 6-5.
And next, standardizing the bus passenger flow coefficient score of the line, wherein the standardized value range is 5-99. Assume by calculation that the net has a total of 5 wires, as shown in the following table:
bus passenger flow coefficient meter for all lines in network
The values in the following table were obtained by normalization:
standardized bus passenger flow coefficient table for all lines
Through the coefficient construction, the travel passenger flow coefficient of each line in a period of time can be obtained, so that the passenger flow distribution condition of each line every day is analyzed, and the bus lines, the bus dispatching and the like can be optimized conveniently by related public transportation departments.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
While embodiments of the invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.
