A method for evaluating the operation service of a bus line

Abstract

The present invention discloses a method for evaluating the operation service of bus lines, including: obtaining index data of different levels of lines; performing quantitative analysis on the index data to obtain quantitative division data of different levels of lines; calculating the index weights by the CRITIC method; obtaining standard line division data based on the quantitative division data and the index data; and comprehensively evaluating the index weights and the standard line division data by the TOPSIS method to obtain line rankings and grade division data. Through the above technical solution, the present invention can effectively, accurately and conveniently evaluate bus lines.

Description

Technical Field

[0001] The present invention belongs to the fields of public transportation data mining and public transportation optimization, and particularly relates to a method for evaluating the operation service of bus lines. Background Art

[0002] Transportation facilities are one of the main infrastructure facilities in a city and are the carriers of the flow of people, logistics, and information in the city. Whether the urban transportation system can operate in a virtuous cycle is related to the effective play of urban functions and the sustainable development of the urban economy and society. At present, bus companies analyze duplicate lines (sections where buses and subways overlap) based on experience and adjust bus lines, but the effect is not very satisfactory. Therefore, timely discovery of problematic lines is a powerful method for effectively solving urban transportation problems. In previous related research, a method and process for classifying and evaluating bus operation indicators with the application number 202110617812 classifies indicators for different levels of lines, divides weights, and then divides each indicator into grades for final evaluation. This method lacks a specific method for weight division, and there is room for improvement in the accuracy and convenience of evaluating lines. At the same time, this method lacks an objective basis, and there is an urgent need for a method that can effectively, accurately, and conveniently evaluate bus lines. Summary of the Invention

[0003] To solve the problems existing in the above-mentioned prior art, the present invention provides a method for evaluating the operation service of bus lines, which can effectively, accurately, and conveniently evaluate bus lines.

[0004] To achieve the above technical objectives, the present invention provides the following technical solutions:

[0005] A method for evaluating the operation service of bus lines, comprising:

[0006] Obtaining index data of different levels of lines; performing quantitative analysis on the index data to obtain quantitative division data of different levels of lines; calculating the index weights by the CRITIC method; obtaining standard line division data based on the quantitative division data and the index data; and comprehensively evaluating the index weights and the standard line division data by the TOPSIS method to obtain line rankings and grade division data.

[0007] Optionally, the index data includes: time evaluation index, space evaluation index, transport capacity evaluation index, and comfort evaluation index;

[0008] Among them, the time evaluation indicators include bus operation duration, on-time rate, bus operation speed, and headway; the space evaluation indicators include line length, non-straightness coefficient, 500m station coverage rate, and maximum line duplication; the transport capacity evaluation indicators include passenger volume, ratio of departures during peak and off-peak hours, and load factor; the comfort evaluation indicators include bus ownership per 10,000 people and the proportion of air-conditioned buses.

[0009] Optionally, the process of quantitatively analyzing the indicator data includes:

[0010] Obtain bus line data, and conduct qualitative analysis on the bus line data to obtain the hierarchical data of the bus lines, where the hierarchical data includes main lines, branch lines, and express lines; based on the hierarchical data, conduct quantitative analysis on the indicator data to obtain the quantitative division data of different hierarchical lines, where the quantitative analysis process includes counting the proportions of different interval ranges of the indicator data.

[0011] Optionally, the process of calculating the indicator data by the CRITIC method includes:

[0012] Perform dimensionless processing on the indicator data; calculate the information carrying capacity of the indicator data based on the dimensionless processing result, and assign weights to the indicator data based on the information carrying capacity of the indicator data to obtain the indicator weights.

[0013] Optionally, the dimensionless processing steps include:

[0014] Obtain the maximum and minimum values of each indicator data, classify the indicator data based on the maximum and minimum values to obtain the classified indicator data, where the classified indicator data includes positive-type indicator data, negative-type indicator data, and interval-type indicator data; perform dimensionless processing on the indicator data based on the classified indicator data to obtain the dimensionless processing result; where the dimensionless processing process includes positive processing of positive indicator data, reverse processing of negative indicator data, and positive processing of interval indicator data.

[0015] Optionally, the process of calculating the information carrying capacity of the indicator data includes:

[0016] Calculate the volatility Y of the indicator data based on the dimensionless processing result j :

[0017]

[0018] In the formula is the column data mean of each indicator data, m is the number of indicator data variables, and n is the number of evaluation objects;

[0019] Calculate the correlation matrix d of the indicator data based on the dimensionless processing result ij :

[0020]

[0021] Correlation matrix d of the index data ij Calculate the conflict of index data:

[0022] The calculation formula for the conflict of index data is:

[0023]

[0024] Based on the conflict and volatility of the index data, the information volume of the index data is calculated,

[0025] The calculation formula for the information volume of the index data is:

[0026] C j = Y j × A j

[0027] Optionally, the process of obtaining the index weights includes:

[0028] Assign weights to each index data based on the information volume of the index data to obtain the index weights:

[0029]

[0030] Optionally, the process of obtaining the standard line division data includes:

[0031] Based on the index data, the index average value data is obtained, and based on the index average value data, the quantitative division data of the different-level lines is adjusted to obtain the evaluation grades of the indexes in the different-level lines. By dividing the evaluation grades, the standard line division data is obtained.

[0032] Optionally, the process of comprehensively evaluating the index weights and the standard line division data by the TOPSIS method includes:

[0033] Construct a weighted normalized matrix C based on the index weights ij , based on the weighted normalized matrix C ij Calculate the positive ideal solution C * and the negative ideal solution C 0 :

[0034] where the process of obtaining the positive ideal solution C * is:

[0035]

[0036] The process of obtaining the negative ideal solution C 0 is:

[0037]

[0038] Based on the bus line data, various alternative solutions are obtained. Based on the positive ideal solution C * and the negative ideal solution C 0 calculate the distances from each alternative solution to the positive ideal solution C * and the negative ideal solution C 0 :

[0039] Among them, the process of obtaining the distance from the alternative solution d i to the positive ideal solution C * is as follows:

[0040]

[0041] The process of obtaining the distance from the alternative solution d i to the negative ideal solution C 0 is as follows:

[0042]

[0043] Based on the distances from each solution to the positive ideal solution C * and the negative ideal solution C 0 calculate the ranking index values (i.e., comprehensive evaluation indices) of each alternative solution:

[0044]

[0045] Based on the comprehensive evaluation index and combined with the standard line division data, obtain the line ranking and grade division data.

[0046] The technical effect of the present invention is as follows: By quantitatively and qualitatively analyzing the time, space, transport capacity and comfort of different levels of lines, the present invention accurately reflects the overall situation of the lines, which is representative. Combining with the objective analysis CRITIC method algorithm for weight analysis and using the TOPSIS method to objectively comprehensively evaluate the lines, a set of commonly used line division situations is summarized. Thus, based on the situation of the index data of different levels of lines, this method has the advantages of wide applicability, objective evaluation, fast calculation, low cost and comprehensive evaluation scope. At the same time, it can also ensure the accuracy of the evaluated lines. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0048] Figure 1A schematic diagram of a method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0050] In order to solve the problems existing in the prior art, the present invention provides the following solutions:

[0051] Example 1

[0052] like Figure 1 As shown, this embodiment provides a bus route operation service evaluation method, including:

[0053] The specific implementation process of the present invention is:

[0054] S1. First, divide the bus routes into different functional levels according to their different functions.

[0055] From the route optimization guidelines of different cities, analyze what types of routes are included and their specific functions.

[0056] Re-qualitatively divide the functions of the lines.

[0057] The lines are divided into trunk lines, express lines, and branch lines, as shown in Table 1. Table 1 shows the division of lines at different levels in the case.

[0058] Table 1

[0059] Line Name Line Type Route 1 Main Line Route 16 Main Line Route 210 Main Line Route 8 Main Line Route 326 Main Line Route 371 Main Line … … Route 109 Express Line Route 382 Express Line Route 383 Express Line … … Route 938 Branch Line Route 412 Branch Line Route 410 Branch Line

[0060] Based on the qualitative analysis of the routes, with reference to the standard guidelines and specifications of other cities and the different levels of routes in the city, as well as the proportion of different intervals of their indicator data, the indicators are quantitatively divided. The present invention selects route length, non-linear coefficient, average bus operation speed, bus route operation time, punctuality rate, passenger volume, peak load rate, departure interval, and maximum route repetition to conduct a quantitative analysis of routes of different functional levels, as shown in Table 2. Table 2 is the quantitative division of routes.

[0061] Table 2

[0062] Main Line Express Line Branch Line Line Length > 1 Simultaneously < 30 km > 30 km <= 10 km Non - straight Coefficient <＝1.4 <＝1.4 / Average Operating Speed of Bus 20 km / h ≥ 25 km / h <= 17 km / h Operating Time of Bus Line > 16 hours > 15 hours > 15 hours On - time Rate >＝80％ >＝80％ >＝75％ Passenger Volume > 0.5 ten thousand people 0.5 - 2 ten thousand people 0.05 - 0.5 ten thousand people Peak Load Factor 0.5-0.9 0.5-0.9 / Departure Interval 5 - 10 minutes About 10 minutes About 20 minutes Maximum Line Duplication Degree 0.2-0.6 0.2-0.5 0.1-0.4

[0063] S2. The selection of line indicators in this embodiment should be based on actual conditions, and the operational service level of a line can be evaluated. The selection method is as follows:

[0064] Search for relevant research literature and determine the principles for selecting indicators, including the combination of qualitative and quantitative, hierarchical principle, normative principle, independence principle, comparability principle, and practicality principle.

[0065] Steps for selecting indicators:

[0066] Combined with the route optimization guidelines of some cities, consult relevant literature and select evaluation indicators for routes from the aspects of time, space, transport capacity, and comfort.

[0067] According to the selection rules of indicators, screen out the evaluation indicators that do not meet the conditions.

[0068] The said indicator data includes: time evaluation indicators, space evaluation indicators, transport capacity evaluation indicators, and comfort evaluation indicators.

[0069] Among them, the time evaluation indicators include bus operation duration, on-time rate, bus operation speed, and departure interval;

[0070] The bus operation duration (one-way operation duration of the bus line, overall operation duration of the bus line) refers to the time length of the bus line operating in a day, which can be represented by the difference between the arrival time at the terminal and the departure time at the first station, reflecting the time situation of the bus line to improve service.

[0071] T = T 末 -T 初

[0072] In the formula: T - bus operation duration;

[0073] T 末 ——The latest departure time at the first station;

[0074] T 初 ——The earliest departure time at the first station.

[0075] The on-time rate is the ratio of the actual departure time of the vehicle to the planned departure time when the bus enterprise executes the transportation plan. It is an important indicator to measure the bus transportation efficiency and quality, and directly reflects the quality of the route operation.

[0076]

[0077] In the formula: ρ - on-time rate of the bus line;

[0078] D S ——Arrival on-time rate of the bus line;

[0079] X S ——Departure on-time rate of the bus line.

[0080] The arrival on-time rate is the probability that a bus arrives at a certain stop according to the planned time, and it is also an important indicator to measure the efficiency and quality of bus transportation.

[0081]

[0082] In the formula: D s —— The on-time probability of arrival;

[0083] ∑D —— The number of buses arriving on time, which is the number of buses that follow the condition: planned arrival time - 5 minutes ≤ actual arrival time ≤ planned arrival time + 5 minutes;

[0084] ∑S —— The total number of buses.

[0085] The departure on-time rate is the probability that a bus departs on time, which reflects the punctuality of the bus stop.

[0086]

[0087] In the formula: X s —— The on-time probability of departure;

[0088] ∑X —— The number of buses departing on time, which is the number of buses that follow the condition: actual departure time ≤ planned departure time + 2 minutes;

[0089] ∑S —— The total number of buses.

[0090] The operating speed of buses

[0091] The average operating speed of buses refers to the average speed of buses under normal driving conditions, which is the ratio of the line length to the transportation time. It can reflect the operation efficiency of urban buses. Therefore, the bus transportation speed can be used to characterize the level of the bus line supply.

[0092]

[0093] In the formula: V a —— The average transportation rate during the riding interval;

[0094] L a —— The line length;

[0095] T a —— The transportation time.

[0096] The departure frequency during peak hours

[0097] The headway is the average interval time for buses on a bus route to depart according to the schedule within a time cycle. The maximum allowable headway depends on the requirements for passenger service quality and is generally preferably no greater than 20 minutes. The minimum allowable headway, under normal traffic conditions, for peak-hour bus routes in large and medium-sized cities, is generally preferably not less than 1 minute.

[0098] Spatial evaluation indicators include route length, non - straight - line coefficient, 500 - m stop coverage rate, and maximum route duplication; the non - straight - line coefficient uses spatial thinking to represent the tortuosity of a bus route. With the complexity of the urban spatial structure and road network structure, when determining a reasonable value, it should be specifically determined in combination with the city scale, layout, and passenger flow direction. The larger the non - straight - line coefficient, the longer the bus running cycle and the lower the operation punctuality rate.

[0099]

[0100] In the formula: Z a —— the non - straight - line coefficient of the route;

[0101] L a —— the actual distance of the bus route;

[0102] L s —— the straight - line distance between the first and last stops of the bus route.

[0103] The route length is the length of the route operation. It is the route that the operating vehicle follows along the bus route. If the route is not a loop, the route operation length is divided into the up - bound length and the down - bound length. The up - bound length is the length of the route that the operating vehicle runs from the last stop to the first stop along the bus route; the down - bound length is the length of the route that the operating vehicle runs from the first stop to the last stop along the bus route. The operating length of a non - loop bus route is the sum of the up - bound and down - bound lengths. The route length should be appropriate. If the route is too long, on the one hand, it will cause problems such as a decrease in bus punctuality rate and operation efficiency, and on the other hand, it is easy to cause driver fatigue and is not conducive to driving safety; if the route is too short, it is not conducive to bus operation scheduling and will also increase the number of passenger transfers.

[0104] L a =L a1 +L a2

[0105] Among them, L a represents the length of the route; L a1 represents the up - bound length of the route; L a2 represents the down - bound length of the route.

[0106] The maximum line redundancy can indicate whether a line is replaceable. For a bus line, assuming there are 10 bus stops on a bus line, there will be 9 lines between the stops. If the vast majority of the passenger flow can be borne by the line with the largest redundancy among these 9 lines and the stop lines of other bus lines, it is a waste of transport capacity.

[0107]

[0108] α: The maximum line redundancy

[0109] Max 重复 : The number of lines with the most repetitions compared to all other lines

[0110] δ: All the stop lines of a bus line

[0111] The 500m stop coverage rate represents the percentage of the area covered by a circle with a radius of 500m centered on a stop in the area where bus stops can be set in the city. The stop coverage rate reflects the rationality of urban bus layout. The higher the stop coverage rate within a certain range, the more convenient it is to serve passengers' travel.

[0112]

[0113] In the formula: S γ —— The 500m stop coverage rate;

[0114] S a —— The service area of a bus stop. The area within a circle with a radius of 500m centered on a bus stop represents the service area of a bus stop;

[0115] S 城 —— The area of urban land.

[0116] Transport capacity evaluation indicators include passenger volume, the ratio of peak-hour to off-peak-hour departure frequencies, and load factor;

[0117] The passenger volume is the number of passengers transported by buses during the statistical period and is greatly affected by the passenger flow demand of the line. The larger the passenger flow of the line, the larger the passenger volume. This characterizes the magnitude of the demand for the bus line.

[0118] The ratio of peak-hour to off-peak-hour departure frequencies. The number of departure trips is the number of round trips made by operating vehicles along the line direction, which reflects the congestion degree of the line to a certain extent.

[0119]

[0120] In the formula: N —— The ratio of peak-hour to off-peak-hour departure frequencies;

[0121] N 高 —— The number of departures during peak hours;

[0122] N 平 —— The number of departures during the flat peak period.

[0123] The load factor is a relative value that reflects the degree of passenger fullness of the vehicles running on the line within a certain period of time. It is an indicator to measure the utilization degree of vehicles, an important indicator to reflect the service quality and level of urban public transportation, and also one of the bases for the public transportation operation and dispatching department to compile operation plans and conduct on-site dispatching.

[0124] r = Q s / Q e

[0125] In the formula, Q s is the actual number of passengers carried by the bus, and Q e is the rated passenger capacity of the vehicles on the bus line.

[0126] The comfort evaluation indicators include the public transportation vehicle ownership per 10,000 people and the proportion of air-conditioned buses.

[0127] The public transportation vehicle ownership per 10,000 people, that is, the standard number of operating vehicles of public transportation owned per 10,000 people on average. It can reflect the level of public transportation development in a city. Thus, it can reflect the comfort of passengers when waiting for the bus.

[0128]

[0129] In the formula:

[0130] PTI4 represents the public transportation vehicle ownership per 10,000 people, with the unit of standard vehicle per 10,000 people.

[0131] U 汽 represents the number of operating vehicles obtained by converting the standard operating vehicles of the bus according to a unified standard equivalent, with the unit of standard vehicle.

[0132] P 城区 represents the total urban population, with the unit of person.

[0133] The proportion of air-conditioned buses, the proportion of buses equipped with air conditioners, can relieve the discomfort caused by the temperature, thus affecting the comfort of passengers.

[0134]

[0135] Among them, K β represents the proportion of buses equipped with air conditioners; K 总 represents the total number of buses; K 空 represents the proportion of buses equipped with air conditioners. The selection of some indicators is shown in Table 3, where Table 3 shows the situations (partial) of various indicators of different levels of lines.

[0136] Table 3

[0137]

[0138] For the establishment of the evaluation model of bus lines, the evaluation indicators required by this model should be able to comprehensively reflect the operating conditions of buses. The evaluation indicators must be comprehensive and diverse, and each indicator should be able to be calculated and have representative characteristics. The constructed indicator system has both an analysis of the overall line and a more detailed analysis of important periods of the line. For example, the on-time rate reflects the overall situation of the line (including the overall situation during peak and off-peak hours), while the peak on-time rate can more precisely highlight the operating capacity of the line during important periods, thereby improving the evaluation accuracy of this indicator. Evaluate the operating capacity of a line in terms of time, space, and transport capacity.

[0139] The results of the index analysis of the city show that for most bus trunk lines, the bus operation duration meets the requirements; the average speed during peak hours is relatively low; the maximum line repetition rate generally meets the requirements, and the waste of transport capacity is small. For most trunk lines, the line length meets the requirements; the overall on-time rate is relatively low.

[0140] For most bus express lines, the bus operation duration meets the requirements; the average operating speed during peak hours and off-peak hours is slow, and there is no obvious difference from the speed of trunk lines; the maximum line repetition rate generally meets the requirements; the on-time rate of express lines is relatively low, and for most lines, it does not reach more than 0.8.

[0141] For most bus feeder lines, the bus operation duration meets the requirements; for most lines, the average operating speed during peak hours and off-peak hours meets the conditions; for most lines, the maximum line repetition rate meets the conditions; for most lines, the on-time rate also meets the conditions; the line length of feeder lines is relatively long, and a large part of the lines do not meet the conditions.

[0142] S3. The process of calculating the index data by the CRITIC method includes: performing dimensionless processing on the index data; calculating the information carrying capacity of the index data based on the result of the dimensionless processing, and obtaining the index weight by weighting the index data based on the information carrying capacity of the index data.

[0143] The CRITIC method is an objective weight assignment method. Its basic idea is to determine the objective weight of the index, based on two basic concepts. One is the contrast intensity, which represents the size of the value gap of each evaluation scheme of the same index, and is expressed in the form of standard deviation. The other is the conflict between evaluation indicators. The conflict between indicators is based on the correlation between indicators. For example, if there is a strong positive correlation between two indicators, it means that the conflict between the two indicators is relatively low.

[0144] Optionally, the dimensionless processing steps include:

[0145] Obtain the maximum and minimum values of each indicator data, classify the indicator data based on the maximum and minimum values to obtain the classified indicator data, and the classified indicator data includes positive-type indicator data, negative-type indicator data, and interval-type indicator data; perform dimensionless processing on the indicator data based on the classified indicator data to obtain the dimensionless processing result; where the dimensionless processing process includes positive processing of positive indicator data, reverse processing of negative indicator data, and positive processing of interval indicator data.

[0146] Suppose there are m indicator variables for principal component analysis: x1, x2, ……, x n , and there are n evaluation objects in total. The value of the j-th indicator of the i-th evaluation object is x ij .

[0147] For positive indicators, perform positive processing:

[0148]

[0149] For reverse indicators, perform reverse processing:

[0150]

[0151] For interval indicators, perform positive processing:

[0152] {x j} is a sequence of a set of indicators, and the best interval is [a, b]. Then the positive processing formula is as follows:

[0153] M = max{a - min{x j}, max{x j} - b}

[0154]

[0155] Optionally, the process of calculating the information carrying capacity of the indicator data includes:

[0156] Calculate the volatility Y of the indicator data based on the dimensionless processing result j :

[0157]

[0158] In the formula is the column data mean of each indicator data, m is the number of indicator data variables, and n is the number of evaluation objects;

[0159] Calculate the correlation matrix d of the indicator data based on the dimensionless processing result ij :

[0160]

[0161] Correlation matrix d of index data ij Calculate the conflict of index data:

[0162] The calculation formula for the conflict of index data is:

[0163]

[0164] Based on the above conflict and volatility of index data, calculate the information volume of index data,

[0165] The calculation formula for the information volume of index data is:

[0166] C j = Y j × A j

[0167] The information volume is used as the basis for the final weight;

[0168] Optionally, the process of obtaining the index weight includes:

[0169] Assign weights to each index data based on the information volume of index data to obtain the index weight:

[0170]

[0171] The weights of each index of the main line calculated by the CRITIC method are shown in Table 4, where Table 4 is the weights of each index of the main line calculated by the CRITIC method.

[0172] Table 4

[0173]

[0174]

[0175] The process of obtaining the standard line division data includes:

[0176] According to the TOPSIS method, classify the line conditions. The basis for classification is to refer to national and industry standards and the actual research status of urban bus companies. Based on the average value of each index, combined with the quantitative analysis results, appropriately increase and decrease, so as to divide the main line into four grades: "good", "better", "worse", "poor", the express line into three grades: "good", "better", "poor", and the branch line into two grades: "good", "poor", as shown in Tables 5-7, where Table 5 is the standard division of different grades of the main line, Table 6 is the standard division of different grades of the main line, and Table 7 is the division of different grades of the branch line.

[0177] Table 5

[0178]

[0179]

[0180] Table 6

[0181] Item Good Relatively Good Poor Operating Duration of Bus >17 >16 <16 Average Speed during Peak Hours >19 >17 <17 Average Speed during Off - peak Hours >20 >18 <18 Maximum Line Duplication Degree <0.3 <0.5 >0.5 Line Length [30,60] [60,70] >70 On - time Rate >0.7 >0.6 <0.6 Arrival On - time Rate >0.4 >0.3 <0.3 Peak On - time Rate >0.6 >0.4 <0.4 Peak Arrival Rate >0.3 >0.2 <0.2 Passenger Volume >5000 >4500 <4500 Average Passenger Volume during Peak Hours >80 >60 <60 Average Passenger Volume during Off - peak Hours >70 >50 <50 Peak Load Factor [0.9，1] [1, 1.5] and [0.7 - 0. > 1.5 and < 0.7 ​ ​ ​ ​ ​ <1.4 <1.5 >1.5

[0182] Table 7

[0183]

[0184]

[0185] By dividing the above index levels, reference standard lines of different levels can be defined, so as to achieve the division effect of lines at different levels. As shown in Tables 8 - 10: Among them, Table 8 is the standard line of the main line, Table 9 is the standard line of the express line, and Table 10 is the standard line of the branch line.

[0186] Table 8

[0187]

[0188]

[0189] Table 9

[0190] ​ ​ ​ ​ 17 16 ​ 19 17 ​ 20 18 ​ 0.4 0.5 ​ 50 65 ​ 0.7 0.6 ​ 0.4 0.3 ​ 0.65 0.4 ​ 0.3 0.2 ​ 6000 5000 ​ 80 60 ​ 70 50 ​ 0.95 1.4 ​ 0.5 0.5 ​ 1.4 1.5

[0191] Table 10

[0192]

[0193]

[0194] S5. The process of comprehensively evaluating the index weights and standard line division data by the TOPSIS method includes:

[0195] Suppose the multi - attribute decision - making solution set is D = {d1, d2,..., d m , and the attribute variables for measuring the quality of the solutions are x1,..., x n . At this time, each solution di in the solution set D i (i = 1, 2,..., m) is a vector composed of n attribute values [a i 1,..., a i n], which, as a point in the n - dimensional space, can uniquely represent the solution di i .

[0196] The positive ideal solution C * is a virtual optimal solution that does not exist in the solution set D, and each of its attribute values is the optimal value of the corresponding attribute in the decision - making matrix; while the negative ideal solution C 0It is the virtual worst - case scenario, and each of its attribute values is the worst value of that attribute in the decision matrix. In the n - dimensional space, for each alternative d in the set of alternatives D i and the positive ideal solution C * and the negative ideal solution C 0 compare the distances. The alternative D that is close to the positive ideal solution and far from the negative ideal solution is the optimal alternative in the set of alternatives D, and the priority order of each alternative in the set of alternatives D can be determined accordingly.

[0197] Construct a weighted normalized matrix C ij based on the weights of the said indicators, and calculate the positive ideal solution C ij and the negative ideal solution C * from the weighted normalized matrix C 0 :

[0198] Let the weight vector of each attribute given by the decision - maker be ω = [ω1, ω2, …, ω3] T , and the magnitude of the weights is the result calculated by the CRITIC method for the index data. The process of constructing the weighted normalized matrix C=(c ij ) m×n is as follows:

[0199] c ij =ω j ·x ij (j = 1, …, n; i = 1, 2, …, m)

[0200] The process of obtaining the positive ideal solution is as follows:

[0201]

[0202] The process of obtaining the negative ideal solution is as follows:

[0203]

[0204] Based on the bus - line data, obtain each alternative. Calculate the distances of each alternative to the positive ideal solution C * and the negative ideal solution C 0 : * and the negative ideal solution C 0 :

[0205] Among them, the process of obtaining the distance from the alternative d i to the positive ideal solution C * is as follows:

[0206]

[0207] The process of obtaining the distance from the alternative d i to the negative ideal solution C 0 is as follows:

[0208]

[0209] Based on the distance from each solution to the positive ideal solution C * and the negative ideal solution C 0 calculate the ranking index value (i.e., comprehensive evaluation index) of each alternative solution:

[0210]

[0211] Based on the comprehensive evaluation index and combined with the standard line division data, obtain the line ranking and grade division data.

[0212] According to the weights of each index calculated by the above CRITIC method, score and rank each line by the TOPSIS method, as shown in Table 11, where Table 11 is the comprehensive evaluation of the main line by the TOPSIS method.

[0213] Table 11

[0214] ​ ​ ​ ​ ​ ​ 0.439 0.661 0.601 1 ​ 0.466 0.627 0.574 2 … … … … … ​ 0.54 0.587 0.521 19 ​ 0.573 0.613 0.517 20 ​ 0.505 0.538 0.516 21 … … … … … ​ 0.579 0.543 0.484 55 ​ 0.6 0.559 0.482 56 ​ 0.657 0.608 0.481 57 … … … … … ​ 0.693 0.495 0.417 105 ​ 0.695 0.495 0.416 106 ​ 0.671 0.477 0.416 107 … … … … … ​ 0.753 0.464 0.381 119

[0215] The analysis of the evaluation results is as follows:

[0216] From the above lines, select lines of different grades for comparative analysis, as shown in Table 12, where Table 12 is the average value of the line indicators of different grades in the main line.

[0217] Table 12

[0218] ​ ​ ​ ​ ​ ​ 17.67 16.57 16.76 15.49 ​ 17.4 17 15.47 18.8 ​ 21.37 17.92 17.01 19.46 ​ 0.27 0.28 0.32 0.41 ​ 28.8 27.47 24.98 44.95 ​ 0.72 0.67 0.62 0.54 ​ 0.45 0.33 0.24 0.09 ​ 0.66 0.6 0.54 0.52 ​ 0.33 0.21 0.09 0.04 ​ 9635 7623 6305 2080 ​ 103 90 81 55 ​ 87 74 65 38 ​ 1.2 1.15 1.07 0.64 ​ 0.51 0.53 0.48 0.51 ​ 1.58 1.85 1.83 1.85

[0219] It can be seen from the table that the lines with a good evaluation grade are significantly superior to other lines in terms of bus operation duration, average operation speed during off-peak hours, maximum line repetition rate, on-time rate, arrival on-time rate, peak on-time rate, peak arrival on-time rate, peak arrival rate, passenger volume, off-peak passenger volume, and non-straightness coefficient. The lines with a better evaluation grade are superior to the lines with a poor and very poor evaluation grade in terms of bus operation duration, maximum line repetition rate, line length, on-time rate, arrival on-time rate, peak on-time rate, peak arrival on-time rate, passenger volume, peak average passenger volume, and off-peak passenger volume. Comparing the lines with a poor and very poor evaluation grade, the lines with a poor evaluation grade are superior to the lines with a very poor evaluation grade in terms of bus operation duration, maximum line repetition rate, line length, on-time rate, arrival on-time rate, peak on-time rate, peak arrival on-time rate, passenger volume, peak average passenger volume, load factor, and non-straightness coefficient. Based on the above analysis, it can be concluded that the evaluation model is reliable. As shown in Table 13, where Table 13 is the comprehensive evaluation of the express line by the TOPSIS method.

[0220] Table 13

[0221]

[0222] Analysis of evaluation results:

[0223] From the above lines, select lines of different levels for comparative analysis, as shown in Table 14, where Table 14 is the average value of the line indicators of different levels in the express line.

[0224] Table 14

[0225]

[0226]

[0227] It can be seen from the table that the lines with a good evaluation level are significantly superior to other lines in terms of the average operation speed during off-peak hours, the average operation speed during peak hours, the on-time rate, the arrival on-time rate, the peak on-time rate, the peak arrival on-time rate, the peak arrival rate, the off-peak passenger volume, the non-straightness coefficient, and overall. However, in terms of the bus operation duration and the maximum repetition rate, they are slightly worse than those of other levels, but overall they meet the standards of the express line. And the lines with a better evaluation level are superior to the poor lines in terms of the bus operation duration, the maximum repetition rate of the line, the line length, the on-time rate, the arrival on-time rate, the peak on-time rate, the peak arrival on-time rate, the passenger volume, the average peak passenger volume, the off-peak passenger volume, and the non-straightness coefficient. Based on the above analysis, it is obtained that the TOPSIS method for evaluation is reliable. As shown in Table 15, where Table 15 is the comprehensive evaluation of the branch lines by the TOPSIS method.

[0228] Table 15

[0229]

[0230]

[0231] Analysis of evaluation results:

[0232] From the above lines, select lines of different levels for comparative analysis, as shown in Table 16, where Table 16 is the average value of the line indicators of different levels in the branch line.

[0233] Table 16

[0234] ​ ​ ​ ​ 15.55 14.09 ​ 19.71 16.17 ​ 19.99 17.79 ​ 0.33 0.28 ​ 24.50 12.68 ​ 0.84 0.67 ​ 0.67 0.37 ​ 0.80 0.66 ​ 0.61 0.34 ​ 1845 755 ​ 38 28 ​ 23 19 ​ 0.48 0.37 ​ 0.55 0.54 ​ 1.55 2.37

[0235] According to the analysis of the above table, for the lines evaluated as good, the average value of each indicator is better than that of the poor lines, indicating that the lines evaluated as good are overall superior to the lines evaluated as poor, and the effect of the evaluation model is reliable.

[0236] Thus, based on the comprehensive application of the CRITIC method and the TOPSIS method, the ranking and classification of all lines are completed. At the same time, due to the objectivity of the two algorithms, the reliability of the final evaluation results is ensured.

[0237] As described above, only the preferred specific embodiments of the present application are provided, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present application should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for evaluating bus line operation services, characterized in that, It includes the following steps: Obtain the index data of lines at different levels; Conduct quantitative analysis on the index data to obtain the quantitative division data of lines at different levels; Calculate the index weights by the CRITIC method for the index data; Obtain the standard line division data based on the quantitative division data and the index data; Conduct comprehensive evaluation on the index weights and the standard line division data by the TOPSIS method to obtain the line ranking and the grade division data; The index data includes: time evaluation index, space evaluation index, transport capacity evaluation index, comfort evaluation index; Among them, the time evaluation index includes bus operation duration, on-time rate, bus operation speed, and departure interval; the space evaluation index includes line length, non-straightness coefficient, 500m station coverage rate, and maximum line repetition rate; the transport capacity evaluation index includes passenger volume, ratio of departures during peak and off-peak hours, and load factor; the comfort evaluation index includes bus ownership per 10,000 people and proportion of air-conditioned buses; The process of calculating the index data by the CRITIC method includes: Conduct dimensionless processing on the index data; calculate the information carrying capacity of the index data based on the dimensionless processing result, and assign weights to the index data based on the information carrying capacity of the index data to obtain the index weights; The process of obtaining the standard line division data includes: Obtain the index average value data based on the index data, adjust the quantitative division data of lines at different levels based on the index average value data to obtain the evaluation grades of the indexes in lines at different levels, and obtain the standard line division data by dividing the evaluation grades; 2. The evaluation method for bus line operation service according to claim 1, characterized in that The process of conducting quantitative analysis on the index data includes: Obtain the bus line data, conduct qualitative analysis on the bus line data to obtain the hierarchical data of the bus lines, where the hierarchical data includes trunk lines, branch lines, and express lines; based on the hierarchical data, conduct quantitative analysis on the index data to obtain the quantitative division data of lines at different levels, and the quantitative analysis process includes statistically calculating the proportion of different interval ranges of the index data.

3. The method for evaluating bus line operation services according to claim 2, characterized in that The process of dimensionless processing includes: Obtain the maximum and minimum values of each index data, classify the index data based on the maximum and minimum values to obtain the classified index data, and the classified index data includes positive index data, negative index data, and interval index data; conduct dimensionless processing on the index data based on the classified index data to obtain the dimensionless processing result; among them, the dimensionless processing process includes positive processing of the positive index data, reverse processing of the negative index data, and positive processing of the interval index data.

4. The bus line operation service evaluation method according to claim 2, characterized in that, The process of calculating the information carrying capacity of the index data includes: Calculate the volatility Y of the index data based on the dimensionless processing result j : where is the column data mean of each index data, m is the number of index data variables, and n is the number of evaluation objects; x ij is the value of the j-th index of the i-th evaluation object; Calculate the correlation matrix d of the index data based on the dimensionless processing results ij : where k is a set variable, k = 1, 2, 3......n, is the column data mean of each index data, x ik is the value of the k-th index of the i-th evaluation object; Correlation matrix d based on index data ij Calculate the conflict A of index data j : Calculate the information amount C of the index data based on the conflict and volatility of the index data j : C j = Y j × A j .

5. The evaluation method for bus line operation service according to claim 2, characterized in that The process of obtaining the index weights includes: Assign weights to each indicator data based on the information volume of the indicator data to obtain the indicator weight F j :

6. The evaluation method for a bus line operation service according to claim 1, characterized in that, The process of conducting comprehensive evaluation on the index weights and the standard line division data by the TOPSIS method includes: Construct a weighted normalized matrix C based on the index weights ij , based on the weighted normalized matrix C ij calculate the positive ideal solution C * and the negative ideal solution C 0 : Among them, the positive ideal solution C * is obtained as follows: The negative ideal solution C 0 is obtained as follows: Obtain each alternative solution based on bus line data, and based on the positive ideal solution C * and the negative ideal solution C 0 Calculate the distances from each alternative solution to the positive ideal solution C * and the negative ideal solution C 0 : Among them, the alternative d i to the positive ideal solution C * The process of obtaining the distance is as follows: The alternative d i to the negative ideal solution C 0 The process of obtaining the distance is as follows: Based on the distance from each alternative to the positive ideal solution C * and the negative ideal solution C 0 calculate the sorting index value of each alternative: Rank the alternative plans based on the sorting index values of each alternative plan combined with the standard line division data to obtain the line ranking and the grade division data.

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