CN111260926A - Method for evaluating and prompting reliability of bus arrival time prediction result - Google Patents
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Abstract
The invention relates to the technical field of traffic, in particular to a method for evaluating and prompting the reliability of a bus arrival time prediction result, which comprises the steps of firstly carrying out bus arrival time prediction data standardization processing; then, evaluating the reliability of the prediction result of the bus arrival time; calculating the deviation degree of the prediction result of the arrival time of the bus by combining the actual value and the predicted value of the arrival travel time of the bus; then constructing a deviation probability distribution model of the bus arrival time prediction result, and finally evaluating and prompting the reliability of the bus arrival time prediction result; according to the invention, the reliability of the prediction result of the historical bus arrival time is evaluated, and the reliability is prompted by adopting the predicted arrival time with different colors, so that a traveler is attracted to select a ground bus to go out, and the competitiveness, attraction and trip sharing rate of the ground bus are improved.
Description
Technical Field
The invention relates to the technical field of traffic, in particular to a method for evaluating and prompting the reliability of a bus arrival time prediction result.
Background
The prior development of public transport as an important urban traffic development strategy in China becomes a consensus for relieving the problems of urban traffic jam, traffic pollution, traffic energy consumption and the like in China, and is an important measure for realizing the green sustainable development of urban traffic. Because the construction of urban roads is limited by urban space, land resources and other aspects, the sustainable development of cities needs a multi-mode, multi-type, high-quality and high-efficiency public transport system and travel service so as to improve the attraction, competitiveness and bearing capacity of urban ground public transport systems.
In recent years, the rapid development of urban public transport informatization construction and big data technology plays an unprecedented role in promoting the construction of ground public transport systems, and especially the occurrence of urban public transport arrival time prediction service has great significance in improving the operation service and management level of the ground public transport systems, improving the competitiveness and attraction of public transport trips, solving the problems of urban traffic jam, environmental pollution and the like. However, in the operation of the bus arrival time prediction service, the phenomena of unreliable prediction results of the bus arrival time, low accuracy of the arrival time prediction and the like sometimes occur, and particularly, the selection of travelers on the travel mode is seriously influenced under the weather conditions of rain, snow, strong wind and the like. In the face of unreliable forecast waiting time, travelers often need to pay attention to the buses at the station all the time, so that impatience, anxiety and other negative emotions are easily generated, the travelers are caused to select other transportation modes to travel, and the competitiveness, the attractiveness, the travel sharing rate and the like of the ground buses are not obviously improved.
Under the condition, in order to improve the prediction service quality of the bus arrival time, a high-efficiency, on-time and reliable ground bus system is built, the reliability of the prediction result of the bus arrival time can be evaluated and prompted, so that a traveler can more accurately judge the prediction of the bus arrival time, the acceptance and satisfaction of the operation service quality of the ground public service of the traveler are improved, the anxiety, impatience and other negative emotions of the traveler in the waiting process are reduced, and the competitiveness, attraction, trip sharing rate and the like of the ground bus trip are improved.
Disclosure of Invention
In view of the above, the present invention provides a method for evaluating and prompting the reliability of a bus arrival time prediction result, so as to solve the problems in the background art.
The invention aims to provide a method for evaluating and prompting the reliability of a bus arrival time prediction result. The tolerance degree of a traveler on the deviation of the bus arrival time prediction result and the subjective feeling of the traveler on the reliability are obtained in a questionnaire survey mode, the evaluation grade and the division standard of the bus arrival time prediction result reliability are formulated, and the reliability is prompted through the predicted arrival time with different colors, so that the service quality and the service level of the bus arrival time prediction are improved.
In order to achieve the purpose, the method for evaluating and prompting the reliability of the bus arrival time prediction result is specifically executed according to the following steps:
further, step S1, standardizing the bus arrival time prediction data;
based on the bus arrival time prediction service, acquiring bus arrival time prediction data and carrying out standardization processing to generate a bus arrival time prediction data table, wherein the bus arrival time prediction data table mainly comprises data fields such as date, time, line number, vehicle number and driving direction, namely the number of a bus station to arrive at a station, the name of the bus station to arrive at the station, the distance of the bus station to arrive at the station, the predicted bus arrival time and the like. The standardized format of the data fields is shown in table 1:
TABLE 1 bus arrival time prediction data example table
The data field description of the bus arrival time prediction data table is shown in table 2:
table 2 data field description
| Serial number | Data field | Description of the invention |
| 1 | Date | YYYY/MM/DD (year/month/day) |
| 2 | Time of day | HH MM SS (hour/minute/second) |
| 3 | Line numbering | / |
| 4 | Vehicle number | / |
| 5 | Direction of travel | 0, 1(0 is ascending and 1 is descending) |
| 6 | Namely numbering the arriving bus stops | Integers from 1 |
| 7 | Name of bus station to be arrived at | / |
| 8 | I.e. the distance to the station of the bus | Unit: rice (-1 represents bus arriving) |
| 9 | Predicting bus arrival time | Unit: second (0 represents bus arriving) |
Further, step S2, evaluating the reliability of the bus arrival time prediction result;
s2.1, calculating the deviation degree of the prediction result of the arrival time of the bus;
through associating date, time, vehicle number, driving direction and data fields such as the names of the bus stations which will arrive at the station, the continuous arrival time prediction data and the actual arrival time data of the vehicles of the specific bus line in the specific evaluation period are obtained, the actual travel time of the buses from the prediction time to the actual arrival time is further calculated, and the calculation formula is shown as the formula (1):
in the formula, Tijm arriveThe actual travel time of the bus j reaching the stop m is the bus route i; t is tijm arriveThe actual arrival time of the bus j at the station m is the bus route i; t is tim forecastPredicting the arrival time of the stop m for the bus j on the bus line i;
further, step S2.3 is to calculate the deviation of the prediction result of the arrival time of the bus by combining the actual value and the predicted value of the arrival travel time of the bus, and the calculation formula is as shown in formula (2):
in the formula, DijmPredicting the deviation degree of the arrival time prediction result of the bus j at the station m on the bus route i; t isijm arriveThe actual travel time of the bus j on the bus line i to the station m; t isijm forecastAnd predicting the travel time of the bus j to the stop m for the bus line i.
Further, step S3, constructing a probability distribution model of the deviation degree of the bus arrival time prediction result;
according to the actual bus operation time, each hour is divided into 4 evaluation time periods by taking 15 minutes as a minimum unit, and time attribute labels such as working days, non-working days, holidays and the like and weather attribute labels such as rainfall, snowfall, strong wind and the like are given according to the particularity of each evaluation time period in different dates. Respectively counting the deviation data of the bus arrival time prediction result of each bus route stop in each evaluation period of different attribute labels from the beginning of providing the bus arrival time prediction service to the present, and constructing a bus arrival time prediction result deviation probability distribution model: as shown in formula (3):
in the formula, Fanim(x) A probability distribution model of the deviation of the bus arrival time prediction result under the condition of an attribute label a evaluating time interval n bus line station i and station m; f. ofanim(x) As a function of the probability density of the degree of deviation.
Wherein, the specific attribute label is shown in table 3:
TABLE 3 Attribute tags
Further, step S4 bus arrival time prediction result reliability evaluation;
the method comprises the following steps of obtaining tolerance of a traveler to the deviation of a bus arrival time prediction result in a questionnaire survey mode, defining that the prediction result is accurate when the deviation value is smaller than α, calculating the probability that the deviation of the bus arrival time prediction result of each bus line stop is smaller than α in each evaluation period under different attribute labels based on a bus arrival time prediction result deviation probability distribution model, and taking the probability as a reliability evaluation index, and formulating reliability evaluation grade division standards based on subjective feeling of the traveler on the reliability, wherein the reliability evaluation grade division standards are shown in a table 4:
TABLE 4 reliability rating Scale
| Degree of reliability | Ranim≥β2 | β2＞Ranim≥β1 | β1＞Ranim |
| Reliability evaluation level | Is relatively reliable | Is unreliable | Is very unreliable |
Step S5, a method for prompting the reliability of the prediction result of the arrival time of the bus;
on the basis that the predicted arrival time of the next bus is displayed in the existing electronic bus stop board and bus arrival time prediction service APP, the reliability evaluation grade of the prediction result is prompted by the predicted arrival time of different colors by matching the reliability numerical values corresponding to the attribute label, the evaluation time period, the bus line and the bus stop at the current moment. The correspondence between the reliability evaluation level and the cue color is shown in table 5:
TABLE 5 correspondence between reliability evaluation level and prompt color
| Degree of reliability | Ranim≥β2 | β2＞Ranim≥β1 | β1＞Ranim |
| Reliability evaluation level | Is relatively reliable | Is unreliable | Is very unreliable |
| Color of the prompt | Green colour | Orange colour | Red colour |
The method for evaluating and prompting the reliability of the bus arrival time prediction result has the beneficial effects that: according to the method, the reliability of the prediction result of the historical bus arrival time is evaluated, and the reliability is prompted by adopting the predicted arrival time with different colors, so that a traveler is attracted to select a ground bus to go out, and the competitiveness, attraction and going-out sharing rate of the ground bus are improved.
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FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The present invention will be described in detail with reference to the drawings and specific embodiments, and it is to be understood that the described embodiments are only a few embodiments of the present invention, rather than the entire embodiments, and that all other embodiments obtained by those skilled in the art based on the embodiments in the present application without inventive work fall within the scope of the present application.
In this embodiment, the method for evaluating and prompting the reliability of the bus arrival time prediction result of the present invention includes the following steps:
step S1, standardizing the predicted bus arrival time data;
in this embodiment, based on the service of predicting the arrival time of buses in beijing city, the prediction data of the arrival time of buses in the ascending directions of 125 lanes and 430 lanes included in the south of the west street where the bus stop is newcomer is obtained and standardized, and a prediction data table of the arrival time of buses is generated, which includes the date, the time, the line number, the vehicle number, the traveling direction, the number of the bus stop to be arrived, the name of the bus stop to be arrived, the distance of the bus stop to be arrived, and the data field of the prediction time of the arrival of buses, and the data are shown in table 6:
table 6 bus arrival time prediction data table
The data field description of the bus arrival time prediction data table is shown in table 2:
s2, evaluating the reliability of the bus arrival time prediction result;
s2.1, calculating the deviation degree of the prediction result of the arrival time of the bus;
through associating date, time, vehicle number, driving direction and name data fields of bus stops to arrive at the station, acquiring continuous arrival time prediction data and actual arrival time data of the bus stops at the south of the Huixian street in the bus stop in different evaluation periods in the traveling directions of 125 roads and 430 roads, calculating the actual travel time of the bus from the prediction time to the actual arrival time, wherein the calculation result is shown in table 7:
TABLE 7 actual travel time data sheet of public transport vehicle
Calculating the deviation degree of the prediction result of the arrival time of the bus by combining the actual value and the predicted value of the arrival travel time of the bus, wherein the calculation formula is as follows:
in the formula, DijmPredicting the deviation degree of the arrival time prediction result of the bus j at the station m on the bus route i; t isijm arriveThe actual travel time of the bus j on the bus line i to the station m; t isijm forecastPredicting the travel time of a bus j to a stop m for a bus route i;
in this embodiment, the calculated deviation data of the prediction results of the partial arrival time of the 125-way and 430-way buses in different evaluation periods is shown in table 8:
TABLE 8 deviation data sheet of bus arrival time prediction result
| Date | Time of day | Evaluation period | Line numbering | Vehicle number | Direction of travel | Degree of deviation |
| 2019/2/12 | 6:08:35 | 06:00-06:15 | 125 | 859247926325 | 0 | -0.22 |
| 2019/2/12 | 6:29:10 | 06:15-06:30 | 125 | 965538160269 | 0 | 0.09 |
| 2019/2/12 | 6:39:46 | 06:30-06:45 | 125 | 547746174302 | 0 | -0.05 |
| 2019/2/12 | 6:55:05 | 06:45-07:00 | 125 | 831147926328 | 0 | -0.12 |
| 2019/2/12 | 7:01:38 | 07:00-07:15 | 125 | 252513678572 | 0 | -0.26 |
| 2019/2/12 | 7:11:07 | 07:00-07:15 | 125 | 343194257158 | 0 | -0.30 |
| 2019/2/12 | 7:21:00 | 07:15-07:30 | 125 | 859247926325 | 0 | 0.05 |
| 2019/2/12 | 7:36:24 | 07:30-07:45 | 125 | 547746174302 | 0 | -0.07 |
| 2019/2/12 | 7:47:06 | 07:45-08:00 | 125 | 965538160269 | 0 | 0.25 |
| 2019/2/12 | 7:57:12 | 07:45-08:00 | 125 | 831147926328 | 0 | -0.17 |
| … | … | … | … | … | … | … |
| 2019/2/12 | 5:26:49 | 05:15-05:30 | 430 | 154688293503 | 0 | -0.08 |
| 2019/2/12 | 5:42:41 | 05:30-05:45 | 430 | 418041415913 | 0 | 0.03 |
| 2019/2/12 | 5:58:14 | 05:45-06:00 | 430 | 836382826326 | 0 | 0.40 |
| 2019/2/12 | 6:08:52 | 06:00-06:15 | 430 | 540995454305 | 0 | 0.21 |
| 2019/2/12 | 6:29:12 | 06:15-06:30 | 430 | 162910104601 | 0 | 0.11 |
| 2019/2/12 | 6:40:26 | 06:30-06:45 | 430 | 924196960269 | 0 | 0.07 |
| 2019/2/12 | 6:54:56 | 06:45-07:00 | 430 | 825555470929 | 0 | -0.03 |
| 2019/2/12 | 7:05:24 | 07:00-07:15 | 430 | 198888293503 | 0 | 0.00 |
| 2019/2/12 | 7:15:58 | 07:15-07:30 | 430 | 163510104604 | 0 | -0.08 |
| 2019/2/12 | 7:31:26 | 07:30-07:45 | 430 | 208527278570 | 0 | 0.13 |
| … | … | … | … | … | … | … |
In the embodiment, step S3 is to construct a probability distribution model of the deviation of the bus arrival time prediction result;
according to the actual operation time of the public transportation line in Beijing, taking 15 minutes as the minimum unit, dividing each hour into 4 evaluation periods, and endowing time attribute labels of working days, non-working days and holidays and weather attribute labels of rainfall, snowfall and strong wind according to the particularity of each evaluation period in different dates, wherein the attribute labels are shown in a table 9:
TABLE 9 evaluation period attribute tags for different dates
In this embodiment, the deviation data of the bus arrival time prediction results of 125-way and 430-way ascending directions at the south of the hui-new west street at the bus stop in each evaluation period of different attribute tags from 1 month to 6 months in 2019 are respectively counted, and a probability distribution model of the deviation of the bus arrival time prediction results is constructed, as shown in formula (3)
In the formula, Fanim(x) A probability distribution model of the deviation of the bus arrival time prediction result under the condition of an attribute label a evaluating time interval n bus line station i and station m; f. ofanim(x) As a function of the probability density of the degree of deviation.
In this embodiment, the statistical conditions of the departure time prediction result deviation data of the arrival time prediction results of the 125-way and 430-way ascending directions at the south of the hewlett-packard west street at the bus stop are shown in table 10 and table 11:
table 10 departure time prediction result deviation data statistics table for 125 buses at south of hui-xin west street
TABLE 11 departure data statistics table for prediction results of arrival time of 430 buses at south China entrance of Uygur west street
In the embodiment, step S4, evaluating the reliability of the prediction result of the arrival time of the bus;
and obtaining the tolerance of the traveler to the deviation of the bus arrival time prediction result in a questionnaire survey mode. The investigation result shows that more than 85% of travelers consider that the prediction result is relatively accurate when the deviation degree value is less than 0.2. Therefore, based on the probability distribution model of the deviation degree of the predicted result of the bus arrival time, the probability that the deviation degree of the predicted result of the bus arrival time of each bus line stop in each evaluation time interval of different attribute labels of the southwest of the Huixime street in the ascending directions of 125 lines and 430 lines is less than 0.2 is calculated and used as the reliability evaluation index. Reliability index values of 125-way and 430-way ascending directions calculated based on historical data at the south of the Hui-Xin west street at the bus stop are shown in tables 12 and 13:
table 12 reliability of 125 bus arrival time prediction results at west street entrance to west hui-new
TABLE 13 reliability of prediction results of 430 bus arrival times at south China entrance of Hui New west street
Subjective feeling of a traveler on reliability is obtained through questionnaire survey, and a reliability evaluation grade division standard is formulated as shown in table 14:
TABLE 14 reliability rating Scale
| Degree of reliability | Ranim≥β2 | β2＞Ranim≥β1 | β1＞Ranim |
| Reliability evaluation level | Is relatively reliable | Is unreliable | Is very unreliable |
Therefore, the prediction results of the arrival time of 125-way and 430-way ascending directions at the south of the Huishen west street at the bus stop are relatively reliable within the evaluation time period of 05:30-05:45 of the working day.
In the embodiment, step S5 is a method for prompting the reliability of the prediction result of the arrival time of the bus;
on the basis that the predicted arrival time of the next bus is displayed in the existing electronic bus stop board and bus arrival time prediction service APP, the reliability evaluation grade of the prediction result is prompted by the predicted arrival time of different colors by matching the reliability numerical values corresponding to the attribute label, the evaluation time period, the bus line and the bus stop at the current moment. The correspondence between the reliability evaluation level and the cue color is shown in table 15:
TABLE 15 correspondence between reliability evaluation level and prompt color
| Degree of reliability | Ranim≥0.85 | 0.85＞Ranim≥0.60 | 0.60＞Ranim |
| Reliability evaluation level | Is relatively reliable | Is unreliable | Is very unreliable |
| Color of the prompt | Green colour | Orange colour | Red colour |
For example, a traveler selects to take the bus at the south of the west street of Huisn city of the bus stop within the time period of 05:30-05:45 of the working day, the predicted reliability of the arrival time in the ascending directions of 125 roads and 430 roads is 0.85 and 0.85 respectively, and the predicted reliability is relatively reliable level, so that the predicted result of the arrival time is displayed in green, and the predicted result of the arrival time of the traveler is prompted to be relatively reliable.
Although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the spirit and scope of the invention as defined in the appended claims. The techniques, shapes, and configurations not described in detail in the present invention are all known techniques.
Claims (4)
1. A method for evaluating and prompting the reliability of a bus arrival time prediction result specifically comprises the following steps:
s1: standardizing the predicted data of the bus arrival time;
s1.1: acquiring bus arrival time prediction data, including data fields of date, time, line number, vehicle number, driving direction, number of bus stations to arrive at the station, name of bus stations to arrive at the station, distance of bus stations to arrive at the station and predicted bus arrival time;
s2: evaluating the reliability of the prediction result of the bus arrival time;
s2.1: calculating the deviation of the prediction result of the arrival time of the bus, and acquiring the continuous arrival time prediction data and the actual arrival time data of the bus of a specific bus route in a specific evaluation period by associating the date, the time, the number of the bus, the driving direction and the data field of the name of the bus station to be arrived;
s2.2: calculating the actual travel time of the bus from the predicted time to the actual arrival time;
s2.3: calculating the deviation degree of the prediction result of the arrival time of the bus by combining the actual value and the predicted value of the arrival travel time of the bus;
s3: constructing a probability distribution model of the deviation degree of the bus arrival time prediction result; dividing each hour into 4 evaluation time periods by taking 15 minutes as a minimum unit according to actual bus operation time, giving time attribute labels such as working days, non-working days, holidays and the like and weather attribute labels such as rainfall, snowfall, strong wind and the like according to the particularity of each evaluation time period in different dates, respectively counting the deviation data of the bus arrival time prediction results of each bus route stop in each evaluation time period of different attribute labels from the beginning of providing bus arrival time prediction service to the present, and constructing a bus arrival time prediction result deviation probability distribution model:
the method comprises the steps of S4, evaluating the reliability of the bus arrival time prediction result, obtaining the tolerance of a traveler to the deviation of the bus arrival time prediction result in a questionnaire survey mode, defining that the prediction result is accurate when the deviation value is less than α, calculating the probability that the deviation of the bus arrival time prediction result of each bus route stop is less than α in each evaluation time period under different attribute labels based on a bus arrival time prediction result deviation probability distribution model, taking the probability as a reliability evaluation index, and establishing a reliability evaluation grade division standard based on the subjective feeling of the traveler to the reliability;
and S5, prompting the reliability of the predicted result of the arrival time of the bus, and prompting the reliability evaluation grade of the predicted result by the predicted arrival time of different colors by matching the attribute label of the current time, the evaluation time interval, the bus route and the reliability value corresponding to the stop on the basis of displaying the predicted arrival time of the next bus in the conventional electronic bus stop board and bus arrival time prediction service APP.
2. The method for evaluating and prompting the reliability of the bus arrival time prediction result according to claim 1, characterized in that:
in S2.2, the calculation formula is shown in formula (1):
Tijm arrive＝tijm arrive-tijm forecastformula (1)
In the formula, Tijm arriveThe actual travel time of the bus j reaching the stop m is the bus route i; t is tijm arriveThe actual arrival time of the bus j at the station m is the bus route i; t is tijm forecastAnd predicting the arrival time moment of the stop m for the bus j on the bus line i.
3. The method for evaluating and prompting the reliability of the bus arrival time prediction result according to claim 1, characterized in that:
in S2.3, the calculation formula is shown in formula (2):
in the formula, DijmPredicting the deviation degree of the arrival time prediction result of the bus j at the station m on the bus route i; t isijm arriveThe actual travel time of the bus j on the bus line i to the station m; t isijm forecastAnd predicting the travel time of the bus j to the stop m for the bus line i.
4. The method for evaluating and prompting the reliability of the bus arrival time prediction result according to claim 1, characterized in that: in step S3, the calculation formula is as shown in equation (3):
in the formula, Fanim(x) A probability distribution model of the deviation of the bus arrival time prediction result under the condition of an attribute label a evaluating time interval n bus line station i and station m; f. ofanim(x) As a function of the probability density of the degree of deviation.
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| CN112150802B (en) * | 2020-08-21 | 2022-04-05 | 同济大学 | Urban road grade division method based on ground bus running state reliability |
| CN112990658A (en) * | 2021-02-05 | 2021-06-18 | 福建工程学院 | Bus network timetable reliability calculation method for line simplification optimization |
| CN113658429A (en) * | 2021-08-11 | 2021-11-16 | 青岛海信网络科技股份有限公司 | Cooperative scheduling method and related device for bus corridor |
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