A business optimization scheduling method and system based on green cloud platform

Abstract

The present application discloses a business optimization scheduling method and system based on a green cloud platform, which relates to the technical field of business scheduling. The method includes: obtaining the number of passengers at each subway station, determining the subway operation route and the initial scheduling plan; extracting subway stations in the subway operation route as scheduling stations, obtaining the passenger behavior at the scheduling stations, and judging whether to change the initial scheduling plan; if the initial scheduling plan is changed, the interval duration of the subway vehicle is obtained according to the passenger behavior and recorded as the initial interval duration; obtaining the environmental conditions and passenger age distribution of each scheduling station, obtaining the scheduling station safety value, and obtaining the vehicle interval duration; obtaining the passenger distribution at the scheduling station, and determining the passenger's stay location; forming a real-time scheduling plan for the subway vehicle, and publishing it on the green cloud platform to guide passengers to take the vehicle. The present application improves the security of business optimization scheduling based on the green cloud platform.

Description

Technical Field

[0001] The present application relates to the technical field of business scheduling, and in particular to a business optimization scheduling method and system based on a green cloud platform. Background Art

[0002] Green platform refers to an environmentally friendly and sustainable development platform established and developed in the process of development. In the green platform, subway business is an important business. Subway is a type of urban rail transit line system, which refers to a fast, large-capacity, electric-powered rail transit built in the city. The subway is an urban rail transit system that covers all kinds of underground and above-ground road rights in urban areas, with high density and high capacity. At the same time, it is more environmentally friendly than other means of transportation. For subway companies, scheduling subway operations can more effectively improve resource utilization and service quality. However, the current business scheduling of subways is often only based on the number of subway passengers, and has not greatly improved the service quality, which makes passengers feel bad. At the same time, it increases the occurrence of accidents in the subway and increases the insecurity of business scheduling. Summary of the invention

[0003] The purpose of the present invention is to provide a business optimization scheduling method and system based on a green cloud platform to solve the problems raised in the above background technology.

[0004] In the first aspect, the present application provides a service optimization scheduling method based on a green cloud platform, which adopts the following technical solutions:

[0005] Obtain the number of passengers at each subway station, and determine the subway operation route and initial scheduling plan based on the number of passengers;

[0006] Extract subway stations in the subway operation route as dispatching stations, obtain passenger behavior at the dispatching stations, and determine whether to change the initial dispatching plan based on passenger behavior and the initial dispatching plan;

[0007] If the initial dispatching plan is changed, the interval between subway vehicles is obtained according to the passenger behavior and recorded as the initial interval;

[0008] Obtain the environmental conditions and passenger age distribution of each dispatching station, obtain the dispatching station safety value, and obtain the vehicle interval duration based on the dispatching station safety value and the initial interval duration;

[0009] Obtain the passenger distribution at the dispatching station and determine the passenger's stop location based on the passenger distribution;

[0010] A real-time dispatch plan for subway vehicles is formed based on the vehicle interval duration and stop locations, and announced on the green cloud platform to guide passengers.

[0011] Preferably, the step of obtaining the number of passengers at each subway station and determining the subway operation route and the initial scheduling plan according to the number of passengers is specifically as follows:

[0012] Get the area of ​​each subway station and set the corresponding number of passengers to be accommodated according to the station area;

[0013] Obtain the number of boarding passengers at each subway station, and mark the station where the number of boarding passengers exceeds the corresponding number of passengers that can be accommodated as a crowded station;

[0014] Count the number of passengers getting off at each station, and record the stations where the number of passengers getting off exceeds the corresponding number of passengers that can be accommodated as crowded stations;

[0015] Mark the crowded stations on the subway line map, connect the adjacent crowded stations without any stations in between, and get the crowded lines;

[0016] If the number of stations on a congested line reaches a preset threshold, a small-intersection route is established based on the congested line, and the subway start point to the end point is a large-intersection route;

[0017] The vehicle interval time of the major route is calculated based on the number of passengers at the non-crowded station and recorded as the major route time;

[0018] The number of remaining passengers is calculated based on the average number of people boarding each subway train at the crowded station. The vehicle interval time of the short-distance route is calculated based on the remaining number of passengers and recorded as the short-distance route time.

[0019] Preferably, the steps of extracting subway stations in the subway operation route as dispatching stations, obtaining passenger behavior at the dispatching stations, and judging whether to change the initial dispatching plan according to the passenger behavior and the initial dispatching plan are specifically as follows:

[0020] Get the real-time time point, and determine whether it is a peak period based on the real-time time point. If the real-time time point is a peak period, it is considered that the passengers have a high demand for riding speed, and the initial scheduling plan needs to be changed;

[0021] If the real-time time point is not a peak period, the passenger behavior is obtained, wherein the passenger behavior includes the real-time walking speed, viewing time frequency and facial expression;

[0022] The average walking speed of passengers during non-peak hours is calculated and recorded as the reference walking speed. If the real-time walking speed of a passenger exceeds the reference walking speed, it is recorded as the first passenger characteristic.

[0023] If the passenger's viewing time frequency reaches a preset frequency threshold, it is recorded as the second passenger feature;

[0024] Judging whether the passenger is anxious and impatient based on the passenger's facial expression, if the passenger is anxious and impatient, it is recorded as the third passenger characteristic;

[0025] The number of passengers having the first passenger characteristic, the second passenger characteristic, and the third passenger characteristic is counted to determine whether to change the initial scheduling plan.

[0026] Preferably, the step of counting the number of passengers having the first passenger characteristic, the second passenger characteristic, and the third passenger characteristic and determining whether to change the initial scheduling plan is specifically as follows:

[0027] Counting the number of passengers having any one of the first passenger characteristic, the second passenger characteristic and the third passenger characteristic and recording the number as the first number;

[0028] Counting the number of passengers having any two of the first passenger characteristic, the second passenger characteristic and the third passenger characteristic and recording the number as the second number;

[0029] Count the number of passengers having all the passenger characteristics among the first passenger characteristic, the second passenger characteristic and the third passenger characteristic and record the number as the third number;

[0030] The quantity weight ratios of the first quantity, the second quantity and the third quantity are respectively set, and the required quantity is calculated according to the first quantity, the second quantity, the third quantity and the corresponding quantity weight ratios;

[0031] If the demand quantity reaches the preset demand quantity threshold, it is determined to change the initial scheduling plan.

[0032] Preferably, if the initial scheduling plan is changed, the step of obtaining the interval duration of subway vehicles according to passenger behavior and recording it as the initial interval duration is specifically as follows:

[0033] If the real-time point is a peak period, obtain the time range of the peak period and calculate the minimum difference between the real-time point and the time range;

[0034] Find the corresponding first interval duration difference according to the correlation curve between the preset minimum difference and the first interval duration difference;

[0035] If the demand quantity reaches a preset demand quantity threshold, the corresponding first interval time difference is obtained by searching for the correlation curve between the preset demand quantity and the first interval time difference;

[0036] The vehicle interval time in the initial scheduling plan is extracted, and the initial interval time is obtained by subtracting the first interval time difference from the vehicle interval time in the initial scheduling plan.

[0037] Preferably, the steps of obtaining the environmental conditions and passenger age distribution of each dispatching station, obtaining the dispatching station safety value, and obtaining the vehicle interval duration according to the dispatching station safety value and the initial interval duration are specifically as follows:

[0038] Obtain the meteorological data of the dispatching station and determine whether changes have occurred inside the subway based on the meteorological data of the dispatching station;

[0039] If the meteorological data at the dispatching station causes changes inside the subway, then the degree of impact of the meteorological data on the inside of the subway is obtained;

[0040] Find the corresponding environmental safety value according to the preset correlation curve between the impact degree and the environmental safety value;

[0041] If the meteorological data at the dispatching station does not cause changes inside the subway, the environmental safety value is the highest value;

[0042] Obtain the passenger age, and obtain the accident safety value based on the passenger age and environmental safety value;

[0043] The personal safety value is obtained based on the number of passengers and meteorological data, and the dispatching station safety value is obtained by combining the environmental safety value, accident safety value and personal safety value;

[0044] According to the preset scheduling site safety value and the correlation curve of the second interval time difference, the corresponding second interval time difference is obtained;

[0045] The vehicle interval duration is obtained by subtracting the maximum second interval duration difference of each scheduling station from the initial interval duration.

[0046] Preferably, the step of obtaining the passenger age and obtaining the accident safety value according to the passenger age and the environmental safety value is specifically as follows:

[0047] Extract the personnel density in historical dangerous accidents and form a correlation curve between personnel density and accident probability;

[0048] The personnel density of the dispatching station is calculated according to the number of passengers at the dispatching station, and the corresponding accident probability is found according to the correlation curve of personnel density-accident probability;

[0049] Get the age ratio of passengers at the dispatch station, and get the number of old and young passengers based on the age ratio of passengers;

[0050] The number of passengers with limited mobility is determined based on passenger behavior, and the number of elderly and children is added to obtain the number of cared-for passengers;

[0051] The accident weight ratio of accident probability, number of caring people and environmental safety value is set, and the accident safety value is calculated based on the accident probability, number of caring people, environmental safety value and the corresponding accident weight ratio.

[0052] Preferably, the step of obtaining the personal safety value according to the number of passengers and the meteorological data is specifically:

[0053] Extract the historical air quality data of the subway and form the correlation curve between air quality and passenger quantity;

[0054] Obtain the initial air quality of the dispatching station, and find the primary air quality based on the air quality-passenger number correlation curve;

[0055] Extract temperature and humidity from meteorological data, and estimate passenger body temperature and passenger sweating amount based on the impact of temperature and humidity on passenger body temperature;

[0056] The temperature rise value at the dispatching station is calculated based on the number of passengers and their body temperature, and the humidity rise value at the dispatching station is calculated based on the amount of passenger sweat and the number of passengers;

[0057] The air quality of the dispatching station is obtained according to the temperature rise value, humidity rise value and primary air quality;

[0058] The personal safety value is obtained by searching the correlation curve between the preset dispatching station air quality and meteorological data.

[0059] Preferably, the step of obtaining the passenger distribution of the dispatching station and determining the passenger's stop location according to the passenger distribution is specifically as follows:

[0060] Obtain the distribution of the number of passengers in front of the subway car doors at the dispatching station and record it as the waiting distribution;

[0061] Obtain the distribution of the number of passengers in the subway car that is about to arrive at the station and record it as the car distribution;

[0062] Adjust the number of passengers in front of the doors of different subway cars according to the distribution of cars and waiting conditions;

[0063] If there are empty seats in the car, the caring person is moved to the door of the subway car corresponding to the empty seat to obtain the stop position;

[0064] If there are no empty seats in the carriage, it is determined that the non-caring person is moved and gets a stopping position.

[0065] In the second aspect, the application provides a service optimization and scheduling system based on a green cloud platform, which adopts the following technical solutions:

[0066] A business optimization and dispatching system based on a green cloud platform, comprising: an initial dispatching module, which obtains the number of passengers at each subway station, and determines the subway operation route and the initial dispatching plan according to the number of passengers;

[0067] The judgment and dispatching module extracts subway stations in the subway operation route as dispatching stations, obtains the passenger behavior at the dispatching stations, and determines whether to change the initial dispatching plan based on the passenger behavior and the initial dispatching plan;

[0068] Change the scheduling module. If the initial scheduling plan is changed, the interval between subway vehicles is obtained according to the passenger behavior and recorded as the initial interval;

[0069] The interval duration module obtains the environmental conditions and passenger age distribution of each dispatching station, obtains the dispatching station safety value, and obtains the vehicle interval duration based on the dispatching station safety value and the initial interval duration;

[0070] The stop location module obtains the passenger distribution at the dispatching station and determines the passenger's stop location based on the passenger distribution;

[0071] The announcement guidance module forms a real-time dispatch plan for subway vehicles based on the vehicle interval duration and stop locations, and announces it on the green cloud platform to guide passengers.

[0072] In summary, the present application includes at least one of the following beneficial technical effects:

[0073] 1. Preliminary scheduling plans are set up based on the number of subway passengers, and the routes and vehicle intervals of the subway's large and small routes are determined. The preliminary scheduling plans are judged based on passenger behavior to determine whether the preliminary scheduling plans need to be adjusted. Then, the safety of the station is judged based on the environmental conditions and the age distribution of passengers, and the passenger positions are determined based on the number of passengers in the subway car compartments. The scheduling plans are formed and published on the green platform. This can effectively reduce the accident rate of passengers taking the subway, improve the comfort of passengers taking the subway, and improve the safety of business optimization scheduling based on the green cloud platform.

[0074] 2. Determine whether passengers are anxious and impatient based on their real-time pace, viewing frequency, and facial expressions. According to the number of anxious passengers and their degree of anxiety, obtain passengers' demand for subway vehicle speed. Adjust the vehicle interval length according to passengers' travel needs, which can effectively meet passengers' needs and improve the effectiveness of business optimization scheduling based on the green cloud platform.

[0075] 3. According to the degree of impact of weather on the interior of the subway, the number of passengers, age distribution, the probability of accident risks caused by mobility problems, and the physiological changes of passengers caused by weather, which affect the temperature and humidity inside the subway and the air quality, the dispatching station can obtain the personal safety of passengers. At the same time, the staying positions of different passengers are determined according to the age distribution and the number of passengers in the car, which improves the comfort of business optimization dispatching based on the green cloud platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Figure 1It is a schematic diagram of the specific steps of an embodiment of a business optimization scheduling method based on a green cloud platform of the present invention.

[0077] Figure 2 It is a module connection diagram of an embodiment of a business optimization scheduling system based on a green cloud platform of the present invention. DETAILED DESCRIPTION

[0078] Below is a combination of the embodiments and Figure 1-Figure 2 The present invention is further described in detail, but the embodiments of the present invention are not limited thereto.

[0079] The present invention discloses a service optimization scheduling method based on a green cloud platform, which specifically comprises the following steps:

[0080] Step S1, obtaining the number of passengers at each subway station, and determining the subway operation route and initial scheduling plan according to the number of passengers.

[0081] Step S2, extracting subway stations in the subway operation route as dispatching stations, obtaining passenger behavior at the dispatching stations, and judging whether to change the initial dispatching plan based on the passenger behavior and the initial dispatching plan.

[0082] Step S3: If the initial scheduling plan is changed, the interval duration of subway vehicles is obtained according to the passenger behavior and recorded as the initial interval duration.

[0083] If the initial scheduling plan does not need to be changed, the vehicle interval duration in the initial scheduling plan is extracted as the initial interval duration.

[0084] Step S4, obtaining the environmental conditions and passenger age distribution of each dispatching station, obtaining the dispatching station safety value, and obtaining the vehicle interval duration according to the dispatching station safety value and the initial interval duration.

[0085] Step S5, obtaining the passenger distribution of the dispatching site, and determining the passenger's stop location according to the passenger distribution.

[0086] Step S6, forming a real-time dispatching plan for subway vehicles based on the vehicle interval duration and stop position, and publishing it on the green cloud platform to guide passengers to board the train.

[0087] In actual use, the subway, as the main means of transportation in the city, has greatly reduced the city's traffic burden. How to dispatch subway vehicles to provide passengers with a higher travel experience has become an important issue in subway operation. In existing technologies, we found that the interval between vehicles is shorter during peak hours in the morning and evening, and the interval between vehicles is longer at other times. It is adjusted according to the number of passengers, and does not take into account other aspects of the passenger experience. Therefore, the vehicle scheduling is inaccurate. For example, if a passenger is anxious, the waiting time is shorter. At this time, the subway vehicle should be dispatched faster to reduce the impact on the passenger's time. When the passenger is not in a hurry, the interval between vehicles can be appropriately increased to save resources.

[0088] The steps to obtain the number of passengers at each subway station and determine the subway operation route and initial scheduling plan based on the number of passengers are as follows:

[0089] Step S11, obtaining the area of ​​each subway station, and setting the corresponding number of passengers to be accommodated according to the station area.

[0090] The larger the station area, the more passengers it can accommodate. Set the appropriate number of passengers based on the station area. For example, station A can accommodate up to 1,000 people, but it is not crowded and more comfortable when accommodating 500 people. Therefore, the corresponding number of passengers for station A is 500.

[0091] Step S12, obtaining the number of boarding passengers at each subway station, and marking the station where the number of boarding passengers exceeds the corresponding number of passengers that can be accommodated as a crowded station.

[0092] Step S13, counting the number of passengers getting off at each station, and recording the stations where the number of passengers getting off exceeds the corresponding number of passengers that can be accommodated as crowded stations.

[0093] Step S14, marking the crowded stations on the subway line map, connecting the adjacent crowded stations without any stations in between, and obtaining the crowded lines.

[0094] Step S15: If the number of stations on the crowded line reaches a preset threshold of the number of stations, a small route is established according to the crowded line, and the route from the subway start point to the end point is a large route.

[0095] Step S16, calculating the vehicle interval time of the large route according to the number of passengers at the non-crowded station and recording it as the large route time.

[0096] The more passengers there are, the shorter the vehicle interval time is. Therefore, the vehicle interval time can be calculated based on the number of passengers.

[0097] Step S17, the number of remaining passengers is calculated according to the average number of passengers boarding each subway car at the crowded station, and the vehicle interval time of the short-distance route is calculated according to the remaining number of passengers and recorded as the short-distance route time.

[0098] Passengers who take the small route vehicle can also take the large route vehicle to reach their destination, so after the large route vehicle runs, it will take away a group of passengers. In this way, the number of passengers at the station will decrease. At this time, the small route determines the vehicle interval length based on the remaining number of passengers.

[0099] In actual use, the large and small route operation mode of the subway is a flexible operation mode adopted to improve operation efficiency and relieve passenger flow pressure. The large route refers to the operation mode in which the train runs from the starting station of the line to the terminal station and completes the entire journey. The small route refers to the operation mode in which the train does not reach the terminal station during operation, but turns back at an intermediate station and only covers part of the line. Through the large and small route operation, the train operation plan can be flexibly adjusted according to the passenger flow characteristics of different sections, the operation efficiency can be improved, and the passenger flow pressure during peak hours can be relieved. The crowded stations are determined according to the number of passengers getting on and off. For example, there are many passengers at station B, so the passengers waiting at station B are relatively crowded. There are not many passengers getting on at station D, but there are many passengers getting off, so more vehicles need to stop to allow passengers to get off. After obtaining continuous crowded stations, a crowded line is formed. If the station number threshold is set to 5 stations in advance, the small route will be opened only when the crowded line reaches 5 stations. If the crowded line has only 3 stations, it is a waste of resources to open the small route, so the small route will not be opened for the time being.

[0100] The steps of extracting subway stations in the subway operation route as dispatching stations, obtaining passenger behavior at the dispatching stations, and judging whether to change the initial dispatching plan according to the passenger behavior and the initial dispatching plan are as follows:

[0101] Step S21, obtain the real-time time point, and determine whether it is a peak period based on the real-time time point. If the real-time time point is a peak period, it is considered that the passengers have a high demand for riding speed and the initial scheduling plan needs to be changed.

[0102] Step S22, if the real-time time point is not a peak period, the passenger behavior is obtained, and the passenger behavior includes real-time walking speed, viewing time frequency and facial expression.

[0103] Step S23, counting the average walking speed of passengers during non-peak hours and recording it as a reference walking speed, if the real-time walking speed of the passenger exceeds the reference walking speed, it is recorded as the first passenger characteristic.

[0104] Step S24: If the passenger's viewing time frequency reaches a preset frequency threshold, it is recorded as a second passenger feature.

[0105] Step S25, judging whether the passenger is anxious and irritable based on the passenger's facial expression, and if the passenger is anxious and irritable, it is recorded as the third passenger characteristic.

[0106] Taking the anxious and impatient facial expression as the reference expression, whether the passenger is anxious and impatient is confirmed based on the similarity between the passenger's facial expression and the reference expression.

[0107] Step S26, counting the number of passengers having the first passenger characteristics, the second passenger characteristics and the third passenger characteristics, and determining whether to change the initial scheduling plan.

[0108] The situations of different scheduling sites are different. Whether to change the initial scheduling plan is determined based on the average number of all scheduling sites.

[0109] In actual use, if it is during peak hours, most passengers will be in a hurry to get to and from get off work, so it is necessary to consider the passengers' demand for subway speed and adjust the interval time of the vehicles appropriately. During non-peak hours, if a large number of passengers are in a hurry to take the bus, the scheduling plan also needs to be adjusted to meet the needs of passengers. For example, some concerts and other activities, when approaching the entry time, some passengers will be in a hurry. At this time, the scheduling plan can be adjusted to reduce the time impact of subway operation on passengers. Anxious passengers usually walk faster and more hurriedly, and will trot or walk quickly to reach their destination as soon as possible. If passengers frequently check their watches, mobile phones or other time display devices, it means that they are sensitive to time and are in a hurry. Anxious passengers will also show anxious, nervous or impatient expressions, such as frowning, staring or pursing their lips.

[0110] The steps of counting the number of passengers having the first passenger characteristic, the second passenger characteristic, and the third passenger characteristic and determining whether to change the initial dispatching plan are specifically as follows:

[0111] Step S261, counting the number of passengers having any one of the first passenger characteristic, the second passenger characteristic and the third passenger characteristic and recording it as a first number.

[0112] Step S262, counting the number of passengers having any two of the first passenger characteristic, the second passenger characteristic and the third passenger characteristic and recording the number as the second number.

[0113] Step S263, counting the number of passengers having all the first passenger characteristics, the second passenger characteristics and the third passenger characteristics and recording it as a third number.

[0114] Step S264, respectively set the quantity weight ratios of the first quantity, the second quantity and the third quantity, and calculate the required quantity according to the first quantity, the second quantity, the third quantity and the corresponding quantity weight ratios.

[0115] Step S265: If the demand quantity reaches a preset demand quantity threshold, it is determined whether to change the initial scheduling plan.

[0116] In actual use, if only one or two passengers are anxious, scheduling plans for these one or two passengers will obviously cause a lot of resource waste, so it is necessary to count the number of passengers with anxious characteristics. The more anxious characteristics a passenger has, the greater the probability that the passenger is anxious and the greater the degree of anxiety. The more passengers with anxious characteristics there are, the shorter the interval time for reducing vehicle operation, and the higher the demand for vehicle scheduling. For example, if the number of people in the subway is not crowded, but most passengers are anxious, and the number reaches the threshold of the required number, the interval time between vehicles will be reduced and the vehicle will be dispatched more quickly. This can respond to emergencies in a timely manner and reduce the impact of vehicle scheduling on passengers.

[0117] If the initial scheduling plan is changed, the steps to obtain the interval time of subway vehicles according to passenger behavior and record it as the initial interval time are as follows:

[0118] Step S31, if the real time point is a peak period, then the time range of the peak period is obtained, and the minimum difference between the real time point and the time range is calculated.

[0119] Step S32: searching for the corresponding first interval duration difference according to the correlation curve between the preset minimum difference and the first interval duration difference.

[0120] Step S33: if the demand quantity reaches a preset demand quantity threshold, the corresponding first interval time difference is obtained by searching for the preset correlation curve between the demand quantity and the first interval time difference.

[0121] Step S34, extracting the vehicle interval time in the initial scheduling plan, and subtracting the first interval time difference from the vehicle interval time in the initial scheduling plan to obtain the initial interval time.

[0122] In actual use, if it is during peak hours, then considering that passengers need to clock in for work in time and go home in time to handle personal matters, such as cooking and picking up children, then the passengers have a higher demand for vehicle speed. The shorter the interval of vehicle dispatch, the greater the impact of vehicle dispatch on passengers. For example, the time range of peak hours is from 7 am to 9 am, so the closer to 7 or 9 am, the less demand passengers have for vehicle dispatch speed. During non-peak hours, the corresponding interval duration is obtained according to the urgency of all passengers. The greater the number of passenger demands, the shorter the vehicle interval duration should be. For example, when the number of passenger demands is 50, the first interval duration difference is 30 seconds. The interval duration of subway vehicles in the initial dispatch plan is 4 minutes, minus 30 seconds, it is 3 minutes and 30 seconds. If the number of passenger demands is 100, the first interval duration difference is 1 minute, and the initial interval duration is 3 minutes.

[0123] The steps of obtaining the environmental conditions and passenger age distribution of each dispatching station, obtaining the dispatching station safety value, and obtaining the vehicle interval duration according to the dispatching station safety value and the initial interval duration are as follows:

[0124] Step S41, obtaining the meteorological data of the dispatching station, and judging whether changes have been caused inside the subway according to the meteorological data of the dispatching station.

[0125] In some rainy and snowy weather, passengers will bring water into the subway station, resulting in more water stains on the ground inside the subway station. However, sunny and cloudy weather will not bring extra things into the subway and is not considered to cause changes inside the subway.

[0126] Step S42: If the meteorological data of the dispatching station causes changes inside the subway, the degree of influence of the meteorological data on the inside of the subway is obtained.

[0127] The degree of influence depends on the severity of rain and snow and the number of passengers. For example, for the same number of passengers, the rainwater on the subway floor is more when it rains heavily than when it rains lightly. On the same rainy day, the more passengers there are, the greater the amount of rainwater brought in.

[0128] Step S43, searching for the corresponding environmental safety value according to the preset correlation curve between the impact degree and the environmental safety value.

[0129] The greater the impact, the less safe it is; the more rain there is, the more likely it is that passengers will fall.

[0130] Step S44: If the meteorological data of the dispatching station does not cause changes inside the subway, the environmental safety value is the highest value.

[0131] Step S45, obtaining the age of the passenger, and obtaining the accident safety value according to the age of the passenger and the environmental safety value.

[0132] Step S46, obtaining a personal safety value based on the number of passengers and meteorological data, and obtaining a dispatch station safety value by combining the environmental safety value, the accident safety value and the personal safety value.

[0133] The weight ratios corresponding to the environmental safety value, accident safety value and personal safety value are set respectively, and the dispatching site safety value is calculated according to the weight ratio.

[0134] Step S47, searching for the corresponding second interval time difference according to the preset association curve between the scheduling site safety value and the second interval time difference.

[0135] The higher the safety value, the smaller the second interval time difference is, and the longer the vehicle interval time is.

[0136] Step S48, the vehicle interval duration is obtained by subtracting the maximum second interval duration difference of each scheduling station from the initial interval duration.

[0137] Because the safety values ​​of different dispatching sites are different, the risk is higher, that is, the site with the largest interval time difference is used as the basis for dispatching.

[0138] In actual use, the external environment will affect the interior of the subway, thereby increasing the risk of passenger accidents. For example, rainy and snowy days will make the ground more slippery. With the same number of passengers, crowding and pushing are more likely to cause accidents when the ground is slippery. Therefore, when the weather affects subway safety, it is necessary to reduce the vehicle interval time to reduce the number of passengers at the station and improve passenger safety. At the same time, it is not only the weather that affects passenger safety, but also the different age distribution of passengers, which will affect passenger safety and cause changes in the safety value of the dispatching station.

[0139] The steps for obtaining the passenger age and obtaining the accident safety value based on the passenger age and the environmental safety value are as follows:

[0140] Step S451, extracting the personnel density in historical dangerous accidents to form a correlation curve between personnel density and accident probability.

[0141] Step S452, the personnel density of the dispatching station is calculated according to the number of passengers at the dispatching station, and the corresponding accident probability is found according to the correlation curve of personnel density-accident probability.

[0142] Step S453, obtain the age ratio of passengers at the dispatching station, and obtain the number of old and young passengers based on the age ratio of passengers.

[0143] Step S454, the number of passengers with limited mobility is determined based on the passenger behavior, and the number of elderly and children is added to obtain the number of cared-for persons.

[0144] Determine whether a passenger has mobility difficulties based on his or her walking posture and speed. For example, a foot injury or blindness will affect the passenger's walking posture and speed.

[0145] Step S455, setting the accident weight ratio of the accident probability, the number of caring people and the environmental safety value, and calculating the accident safety value according to the accident probability, the number of caring people, the environmental safety value and the corresponding accident weight ratio.

[0146] In actual use, on the one hand, the number of passengers will increase the density of people, that is, the number of people per square meter, so it will increase the probability of accidents such as trampling and falling. On the other hand, if the number of elderly, children and passengers with limited mobility in the crowd increases, because the space in the subway car is relatively narrow and the passenger density is high, this environment increases the possibility of friction and collision between passengers, and the elderly, children and passengers with limited mobility have low reaction and avoidance capabilities, making accidents more likely to occur. If the environmental conditions are even worse at this time, the risk of accidents will be further increased, resulting in a decrease in the accident safety value.

[0147] The steps to obtain the personal safety value based on the number of passengers and meteorological data are as follows:

[0148] Step S461, extracting historical air quality data of the subway to form an air quality-passenger quantity correlation curve.

[0149] Step S462, obtaining the initial air quality of the dispatching station, and finding the primary air quality according to the air quality-passenger number correlation curve.

[0150] Step S463, extracting the temperature and humidity from the meteorological data, and estimating the passenger's body temperature and the amount of sweat produced by the passenger based on the impact of the temperature and humidity on the passenger's body temperature.

[0151] Under different external temperatures and humidities, the average body temperature and average sweat volume of passengers are different. Therefore, the passenger body temperature and average sweat volume are estimated based on the average body temperature and average sweat volume.

[0152] Step S464, the temperature rise value of the dispatching station is calculated according to the number of passengers and the body temperature of the passengers, and the humidity rise value of the dispatching station is calculated according to the amount of passenger sweat and the number of passengers.

[0153] Step S465, obtaining the dispatching station air quality according to the temperature rise value, humidity rise value and primary air quality.

[0154] Step S466, obtaining the personal safety value according to the preset correlation curve between the dispatch station air quality and the meteorological data.

[0155] In actual use, in addition to the physical damage caused to passengers by crowding, friction, etc., air quality will not only affect the comfort of passengers, but also their personal safety. Poor air quality will cause passengers to feel stuffy and uncomfortable, and may even cause symptoms such as dizziness and nausea, thus affecting their travel experience. Passengers who are exposed to the heavily polluted subway environment for a long time will face health risks such as respiratory diseases and allergic reactions. As the number of passengers increases, the density of people in subway cars and station halls will also increase accordingly. High-density people will exhale more carbon dioxide and may release other pollutants, such as bacteria and viruses, thereby aggravating air pollution in the subway. The temperature and humidity in the subway car will also affect the air quality. The high temperature and high humidity environment is conducive to the reproduction of microorganisms and the spread of pollutants. Passengers will release moisture in the subway car through breathing, sweating, etc., which will increase the humidity in the car. When passengers move, stand or wait in the subway station, they will release heat and moisture through skin heat dissipation and breathing. The heat dissipation and perspiration of passengers are related to the external environment. In summer, the heat dissipation of passengers is significantly higher than in winter. Therefore, the impact of passengers on the temperature and humidity of the subway can be obtained based on the weather, and the air quality can be obtained. When the air quality is poor, in order to reduce the discomfort of passengers and reduce the risk of illness of passengers, the interval between vehicles can be reduced.

[0156] The steps of obtaining the passenger distribution of the dispatching station and determining the passenger's stop location according to the passenger distribution are as follows:

[0157] Step S51, obtaining the distribution of the number of passengers in front of the subway car doors at the dispatching station and recording it as the waiting distribution.

[0158] Step S52, obtaining the distribution of the number of passengers in the subway car that is about to arrive at the station and recording it as the car distribution.

[0159] Step S53, adjusting the number of passengers in front of doors of different subway cars according to the car distribution and waiting distribution.

[0160] Step S54: If there are empty seats in the carriage, the caring person is moved to the door of the subway carriage corresponding to the empty seat to obtain a stop position.

[0161] Step S55: If there are no empty seats in the carriage, it is determined that the non-caring person is moving and a stop position is obtained.

[0162] In actual use, when taking the subway, there will be staff to guide passengers to move to avoid all passengers gathering in front of a subway car door. The existing guidance almost always evenly distributes passengers to the door of each car. Such position guidance cannot solve the problem of getting on and off the train well, because the distribution of passengers in the subway car is also uneven. For example, there are more passengers in cars C and E, while there are fewer people in cars A and G. When confirming the passenger position, naturally there are more passengers in front of the doors of cars A and G, and fewer passengers in front of the doors of cars C and E. When there are vacancies in the car, the elderly, children and passengers with limited mobility are guided to the car with seats first. When there are no vacancies in the car, other passengers are guided to move first.

[0163] A business optimization and scheduling system based on a green cloud platform, by applying a business optimization and scheduling method based on a green cloud platform as described above, includes: an initial scheduling module, which obtains the number of passengers at each subway station, and determines the subway operation route and initial scheduling plan based on the number of passengers.

[0164] The judgment scheduling module extracts subway stations in the subway operation route as scheduling stations, obtains passenger behavior at the scheduling stations, and determines whether to change the initial scheduling plan based on passenger behavior and the initial scheduling plan.

[0165] Change the scheduling module. If the initial scheduling plan is changed, the interval duration of subway vehicles is obtained according to the passenger behavior and recorded as the initial interval duration.

[0166] The interval duration module obtains the environmental conditions and passenger age distribution of each dispatching station, obtains the dispatching station safety value, and obtains the vehicle interval duration based on the dispatching station safety value and the initial interval duration.

[0167] The stop location module obtains the passenger distribution at the dispatching station and determines the passenger's stop location based on the passenger distribution.

[0168] The announcement guidance module forms a real-time dispatch plan for subway vehicles based on the vehicle interval duration and stop locations, and announces it on the green cloud platform to guide passengers.

[0169] In actual use, the initial dispatching plan is set according to the number of passengers, and then the subway dispatching plan is adjusted according to the passengers' travel needs. The safety level of the dispatching station is determined according to the age distribution of passengers, and the interval time of vehicle dispatch is further adjusted according to the safety level. The passenger's stop position is determined according to the passenger distribution, and the dispatching plan is formed in combination with the vehicle interval time, and announced on the platform to guide passengers to take the bus.

[0170] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A business optimization scheduling method based on a green cloud platform, characterized in that: The following steps are involved: Obtain the number of passengers at each subway station, and determine the subway operation route and initial scheduling plan based on the number of passengers; Extract subway stations in the subway operation route as dispatching stations, obtain passenger behavior at the dispatching stations, and determine whether to change the initial dispatching plan based on passenger behavior and the initial dispatching plan; If the initial dispatching plan is changed, the interval between subway vehicles is obtained according to the passenger behavior and recorded as the initial interval; Obtain the environmental conditions and passenger age distribution of each dispatching station, obtain the dispatching station safety value, and obtain the vehicle interval duration based on the dispatching station safety value and the initial interval duration; The steps of obtaining the environmental conditions and passenger age distribution of each dispatching station, obtaining the dispatching station safety value, and obtaining the vehicle interval duration according to the dispatching station safety value and the initial interval duration are specifically as follows: Obtain the meteorological data of the dispatching station and determine whether changes have occurred inside the subway based on the meteorological data of the dispatching station; If the meteorological data at the dispatching station causes changes inside the subway, then the degree of impact of the meteorological data on the inside of the subway is obtained; Find the corresponding environmental safety value according to the preset correlation curve between the impact degree and the environmental safety value; If the meteorological data at the dispatching station does not cause changes inside the subway, the environmental safety value is the highest value; Obtain the passenger age, and obtain the accident safety value based on the passenger age and environmental safety value; The personal safety value is obtained based on the number of passengers and meteorological data, and the dispatching station safety value is obtained by combining the environmental safety value, accident safety value and personal safety value; According to the preset scheduling site safety value and the correlation curve of the second interval time difference, the corresponding second interval time difference is obtained; The vehicle interval duration is obtained by subtracting the maximum second interval duration difference of each dispatching station from the initial interval duration; The steps of obtaining the passenger age and obtaining the accident safety value according to the passenger age and the environmental safety value are specifically as follows: Extract the personnel density in historical dangerous accidents and form a correlation curve between personnel density and accident probability; The personnel density of the dispatching station is calculated according to the number of passengers at the dispatching station, and the corresponding accident probability is found according to the correlation curve of personnel density-accident probability; Get the age ratio of passengers at the dispatch station, and get the number of old and young passengers based on the age ratio of passengers; The number of passengers with limited mobility is determined based on passenger behavior, and the number of elderly and children is added to obtain the number of cared-for passengers; Set the accident weight ratio of accident probability, number of caring people and environmental safety value, and calculate the accident safety value based on the accident probability, number of caring people, environmental safety value and the corresponding accident weight ratio; The step of obtaining the personal safety value according to the number of passengers and the meteorological data is specifically as follows: Extract the historical air quality data of the subway and form the correlation curve between air quality and passenger quantity; Obtain the initial air quality of the dispatching station, and find the primary air quality based on the air quality-passenger number correlation curve; Extract temperature and humidity from meteorological data, and estimate passenger body temperature and passenger sweating amount based on the impact of temperature and humidity on passenger body temperature; The temperature rise value at the dispatching station is calculated based on the number of passengers and their body temperature, and the humidity rise value at the dispatching station is calculated based on the amount of passenger sweat and the number of passengers; The air quality of the dispatching station is obtained according to the temperature rise value, humidity rise value and primary air quality; The personal safety value is obtained by searching the preset correlation curve between the dispatch station air quality and meteorological data; Obtain the passenger distribution at the dispatching station and determine the passenger's stop location based on the passenger distribution; A real-time dispatch plan for subway vehicles is formed based on the vehicle interval duration and stop locations, and announced on the green cloud platform to guide passengers.

2. According to the green cloud platform-based service optimization scheduling method of claim 1, it is characterized in that: The steps of obtaining the number of passengers at each subway station and determining the subway operation route and the initial scheduling plan according to the number of passengers are specifically as follows: Get the area of ​​each subway station and set the corresponding number of passengers to be accommodated according to the station area; Obtain the number of boarding passengers at each subway station, and mark the station where the number of boarding passengers exceeds the corresponding number of passengers that can be accommodated as a crowded station; Count the number of passengers getting off at each station, and record the stations where the number of passengers getting off exceeds the corresponding number of passengers that can be accommodated as crowded stations; Mark the crowded stations on the subway line map, connect the adjacent crowded stations without any stations in between, and get the crowded lines; If the number of stations on a congested line reaches a preset threshold, a small-intersection route is established based on the congested line, and the subway start point to the end point is a large-intersection route; The vehicle interval time of the major route is calculated based on the number of passengers at the non-crowded station and recorded as the major route time; The number of remaining passengers is calculated based on the average number of people boarding each subway train at the crowded station. The vehicle interval time of the short-distance route is calculated based on the remaining number of passengers and recorded as the short-distance route time.

3. A method for optimizing and scheduling services based on a green cloud platform according to claim 2, characterized in that: The steps of extracting subway stations in the subway operation route as dispatching stations, obtaining passenger behavior at the dispatching stations, and determining whether to change the initial dispatching plan according to the passenger behavior and the initial dispatching plan are specifically as follows: Get the real-time time point, and determine whether it is a peak period based on the real-time time point. If the real-time time point is a peak period, it is considered that the passengers have a high demand for riding speed, and the initial scheduling plan needs to be changed; If the real-time time point is not a peak period, the passenger behavior is obtained, wherein the passenger behavior includes the real-time walking speed, viewing time frequency and facial expression; The average walking speed of passengers during non-peak hours is calculated and recorded as the reference walking speed. If the real-time walking speed of a passenger exceeds the reference walking speed, it is recorded as the first passenger characteristic. If the passenger's viewing time frequency reaches a preset frequency threshold, it is recorded as the second passenger feature; Judging whether the passenger is anxious and impatient based on the passenger's facial expression, if the passenger is anxious and impatient, it is recorded as the third passenger characteristic; The number of passengers having the first passenger characteristic, the second passenger characteristic, and the third passenger characteristic is counted to determine whether to change the initial scheduling plan.

4. The service optimization scheduling method based on the green cloud platform according to claim 3 is characterized in that: The step of counting the number of passengers having the first passenger characteristic, the second passenger characteristic, and the third passenger characteristic to determine whether to change the initial scheduling plan is specifically as follows: Counting the number of passengers having any one of the first passenger characteristic, the second passenger characteristic and the third passenger characteristic and recording the number as the first number; Counting the number of passengers having any two of the first passenger characteristic, the second passenger characteristic and the third passenger characteristic and recording the number as the second number; Count the number of passengers having all the passenger characteristics among the first passenger characteristic, the second passenger characteristic and the third passenger characteristic and record the number as the third number; The quantity weight ratios of the first quantity, the second quantity and the third quantity are respectively set, and the required quantity is calculated according to the first quantity, the second quantity, the third quantity and the corresponding quantity weight ratios; If the demand quantity reaches the preset demand quantity threshold, it is determined to change the initial scheduling plan.

5. The service optimization scheduling method based on the green cloud platform according to claim 4 is characterized in that: If the initial scheduling plan is changed, the steps of obtaining the interval duration of subway vehicles according to passenger behavior and recording it as the initial interval duration are specifically as follows: If the real-time point is a peak period, obtain the time range of the peak period and calculate the minimum difference between the real-time point and the time range; Find the corresponding first interval duration difference according to the correlation curve between the preset minimum difference and the first interval duration difference; If the demand quantity reaches a preset demand quantity threshold, the corresponding first interval time difference is obtained by searching for the correlation curve between the preset demand quantity and the first interval time difference; The vehicle interval time in the initial scheduling plan is extracted, and the initial interval time is obtained by subtracting the first interval time difference from the vehicle interval time in the initial scheduling plan.

6. A method for optimizing and scheduling services based on a green cloud platform according to claim 5, characterized in that: The step of obtaining the passenger distribution of the dispatching station and determining the passenger's stop location according to the passenger distribution is specifically as follows: Obtain the distribution of the number of passengers in front of the subway car doors at the dispatching station and record it as the waiting distribution; Obtain the distribution of the number of passengers in the subway car that is about to arrive at the station and record it as the car distribution; Adjust the number of passengers in front of the doors of different subway cars according to the distribution of cars and waiting conditions; If there are empty seats in the car, the caring person is moved to the door of the subway car corresponding to the empty seat to obtain the stop position; If there are no empty seats in the carriage, it is determined that the non-caring person is moved and gets a stopping position.

7. A business optimization and scheduling system based on a green cloud platform, characterized in that: By applying a service optimization scheduling method based on a green cloud platform as described in any one of claims 1 to 6, the method comprises: The initial scheduling module obtains the number of passengers at each subway station and determines the subway operation route and initial scheduling plan based on the number of passengers; The judgment and dispatching module extracts subway stations in the subway operation route as dispatching stations, obtains the passenger behavior at the dispatching stations, and determines whether to change the initial dispatching plan based on the passenger behavior and the initial dispatching plan; Change the scheduling module. If the initial scheduling plan is changed, the interval between subway vehicles is obtained according to the passenger behavior and recorded as the initial interval; The interval duration module obtains the environmental conditions and passenger age distribution of each dispatching station, obtains the dispatching station safety value, and obtains the vehicle interval duration based on the dispatching station safety value and the initial interval duration; The stop location module obtains the passenger distribution at the dispatching station and determines the passenger's stop location based on the passenger distribution; The announcement guidance module forms a real-time dispatch plan for subway vehicles based on the vehicle interval duration and stop locations, and announces it on the green cloud platform to guide passengers.

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