CN109544901A - A kind of Research on Intelligent Scheduling of Public Traffic Vehicles method and device based on history passenger flow big data - Google Patents
A kind of Research on Intelligent Scheduling of Public Traffic Vehicles method and device based on history passenger flow big data Download PDFInfo
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- CN109544901A CN109544901A CN201811419978.6A CN201811419978A CN109544901A CN 109544901 A CN109544901 A CN 109544901A CN 201811419978 A CN201811419978 A CN 201811419978A CN 109544901 A CN109544901 A CN 109544901A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/20—Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
- G08G1/202—Dispatching vehicles on the basis of a location, e.g. taxi dispatching
Abstract
The invention discloses a kind of Research on Intelligent Scheduling of Public Traffic Vehicles method and devices based on history passenger flow big data, and this method comprises the following steps: step 1, obtaining public transport company's basic data collection；Step 2, history passenger flow big data is obtained；Step 3, history passenger flow large data sets are handled: step 4, obtains the Time-distribution of passenger flow；Step 5, schedule is obtained；Step 6, schedule is intelligently generated with vehicle and is arranged an order according to class and grade；Step 7, the output of arranging an order according to class and grade that will be automatically generated.The present invention more close to passenger flow rule, suits the trip requirements of citizen, when passenger flow is more, arranges more transport power, to guarantee service level, after passenger flow reduction, cuts down transport power in time, economizes on resources；The level of resources utilization and citizen are improved to the satisfaction of bus trip, reduces the operation cost of car operation company, while can also indirectly reduce the consumption of vehicle exhaust emission and electric power or fuel source, optimizes the treatment effeciency to traffic incident.
Description
Technical field
The present invention relates to intelligent transportation research fields, especially public transport scheduling method, and in particular to one kind is based on history visitor
Flow the Research on Intelligent Scheduling of Public Traffic Vehicles method and device of big data.
Background technique
The traditional bus operation plan scheduling method in China is based primarily upon the operation feelings of the experience and history of practitioner
Condition, with the fast development of public transport and the increase of public trip population, previous public transport is arranged an order according to class and grade, and to be no longer satisfied day new
, there is the typical unmatched situation of transport power freight volume in month different bus trip demand, not only influences the seating of passenger peak period
Experience, also causes a large amount of wasting of resources in the flat peak phase.Therefore it provides a kind of more close to passenger flow rule based on history passenger flow
The Research on Intelligent Scheduling of Public Traffic Vehicles method of big data is particularly important.
Summary of the invention
For overcome the deficiencies in the prior art, the purpose of the present invention is to provide a kind of public affairs based on history passenger flow big data
Smart shift scheduling method is handed over, this method more close to passenger flow rule, suits the trip requirements of citizen.
In order to achieve the above objectives, the present invention is achieved by the following technical solutions.
Step 1, obtain public transport company's basic data collection: the basic data collection includes certain railroad embankment time, Si Jipei
Standby quantity, vehicle are equipped with the site location information of quantity and route；
Step 2, it obtains the history passenger flow big data of a couple of days: history passenger flow data is acquired by vehicle-mounted passenger flow acquisition device,
GPS position information when public transport switch gate time, passenger flow of getting on the bus number including certain route, passenger flow of getting off number, public transport switch gate, vehicle
Unique number etc..Step 1 and step 2 do not have sequencing relationship.
Step 3, the history passenger flow large data sets in step 2 are handled, removes wrong data, and fill in the blanks
Data:
Step 31, wrong data is removed, the specific steps are as follows:
(1) if the loss of data of GPS position information described in certain passenger flow data, give up this passenger flow data；
(2) site location information is matched by the GPS position information, if the GPS location and matched site location
Distance be greater than 5-15 meter, then give up this passenger flow data, otherwise with the corresponding GPS position information of site location information replacement；
(3) if two or a plurality of identical passenger flow data occurs in history passenger flow data concentration, retain
A passenger flow data therein, others are deleted；
Step 32, fill in the blanks data: to avoid the passenger flow data given up from influencing the passenger flow data collection, causing with partially general
Full defect, same time point or time of closest approach point, the effective of same site position record to fill in the date before use
The blank of passenger flow data is given up；
Step 4, the average volume of the flow of passengers Q for counting each period in a couple of days, obtains the Time-distribution of passenger flow；
Step 5, quantity, railroad embankment time and history passenger flow big data are equipped with according to the vehicle of public transport company, and
The Time-distribution of the passenger flow obtains schedule；
Step 6, schedule is intelligently generated with vehicle and is arranged an order according to class and grade；
Step 7, by the output of arranging an order according to class and grade automatically generated to public transportation management system,；
Preferably, schedule is obtained in the step 5, the specific steps are as follows:
Step 51, obtain the one way service time: by the history passenger flow big data, count in a couple of days a certain shift some
The average value of the time difference of the switch gate time at the first and last station of period obtains the one way service time t of time period vehicle, from
And obtain the one way service time of vehicle in different time periods；
Step 52, it obtains the turnaround time of vehicle: by the history passenger flow big data, counting a certain shift in a couple of days
The average down time of a period terminal, to obtain the turnaround time T, T=t of time period vehicleUplink+tUplink is stopped+tDownlink+
tDownlink is stopped, wherein tUplinkAnd tDownlinkThe respectively one way runing time of uplink and downlink, tUplink is stoppedAnd tDownlink is stoppedRespectively uplink and downlink
Terminal down time, the turnaround time are that vehicle is completed the time required for the uplink and downlink of a cycle of operation, and then is obtained
To car cycle in different time periods；The down time is to determine the vehicle driving down by the unique number of the vehicle
(uplink) reaches home time difference of time and back to back uplink (downlink) time of departure；
Step 53, different time sections are obtained and need online vehicle number:
By the history passenger flow big data, the average vehicle of multiple vehicles of a certain some period of shift in a couple of days is counted
Carrying flow q passes through turnaround time T, the period duration T of average volume of the flow of passengers Q, vehicle in time periodAlways, obtain at this
Between need online vehicle number in section；
The shift sum f needed in time period (f is also referred to as service frequency) are as follows:
The number of turnover η of a vehicle in time period (η is also referred to as turnover coefficient) are as follows:
Need online vehicle number A are as follows:If desired online vehicle number A is greater than the vehicle of the route
It is equipped with quantity, then A takes the vehicle of the route to be equipped with quantity；
Step 54, the hair class interval in different time sections is obtained:
The hair class interval of time period is calculated by the turnaround time T and the online vehicle number A,Into
And obtain hair class interval in different time periods；
Step 55, schedule is obtained；According in different time sections hair class interval and route earliest dispatch a car the latest
Time obtains schedule.
Preferably, the hair class interval T of the step 540If not integer, there are two kinds of hair class interval T'0=INT (T0)+1
And T "0=INT (T0), then according to T'0Send out the vehicle number at class interval are as follows: A'=T-AT "0, according to T "0Hair class interval vehicle number be
A "=A-A'；The arrangement method at two kinds of hair class intervals are as follows: if the affiliated period is the commuter rush hour to passenger flow ebb transition, drive a vehicle
A T " of A " is first arranged in timetable0Hair class interval, then arrange A' T'0Hair class interval；If the affiliated period is passenger flow ebb to visitor
Peak transition is flowed, then first arranges A' T' in schedule0Hair class interval, then arrange a T " of A "0Hair class interval；If when affiliated
Between section be in passenger flow ebb or in the commuter rush hour, then in schedule, A' T'0And a T " of A "0Uniform crossover is arranged as far as possible
Cloth.
Preferably, specific steps of arranging an order according to class and grade intelligently are generated with vehicle to schedule in the step 6 are as follows:
Step 61, the quantity of three kinds of shift types is determined:
The shift type includes Straight Run quantity and non-Straight Run quantity, and the Straight Run is the driver's morning and afternoon of certain vehicle
For different people, the non-Straight Run is divided into split run and puts into several classes, and the split run is driver's morning of certain vehicle and be same people in the afternoon,
The driver to put into several classes for certain vehicle is same people and only runs in the commuter rush hour；
Quantity is equipped with according to the driver, vehicle is equipped in quantity and different time sections and online vehicle number is needed to obtain difference
Shift number of types, Straight Run quantity=driver are equipped with quantity-vehicle and are equipped with quantity, split run quantity=arrange an order according to class and grade first time of the same day
Online vehicle number-Straight Run quantity of section；Such as driver 27 are equipped with, being equipped with vehicle has 20, arranges an order according to class and grade first period of the same day
Online vehicle number be 12, then Straight Run quantity is 7, and split run quantity is 5, and remaining vehicle is to put into several classes type or reserve wagon；
Step 62, vehicle is matched to schedule, completes to arrange an order according to class and grade:
Vehicle is successively first matched to the vehicle of Straight Run and split run type, is judged further according to the one way service time of uplink or downlink
Whether certain vehicle arrives terminus, if to further judging whether this vehicle can arrange an order according to class and grade again behind terminus, to can be with after arriving at a station
The vehicle arranged an order according to class and grade again is successively arranged an order according to class and grade according to the sequencing to arrive at a station；
When the vehicle that the moment a certain in schedule can not arrange an order according to class and grade, with increasing the vehicle for type of putting into several classes to the moment
It arranges an order according to class and grade；Later when have in the vehicle that can be arranged an order according to class and grade again put into several classes, the vehicle of Straight Run or split run type when, preferentially to Straight Run or list
The vehicle of class's type is arranged an order according to class and grade, and according to the method described above, is completed until arranging an order according to class and grade.
Further, further judge whether this vehicle can arrange an order according to class and grade again after the vehicle to terminus, specifically: sentence
Whether disconnected driver's time of having a rest or mealtime terminate；Judge whether vehicle needs to fill according to vehicle hour or mileage
Electricity.
Preferably, further include step 8, execution arrange an order according to class and grade as a result, and result of arranging an order according to class and grade is adjusted in real time: in the step 62
Further judge whether this vehicle can arrange an order according to class and grade again after vehicle to terminus, further includes whether judging the public transportation management system
The delay correlation temporal information for having received driver's input, to the shift of not dispatching a car on the same day according to step 6 if having delay information
Method arrange an order according to class and grade again.
In addition, the above-mentioned period can the volume of the flow of passengers divides according to section of several service times, including it is peak, Ping Feng, low
Paddy etc..
Compared with prior art, the invention has the following beneficial effects:
Research on Intelligent Scheduling of Public Traffic Vehicles method based on history passenger flow big data of the invention suits city more close to passenger flow rule
The trip requirements of the people arrange more transport power when passenger flow is more, to guarantee service level, after passenger flow reduction, cut down fortune in time
Power economizes on resources；The level of resources utilization and citizen are improved to the satisfaction of bus trip, reduces the operation of car operation company
Cost, while the consumption of vehicle exhaust emission and electric power or fuel source can also be indirectly reduced, optimize to traffic incident
Treatment effeciency.
Detailed description of the invention
Fig. 1 is that the Research on Intelligent Scheduling of Public Traffic Vehicles method flow diagram based on history passenger flow big data of the embodiment of the present invention and device show
It is intended to；
Specific embodiment
In order to illustrate technical solution of the present invention and working principle, the present invention is done with specific embodiment with reference to the accompanying drawing
Detailed introduction.In the present embodiment, the including but not limited to public transport of arranging an order according to class and grade also includes with public transport using similar operational mode
Subway, passenger traffic etc..
Attached drawing 1 is the Research on Intelligent Scheduling of Public Traffic Vehicles method flow diagram and device based on history passenger flow big data of the embodiment of the present invention
Schematic diagram, in conjunction with the figure, this method is mainly comprised the steps that
Step 1, the service time of public transport company's route is obtained, driver is equipped with quantity, vehicle is equipped with quantity and route
Site location information, as basic data set.Such as certain railroad embankment time is 05:00-22:00, is equipped with driver 27, matches
Standby vehicle has 20, site location information are as follows: website 1 (119.444152,32.212934), website 2 (119.444199,
32.210873), website 3 (119.448135,32.209679), website 4 (119.453278,32.207169) ...
Step 2, it obtains history passenger flow data: history passenger flow data, including certain line is acquired by vehicle-mounted automatic acquisition device
GPS position information when public transport switch gate time on road, passenger flow of getting on the bus number, passenger flow of getting off number, public transport switch gate preferably also includes
Corresponding vehicle unique number constitutes passenger flow data collection.Such as gps be (119.444152,32.212932) position, 001
The bus door open time of number be 2018/9/108:00:57,2 passenger getting off car, 0 passenger loading, 20,18/,9/1 08:
01:07 closing of the door.
1 2018-11-01 history passenger flow data table of table
The treated 2018-10-31 history passenger flow data table of table 2
Step 3, the passenger flow data in step 2 is handled, removes wrong data, and the data that fill in the blanks:
Step 31, wrong data is removed
(1) if GPS data is lost in certain passenger flow data, give up this passenger flow data；As serial number 2 data in GPS
Location information data is lost, and the data of serial number 2 are given up.
(2) site location information is matched by the GPS position information, if the GPS location and matched site location
Distance be greater than 8 meters, then give up this passenger flow data, otherwise replace corresponding GPS position information with site location information, pass through
The data of inaccuracy are given up in the judgement of distance.For example, passing through the calculating to the GPS location at a distance from matched site location
It was found that the GPS location of serial number 4 is 24.4 meters at a distance from matched site location, it is greater than 8, gives up the data of serial number 4；Serial number 1
GPS location with serial number 5 is respectively 0.2 meter and 0.1 meter, both less than 8 at a distance from matched site location；Other serial numbers
GPS location is identical as matched site location, therefore replaces corresponding GPS to serial number 1,3, the corresponding site name of 5-8
Set coordinate.
(3) if two or a plurality of identical passenger flow data occurs in history passenger flow data concentration, retain
A passenger flow data therein, others are deleted；There is two or a plurality of complete phase in the accuracy that ensure that passenger flow data
With passenger flow data the reason of be repetition upload operation that vehicle-mounted passenger flow acquisition device carries out same passenger flow data.
Step 32, fill in the blanks data: to avoid the passenger flow data given up from influencing the passenger flow data collection, causing with partially general
Full defect, same time point or time of closest approach point, the effective of same site position record to fill in the date before use
The blank of passenger flow data is given up.I.e. with corresponding data filling in the previous day treated passenger flow data (as shown in table 2)
The serial number 2 and serial number 4 of blank finally obtain treated 2018-11-01 history passenger flow data table, as shown in table 3.
The treated 2018-11-01 history passenger flow data table of table 3
Step 4, the average volume of the flow of passengers for counting each period in a couple of days, obtains the Time-distribution of passenger flow.
For example, the average volume of the flow of passengers hourly is as shown in table 4 in a certain route one month, drawn according to the distribution of passenger flow quantity
Divide multiple service times sections (such as peak, Ping Feng, low ebb), and obtains the volume of the flow of passengers in each service time section.
The passenger flow Annual distribution table of a certain route of table 4
| Direction | Period | The average volume of the flow of passengers |
| Uplink | 05:00-06:00 | 56 |
| Downlink | 05:00-06:00 | 24 |
| Uplink | 06:00-07:00 | 124 |
| Downlink | 06:00-07:00 | 134 |
| Uplink | 07:00-08:00 | 356 |
| Downlink | 07:00-08:00 | 412 |
| …… | …… | …… |
Step 5, quantity, railroad embankment time, history passenger flow big data and institute are equipped with according to the vehicle of public transport company
The Time-distribution of passenger flow is stated, the hair class interval in different time sections and corresponding schedule are obtained.
(1) it obtains the one way service time: by the history passenger flow big data, counting some time of a certain shift in a couple of days
The average value of the time difference of the switch gate time at the first and last station of section, obtains the one way service time t of time period vehicle, to obtain
Obtain the one way service time of vehicle in different time periods；
(2) obtain the turnaround time of vehicle: by the history passenger flow big data, count in a couple of days a certain shift some when
Between section terminal average down time, the down time be determined by the unique number of the vehicle vehicle driving down (on
Row) reach home time and back to back uplink (downlink) time of departure time difference, to obtain the week of time period vehicle
Turn time T, T=tUplink+tUplink is stopped+tDownlink+tDownlink is stopped, wherein tUplinkAnd tDownlinkThe respectively one way runing time of uplink and downlink, tUplink is stopped
And tDownlink is stoppedThe respectively terminal down time of uplink and downlink, the turnaround time are the uplink that vehicle completes a cycle of operation
With the time required for downlink, and then the turnaround time of different time sections vehicle is obtained；
(3) different time sections are obtained and need online vehicle number:
By the history passenger flow big data, the average vehicle of multiple vehicles of a certain some period of shift in a couple of days is counted
Carrying flow q, the vehicle-mounted passenger flow amount of one shift of a vehicle are the average value of every station number of people in car.By in time period
Average volume of the flow of passengers Q, turnaround time T, the period duration T of vehicleAlwaysIt obtains out needing online vehicle number during this period of time.
The shift sum f needed in time period (f is also referred to as service frequency) are as follows:
The number of turnover η of a vehicle in time period (η is also referred to as turnover coefficient) are as follows:
Need online vehicle number A are as follows:If desired online vehicle number A is greater than the vehicle of the route
It is equipped with quantity, then A takes the vehicle of the route to be equipped with quantity；
(4) the hair class interval in different time sections is obtained:
The hair class interval T of time period is calculated by the turnaround time T and the online vehicle number A0,
And then obtain hair class interval in different time periods, by the ratio of turnaround time T and the online vehicle number A obtain send out class between
It is all effectively online every the vehicle that ensure that the outfit of certain route, and guarantee the orderly turnover of vehicle on the line.
(5) schedule is obtained；According to time of departure the latest earliest at hair class interval and route in different time sections,
Obtain schedule；
Preferably, if the hair class interval T0It is not integer, there are two kinds of hair class interval T'0=INT (T0)+1 and T "0=
INT(T0), then according to T'0Send out the vehicle number at class interval are as follows: A'=T-AT "0, according to T "0The vehicle number for sending out class interval is A "=A-
A'；The arrangement method at two kinds of hair class intervals are as follows: if the affiliated period is the commuter rush hour to passenger flow ebb transition, schedule
It is middle first to arrange a T " of A "0Hair class interval, then arrange A' T'0Hair class interval；If the affiliated period is passenger flow ebb to the commuter rush hour
A' T' is then first arranged in transition in schedule0Hair class interval, then arrange a T " of A "0Hair class interval；If at the affiliated period
In passenger flow ebb or in the commuter rush hour, then in schedule, A' T'0And a T " of A "0Uniform crossover is arranged as far as possible.
Step 6, schedule is intelligently generated with vehicle and is arranged an order according to class and grade
Step 61, the quantity of three kinds of shift types is determined:
The shift type includes Straight Run quantity and non-Straight Run quantity, and the Straight Run is the driver's morning and afternoon of certain vehicle
For different people, the non-Straight Run is divided into split run and puts into several classes, and the split run is driver's morning of certain vehicle and be same people in the afternoon,
The driver to put into several classes for certain vehicle is same people and only in morning and evening peak load operation；
Quantity is equipped with according to the driver, vehicle is equipped in quantity and different time sections and online vehicle number is needed to obtain difference
Shift number of types, Straight Run quantity=driver are equipped with quantity-vehicle and are equipped with quantity, split run quantity=arrange an order according to class and grade first time of the same day
Online vehicle number-Straight Run quantity of section；Such as driver 27 are equipped with, being equipped with vehicle has 20, arranges an order according to class and grade first period of the same day
Online vehicle number be 12, then Straight Run quantity is 7, and split run quantity is 5, and remaining vehicle is to put into several classes type or reserve wagon.
Step 62, vehicle is matched to schedule, completes to arrange an order according to class and grade
Vehicle is successively first matched to the vehicle of Straight Run and split run type, certain is judged according to the one way service time of uplink or downlink
Whether vehicle arrives at a station, and further judges whether this vehicle can arrange an order according to class and grade again if arriving at a station, to the vehicle that can be arranged an order according to class and grade again after arriving at a station
It successively arranges an order according to class and grade according to the sequencing to arrive at a station；
When the vehicle that the moment a certain in schedule can not arrange an order according to class and grade, with increasing the vehicle for type of putting into several classes to the moment
Arrange an order according to class and grade, later when have in the vehicle that can be arranged an order according to class and grade again put into several classes, the vehicle of Straight Run or split run type when, preferentially to Straight Run and list
The vehicle of class's type is arranged an order according to class and grade, and ensure that increased vehicle of putting into several classes before reducing automatically when vehicle abundance, according to the method described above, directly
It is completed to arranging an order according to class and grade.The method for increasing vehicle of putting into several classes can be with are as follows: if the online vehicle number of two neighboring period is different, root
It needs to increase the online vehicle number perhaps reduced relative to this period according to subsequent time period and successively increases or reduce corresponding number
The vehicle of the type of putting into several classes of amount matches vehicle to schedule.
It is described judge after certain vehicle to terminus whether can again to schedule with vehicle, specifically: according to predetermined
Time of having a rest and mealtime judge whether driver's time of having a rest or mealtime terminate；According to vehicle hour or in
Journey judges whether vehicle needs to charge；
Step 7, the plan of arranging an order according to class and grade automatically generated is exported to public transportation management system, and executes result of arranging an order according to class and grade.
Preferably, on the same day for executing result of arranging an order according to class and grade, result of arranging an order according to class and grade can be adjusted in real time according to the actual situation: described
Whether vehicle can be matched to schedule again after judging certain vehicle to terminus, further include judging whether public transportation management system connects
The delay correlation temporal information of driver's input is received, specifically ,' working as driver's time of having a rest or mealtime and predetermined time not
Together, when and encountering emergency situations, after public transportation management system receives the delay correlation temporal information of driver's input, to the class of not dispatching a car
The secondary method according to step 6 is arranged an order according to class and grade again.
Based on the same technical idea, Fig. 1 also provides a kind of public transport intelligence based on history passenger flow big data of the invention
Can arrange an order according to class and grade device, which can execute the process of the Research on Intelligent Scheduling of Public Traffic Vehicles method based on history passenger flow big data.Such as Fig. 1 institute
Show, which, which specifically includes, obtains module, data processing module, schedule generation module, generation module of arranging an order according to class and grade, above-mentioned mould
Block is sequentially connected electrically；
The step of acquisition module executes the step 1 and step 2 of above-mentioned Research on Intelligent Scheduling of Public Traffic Vehicles method；
The data processing module executes the step of step 3 of above-mentioned Research on Intelligent Scheduling of Public Traffic Vehicles method；
The schedule generation module executes the step of step 4 and step 5 of above-mentioned Research on Intelligent Scheduling of Public Traffic Vehicles method；
The generation module of arranging an order according to class and grade executes the step of step 6 and step 7 of above-mentioned Research on Intelligent Scheduling of Public Traffic Vehicles method.
The present invention is exemplarily described in conjunction with attached drawing above, it is clear that the present invention implements not by above-mentioned side
The limitation of formula, the improvement of all various unsubstantialities carried out using the inventive concept and technical scheme of the present invention；Or not
Above-mentioned conception and technical scheme of the invention are directly applied to other occasions, of the invention by improved, equivalent replacement
Within protection scope.
Claims (10)
1. a kind of Research on Intelligent Scheduling of Public Traffic Vehicles method based on history passenger flow big data, which comprises the following steps:
Step 1, obtain public transport company's basic data collection: the basic data collection includes certain railroad embankment time, driver's outfit number
Amount, vehicle are equipped with the site location information of quantity and route；
Step 2, it obtains the history passenger flow big data of a couple of days: history passenger flow data is acquired by vehicle-mounted passenger flow acquisition device, including
GPS position information when public transport switch gate time of certain route, passenger flow of getting on the bus number, passenger flow of getting off number, public transport switch gate, vehicle is only
One number；
Step 3, the history passenger flow large data sets daily in step 2 are handled, removes wrong data, and fill in the blanks
Data:
Step 31, wrong data is removed, the specific steps are as follows:
(1) if the loss of data of GPS position information described in certain passenger flow data, give up this passenger flow data；
(2) site location information is matched by the GPS position information, if the GPS location and matched site location away from
From being greater than 5-15 meters, then give up this passenger flow data, otherwise replaces corresponding GPS position information with site location information；
(3) if two or a plurality of identical passenger flow data occurs in history passenger flow data concentration, retain wherein
A passenger flow data, others delete；
Step 32, fill in the blanks data: same time point or time of closest approach point in the date before use, same site position
Effectively record is to fill the blank for having given up passenger flow data；
Step 4, the average volume of the flow of passengers Q for counting each period in a couple of days, obtains the Time-distribution of passenger flow；
Step 5, quantity, railroad embankment time and history passenger flow big data and described are equipped with according to the vehicle of public transport company
The Time-distribution of passenger flow obtains schedule；
Step 6, schedule is intelligently generated with vehicle and is arranged an order according to class and grade；
Step 7, by the output of arranging an order according to class and grade automatically generated to public transportation management system.
2. a kind of Research on Intelligent Scheduling of Public Traffic Vehicles method based on history passenger flow big data according to claim 1, which is characterized in that
Schedule is obtained in the step 5, the specific steps are as follows:
Step 51, it obtains the one way service time: by the history passenger flow big data, counting some time of a certain shift in a couple of days
The average value of the time difference of the switch gate time at the first and last station of section, obtains the one way service time t of time period vehicle, to obtain
Obtain the one way service time of vehicle in different time periods；
Step 52, obtain the turnaround time of vehicle: the turnaround time is the uplink and downlink that vehicle completes a cycle of operation
The required time counts the average parking of some period terminal of a certain shift in a couple of days by the history passenger flow big data
Time, to obtain the turnaround time T, T=t of time period vehicleUplink+tUplink is stopped+tDownlink+tDownlink is stopped, wherein tUplinkAnd tDownlinkRespectively
The one way runing time of uplink and downlink, tUplink is stoppedAnd tDownlink is stoppedThe respectively terminal down time of uplink and downlink；And then it obtains not
With the car cycle of period；
Step 53, different time sections are obtained and need online vehicle number:
By the history passenger flow big data, the average vehicle-mounted visitor of multiple vehicles of a certain some period of shift in a couple of days is counted
Flow q passes through turnaround time T, the period duration T of average volume of the flow of passengers Q, vehicle in time periodAlways, obtain in the period
It is interior to need online vehicle number；
The shift sum f needed in time period are as follows:
The number of turnover η of a vehicle in time period are as follows:
Need online vehicle number A are as follows:If desired the vehicle that online vehicle number A is greater than the route is equipped with number
Amount, then A takes the vehicle of the route to be equipped with quantity；
Step 54, the hair class interval in different time sections is obtained:
The hair class interval of time period is calculated by the turnaround time T and the online vehicle number A,
And then obtain hair class interval in different time periods；
Step 55, schedule is obtained；According to time of departure the latest earliest at hair class interval and route in different time sections,
Obtain schedule.
3. a kind of Research on Intelligent Scheduling of Public Traffic Vehicles method based on history passenger flow big data according to claim 2, which is characterized in that
The down time of the step 52 is to determine that the vehicle driving down (uplink) is reached home the time by the unique number of the vehicle
With the time difference at back to back uplink (downlink) time of departure.
4. any Research on Intelligent Scheduling of Public Traffic Vehicles method based on history passenger flow big data according to claim 2 or 3, feature
It is, the hair class interval T of the step 540If not integer, there are two kinds of hair class interval T '0=INT (T0)+1 and T "0=INT
(T0), then according to T0' hair class interval vehicle number are as follows: A'=T-AT "0, according to T "0The vehicle number for sending out class interval is A "=A-A'.
5. a kind of Research on Intelligent Scheduling of Public Traffic Vehicles method based on history passenger flow big data according to claim 4, which is characterized in that
The arrangement method at described two hair class intervals are as follows: if the affiliated period is commuter rush hour to passenger flow ebb transition, running time
A " a T " is first arranged in table0Hair class interval, then arrange A' T '0Hair class interval；If the affiliated period is passenger flow ebb to passenger flow height
A' T ' is then first arranged in peak transition in schedule0Hair class interval, then arrange A " a T "0Hair class interval；If the affiliated period
In passenger flow ebb or in the commuter rush hour, then in schedule, A' T '0And A " a T "0Uniform crossover is arranged as far as possible.
6. any Research on Intelligent Scheduling of Public Traffic Vehicles method based on history passenger flow big data according to claim 2,3 or 5, special
Sign is, intelligently generates specific steps of arranging an order according to class and grade with vehicle to schedule in the step 6 are as follows:
Step 61, the quantity of three kinds of shift types is determined:
The shift type includes Straight Run quantity and non-Straight Run quantity, and the Straight Run is driver's morning of certain vehicle and be not in the afternoon
Same people, the non-Straight Run are divided into split run and put into several classes, and the split run is driver's morning of certain vehicle and be same people in the afternoon, described
The driver for certain vehicle that puts into several classes is same people and only runs in the commuter rush hour；
Quantity is equipped with according to the driver, vehicle is equipped in quantity and different time sections and online vehicle number is needed to obtain different shifts
Number of types, Straight Run quantity=driver are equipped with quantity-vehicle and are equipped with quantity, first period on split run quantity=the arrange an order according to class and grade same day
Online vehicle number-Straight Run quantity, remaining vehicle are put into several classes type or reserve wagon；
Step 62, vehicle is matched to schedule, completes to arrange an order according to class and grade:
Vehicle is successively first matched to the vehicle of Straight Run and split run type, judges certain vehicle further according to the one way service time of uplink or downlink
Whether terminus is arrived, if to further judging whether this vehicle can arrange an order according to class and grade again behind terminus, to can be again after arriving at a station
The vehicle arranged an order according to class and grade successively is arranged an order according to class and grade according to the sequencing to arrive at a station；
When the vehicle that the moment a certain in schedule can not arrange an order according to class and grade, the moment is arranged with the vehicle for increasing type of putting into several classes
Class；Later when have in the vehicle that can be arranged an order according to class and grade again put into several classes, the vehicle of Straight Run or split run type when, preferentially to Straight Run or split run
The vehicle of type is arranged an order according to class and grade, and according to the method described above, is completed until arranging an order according to class and grade.
7. a kind of Research on Intelligent Scheduling of Public Traffic Vehicles method based on history passenger flow big data according to claim 6, which is characterized in that
Further judge whether this vehicle can arrange an order according to class and grade again after vehicle to terminus in the step 62, specifically: judge that driver stops
Whether breath time or mealtime terminate；Judge whether vehicle needs to charge according to vehicle hour or mileage.
8. a kind of Research on Intelligent Scheduling of Public Traffic Vehicles method based on history passenger flow big data according to claim 7, which is characterized in that
Further include step 8, execution arrange an order according to class and grade as a result, and result of arranging an order according to class and grade is adjusted in real time: in the step 62 after vehicle to terminus
Further judge whether this vehicle can arrange an order according to class and grade again, further includes that judge whether the public transportation management system has received driver defeated
The delay correlation temporal information entered arranges an order according to class and grade to the shift of not dispatching a car on the same day according to the method for step 6 if having delay information again.
9. according to claim 1 to any Research on Intelligent Scheduling of Public Traffic Vehicles side based on history passenger flow big data described in 3,5,7 to 8
Method, which is characterized in that the period can the volume of the flow of passengers divides according to section of several service times, including it is peak, Ping Feng, low
Paddy etc..
10. a kind of Research on Intelligent Scheduling of Public Traffic Vehicles device based on history passenger flow big data, which is characterized in that including obtaining module, data
Processing module, schedule generation module, generation module of arranging an order according to class and grade, above-mentioned module are sequentially connected electrically；
It is described to obtain the step of module perform claim requires the step 1 and step 2 of any Research on Intelligent Scheduling of Public Traffic Vehicles method in 1 to 9；
The data processing module perform claim requires the step of step 3 of any Research on Intelligent Scheduling of Public Traffic Vehicles method in 1 to 9；
The schedule generation module perform claim requires the step 4 of any Research on Intelligent Scheduling of Public Traffic Vehicles method and step in 1 to 9
Rapid 5 the step of；
The generation module perform claim of arranging an order according to class and grade requires the step 6 and step 7 of any Research on Intelligent Scheduling of Public Traffic Vehicles method in 1 to 9
Step.
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| CN112396271A (en) * | 2019-08-16 | 2021-02-23 | 顺丰科技有限公司 | Vehicle shift scheduling time reduction method and system |
| CN112289066A (en) * | 2019-12-30 | 2021-01-29 | 南京行者易智能交通科技有限公司 | Bus driving plan approach station and arrival time setting method thereof |
| CN111695726A (en) * | 2020-06-02 | 2020-09-22 | 广州通达汽车电气股份有限公司 | Bus scheduling schedule updating method and device |
| CN111709562A (en) * | 2020-06-02 | 2020-09-25 | 广州通达汽车电气股份有限公司 | Method and device for generating scheduling schedule of public transport vehicle |
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| CN113900391A (en) * | 2021-09-10 | 2022-01-07 | 苏州贝基电子科技有限公司 | Commercial building intelligent management system based on big data |
| CN113936496A (en) * | 2021-12-17 | 2022-01-14 | 广东机电职业技术学院 | Passenger identification-based intelligent interactive traffic scheduling method and system |
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