US 2020/0027347 A1 · COLLABORATIVE OPTIMIZATION METHOD FOR BUS TIMETABLE BASED ON BIG DATA

Abstract

The present invention relates to a collaborative optimization method for bus timetables based on big data, which belongs to the technical field of urban bus operation and management. Bus GPS data, IC card data and line station data are fused together to provide real-time operation data for the formulation of bus timetables, and a bus timetable optimization model considering transfer between buses and rail transit lines is proposed. In the model, by taking the departure interval of each time period as a decision variable and taking the minimum total system cost as an objective function, the waiting time cost of non-transfer passengers, the waiting time cost of transfer passengers, and the operation cost of bus operation enterprises are comprehensively considered. By means of the present invention, passenger flow data are acquired through multisource data fusion, a large number of manpower is saved, and the accuracy of data is increased. The rationality of compiling the bus timetable is increased by considering transfer between ground buses and rail transit lines. The bus timetable is optimized by establishing a data model. The model takes into account both the waiting time cost of passengers and the operation cost of enterprises, and realizes the coordination of benefits between passengers and enterprises.

A collaborative optimization method for bus timetable based on big data, comprising the following steps:

I. Acquisition of Bus Operation Data and Passenger Flow Data
(1). Acquisition of Bus Operation Data
(1.1) Judgment of Bus Operation Direction
The bus operation direction is divided into an up direction and a down direction, and buses move in two directions according to the order of scheduling;
up and down bus lines respectively possess independent operation lines, bus stops, and operation time periods;
bus operation states and passenger flow requirements are also relatively independent, and data are divided into data of two operation directions;
(1.2) Acquisition of Bus Arrival Data
A bus arrival data sheet is established first, including four fields in total in Table 1, i.e. station ID (S_ID), bus arrival time (S_TIME), bus number (NUMBER), and bus operation direction (DIRECTION);
TABLE 1
Bus Arrival Data Sheet
Bus Arrival Data Field
Data type
S_ID
INT
S_TIME
DATETIME
NUMBER
VARCHAR
DIRECTION
VARCHAR
Data of arriving at station S of all buses in the up direction are recorded in the bus arrival data sheet, including the steps as follows:
(1) Extracting all data from the bus GPS data in which the buses run in the “up” direction;
(2) Ranking the bus GPS data extracted in step (1) according to bus numbers first, and then ranking bus numbers of the same bus according to bus arrival time;
and in the continuous bus numbers of the same bus, if the previous bus GPS data is matched with a road section L1, and the latter bus GPS data is matched with a road section L2, taking a GPS time data intermediate value between L1 and L2 as the time when the bus arrives at station S;
(3) Writing station SID, the time when bus arrives at station S , bus numbers, and bus operation directions into corresponding bus arrival time data sheet, until all bus GPS data in the up direction are processed, and obtaining a bus arrival data sheet;
Bus arrival data in the down direction is obtained in the same manner;
(1.3) Acquisition of Bus Travel Time
Establishing a bus travel time data table, including five fields, i.e. bus number (NUMBER), operation direction (DIRECTION), origin station arrival time (O_TIME), end station arrival time (E_TIME) and travel time (INTERVAL), the data structure is shown in Table 2.
TABLE 2
Bus Travel Time Data Structure
Travel Time Data Field
Data Type
NUMBER
INT
DIRECTION
VARCHAR
O_TIME
DATETIME
E_TIME
DATETIME
INTERVAL
INT
The steps of acquiring up line bus travel time are as follows:
(1) Extracting all data of buses in operation direction “up” from the bus arrival data sheet, ranking the bus GPS data according to bus numbers first, and then further ranking bus number of the same bus according to bus arrival time;
(2) For each bus arrival time data, if the station ID is consistent with the origin station of the bus operation direction, taking the data as departure data of the origin station, and if the station ID is consistent with the end station of the bus operation direction, taking the data as arrival data of the end station;
respectively writing bus number, bus operation direction, origin station arrival time, and end station arrival time into corresponding bus travel time data table;
(3) Calculating the interval between the origin station arrival time and the end station arrival time, and writing itin the travel time field, until all arrival time data of buses in the up direction are traversed, obtaining a bus travel time data sheet;
Bus travel time in the down direction is obtained in the same manner;
(2) Acquisition of Passenger Flow Data
(2.1) Acquisition of Passenger Boarding stations
Rail transit card data records the passenger inbound and outbound station data. Thus the boarding station and getting-off station can be determined directly;
Bus IC card data does not record passenger boarding station information. To determine passenger boarding time, we need to match and fuse the card-swiping time and bus number field in the bus IC card data with the bus arrival time and bus number field in the bus arrival data sheet;
A Mix_IC data sheet is established to store data. The Mix_IC data sheet includes ten fields, i.e. IC card record ID (ID), line name (LINE), bus number (NUMBER), line operation direction (DIRECTION), boarding station ID (U_ID), boarding station name (U_NAME), boarding time (U_TIME), getting-off station ID (D_ID), getting-off station name (D_NAME), and getting-off time (D_TIME). See Table 3 for the data structure.
TABLE 3
Structure of Mix_IC Data Sheet
Field Name
Attribute
Data Type
Length
ID
IC card record ID
VARCHAR
10
LINE
Line name
VARCHAR
10
NUMBER
Bus number
VARCHAR
5
DIRECTION
Line operation direction
VARCHAR
2
U_ID
Boarding Station ID
INT
2
U_NAME
Boarding station name
VARCHAR
5
U_TIME
Boarding time
DATETIME
19
D_ID
Getting-off station ID
INT
2
D_NAME
Getting-off station name
VARCHAR
5
D_TIME
Getting-off time
DATETIME
19
Steps of matching and fusing bus arrival data with bus IC card data are as follows:
(1) Extracting any bus IC card data, and correspondingly writing data of ID, LINE, and NUMBER in the bus IC card data into the ID, LINE, and NUMBER fields of the Mix_IC data sheet;
(2) Matching a record indicating that the bus arrival time is closest to the card-swiping time field, which is consistent with the bus IC card data NUMBER field extracted in step (1) in the bus arrival data sheet, and correspondingly writing station ID and bus arrival time fields of this record into the boarding station ID and boarding time fields of the Mix_IC data sheet, until all the bus IC card data are traversed;
Data of the same rail transit trip are recorded in “boarding station” and “getting-off station “two fields. The rail transit card-swiping data need to be processed before being placed in the Mix_IC data sheet, the steps are as follows:
(1) Arranging rail transit card-swiping data according to IC card record IDs first, and then further arranging record time fields of the same IC card record ID;
(2) Extracting two continuous rail transit card-swiping data of step (1), wherein the IC card record ID and line name fields are identical, the line operation direction field of the previous data is “boarding station”, and the line operation direction field of the latter data is “getting-off station”;
and correspondingly writing data of the IC card record ID and line name fields into the IC card record ID and line name fields of the Mix_IC data sheet;
(3) Correspondingly writing station name and card-swiping time for boarding station of the previous data into the boarding station name and boarding time fields of the Mix_IC data sheet, and correspondingly writing station name and card-swiping time for getting-off station of the latter data into the getting-off station name and getting-off time fields of the Mix_IC data sheet;
(4) Matching boarding and getting-off station IDs according to the station ID sheet, station name for the boarding station, and the station name for getting-off station, and writing these data into the boarding station ID and getting-off station ID fields of the Mix_IC data sheet, until all rail transit card-swiping data are traversed;
(2.2) Acquisition of Passenger Getting-off Stations
It is found by analyzing the residents travel behavior that the number of home-based bus travelers takes a high proportion in the total number of travelers, i.e. most travelers take home as both starting point and end point in their daily trip, and the travel activity chain forms a closed loop;
for a traveler using the bus IC card more than twice in a day, the getting-off station where he/she takes the ground bus arrives can be determined according to the travel activity chain;
The getting-off station is determined using data recorded in the Mix_IC data sheet, and the acquired getting-off station data are written into the getting-off station ID field of the Mix_IC data sheet;
steps of judging passenger getting-off stations are as follows:
(1) Extracting data of the same ID from the Mix_IC data sheet, and arranging them according to the boarding time field;
(2) Judging whether the previous data and the latter data of the same ID are for the same line:
if it is judged that the two data are for the same line, taking the latter card-swiping boarding station as the previous card-swiping getting-off station;
and if it is judged that the two data are for different lines, taking a transfer station of the previous card-swiping line nearest to the latter card-swiping boarding station as the getting-off station of the previous data;
(3) Taking the boarding station of the first card-swiping as the getting-off station of the last card-swiping for the same ID, until all data in the Mix_IC data sheet are traversed;
(2.3) Judgment of Passenger Transfer Behavior
Whether the interval between the previous getting-off time and the latter boarding time exceeds the set upper limit of transfer time is used as a basis for judging whether the two consecutive bus travel is a transfer behavior. 30 minutes are set as the upper limit of transfer time.
First, there is a need to match getting-off time of passengers, the steps are as follows:
(1) Extracting a data from the Mix_IC data sheet, matching the bus number, line operation direction, and getting-off station ID fields in the Mix_IC data sheet with the bus number, line operation direction, and station ID fields in the bus arrival data sheet to obtain bus arrival time;
Buses repeatedly operate between the up direction and the down direction in one day, there should be multiple bus arrival time at the same getting-off station in the bus arrival data sheet;
(2) Selecting bus arrival time, from the boarding time field in the Mix_IC data sheet, which is after the boarding time and having the shortest time interval as the getting-off time;
and writing the matched getting-off time into the getting-off time field of the Mix_IC data sheet, until all data in the Mix_IC data sheet are traversed;
Judging whether two consecutive card-swiping records of a passenger belong to a transfer, the steps are as follows:
(1) Arranging the Mix_IC data sheet according to the IC card record IDs first, and then ranking record IDs of the same IC card according to the boarding time field;
(2) Extracting two consecutive records of the same ID, subtracting the getting-off card-swiping time of the previous data from the boarding card-swiping time of the latter data, and if the time interval is less than 30 minutes, considering it as a transfer;
and traversing all data in the Mix_IC data sheet.
II. Establishment of Model
2. Model Hypothesis
(1) Up and down directions of both ground buses and rail transits are taken as two different lines, i.e. there is only one operation direction for one line. it is supposed that all buses depart from the origin station according to the timetable strictly, the influence of road traffic condition on bus operation is neglected, and the travel time distribution of buses among all stations is already known;
departure intervals of buses at the same time period are identical, the number of buses on the same line is fixed, and models of buses are all identical;
buses departure according to the sequence of operation, there is no bunching and delay at station;
non-transfer passengers are evenly distributed in the process of arriving at the station, and the arrival rates of passengers at the same time period are identical;
the transfer walking time of passengers at the transfer station is already known, and the transfer walking time is less than the departure interval between a ground bus and a rail transit;
passengers get on the bus as long as the bus arrives at the station, ignoring the situation of continuing to wait due to traffic jam and other reasons;
operation buses on the line are all whole-line buses, ignoring the shuttle bus, station express scheduling scheme.
(2) Parameter Definitions
s-Sequence of ground bus stations, s ∈ S;
s-Sequence of transfer stations,;
es-Number of transfer stations;
Bi-Ground bus departing within the study period and having the serial number of i;
Rj-Rail transit departing at study time period and having the serial number of j;
eB-Departure number of ground buses B within the study period;
eR-Departure number of rail transit R within the study period;
α-Duration of study time period, α=Tend−Tstart;
hB-Departure interval of ground buses B within the study period;
hR-Departure interval of rail transit R within the study period;
hB.min,HB.max-Minimum and maximum departure intervals of ground buses;
hR.min,hR.max-Minimum and maximum departure intervals of rail transit;
γBs-Arrival rate of passengers taking ground buses B at station s within the study period;
tBRS-Walking time at transfer station s from ground bus station to rail transit station;
TBi.s-Time when ground bus Bi arrives at transfer station s;
TRj.s-Time when rail transit Rj arrives at transfer station s;
TB1-Time when the ground bus with the serial number of 1 departs from the origin station;
TR1-Time when the rail transit with the serial number of 1 departs from the origin station;
tBs-Travel time for ground bus to run to transfer station s from the origin station;
tRs-Travel time for rail transit to run to transfer station s from the origin station in the study section;
tB-Travel time of ground bus within the study period;
tR-Travel time of rail transit in the study section within the study time period;
LBs-Distance between origin station of ground bus line and transfer station s;
LRs-Distance between origin station of rail transit line and transfer station s;
LB-Entire length of ground bus line;
LR-Length of rail transit line in study section;
Uc-Time value of unit passenger waiting time (dollar/minute);
Up-Operation cost of unit departure number of ground bus line (dollar/km);
CB-Waiting time cost for non-transfer passengers to take a ground bus within the study period;
CBR-Transfer waiting time cost for passengers to transfer from ground bus to rail transit within the study period;
CRB-Transfer waiting time cost for passengers to transfer from rail transit to ground bus within the study period;
CP-Cost of bus operation enterprise within the study period;
CS-Total system cost within the study period;
(3) Constraint Conditions
According to model hypothesis, the transfer walking time of a passenger at the transfer station is less than the departure interval between a ground bus and a rail transit, for all s ∈ S,
tBRs≤(hB,hR)min (3.1)
The departure interval between ground bus and rail transit should not be less than the minimum departure interval, and should not be greater than the maximum departure interval at the same time, then:
hB,min≤hB≤hB,max (3.2)
hR,min≤hR≤hR,max (3.3)
(4) Objective Function
The relationship between the departure number of ground buses eB within the study time period and the departure interval hB is:
e
B
=
[
a
h
B
]
(
4.1
)
The relationship between the departure number of rail transit eR within the study time period and the departure interval is:
e
R
=
[
a
h
R
]
(
4.2
)
1) Waiting time cost for non-transfer passenger to take ground bus
For a passenger who arrives at station s and takes ground bus Bi departing within the study time period and having a serial number of i, the waiting time can be expressed as:
cBi,s=½UcγBs(hB)2 (4.3)
Then, the waiting time cost of the non-transfer passenger can be expressed as:
C
B
=
∑
s
=
1
e
s

∑
i
=
1
e
B

c
B
i
,
s
(
4.4
)
2) Transfer waiting time cost for passenger to transfer from ground bus to rail transit
The time TBi when ground bus Bi with a serial number of i arrives at the transfer station s can be expressed as:
TBi,s=TB1+(i−1)hB+tBs (4.5)
where the travel time tBs for the ground bus to run to the transfer station s from the origin station can be calculated using equation 4.6:
t
B
s
_
=
L
B
s
_
L
B

t
B
(
4.6
)
The time when rail transit Rj with a serial number of j arrives at the transfer station s can be expressed as:
TRj,s=TR1+(j−1)hR+tRs (4.7)
where the travel time tRs for the rail transit to run to the transfer station s from the origin station can be calculated using equation 4.8:
t
R
s
_
=
L
R
s
_
L
R

t
R
(
4.8
)
The walking time for a passenger to transfer from ground bus Bi to rail transit Rj at transfer station s is tBRs, and the transfer waiting time can be expressed as:
ΔtBRs=ηBRi,j(TRj,s−TBi,s−tBRs) (4.9)
where ηBRi,j is a Boolean variable,
η
BR
j
,
i
=
{
1
;
T
B
i
-
1
,
s
_
<
T
B
i
,
s
_
+
t
BR
s
_
≤
T
B
j
,
s
_
0
;
others
(
4.10
)
The total number of passengers who take the ground bus departing within the study time period and get down at transfer station s is Qds, if the transfer rate of transfer from ground bus to rail transit at transfer station s is λBRs, then the total number of passengers who take the ground bus departing within the study time period and get down at transfer station s to transfer to rail transit can be calculated according to equation 4.11:
PBRs=λBRsQds (4.11)
If passengers who transfer from the ground bus to rail transit at transfer station s are equally distributed to all ground buses, the number of passengers who take ground bus Bi and transfer to rail transit at transfer station s can be expressed as:
p
BR
s
_
=
P
BR
s
_
e
B
(
4.12
)
By considering the hypothesis that transfer walking time tBRs does not exceed the departure interval of ground buses, the situation of transfer from ground bus departing within time period k to rail transit departing within time period k+1 cannot occur. Therefore, the transfer waiting time cost for passenger to transfer from rail transit to ground bus at transfer station s is:
C
BR
s
_
=
U
c

∑
j
=
1
e
R
k

∑
i
=
1
e
B
k

η
BR
i
,
j

p
BR
s
_

(
T
R
j
,
s
-
T
B
i
,
s
_
-
t
BR
s
_
)
(
4.13
)
The transfer waiting time cost for passengers to transfer from ground buses to rail transit at all transfer stations within the study time period is:
C
BR
=
U
c

∑
s
=
1
e
s
_

∑
j
=
1
e
R
k

∑
i
=
1
e
B
k

η
BR
i
,
j

p
BR
s
_

(
T
R
j
,
s
_
-
T
B
i
,
s
_
-
t
BR
s
_
)
(
4.14
)
η
BR
i
,
j
=
{
1
;
T
R
j
-
1
,
s
_
<
T
B
i
,
s
_
+
t
BR
s
_
≤
T
R
j
,
s
_
0
;
others
(
4.15
)
3) Transfer waiting time cost for passenger to transfer from rail transit to ground bus
The walking time for a passenger to transfer from rail transit Rj to ground bus Bi at transfer station s is tRBs, and the transfer waiting time can be expressed as:
ΔtRBs=ηRBj,i(TBi,s−TRj.s−tRBs) (4.16)
where is a Boolean variable,
η
RB
j
,
i
=
{
1
;
T
B
i
-
1
,
s
_
<
T
R
j
,
s
_
+
t
RB
s
_
≤
T
B
i
,
s
_
0
;
others
(
4.17
)
The total number of passengers who get on at transfer station s and take ground bus departing within the study time period is Qus, and if the transfer rate of transfer from rail transit to ground bus at transfer station s is λRBs, the total number of passengers who get on at transfer station s and transfer to ground bus departing within the study time period can be calculated according to equation 4.18:
PRBs=λRBsQus (4.18)
If passengers who transfer from rail transit to ground buses at transfer station s are equally distributed to all ground buses, the number of passengers who transfer from rail transit to ground bus Bi at transfer station s can be expressed as:
p
RB
s
_
=
P
RB
s
_
e
R
(
4.19
)
By considering the hypothesis that transfer walking time tBRs does not exceed the departure interval of rail transit, the situation of transfer from rail transit departing within the time period k to ground bus departing within time period k+1 cannot occur. Therefore, the waiting time cost for passengers to transfer from rail transit to ground buses at transfer station s within the time period k is:
c
RB
s
_
=
U
c

∑
i
=
1
e
B
k

∑
j
=
1
e
R
k

η
RB
j
,
i

p
RB
s
_

(
T
B
i
,
s
_
-
T
R
j
,
s
_
-
t
RB
s
_
)
(
4.20
)
The waiting time cost for passengers to transfer from rail transit to ground buses at all transfer stations within the study time period is:
C
RB
=
U
c

∑
s
_
=
1
e
s
_

∑
i
=
1
e
B
k

∑
j
=
1
e
R
k

η
RB
j
,
i

p
RB
s
_

(
T
B
i
,
s
_
-
T
R
j
,
s
_
-
t
RB
s
_
)
(
4.21
)
η
RB
j
,
i
=
{
1
;
T
B
i
-
1
,
s
_
<
T
R
j
,
s
_
+
t
RB
s
_
≤
T
B
i
,
s
_
0
;
others
(
4.22
)
4) Bus Enterprise Operation Cost
The bus enterprise operation cost is related to the entire length of the line and the departure number within the study time period, and can be expressed by equation 4.26:
CP=UpLBeB (4.23)
5) Total System Cost
The total system cost within the study period includes:
waiting time cost for non-transfer passenger to take ground buses, waiting time cost for passenger to transfer from ground bus to rail transit, waiting time cost for passenger to transfer from rail transit to ground bus, and bus enterprise operation cost, i.e.:
CS=CB+CBR+CRB+CP (4.24)
The objective function is to minimize total system cost, i.e. min Cs;
and the decision variable is the departure interval hB of ground buses.

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Collaborative optimization method for bus timetable based on big data

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Collaborative optimization method for bus timetable based on big data

Life of this patent

Abstract

Claims1