CN110782694B - Internet bus arrival and stop management optimization method - Google Patents

Internet bus arrival and stop management optimization method Download PDF

Info

Publication number
CN110782694B
CN110782694B CN201911054958.8A CN201911054958A CN110782694B CN 110782694 B CN110782694 B CN 110782694B CN 201911054958 A CN201911054958 A CN 201911054958A CN 110782694 B CN110782694 B CN 110782694B
Authority
CN
China
Prior art keywords
bus
internet
station
buses
time
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201911054958.8A
Other languages
Chinese (zh)
Other versions
CN110782694A (en
Inventor
马万经
欧诗琪
王玲
俞春辉
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Tongji University
Original Assignee
Tongji University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Tongji University filed Critical Tongji University
Priority to CN201911054958.8A priority Critical patent/CN110782694B/en
Publication of CN110782694A publication Critical patent/CN110782694A/en
Priority to PCT/CN2020/124527 priority patent/WO2021083232A1/en
Application granted granted Critical
Publication of CN110782694B publication Critical patent/CN110782694B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/123—Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams
    • G06Q50/40—

Abstract

The invention relates to an internet bus arrival and stop management optimization method, which comprises the following steps: step S1: establishing a mathematical model for managing the arrival and the stop of the internet buses; step S2: acquiring linear constraint conditions of a networked bus arrival and stop management mathematical model and linear objective functions related to all bus delays, all bus passenger delays or all bus emptying time; step S3: and performing the online bus arrival and stop management based on the real-time parameters and the online bus arrival and stop management mathematical model. Compared with the prior art, the method has the advantages that the result is optimal, the model can be solved, the model can be migrated, the delay of the stop of the internet bus can be effectively reduced, the stop efficiency is improved, and the better bus service is provided for passengers.

Description

Internet bus arrival and stop management optimization method
Technical Field
The invention relates to the field of public transport stop management, in particular to an optimization method for stop management of internet buses.
Background
The public transport has large passenger carrying rate and high resource utilization rate, and is an important component in an urban traffic system. The stop process of the bus at the station is a key in the operation process of the bus, and stop delay is often caused by unbalanced supply and demand and improper management. The delay is mainly caused by the fact that the number of passengers getting on and off each bus at a stop is different, and the service duration, namely the parking duration, of each bus at the stop is also different. Therefore, the bus may wait for the service before the bus stops or wait for the service before the bus stops during the process of stopping at the multi-berth bus stop. And along with the continuous development of car networking technology, bus real-time information can share, like real-time position, speed, direction angle, the passenger demand of station also can acquire. The method has the advantages that the parking sequence of the buses is optimized under the conditions that the real-time positions of the buses on the road section and the available boarding and alighting requirements of each bus are met, the parking resources of the stations are reasonably utilized, the service efficiency of the bus stations can be greatly improved, and the service reliability of a bus operation system is improved.
At present, the management and control of bus stop are very few, and the intelligent bus stop management system mainly focuses on two aspects of bus intelligent induction and fixed-point stop. The students of Liu Yi post and the like put forward the idea of a multi-berth bus station real-time queuing guidance system, the system can concentrate the real-time information of buses on the road section, process and release the information, and the system is also provided with the functions of bus speed guidance, bus fixed-point stop, real-time stop information release and the like. However, the system only proposes related functions at present, and a specific implementation method of the functions is not described. The Li Fei designs a multi-berth dynamic distribution method for the bus stops of the intelligent bus system, and two sets of bus stop algorithms are designed according to whether the bus stops fully. The two sets of algorithms can optimize the stop sequence of the buses at the station, but can only optimize three buses to be arrived at the station at most, the range is small, and the optimization cannot be guaranteed.
Disclosure of Invention
The invention aims to provide a method for managing and optimizing the arrival and stop of the internet-connected bus in order to overcome the defects that an optimization system in the prior art has no specific implementation method, a small optimization range and incapability of ensuring the optimization.
The purpose of the invention can be realized by the following technical scheme:
an internet bus arrival and stop management optimization method comprises the following steps:
step S1: establishing a mathematical model for managing the arrival and the stop of the internet buses;
step S2: acquiring linear constraint conditions of a networked bus arrival and stop management mathematical model and linear objective functions related to all bus delays, all bus passenger delays or all bus emptying time;
step S3: and performing the online bus arrival and stop management based on the real-time parameters and the online bus arrival and stop management mathematical model.
The real-time parameters comprise the number of the internet buses ready to arrive at the bus station for parking service, the number of parking positions contained in the bus station, whether the bus station has the internet buses at the station for parking service at present, the highest speed and the lowest speed of the internet buses in running, the time of the internet buses from arriving at the bus station to arriving at the parking positions, the time of the internet buses from the parking positions to leaving the bus station completely, the minimum safe headway between the internet buses and the running information of the internet buses.
The running information of the internet buses comprises the time when the internet buses should be out of the schedule, the stop time of the internet buses at the stop, the average number of passengers of the internet buses and the distance between the internet buses and the bus stop.
The linear constraint conditions comprise a service part for the current internet-free bus stop of the bus station and a service part for the current internet-connected bus stop of the bus station.
The service part of the current internet-free bus at the bus station comprises:
constraint C1: the running speed of the internet bus can not be higher than the highest speed and can not be lower than the lowest speed, and the mathematical expression is as follows:
Figure BDA0002256306570000021
wherein d isnIs the distance between the nth internet bus and the bus station,
Figure BDA0002256306570000022
the moment when the nth internet bus arrives at the bus station,
Figure BDA0002256306570000023
is the highest speed of the internet bus running,
Figure BDA0002256306570000024
the number of the internet buses to be served at the bus stop is N;
constraint C2: the time when the internet-connected bus arrives at the berth position is at least longer than the time when the internet-connected bus arrives at the bus station, and the expression is as follows:
Figure BDA0002256306570000025
wherein, TinThe time for the internet bus to get in from the bus station to the berth position is required,
Figure BDA0002256306570000026
the moment when the nth internet bus reaches the berth position;
constraint C3: the time when the internet-connected bus completely leaves the bus station is at least longer than the time when the internet-connected bus arrives at the berth position, and the expression is as follows:
Figure BDA0002256306570000031
wherein S isnThe stop time length T of the nth internet busoutThe time for the internet bus to get out of the bus from the parking position to completely leave the bus station,
Figure BDA0002256306570000032
the moment when the nth internet bus completely leaves the bus station;
constraint C4: the berth position of the internet bus is in the berth position of a bus station, the berth number of the berth position of the bus station sequentially adds 1 from downstream to upstream from 1, and the expression is as follows:
Figure BDA0002256306570000033
wherein, PnThe number of the nth networked bus is the number of the nth networked bus, and P is the number of the nth networked bus;
constraint C5: the time when different internet buses arrive at the respective berth positions at least has the minimum safe headway interval, and the expression is as follows:
Figure BDA0002256306570000034
wherein lm,nIs a variable of 0 to 1, the 1 represents that the mth internet bus arrives at the bus station earlier than the nth internet bus, otherwise, the T is 0secM is a sufficiently large number for the minimum safe headway;
constraint C6: the time that different networking buses leave the bus station is minimum safe headway at least interval, and the expression is:
Figure BDA0002256306570000035
constraint C7: if the most upstream parking position of the bus station is occupied when the internet-connected bus arrives at the bus station, the internet-connected bus needs to wait for the occupied internet-connected bus occupying the most upstream parking position to leave the bus station and then enter the bus station, and the expression is as follows:
Figure BDA0002256306570000036
Figure BDA0002256306570000037
Figure BDA0002256306570000038
wherein q ism(t) the number of networked buses which arrive at the bus station before the mth networked bus at the time t and do not arrive at the bus station, e (t) is a variable of 0-1, wherein 1 represents that all parking positions of the bus station at the time t have no networked buses to park, otherwise, 0 is true, o (t) is a variable of 0-1, wherein 1 represents that the most upstream parking position of the bus station at the time t is occupied, otherwise, 0 is true, and alpha (a) ism(t) is a variable of 0-1, a value of 1 indicates that the mth internet bus has arrived at the bus station at the time t, and if the value of 0 is not the case, beta ism(t) is a variable of 0-1, wherein a value of 1 indicates that the mth internet bus has entered the bus station at the time t, and if the value of 0 is not the case, the mth internet bus enters the bus station;
constraint C8: if the rest arbitrary berth positions of the bus station except the most upstream berth position are occupied when the internet-connected bus arrives at the bus station, the free berth position of the upstream berth position of the internet-connected bus stop is represented by the following expression:
qm(t)·M+e(t)·M+o(t)·M+[1-αm(t)]·M+βm(t)·M+lm,n·M+[1-βn(t)]·M+γn(t)·M+Pm≥Pn+1
Figure BDA0002256306570000041
Figure BDA0002256306570000042
wherein, γn(t) is a variable of 0-1, wherein 1 represents that the nth internet bus leaves the bus station at the moment t, and if the value is 0, the opposite is true;
constraint C9: the auxiliary constraint expression is:
Figure BDA0002256306570000043
Figure BDA0002256306570000044
Figure BDA0002256306570000045
Figure BDA0002256306570000046
Figure BDA0002256306570000047
Figure BDA0002256306570000048
Figure BDA0002256306570000049
Figure BDA00022563065700000410
Figure BDA00022563065700000411
Figure BDA00022563065700000412
Figure BDA00022563065700000413
Figure BDA00022563065700000414
Figure BDA00022563065700000415
Figure BDA00022563065700000416
Figure BDA00022563065700000417
Figure BDA00022563065700000418
Figure BDA00022563065700000419
e(t)·M+fn·M+[1-βn(t)]·M+γn(t)·M+(1-hm,n)·M+βm(t)·M≥o(t),
Figure BDA00022563065700000420
e(t)·M+(1-fn)·M+[1-βn(t)]·M+γn(t)·M+o(t)≥1,
Figure BDA00022563065700000421
Figure BDA0002256306570000051
Figure BDA0002256306570000052
Figure BDA0002256306570000053
Figure BDA0002256306570000054
Figure BDA0002256306570000055
Figure BDA0002256306570000056
Figure BDA0002256306570000057
Figure BDA0002256306570000058
wherein f isnIs a variable of 0 to 1, the 1 represents the most upstream berth position of the nth internet bus, and if the value is 0, the reverse is true, FnIs a variable of 0 to 1, the value of 1 indicates that the nth internet bus is the last internet bus, and if the value of 0 is not the last internet bus, r isnIndicating the order of the nth networked bus to the bus station, LnIs a variable of 0-1, is 1, and means that the time when the nth internet bus leaves the bus station is later than the time when the nth internet bus leaves the bus station by more than 5 minutes, and is 0, otherwise,
Figure BDA0002256306570000059
represents the time h of the nth networked bus when the bus should be out of the stationm,nThe variable is 0-1, the variable is 1, the mth internet bus arrives at the bus station right behind the nth internet bus, and the variable is 0 if the variable is not.
The service part of the bus station where the internet-connected buses stop at the bus station at present comprises constraint C1-constraint C9, and further comprises the following steps:
constraint C10: if the most upstream berth position of present bus station is occupied by occupation net connection bus, then the net connection bus that arrives waits occupation net connection bus gets into the bus station after leaving the bus station, and the expression is:
Figure BDA00022563065700000510
wherein the content of the first and second substances,
Figure BDA00022563065700000511
the moment when the occupied internet bus leaves the bus station;
constraint C11: if any other parking position except the most upstream parking position of the current bus station is occupied by the occupied internet bus, the arrived internet bus stops at the vacant parking position at the upstream, and the expression is as follows:
Figure BDA00022563065700000512
wherein K is the number of the internet buses which stop in the current bus station for service.
The linear objective function is:
objective function related to all bus delays:
Figure BDA00022563065700000513
objective function related to passenger delay on all buses:
Figure BDA0002256306570000061
wherein, gnThe average number of passengers of the nth networked bus;
objective function related to the clearing time of all buses:
Figure BDA0002256306570000062
and in the step S3, based on the real-time parameters and the online bus arrival and stop management mathematical model, acquiring the stop sequence of the online buses, the arrival time of the online buses and the departure time of the online buses.
Compared with the prior art, the invention has the following advantages:
(1) the result is optimal: according to the problem characteristics, the sequence problem of the networked buses when arriving at the station and stopping is described by utilizing linear mathematical programming; according to the established linear mathematical programming characteristics, the programming model has an optimal value; compared with the existing optimization algorithm, the method can obtain the optimal stop sequence of the bus queue, effectively reduce the delay of stopping the internet buses, improve the stop efficiency and provide better bus service for passengers.
(2) The model can be solved: the model is simple linear programming, can be directly solved by using a linear programming solver and has certain solution; compared with the complicated solving process of nonlinear programming, the model established by the invention is convenient to solve and is beneficial to practical application.
(3) The model can be migrated: the mathematical programming model established by the invention has mobility and can be applied to the scenes that the real-time data of the bus can be obtained and the passenger getting requirement of the station can be obtained; when the model is applied to a specific bus station, the optimal bus arrival and stop sequence can be calculated only by inputting specific values of parameters such as the real-time position of the bus, the bus arrival service time and the like into the model.
Drawings
FIG. 1 is a flow chart of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
Examples
The embodiment provides an internet bus arrival and stop management optimization method based on the following premises: the system comprises a bus station and a plurality of internet buses ready to arrive at the bus station for stop service, wherein the plurality of internet buses ready to arrive at the bus station for stop service do not allow overtaking when entering the bus station, and a bus lane is arranged on a road section where the bus station is located.
The method comprises the following steps:
step S1: establishing a mathematical model for managing the arrival and the stop of the internet buses;
step S2: acquiring linear constraint conditions of a networked bus arrival and stop management mathematical model and linear objective functions related to all bus delays, all bus passenger delays or all bus emptying time;
step S3: and performing the online bus arrival and stop management based on the real-time parameters and the online bus arrival and stop management mathematical model.
Specifically, the method comprises the following steps:
the real-time parameters comprise the number of the internet buses ready to arrive at the bus station for parking service, the number of berth positions contained in the bus station, whether the bus station has the service of the internet buses at the station at present, the highest speed and the lowest speed of the internet buses in running, the time of the internet buses from arriving at the bus station to arriving at the berth positions, the time of the internet buses from the berth positions to leaving the bus station completely, the minimum safe headway between the internet buses and the running information of the internet buses; the running information of the internet buses comprises the time when the internet buses should be out of the schedule, the stop time of the internet buses at the stop, the average number of passengers of the internet buses and the distance between the internet buses and the bus stop.
The linear constraint conditions comprise a service part for the current internet-free bus at the bus station and a service part for the current internet-connected bus at the bus station;
the service part of the current internet-free bus at the bus station comprises:
constraint C1: the running speed of the internet bus can not be higher than the highest speed and can not be lower than the lowest speed, and the mathematical expression is as follows:
Figure BDA0002256306570000071
wherein d isnThe distance between the nth internet bus and the bus station is expressed in the unit of (m),
Figure BDA0002256306570000072
the unit is(s) which is the time when the nth internet bus arrives at the bus station, is a decision variable,
Figure BDA0002256306570000073
the highest running speed of the internet bus is expressed in the unit of (m/s),
Figure BDA0002256306570000074
the lowest running speed of the internet-connected buses is expressed in the unit of (m/s), N is the serial number of the current internet-connected buses, and N is the number of the internet-connected buses ready for arriving at the bus station to stop service;
constraint C2: the time when the internet-connected bus arrives at the berth position is at least longer than the time when the internet-connected bus arrives at the bus station, and the expression is as follows:
Figure BDA0002256306570000075
wherein, TinThe unit of the time for the internet bus to get into the bus from the bus station to the berth position is(s),
Figure BDA0002256306570000081
the unit is(s) when the nth networked bus arrives at the berth position;
constraint C3: the time when the internet-connected bus completely leaves the bus station is at least longer than the time when the internet-connected bus arrives at the berth position, and the expression is as follows:
Figure BDA0002256306570000082
wherein S isnThe stop time of the nth internet bus is the unit of(s) and ToutThe time for the internet bus to get out of the bus from the parking position to completely leave the bus station,
Figure BDA0002256306570000083
the unit is(s) at the moment when the nth internet bus completely leaves the bus station;
constraint C4: the berth position of networking bus is in bus station berth position, the berth number of bus station berth position adds 1 (should berth late to the berth position of networking bus is upstream berth position) from downstream to upper reaches in proper order from 1 (the expression is:
Figure BDA0002256306570000084
wherein, PnThe number of the nth networked bus is the number of the nth networked bus, and P is the number of the nth networked bus;
constraint C5: the time when different internet buses arrive at the respective berth positions at least has the minimum safe headway interval, and the expression is as follows:
Figure BDA0002256306570000085
wherein lm,nIs a variable of 0 to 1, the 1 represents that the mth internet bus arrives at the bus station earlier than the nth internet bus, otherwise, the T is 0secThe minimum safe headway is given as(s), and M is a large enough number;
constraint C6: the time that different networking buses leave the bus station is minimum safe headway at least interval, and the expression is:
Figure BDA0002256306570000086
constraint C7: if the most upstream parking position of the bus station is occupied when the internet-connected bus arrives at the bus station, the internet-connected bus needs to wait for the occupied internet-connected bus occupying the most upstream parking position to leave the bus station and then enter the bus station, and the expression is as follows:
Figure BDA0002256306570000087
Figure BDA0002256306570000088
Figure BDA0002256306570000089
wherein q ism(t) the number of networked buses which arrive at the bus station before the mth networked bus at the time t and do not arrive at the bus station, e (t) is a variable of 0-1, wherein 1 represents that all berth positions of the bus station at the time t have no networked buses to stop, and if 0, the opposite is true, o (t) is a variable of 0-1, and 1 represents that the bus station at the time tThe most upstream berth position of the traffic station is occupied, if the position is 0, otherwise, alpha ism(t) is a variable of 0-1, a value of 1 indicates that the mth internet bus has arrived at the bus station at the time t, and if the value of 0 is not the case, beta ism(t) is a variable of 0-1, wherein a value of 1 indicates that the mth internet bus has entered the bus station at the time t, and if the value of 0 is not the case, the mth internet bus enters the bus station;
constraint C8: if the rest arbitrary berth positions of the bus station except the most upstream berth position are occupied when the internet-connected bus arrives at the bus station, the free berth position of the upstream berth position of the internet-connected bus stop is represented by the following expression:
qm(t)·M+e(t)·M+o(t)·M+[1-αm(t)]·M+βm(t)·M+lm,n·M+[1-βn(t)]·M+γn(t)·M+Pm≥Pn+1
Figure BDA0002256306570000091
Figure BDA0002256306570000092
wherein, γn(t) is a variable of 0-1, wherein 1 represents that the nth internet bus leaves the bus station at the moment t, and if the value is 0, the opposite is true;
constraint C9: the auxiliary constraint expression is:
Figure BDA0002256306570000093
Figure BDA0002256306570000094
Figure BDA0002256306570000095
Figure BDA0002256306570000096
Figure BDA0002256306570000097
Figure BDA0002256306570000098
Figure BDA0002256306570000099
Figure BDA00022563065700000910
Figure BDA00022563065700000911
Figure BDA00022563065700000912
Figure BDA00022563065700000913
Figure BDA00022563065700000914
Figure BDA00022563065700000915
Figure BDA00022563065700000916
Figure BDA00022563065700000917
Figure BDA00022563065700000918
Figure BDA00022563065700000919
e(t)·M+fn·M+[1-βn(t)]·M+γn(t)·M+(1-hm,n)·M+βm(t)·M≥o(t),
Figure BDA0002256306570000101
e(t)·M+(1-fn)·M+[1-βn(t)]·M+γn(t)·M+o(t)≥1,
Figure BDA0002256306570000102
Figure BDA0002256306570000103
Figure BDA0002256306570000104
Figure BDA0002256306570000105
Figure BDA0002256306570000106
Figure BDA0002256306570000107
Figure BDA0002256306570000108
Figure BDA0002256306570000109
Figure BDA00022563065700001010
wherein f isnIs a variable of 0 to 1, the 1 represents the most upstream berth position of the nth internet bus, and if the value is 0, the reverse is true, FnIs a variable of 0 to 1, the value of 1 indicates that the nth internet bus is the last internet bus, and if the value of 0 is not the last internet bus, r isnIndicating the order of the nth networked bus to the bus station, LnIs a variable of 0-1, is 1, and means that the time when the nth internet bus leaves the bus station is later than the time when the nth internet bus leaves the bus station by more than 5 minutes, and is 0, otherwise,
Figure BDA00022563065700001011
represents the time h of the nth networked bus when the bus should be out of the stationm,nThe variable is 0-1, the variable is 1, the mth internet bus arrives at the bus station right behind the nth internet bus, and the variable is 0 if the variable is not.
The current internet-connected bus stop service part of the bus stop at the bus stop comprises constraint C1-constraint C9 and further comprises the following steps:
constraint C10: if the most upstream berth position of present bus station is occupied by occupation net connection bus, then the net connection bus that arrives waits occupation net connection bus gets into the bus station after leaving the bus station, and the expression is:
Figure BDA00022563065700001012
wherein the content of the first and second substances,
Figure BDA00022563065700001013
the moment when the occupied internet bus leaves the bus station;
constraint C11: if any other parking position except the most upstream parking position of the current bus station is occupied by the occupied internet bus, the arrived internet bus stops at the vacant parking position at the upstream, and the expression is as follows:
Figure BDA00022563065700001014
wherein K is the number of the internet buses which stop in the current bus station for service.
The linear objective function is:
objective function related to all bus delays:
Figure BDA0002256306570000111
objective function related to passenger delay on all buses:
Figure BDA0002256306570000112
wherein, gnThe average number of passengers in the nth internet bus is (people);
objective function related to the clearing time of all buses:
Figure BDA0002256306570000113
and step S3, acquiring the stop sequence of the internet buses, the arrival time of the internet buses and the departure time of the internet buses based on the real-time parameters and the arrival stop management mathematical model of the internet buses, and performing arrival stop management of the internet buses.
The embodiment has the following advantages:
the result is optimal: according to the problem characteristics, the sequence problem of the networked buses when arriving at the station and stopping is described by utilizing linear mathematical programming; according to the established linear mathematical programming characteristics, the programming model has an optimal value; compared with the existing optimization algorithm, the method can obtain the optimal parking sequence of the bus queue.
The model can be solved: the model is simple linear programming, can be directly solved by using a linear programming solver and has certain solution; compared with the complicated solving process of nonlinear programming, the model established by the invention is convenient to solve and is beneficial to practical application.
The model can be migrated: the mathematical programming model established by the invention has mobility and can be applied to the scenes that the real-time data of the bus can be obtained and the passenger getting requirement of the station can be obtained; when the model is applied to a specific bus station, the optimal bus arrival and stop sequence can be calculated only by inputting specific values of parameters such as the real-time position of the bus, the bus arrival service time and the like into the model.
Under the background that the internet of vehicles technology is continuously developed, vehicle-vehicle communication, vehicle-road communication and vehicle-infrastructure communication are more and more mature, the bus parking management is optimized based on the real-time data of the internet buses to be parked, the parking resources of the bus stations can be fully utilized, the delay of the internet buses in parking can be effectively reduced, the parking efficiency is improved, and higher-quality bus service is provided for passengers.

Claims (5)

1. An internet bus arrival and stop management optimization method is characterized by comprising the following steps:
step S1: establishing a mathematical model for managing the arrival and the stop of the internet buses;
step S2: acquiring linear constraint conditions of a networked bus arrival and stop management mathematical model and linear objective functions related to all bus delays, all bus passenger delays or all bus emptying time;
step S3: the online bus arrival and stop management is carried out based on the real-time parameters and the online bus arrival and stop management mathematical model;
the real-time parameters comprise the number of the internet buses ready to arrive at the bus station for parking service, the number of berth positions contained in the bus station, whether the bus station has the service that the internet buses stop at the station at present, the highest speed and the lowest speed of the internet buses in running, the time of the internet buses from arriving at the bus station to arriving at the berth positions, the time of the internet buses from the berth positions to leaving the bus station completely, the minimum safe headway between the internet buses and the running information of the internet buses;
the linear constraint conditions comprise a service part for the current internet-free bus stop of the bus station and a service part for the current internet-connected bus stop of the bus station;
the service part of the current internet-free bus at the bus station comprises:
constraint C1: the running speed of the internet bus can not be higher than the highest speed and can not be lower than the lowest speed, and the mathematical expression is as follows:
Figure FDA0003168866490000011
wherein d isnIs the distance between the nth internet bus and the bus station,
Figure FDA0003168866490000012
the moment when the nth internet bus arrives at the bus station,
Figure FDA0003168866490000013
is the highest speed of the internet bus running,
Figure FDA0003168866490000014
the number of the internet buses to be served at the bus stop is N;
constraint C2: the time when the internet-connected bus arrives at the berth position is at least longer than the time when the internet-connected bus arrives at the bus station, and the expression is as follows:
Figure FDA0003168866490000015
wherein, TinThe time for the internet bus to get in from the bus station to the berth position is required,
Figure FDA0003168866490000016
the moment when the nth internet bus reaches the berth position;
constraint C3: the time when the internet-connected bus completely leaves the bus station is at least longer than the time when the internet-connected bus arrives at the berth position, and the expression is as follows:
Figure FDA0003168866490000021
wherein S isnThe stop time length T of the nth internet busoutThe time for the internet bus to get out of the bus from the parking position to completely leave the bus station,
Figure FDA0003168866490000022
the moment when the nth internet bus completely leaves the bus station;
constraint C4: the berth position of the internet bus is in the berth position of a bus station, the berth number of the berth position of the bus station sequentially adds 1 from downstream to upstream from 1, and the expression is as follows:
Figure FDA0003168866490000023
wherein, PnThe number of the nth networked bus is the number of the nth networked bus, and P is the number of the nth networked bus;
constraint C5: the time when different internet buses arrive at the respective berth positions at least has the minimum safe headway interval, and the expression is as follows:
Figure FDA0003168866490000024
wherein lm,nIs a variable of 0 to 1, the 1 represents that the mth internet bus arrives at the bus station earlier than the nth internet bus, otherwise, the T is 0secM is a sufficiently large number for the minimum safe headway;
constraint C6: the time that different networking buses leave the bus station is minimum safe headway at least interval, and the expression is:
Figure FDA0003168866490000025
constraint C7: if the most upstream parking position of the bus station is occupied when the internet-connected bus arrives at the bus station, the internet-connected bus needs to wait for the occupied internet-connected bus occupying the most upstream parking position to leave the bus station and then enter the bus station, and the expression is as follows:
Figure FDA0003168866490000026
wherein q ism(t) the number of networked buses which arrive at the bus station before the mth networked bus at the time t and do not arrive at the bus station, e (t) is a variable of 0-1, wherein 1 represents that all parking positions of the bus station at the time t have no networked buses to park, otherwise, 0 is true, o (t) is a variable of 0-1, wherein 1 represents that the most upstream parking position of the bus station at the time t is occupied, otherwise, 0 is true, and alpha (a) ism(t) is a variable of 0-1, a value of 1 indicates that the mth internet bus has arrived at the bus station at the time t, and if the value of 0 is not the case, beta ism(t) is a variable of 0-1, wherein a value of 1 indicates that the mth internet bus has entered the bus station at the time t, and if the value of 0 is not the case, the mth internet bus enters the bus station;
constraint C8: if the rest arbitrary berth positions of the bus station except the most upstream berth position are occupied when the internet-connected bus arrives at the bus station, the free berth position of the upstream berth position of the internet-connected bus stop is represented by the following expression:
Figure FDA00031688664900000322
wherein, γn(t) is a variable of 0-1, wherein 1 represents that the nth internet bus leaves the bus station at the moment t, and if the value is 0, the opposite is true;
constraint C9: the auxiliary constraint expression is:
Figure FDA0003168866490000033
Figure FDA0003168866490000034
Figure FDA0003168866490000035
Figure FDA0003168866490000036
Figure FDA0003168866490000037
Figure FDA0003168866490000038
Figure FDA0003168866490000039
Figure FDA00031688664900000310
Figure FDA00031688664900000311
Figure FDA00031688664900000312
Figure FDA00031688664900000313
Figure FDA00031688664900000314
Figure FDA00031688664900000315
Figure FDA00031688664900000316
Figure FDA00031688664900000317
Figure FDA00031688664900000318
Figure FDA00031688664900000319
Figure FDA00031688664900000320
Figure FDA00031688664900000321
Figure FDA0003168866490000041
Figure FDA0003168866490000042
Figure FDA0003168866490000043
Figure FDA0003168866490000044
Figure FDA0003168866490000045
Figure FDA0003168866490000046
wherein f isnIs a variable of 0 to 1, the 1 represents the most upstream berth position of the nth internet bus, and if the value is 0, the reverse is true, FnIs a variable of 0 to 1, the value of 1 indicates that the nth internet bus is the last internet bus, and if the value of 0 is not the last internet bus, r isnIndicating the order of the nth networked bus to the bus station, LnIs a variable of 0-1, is 1, and means that the time when the nth internet bus leaves the bus station is later than the time when the nth internet bus leaves the bus station by more than 5 minutes, and is 0, otherwise,
Figure FDA0003168866490000047
represents the time h of the nth networked bus when the bus should be out of the stationm,nThe variable is 0-1, the variable is 1, the mth internet bus arrives at the bus station right behind the nth internet bus, and the variable is 0 if the variable is not.
2. The method as claimed in claim 1, wherein the driving information of the internet buses comprises the time of departure in the schedule of the internet buses, the stop time of the internet buses at the stop, the average number of passengers in the internet buses and the distance between the internet buses and the bus stop.
3. The method as claimed in claim 1, wherein the service section of the bus station where the internet-connected bus is currently located at the station comprises constraint C1-constraint C9, and further comprises:
constraint C10: if the most upstream berth position of present bus station is occupied by occupation net connection bus, then the net connection bus that arrives waits occupation net connection bus gets into the bus station after leaving the bus station, and the expression is:
Figure FDA0003168866490000048
wherein the content of the first and second substances,
Figure FDA0003168866490000049
the moment when the occupied internet bus leaves the bus station;
constraint C11: if any other parking position except the most upstream parking position of the current bus station is occupied by the occupied internet bus, the arrived internet bus stops at the vacant parking position at the upstream, and the expression is as follows:
Figure FDA00031688664900000410
wherein K is the number of the internet buses which stop in the current bus station for service.
4. The method for optimizing the management of the arrival and the stop of the internet-connected buses as claimed in claim 1, wherein the linear objective function is as follows:
objective function related to all bus delays:
Figure FDA0003168866490000051
objective function related to passenger delay on all buses:
Figure FDA0003168866490000052
wherein, gnThe average number of passengers of the nth networked bus;
objective function related to the clearing time of all buses:
Figure FDA0003168866490000053
5. the method for optimizing the management of the networked buses for arriving at the station as claimed in claim 1, wherein in step S3, the order of the networked buses, the arrival time of the networked buses, and the departure time of the networked buses are obtained based on the real-time parameters and the mathematical model for managing the networked buses for arriving at the station.
CN201911054958.8A 2019-10-31 2019-10-31 Internet bus arrival and stop management optimization method Active CN110782694B (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201911054958.8A CN110782694B (en) 2019-10-31 2019-10-31 Internet bus arrival and stop management optimization method
PCT/CN2020/124527 WO2021083232A1 (en) 2019-10-31 2020-10-28 Networked bus arrival and stop management optimization method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201911054958.8A CN110782694B (en) 2019-10-31 2019-10-31 Internet bus arrival and stop management optimization method

Publications (2)

Publication Number Publication Date
CN110782694A CN110782694A (en) 2020-02-11
CN110782694B true CN110782694B (en) 2021-10-08

Family

ID=69388054

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201911054958.8A Active CN110782694B (en) 2019-10-31 2019-10-31 Internet bus arrival and stop management optimization method

Country Status (2)

Country Link
CN (1) CN110782694B (en)
WO (1) WO2021083232A1 (en)

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110782694B (en) * 2019-10-31 2021-10-08 同济大学 Internet bus arrival and stop management optimization method
CN111047228B (en) * 2020-03-13 2020-08-04 武汉元光科技有限公司 Bus station separating method and system
CN113393137B (en) * 2021-06-22 2023-05-12 华录智达科技股份有限公司 Scheduling sharing system based on Internet of vehicles
CN113470366B (en) * 2021-09-01 2021-11-16 南通华豪巨电子科技有限公司 Intelligent bus stop time prediction method and system based on big data
CN114999207B (en) * 2022-05-27 2023-04-07 大连海事大学 Bus ecological approach guiding method in intelligent network connection environment
CN117058909B (en) * 2023-09-01 2024-01-23 大连海事大学 Bus station-parking electricity supplementing method considering signal coordination and anti-series bus

Family Cites Families (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101388143B (en) * 2007-09-14 2011-04-13 同济大学 Bus arriving time prediction method based on floating data of the bus
TW201220237A (en) * 2010-11-02 2012-05-16 Hon Hai Prec Ind Co Ltd System and method for managing buses
CN102831767B (en) * 2012-08-13 2014-07-09 东南大学 Multi-mode station stopping method at optimized comprehensive cost for urban public transport
CN103903429B (en) * 2014-03-26 2016-03-02 东南大学 A kind of delay time at stop combination forecasting method of bus rapid transit bus stop
US11189167B2 (en) * 2017-11-01 2021-11-30 Avis Budget Car Rental, LLC Connected user communication and interface system with shuttle tracking application
CN108985503B (en) * 2018-07-02 2021-07-09 上海理工大学 Bus rapid transit schedule compiling method
CN109726512A (en) * 2019-01-27 2019-05-07 上海理工大学 A kind of determination method of bay engineering constructions effective berth number
CN109979186B (en) * 2019-03-12 2021-08-10 合肥工业大学 Bus parking position real-time distribution method based on GPS system
CN110245377B (en) * 2019-05-08 2023-08-04 暨南大学 Travel scheme recommendation method and recommendation system
CN110288827B (en) * 2019-06-19 2020-05-05 河海大学 Bus running scheduling method considering influence of queuing overflow of stop
CN110288829B (en) * 2019-06-19 2020-07-17 河海大学 Method for setting and judging parking berth number of bay type bus stop
CN110334867A (en) * 2019-07-05 2019-10-15 河海大学常州校区 A kind of intelligent public transportation system and operation method of passenger-vehicle-cloud interaction
CN110782694B (en) * 2019-10-31 2021-10-08 同济大学 Internet bus arrival and stop management optimization method

Also Published As

Publication number Publication date
CN110782694A (en) 2020-02-11
WO2021083232A1 (en) 2021-05-06

Similar Documents

Publication Publication Date Title
CN110782694B (en) Internet bus arrival and stop management optimization method
WO2021004115A1 (en) Combined dispatching optimization method for manned buses and autonomous buses
CN110245806B (en) Urban rail transit passenger flow management and control method and system
CN104408908B (en) Public transit vehicle more station dispatching method and system
CN106781435B (en) Non-signal control intersection vehicle formation passing method based on wireless communication
CN111063209B (en) Automatic driving bus combined dispatching optimization method matched with inter-section bus
CN107248299B (en) Special-lane bus priority trunk line coordination control method based on standing time
CN107274684A (en) A kind of single-point integrative design intersection policy selection method under bus or train route cooperative surroundings
WO2018000931A1 (en) Small passenger car intensive scheduling method for multi-constraint networks
CN103793760A (en) Multi-mode optimization method for comprehensive transportation junction interior passenger flow transfer distribution ratio
CN112053580A (en) Intersection bus signal priority control optimization method
CN112580866B (en) Bus route bunching optimization method based on whole-course vehicle and inter-vehicle combined scheduling
CN110796877A (en) Traffic signal control and bus dispatching cooperative control method facing one-way bus line
CN112561379A (en) Regional network taxi appointment-oriented scheduling method
CN111667711A (en) Intelligent control method of unmanned public transportation system based on Internet of things
CN106355911A (en) Prior control method for bus rapid transit signal during traffic peak duration
CN113077162A (en) Multi-vehicle type customized bus area scheduling method facing real-time requirements
CN112906179A (en) Urban rail transit passenger flow control optimization method based on fluid queuing network
CN112249101B (en) High-speed rail network delay propagation quantitative analysis method based on matrix representation
CN115730781A (en) Bus route optimization system based on big data analysis
CN116109081A (en) Dynamic bus scheduling optimization method and device based on Internet of things
CN113611132B (en) Saturated single-intersection bus signal control method based on bus-road cooperative system
CN206058511U (en) A kind of bus running planning system
CN114677846A (en) Dynamic allocation method for signalized intersection entrance lane in pure internet automatic driving environment
CN113888387A (en) Multi-objective operation optimization method based on passenger flow demand

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant