CN113140105A - Method and system for managing operation and scheduling of high-peak bus - Google Patents
Method and system for managing operation and scheduling of high-peak bus Download PDFInfo
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- CN113140105A CN113140105A CN202010050920.XA CN202010050920A CN113140105A CN 113140105 A CN113140105 A CN 113140105A CN 202010050920 A CN202010050920 A CN 202010050920A CN 113140105 A CN113140105 A CN 113140105A
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- G—PHYSICS
- G08—SIGNALLING
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- 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
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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
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- 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
- G08G1/127—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 to a central station ; Indicators in a central station
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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Abstract
The invention relates to the technical field of bus dispatching management, in particular to a method and a system for managing bus running dispatching in a rush hour period. The intelligent scheduling method and system based on cloud big data analysis can effectively avoid the problem that passengers at intermediate stations cannot get on the bus due to the fact that the same bus stops at bus stations with a large number of passengers continuously, and can also solve the problem that the running distance between a rear bus and a front bus is too short or even overlapped due to the fact that the front bus consumes too long time because the number of passengers continuously get on the front bus in a short time; and because the system does not need to stop at a station, the one-way passenger carrying time can be greatly improved.
Description
Technical Field
The invention relates to the technical field of bus dispatching management, in particular to a method and a system for managing bus running dispatching in rush hour.
Background
The large-scale city is influenced by high housing rate and high housing renting, city employment personnel often live in an outer ring or a suburb, the working places are mostly concentrated in a city center science and technology park or CBD, the space distance between the working places and the living places is large in span, and the time for getting on and off duty is concentrated, so that the rush hour passenger flow of the city at early night and off duty is formed; at present, a plurality of large cities in China have serious large passenger flow at peak time on and off duty, and bus transportation is one of the main modes of urban public transportation, and due to the limitation of the size of a bus compartment, the passenger volume of a single bus is limited, and the passenger flow must be rapidly conveyed in a short and even mode at the peak time; however, due to the concentrated residence and passenger flow, a large number of passengers are usually on a plurality of consecutive stations of the previous bus, so that the bus is crowded, a large amount of time is consumed for waiting for the passengers to get on the bus, the time for the immediately following bus to wait for the passengers to get on the bus on the previous bus is gradually close to or even exceeds the time for the previous bus, the previous bus has a large number of passengers, the passenger volume on the following bus is usually not saturated, so that the time consumed at the bus station is less, the departure time is earlier, the bus is easier to approach the previous bus, the vicious circle is formed, the passenger transport capacity is wasted, and the congestion and the crowding degree in the peak period are increased. Therefore, how to effectively break the circulation by a regulation and control means is a problem which needs to be solved urgently.
Disclosure of Invention
In order to overcome the defects, the invention aims to provide a high-peak bus operation scheduling management method and system for effectively improving the transportation capacity of public transport in the peak period.
The purpose of the invention is realized by the following technical scheme:
a high-peak bus operation scheduling management method comprises the following steps:
s1, the passenger submits travel information to a cloud server, wherein the travel information comprises the identity of the passenger and the getting-on/off bus stop;
s2, collecting getting-on passenger information by the bus, wherein the passenger information comprises passenger identities, the number of getting-on passengers and the number of passengers in the bus, and uploading the passenger information and the bus position information to a cloud server in real time;
s3, the cloud server carries out grade classification on the bus stops according to the travel information;
s4, the cloud server judges the peak direction according to the travel information;
and S5, the cloud server analyzes and directs the scheduled bus to stop at the designated station according to the travel information, the passenger information, the peak direction and the position information in real time.
As an improvement, the cloud server records information of passengers getting on or off the bus at each bus station and establishes a peak database.
As an improvement, the peak direction bus stops are divided into a plurality of grades according to the number of passengers getting on the bus;
preferably three stages, namely a first-stage station, a second-stage station and a third-stage station;
the cloud server analyzes big data based on the peak database and in combination with real-time passenger information and travel information, and commands the bus to skip the bus stop of a certain level and stop at the next level when the passable limit of the bus is lower than the threshold of the number of passengers getting on the bus stop of the certain level.
As an improvement, when continuous first-level stations exist, the cloud server instructs the bus to stop the first-level stations nearby and skip the next first-level station.
As an improvement, if the bus stops at intervals in the off-peak direction.
A bus operation scheduling management system comprises,
the system comprises a passenger end, a cloud server and a system server, wherein the passenger end uploads travel information to the cloud server, and the travel information comprises passenger identities and bus stations for getting on and off buses;
the bus acquires the information of passengers getting on the bus, wherein the information of the passengers comprises the identity of the passengers, the number of the passengers getting on the bus and the number of the passengers in the bus, and uploads the information of the passengers and the information of the positions of the buses to the cloud server in real time;
the cloud server comprises a site classification module, a peak direction judgment module and an analysis scheduling module; wherein the content of the first and second substances,
the bus stop classification module is used for carrying out grade classification on bus stops according to the travel information;
the peak direction judging module is used for judging the peak direction;
and the analysis scheduling module analyzes and commands a scheduled bus to stop at an appointed station according to the travel information, the passenger information, the peak direction and the position information in real time.
As an improvement, the cloud server further comprises a storage module, which is used for recording information of passengers getting on or off the bus at each bus station and establishing a peak database.
As an improvement, the station classification module classifies bus stations in the peak direction into a plurality of grades according to the number of passengers getting on the bus;
preferably three stages, namely a first-stage station, a second-stage station and a third-stage station;
the analysis scheduling module is used for carrying out big data analysis based on the peak database and in combination with real-time passenger information and travel information, and when the passable limit of the bus is lower than the threshold value of the number of passengers getting on the bus station at a certain level, the bus is instructed to skip the bus station at the certain level and stop at the next level.
As an improvement, when continuous first-level stations exist, the analysis scheduling module instructs the bus to stop the first-level stations nearby and skip the next first-level station.
As an improvement, if the peak direction judging module judges that the bus stop is in the off-peak direction, the analysis scheduling module commands the bus stop at intervals.
The invention discloses a method and a system for managing public transport operation scheduling in rush hour, which command and schedule buses to stop at specified stations according to the grades of bus stations by analyzing according to travel information uploaded by passengers, passenger information and position information uploaded by the buses and judged rush hour directions in real time. The intelligent scheduling method and system based on cloud big data analysis can effectively avoid the problem that passengers at intermediate stations cannot get on the bus due to the fact that the same bus stops at bus stations with a large number of passengers continuously, and can also solve the problem that the running distance between a rear bus and a front bus is too short or even overlapped due to the fact that the front bus consumes too long time because the number of passengers continuously get on the front bus in a short time; and because the system does not need to stop at a station, the one-way passenger carrying time can be greatly improved.
Drawings
For the purpose of easy explanation, the present invention will be described in detail with reference to the following preferred embodiments and the accompanying drawings.
FIG. 1 is a schematic block diagram of logic steps of a method for managing public transportation operation scheduling in rush hour;
FIG. 2 is a schematic block diagram of a logical structure of a public transportation operation scheduling management system in a rush hour;
fig. 3 is a scene schematic diagram of a method and a system for managing public transportation operation scheduling in rush hour.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", and the like, indicate orientations and positional relationships based on those shown in the drawings, and are used only for convenience of description and simplicity of description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be considered as limiting the present invention. Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
In the description of the present invention, it should be noted that the terms "mounted," "connected," and "connected" are to be construed broadly and may be, for example, fixedly connected, detachably connected, or integrally connected unless otherwise explicitly stated or limited. Either mechanically or electrically. Either directly or indirectly through intervening media, either internally or in any other relationship. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Example 1
An embodiment of the method for managing bus operation scheduling in high peak section of the present invention is described in detail below, please refer to fig. 1, which includes the following steps:
s1, the passenger submits travel information to a cloud server, wherein the travel information comprises the identity of the passenger and the getting-on/off bus stop;
s2, collecting getting-on passenger information by the bus, wherein the passenger information comprises passenger identities, the number of getting-on passengers and the number of passengers in the bus, and uploading the passenger information and the bus position information to a cloud server in real time;
s3, the cloud server carries out grade classification on the bus stops according to the travel information; the public transport stations in the peak direction are divided into a plurality of grades according to the number of passengers getting on the bus; preferably three stages, namely a first-stage station, a second-stage station and a third-stage station;
s4, the cloud server judges the peak direction according to the travel information;
and S5, the cloud server analyzes and directs the scheduled bus to stop at the designated station according to the travel information, the passenger information, the peak direction and the position information in real time. The cloud server records information of passengers getting on and off the bus at each bus station and establishes a peak database.
The cloud server analyzes big data based on the peak database and in combination with real-time passenger information and travel information, and commands the bus to skip the bus stop of a certain level and stop at the next level when the passable limit of the bus is lower than the threshold of the number of passengers getting on the bus stop of the certain level. And when continuous first-level stations exist, the cloud server instructs the bus to stop the first-level stations nearby and skip the next first-level station. If the direction is judged to be the off-peak direction, the bus stops at intervals.
Example 2
The invention also provides a bus operation scheduling management system, as shown in fig. 2, comprising,
the passenger end 200 uploads the travel information to the cloud server, wherein the travel information comprises the identity of a passenger and the bus stop of getting on or off the bus;
the bus 100 is used for acquiring the information of passengers getting on the bus, wherein the information of the passengers comprises the identity of the passengers, the number of the passengers getting on the bus and the number of the passengers in the bus, and uploading the information of the passengers and the information of the positions of the buses to a cloud server in real time;
the cloud server 300 comprises a site classification module 301, a peak direction judgment module 302 and an analysis scheduling module 303; wherein the content of the first and second substances,
the station classification module 301 is configured to perform level classification on bus stations according to the travel information; the station classification module 301 classifies bus stations in the peak direction into a plurality of grades according to the number of passengers getting on the bus; preferably three stages, namely a first-stage station, a second-stage station and a third-stage station;
the peak direction judging module 302 is configured to judge a peak direction;
the analysis scheduling module 303 analyzes and directs the scheduled bus to stop at the designated station according to the travel information, the passenger information, the peak direction and the position information in real time.
The analysis scheduling module 303 performs big data analysis based on the peak database and in combination with the real-time passenger information and the travel information, and instructs the bus to stop at the next bus stop by skipping the bus stop when the passable limit of the bus is lower than the threshold of the number of passengers getting on the bus stop at a certain level. When there are consecutive first-level stops, the analysis scheduling module 303 directs the bus to stop at the first-level stop nearby and skip the next first-level stop. If the peak direction judging module 302 judges that the bus stop is in the off-peak direction, the analysis and scheduling module commands the bus stop to stop at intervals.
The cloud server further includes a storage module 304, which is used for recording information of passengers getting on or off the bus at each bus station, and establishing a peak database.
Example 3
As shown in fig. 3, a plurality of bus stops exist on the whole line, when a passenger arrives at a boarding stop, the passenger uploads the trip information of the boarding and disembarking stops to the cloud server through passenger-side software, and the cloud server receives the trip information and the passenger identity information encapsulated by the trip information; the bus uploads the position information, the identity information of passengers on the bus and the number of the passengers to a cloud server in real time; in the cloud server, passenger carrying limit quantity is preset according to the type of the bus; the cloud server divides the bus stops in the peak direction into three stages according to the number of passengers getting on the bus, and the three stages are respectively a primary stop, a secondary stop and a tertiary stop; the cloud server judges according to the current number of passengers of the bus and the grade of a bus stop to be reached, and commands the bus to stop at the bus stop when the limit of the number of passengers which can be carried by the bus is higher than the threshold value of the number of passengers getting on the bus stop at a certain grade; specifically, as shown in fig. 3, if the bus station 1 is a primary station and the limit of passengers that can be carried in the bus 1 is higher than the lowest threshold of boarding at the primary station, the bus 1 stops at the bus station 1; when the limit of passengers available for the bus is lower than the threshold of the number of passengers getting on the bus stop at a certain level, commanding the bus to skip the bus stop at the certain level and stop at the next level; specifically, as shown in fig. 3, if the bus station 1 is a secondary station, the bus station 2 is a tertiary station, and the limit of passengers that can be taken by the bus 1 is lower than the minimum threshold for getting on the bus at the secondary station, the bus 1 skips over the bus station 1, and stops at the bus station 2.
And if the cloud server judges that the current driving direction of the bus is not the peak direction, commanding the bus to stop at the bus stop at intervals. As shown in fig. 3, the driving direction of the bus 2 is a non-peak direction, and the bus 2 stops at the bus station 5 and the bus station 7 at intervals and does not stop at the bus station 6 and the bus station 8; the latter bus in the non-peak direction stops with the former bus in a cross way; for example, stop at the bus station 6 and 8, and stop at the bus station 5 and 7. Through stopping at intervals, the bus can rapidly return at a peak section and start from the peak direction again to increase the transport capacity.
The invention discloses a method and a system for managing public transport operation scheduling in rush hour, which command and schedule buses to stop at specified stations according to the grades of bus stations by analyzing according to travel information uploaded by passengers, passenger information and position information uploaded by the buses and judged rush hour directions in real time. The intelligent scheduling method and system based on cloud big data analysis can effectively avoid the problem that passengers at intermediate stations cannot get on the bus due to the fact that the same bus stops at bus stations with a large number of passengers continuously, and can also solve the problem that the running distance between a rear bus and a front bus is too short or even overlapped due to the fact that the front bus consumes too long time because the number of passengers continuously get on the front bus in a short time; and because the system does not need to stop at a station, the one-way passenger carrying time can be greatly improved.
In the description of the present specification, reference to the description of the terms "one embodiment", "some embodiments", "an illustrative embodiment", "an example", "a specific example", or "some examples", etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. A high-peak bus operation scheduling management method is characterized by comprising the following steps:
s1, the passenger submits travel information to a cloud server, wherein the travel information comprises the identity of the passenger and the getting-on/off bus stop;
s2, collecting getting-on passenger information by the bus, wherein the passenger information comprises passenger identities, the number of getting-on passengers and the number of passengers in the bus, and uploading the passenger information and the bus position information to a cloud server in real time;
s3, the cloud server carries out grade classification on the bus stops according to the travel information;
s4, the cloud server judges the peak direction according to the travel information;
and S5, the cloud server analyzes and directs the scheduled bus to stop at the designated station according to the travel information, the passenger information, the peak direction and the position information in real time.
2. The method as claimed in claim 1, wherein the cloud server records information of passengers getting on/off bus at each bus station and establishes a peak database.
3. The method as claimed in claim 2, wherein the peak direction bus stops are divided into a plurality of classes according to the number of passengers getting on the bus;
preferably three stages, namely a first-stage station, a second-stage station and a third-stage station;
the cloud server analyzes big data based on the peak database and in combination with real-time passenger information and travel information, and commands the bus to skip the bus stop of a certain level and stop at the next level when the passable limit of the bus is lower than the threshold of the number of passengers getting on the bus stop of the certain level.
4. The method as claimed in claim 3, wherein when there are consecutive first-class stops, the cloud server directs the bus to stop at the first-class stop nearby and skip the next first-class stop.
5. The method as claimed in claim 4, wherein if it is determined that the bus is in the off-peak direction, the bus stops are stopped at intervals.
6. A bus operation scheduling management system is characterized by comprising,
the system comprises a passenger end, a cloud server and a system server, wherein the passenger end uploads travel information to the cloud server, and the travel information comprises passenger identities and bus stations for getting on and off buses;
the bus acquires the information of passengers getting on the bus, wherein the information of the passengers comprises the identity of the passengers, the number of the passengers getting on the bus and the number of the passengers in the bus, and uploads the information of the passengers and the information of the positions of the buses to the cloud server in real time;
the cloud server comprises a site classification module, a peak direction judgment module and an analysis scheduling module; wherein the content of the first and second substances,
the bus stop classification module is used for carrying out grade classification on bus stops according to the travel information;
the peak direction judging module is used for judging the peak direction;
and the analysis scheduling module analyzes and commands a scheduled bus to stop at an appointed station according to the travel information, the passenger information, the peak direction and the position information in real time.
7. The system as claimed in claim 6, wherein the cloud server further comprises a storage module for recording information of passengers getting on/off the bus at each bus station and establishing a peak database.
8. The system as claimed in claim 6, wherein the station classification module classifies the bus stations in the peak direction into a plurality of classes according to the number of passengers getting on the bus;
preferably three stages, namely a first-stage station, a second-stage station and a third-stage station;
the analysis scheduling module is used for carrying out big data analysis based on the peak database and in combination with real-time passenger information and travel information, and when the passable limit of the bus is lower than the threshold value of the number of passengers getting on the bus station at a certain level, the bus is instructed to skip the bus station at the certain level and stop at the next level.
9. The system as claimed in claim 8, wherein when there are consecutive primary stops, the analysis and scheduling module directs the bus to stop at the primary stop nearby and skip the next primary stop.
10. The method as claimed in claim 9, wherein if the peak direction determining module determines that the peak direction is an off-peak direction, the analyzing and dispatching module commands the bus stations to stop at different bus stops.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN202010050920.XA CN113140105A (en) | 2020-01-17 | 2020-01-17 | Method and system for managing operation and scheduling of high-peak bus |
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| CN202010050920.XA CN113140105A (en) | 2020-01-17 | 2020-01-17 | Method and system for managing operation and scheduling of high-peak bus |
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| CN113140105A true CN113140105A (en) | 2021-07-20 |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114418349A (en) * | 2021-12-30 | 2022-04-29 | 深圳云天励飞技术股份有限公司 | Bus peak special line evaluation method, device, equipment and storage medium |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114418349A (en) * | 2021-12-30 | 2022-04-29 | 深圳云天励飞技术股份有限公司 | Bus peak special line evaluation method, device, equipment and storage medium |
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