CN112700360A - Intelligent riding guidance device and method for subway station - Google Patents
Intelligent riding guidance device and method for subway station Download PDFInfo
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Abstract
The invention discloses an intelligent riding guidance device and method for a subway station, wherein the intelligent riding guidance device comprises a data interface unit, an intelligent analysis unit, a network switch and a riding guidance terminal, wherein the network switch is respectively and electrically connected with the data interface unit, the intelligent analysis unit and the riding guidance terminal; the data interface unit is used for acquiring train position information, train weighing data and station passenger flow density distribution data in real time; the intelligent analysis unit is used for matching the arrival train, analyzing and calculating the crowdedness of each carriage of the arrival train and the crowdedness of each waiting area of the station and generating a riding suggestion; the bus taking guidance terminal is used for displaying the degree of congestion of each carriage of the arriving train, the degree of congestion of each waiting area of the station and the bus taking advice in real time. The bus taking guidance function can be realized through the bus taking guidance system, the difficulty of a station passenger transportation organization can be effectively relieved, and the bus taking experience of passengers is improved.
Description
Technical Field
The invention relates to the field of urban rail transit, in particular to an intelligent bus taking induction device and method for a subway station.
Background
The Passenger Information System (PIS) arranged at the subway station can provide the time information of the last three arriving trains, but cannot provide guidance and help for passengers waiting for the trains. Especially for stations with large passenger traffic, it is common that passengers get congested in local areas, thus resulting in a situation where passengers cannot get on the train. In fact, a subway train generally consists of 6 or 8 sections, some carriages are possibly crowded, but some carriages are relatively empty, passengers cannot get on the train in time due to asymmetric information, so that not only is the time influence on the trip of the passengers caused, but also the difficulty is brought to station passenger transportation management, more importantly, under the background that the current subway train transportation capacity is limited, unbalanced passenger carrying of each carriage causes the waste of train transportation capacity resources, and the loss and the influence cannot be formulated by economic indexes.
The subway station riding guidance is a complex technology, and not only the passenger flow condition of each waiting area of a station needs to be mastered, but also the passenger carrying condition of each carriage of a train arriving at the station needs to be mastered. For technical reasons, no ideal ride induction product and scheme are available at home at present.
Disclosure of Invention
The invention aims to solve the technical problem in the prior art and provides an intelligent bus taking guidance device and method for a subway station.
The invention solves the technical problems through the following technical scheme:
the invention provides an intelligent riding guidance device for a subway station, which comprises a data interface unit, an intelligent analysis unit, a network switch and a riding guidance terminal, wherein the network switch is electrically connected with the data interface unit, the intelligent analysis unit and the riding guidance terminal respectively;
the data interface unit is used for acquiring train position information, train weighing data and station passenger flow density distribution data in real time and sending the train position information, the train weighing data and the station passenger flow density distribution data to the intelligent analysis unit through the network switch;
the intelligent analysis unit is used for matching the arriving train, analyzing and calculating the crowdedness of each carriage of the arriving train and the crowdedness of each waiting area of the station, generating a riding suggestion, and sending the crowdedness of each carriage of the arriving train, the crowdedness of each waiting area of the station and the riding suggestion to the riding guidance terminal through the network switch;
the bus taking guidance terminal is used for displaying the degree of congestion of each carriage of the arriving train, the degree of congestion of each waiting area of the station and the bus taking advice in real time.
Optionally, the data interface unit includes a video analysis interface module, a vehicle system interface module, and a signal system interface module;
the video analysis interface module is connected with the station intelligent video analysis system and is used for collecting station passenger flow density distribution data;
the vehicle system interface module is connected with a vehicle system and used for acquiring train group numbers of the train running on the whole line and weighing data of each carriage of the train;
and the signal system interface module is connected with the signal system and is used for acquiring train group numbers and train position information of the train running on the whole line.
Optionally, the intelligent analysis unit comprises an arrival train matching module, a congestion degree measuring and calculating module and an optimal waiting area calculating module;
the arrival train matching module is used for matching the arrival train and acquiring the train group number of the arrival train according to the position information of the whole-line running train and the preset station position information;
the congestion degree measuring and calculating module is used for measuring and calculating the congestion degree of each carriage of the arriving train according to the weighing data of each carriage of the arriving train and measuring and calculating the congestion degree of each waiting area of the station according to the passenger flow density data of each waiting area of the station;
the optimal waiting area calculating module is used for calculating the optimal waiting area according to the crowdedness of each carriage of the arriving train and the crowdedness of each waiting area of the station and generating a riding suggestion.
Optionally, the riding guidance terminal comprises an optimal waiting route calculation module and a guidance information display module which are electrically connected with each other;
the optimal waiting route calculation module is used for calculating an optimal waiting route and generating a riding route guide identifier;
the guidance information display module is used for displaying the crowdedness, riding suggestions and passenger route guidance marks of each waiting area of the station and each carriage of the arriving train.
Optionally, the riding guidance terminal is further configured to display the degree of congestion of each carriage of the train and the degree of congestion of each waiting area of the station at different levels in different colors.
A second aspect of the present invention provides an intelligent bus taking guidance method for a subway station, which is implemented by using the intelligent bus taking guidance device provided in the first aspect, and the method includes the following steps:
S1acquiring passenger flow density data of each waiting area of a station in real time to generate a comparison relation table of the waiting areas of the station and the passenger flow density data;
S2acquiring the train group number of the whole-line running train and weighing data of each compartment of the corresponding train in real time, and generating a comparison relation table of the train group number and the weighing data of each train;
S3acquiring the train group number of the train running on the whole line and the position information of the corresponding train in real time, and generating a comparison relation table of the train group number and the train position information;
S4analyzing and calculating the matching of the position information of the train running on the whole line and the preset station position information, determining the next train arriving at the station, and acquiring the train set number corresponding to the train arriving at the station;
S5acquiring weighing data of each carriage of the arriving train according to the train set number of the arriving train, and converting the weighing data of each carriage of the arriving train into carriage crowding degree;
S6converting passenger flow density data of each waiting area of the station into crowdedness of each waiting area of the station;
S7generating a riding suggestion according to the degree of congestion of each carriage of the arriving train and the degree of congestion of each waiting area of the station;
S8and displaying the crowdedness of each carriage of the arrival train, the crowdedness of each waiting area of the station and the riding advice in real time.
Optionally, the step S7The method specifically comprises the following steps:
S71establishing a corresponding relation between each carriage of the train and each waiting area of the station, and sequentially calculating the arithmetic sum of the congestion degree of each carriage of the train and the congestion degree of each waiting area of the station to obtain the comprehensive congestion degree of each area;
S72and generating a riding suggestion according to the comprehensive congestion degree of each area.
Optionally, the step S72The method specifically comprises the following steps:
S721analyzing and calculating an optimal waiting area Z1 based on single area statistics by taking the single area as a statistical object and the comprehensive congestion degree as a statistical index;
S722analyzing and calculating an optimal waiting area Z2 based on the statistics of the two continuous areas by taking the two continuous areas as statistical objects and the sum of the comprehensive congestion degrees of the two continuous areas as a statistical index;
S723and generating a riding suggestion according to the optimal waiting area Z1 and the optimal waiting area Z2.
Optionally, the ride advice comprises at least one of:
when the optimal waiting area Z1 and the optimal waiting area Z2 are both in the direction of the head of the vehicle, the riding suggestion is 'please wait in the direction of the head of the vehicle';
when the optimal waiting area Z1 is in the direction of the head of the vehicle and the optimal waiting area Z2 is in the direction of the middle of the vehicle, the riding suggestion is 'please wait in the direction of the head of the vehicle';
when the optimal waiting area Z1 is in the direction of the head of the train and the optimal waiting area Z2 is in the direction of the tail of the train, the riding suggestion is 'please wait for the two ends of the train';
when the optimal waiting area Z1 is in the direction of the train, the riding suggestion is 'please wait in the middle of the train';
when the optimal waiting area Z1 is in the tail direction and the optimal waiting area Z2 is in the head direction, the riding suggestion is 'please wait for the two ends of the train';
when the optimal waiting area Z1 is in the direction of the tail of the vehicle and the optimal waiting area Z2 is in the direction of the middle of the vehicle, the riding suggestion is 'please wait in the direction of the tail of the vehicle';
when the optimal waiting area Z1 and the optimal waiting area Z2 are both in the direction of the tail of the vehicle, the riding suggestion is 'please wait in the direction of the tail of the vehicle'.
Optionally, the method further comprises the steps of:
S9and analyzing an reachable path between the position of the riding guidance terminal and the optimal waiting area, and selecting an optimal riding route.
S10And displaying a riding route guide identifier according to the optimal riding route.
On the basis of the common knowledge in the field, the above preferred conditions can be combined randomly to obtain the preferred embodiments of the invention.
The positive progress effects of the invention are as follows: the invention can provide an all-around visual intelligent bus taking guidance system for the subway station, can show the congestion degree of passenger flow of each waiting area and each carriage of the arriving train in the station in real time, provides bus taking route guidance and bus taking advice for passengers, realizes the bus taking guidance function, can effectively relieve the difficulty of the passenger transportation organization of the station, promotes the bus taking experience of the passengers, and can effectively promote the actual passenger capacity of the train and relieve the peak passenger transportation pressure under the condition of limited transportation capacity of the current subway line.
Drawings
Fig. 1 is a block diagram of an intelligent vehicle taking guidance device according to an embodiment of the present invention.
Fig. 2 is a block diagram of an intelligent vehicle taking guidance device according to another embodiment of the present invention.
Fig. 3 is a flowchart of an intelligent ride guidance method according to an embodiment of the present invention.
Fig. 4 is a flowchart of an intelligent ride guidance method according to another embodiment of the present invention.
Detailed Description
The invention is further illustrated by the following examples, which are not intended to limit the scope of the invention.
The present embodiment provides an intelligent riding guidance device for a subway station, as shown in fig. 1, which includes a data interface unit 100, an intelligent analysis unit 200, a network switch 300 and a riding guidance terminal 400, wherein the network switch 300 is electrically connected to the data interface unit 100, the intelligent analysis unit 200 and the riding guidance terminal 400, respectively.
In an optional embodiment, the network switch is a MOXA EDS-208A industrial switch, and different ports of the network switch are respectively connected to the data interface unit, the intelligent analysis unit and the ride guidance terminal.
The data interface unit 100 is configured to collect train position information, train weighing data, and station passenger flow density distribution data in real time, and send the train position information, train weighing data, and station passenger flow density distribution data to the intelligent analysis unit through the network switch.
In an alternative embodiment, as shown in fig. 2, the data interface unit 100 includes a video analysis interface module 11, a vehicle system interface module 12, and a signal system interface module 13.
The video analysis interface module 11 is connected with the station intelligent video analysis system and used for collecting station passenger flow density distribution data.
The passenger flow density data of each waiting area of the station is divided into 8 areas of an upstream platform and 8 areas of a downstream platform according to the number of train marshalls (considered according to the marshalling of the A-type train and the 8-section marshalling in the embodiment).
The vehicle system interface module 12 is connected to a vehicle system and is used for acquiring train group numbers of the train running on the whole line and weighing data of each carriage of the train.
The signal system interface module 13 is connected with a signal system and used for acquiring train group numbers and train position information of the train running on the whole line.
In an alternative embodiment, the data interface unit is selected from a MOXA DA-682B industrial control computer.
The intelligent analysis unit 200 is configured to match the arriving train, analyze and calculate the degree of congestion of each carriage of the arriving train and the degree of congestion of each waiting area of the station, generate a riding recommendation, and send the degree of congestion of each carriage of the arriving train, the degree of congestion of each waiting area of the station, and the riding recommendation to the riding guidance terminal through the network switch.
In an alternative embodiment, as shown in fig. 2, the intelligent analysis unit 200 includes an arrival train matching module 21, a congestion degree calculation module 22, and an optimal waiting area calculation module 23;
the arrival train matching module 21 is used for matching the arrival train and acquiring the train group number of the arrival train according to the position information of the all-line running train and the preset station position information;
the congestion degree measuring and calculating module 22 is used for measuring and calculating the congestion degree of each carriage of the arriving train according to the weighing data of each carriage of the arriving train, and measuring and calculating the congestion degree of each waiting area of the station according to the passenger flow density data of each waiting area of the station.
The optimal waiting area calculating module 23 is configured to calculate an optimal waiting area according to the degree of congestion of each carriage of the arriving train and the degree of congestion of each waiting area at the station, and generate a riding recommendation.
The bus taking guidance terminal 400 is used for displaying the degree of congestion of each carriage of the arriving train, the degree of congestion of each waiting area of the station and the bus taking advice in real time.
In an alternative embodiment, as shown in fig. 2, the ride guidance terminal 400 includes an optimal waiting route calculation module 41 and a guidance information display module 42 electrically connected to each other.
The optimal waiting route calculating module 41 is configured to calculate an optimal waiting route and generate a riding route guide identifier;
the guidance information display module 42 is used for displaying the congestion degree, the riding advice and the passenger route guidance identification of each waiting area and each carriage of the arriving train at the station.
In an alternative embodiment, in order to better show the crowdedness, the riding advice and the passenger route guidance identification of each waiting area of the station and each carriage of the arriving train to the user, the number of the riding guidance terminals is multiple, as shown in fig. 2.
In an optional implementation manner, the intelligent analysis unit selects a server of RH2288V3, and is connected to the network switch through the internet access, so as to implement interface communication and data interaction with the data interface unit and the ride guidance terminal.
The intelligent analysis unit receives the comparison table of the position information (including direction) of the train running on the whole line and the train group number forwarded by the data interface unit, matches the train position information in the comparison table with the preset station position information, positions the train arriving at the station in real time, updates the train group number of the train arriving at the station and estimates the time for counting down when the train arrives at the station.
The intelligent analysis unit receives the train group number of the full-line running train and the weighing data comparison table of each carriage of the train, which are forwarded by the data interface unit, positions and acquires the weighing data of each carriage of the arriving train according to the updated train group number of the arriving train; on the basis, the weighing data of each carriage of the arriving train is converted into the carriage congestion degree according to a preset conversion rule. The present embodiment expresses the degree of congestion of each car by the number of passengers accommodated per square meter of area.
And the intelligent analysis unit receives the passenger flow density data of each waiting area of the station forwarded by the data interface unit and converts the passenger flow density data of each waiting area of the station into the congestion degree of each waiting area of the station according to a preset conversion rule. The present embodiment expresses the degree of congestion of each waiting area of a station by the number of passengers accommodated per square meter of area.
The intelligent analysis unit respectively calculates the comprehensive congestion degrees of 8 waiting areas in an uplink and a downlink by adopting arithmetic and operation according to the congestion degree of each waiting area in a station and the congestion degree of each carriage of an arriving train; on the basis of the calculation, an optimal waiting area Z1 based on single area statistics and an optimal waiting area Z2 based on two continuous area statistics are calculated respectively.
And the intelligent analysis unit analyzes and forms a riding suggestion according to the optimal waiting areas Z1 and Z2:
when the optimal waiting area Z1 and the optimal waiting area Z2 are both in the direction of the head of the vehicle, the riding suggestion is 'please wait in the direction of the head of the vehicle';
when the optimal waiting area Z1 is in the direction of the head of the vehicle and the optimal waiting area Z2 is in the direction of the middle of the vehicle, the riding suggestion is 'please wait in the direction of the head of the vehicle';
when the optimal waiting area Z1 is in the direction of the head of the train and the optimal waiting area Z2 is in the direction of the tail of the train, the riding suggestion is 'please wait for the two ends of the train';
when the optimal waiting area Z1 is in the direction of the train, the riding suggestion is 'please wait in the middle of the train';
when the optimal waiting area Z1 is in the tail direction and the optimal waiting area Z2 is in the head direction, the riding suggestion is 'please wait for the two ends of the train';
when the optimal waiting area Z1 is in the direction of the tail of the vehicle and the optimal waiting area Z2 is in the direction of the middle of the vehicle, the riding suggestion is 'please wait in the direction of the tail of the vehicle';
when the optimal waiting area Z1 and the optimal waiting area Z2 are both in the direction of the tail of the vehicle, the riding suggestion is 'please wait in the direction of the tail of the vehicle'.
In a specific embodiment, two sets of riding guidance terminals are configured and respectively deployed at the entrances of charging areas at two ends of a subway station hall. The riding guidance terminal selects a joint P320 workstation (provided with a Philips 43 inch 4K high-definition liquid crystal display screen). The intelligent analysis unit is connected with a network switch through a network port to realize interface communication and data interaction with the intelligent analysis unit; the association P320 workstation host computer is connected with the high-definition liquid crystal display screen through an HDMI cable, and bus taking guidance information is released.
In an alternative embodiment, the taking guidance terminal is further configured to display the degree of congestion of each carriage of the train and the degree of congestion of each waiting area of the station at different levels in different colors.
And the bus taking guidance terminal receives the congestion degree data of each waiting area of the station forwarded by the intelligent analysis unit, judges the congestion degree grade and displays the color corresponding to the congestion degree grade of each waiting area of the station according to a preset comparison table of the congestion degree grade of the station and the display color.
And the riding guidance terminal receives the congestion degree data of each carriage of the arriving train forwarded by the intelligent analysis unit, judges the congestion degree grade and displays the color corresponding to each carriage congestion degree grade of the arriving train according to a preset train congestion degree grade and a display color comparison table.
And the riding guidance terminal receives the optimal waiting area and riding advice forwarded by the intelligent analysis unit, dynamically calculates an optimal riding route according to the position of the riding guidance terminal, and displays a riding route guide identifier and the riding advice.
The station congestion degree grades are divided into four grades of severe congestion, quite congestion, more congestion and normal, and corresponding threshold values and display color default values are shown in the following table:
| station congestion degree grade | Threshold value of station congestion degree | Displaying color |
| Severe congestion | Greater than 6 persons/square meter | Red colour |
| Is quite crowded | Less than or equal to 6 per square meter and more than 4 per square meter | Orange colour |
| Is more crowded | Less than or equal to 4 per square meter and more than 2 per square meter | Yellow colour |
| Is normal | Less than or equal to 2 persons per square meter | Green colour |
The bus taking guidance terminal can manually set and adjust the threshold value and the display color corresponding to the station crowdedness level according to the actual application condition.
The train congestion degree grades are divided into four grades of severe congestion, quite congestion, more congestion and normal, and corresponding threshold values and display color default values are shown in the following table:
| train crowding degree grade | Threshold of train congestion degree | Displaying color |
| Severe congestion | Greater than 7 persons/square meter | Red colour |
| Is quite crowded | Less than or equal to 7 per square meter and more than 5 per square meter | Orange colour |
| Is more crowded | Less than or equal to 5 per square meter and more than 3 per square meter | Yellow colour |
| Is normal | Less than or equal to 3 persons per square meter | Green colour |
The riding guidance terminal can manually set and adjust the threshold value and the display color corresponding to the train crowdedness level according to the actual application condition.
The embodiment of the invention also provides an intelligent bus taking guidance method for a subway station, which is realized by using the intelligent bus taking guidance device in the embodiment, as shown in fig. 3, and comprises the following steps:
And 102, acquiring the train group number of the whole-line running train and the weighing data of each compartment of the corresponding train in real time, and generating a comparison relation table of the train group number and the weighing data of each train.
And 103, acquiring the train group number of the train running on the whole line and the position information of the corresponding train in real time, and generating a comparison relation table of the train group number and the train position information.
And 104, analyzing and calculating the matching between the position information of the train running on the whole line and the preset station position information, determining the next train arriving at the station, and acquiring the train group number corresponding to the train arriving at the station.
And 105, acquiring weighing data of each compartment of the arriving train according to the train set number of the arriving train, and converting the weighing data of each compartment of the arriving train into the compartment crowdedness.
And step 106, converting the passenger flow density data of each waiting area of the station into the crowdedness of each waiting area of the station.
And step 107, generating a riding suggestion according to the congestion degree of each carriage of the arriving train and the congestion degree of each waiting area of the station.
In an alternative embodiment, step 107 comprises the steps of:
and step 1071, analyzing and calculating the optimal waiting area Z1 based on the single area statistics by taking the single area as a statistical object and the comprehensive congestion degree as a statistical index.
Step 1072, the optimal waiting area Z2 is analyzed and calculated based on the statistics of the two continuous areas by taking the two continuous areas as the statistical objects and the sum of the comprehensive congestion degrees of the two continuous areas as the statistical index.
And step 1073, generating a riding suggestion according to the optimal waiting area Z1 and the optimal waiting area Z2.
In an alternative embodiment, the ride recommendation includes at least one of:
when the optimal waiting area Z1 and the optimal waiting area Z2 are both in the direction of the head of the vehicle, the riding suggestion is 'please wait in the direction of the head of the vehicle'.
When the optimal waiting area Z1 is in the direction of the head of the vehicle and the optimal waiting area Z2 is in the direction of the middle of the vehicle, the riding suggestion is 'please wait in the direction of the head of the vehicle'.
When the optimal waiting area Z1 is in the direction of the head of the train and the optimal waiting area Z2 is in the direction of the tail of the train, the riding suggestion is 'please wait for the two ends of the train'.
When the optimal waiting area Z1 is in the direction of the train, the riding recommendation is "please wait in the middle of the train".
When the optimal waiting area Z1 is in the tail direction and the optimal waiting area Z2 is in the head direction, the riding suggestion is 'please wait for the two ends of the train'.
When the optimal waiting area Z1 is in the direction of the tail of the vehicle and the optimal waiting area Z2 is in the direction of the middle of the vehicle, the riding suggestion is 'please wait in the direction of the tail of the vehicle'.
When the optimal waiting area Z1 and the optimal waiting area Z2 are both in the direction of the tail of the vehicle, the riding suggestion is 'please wait in the direction of the tail of the vehicle'.
And step 108, displaying the crowdedness of each carriage of the arrival train, the crowdedness of each waiting area of the station and the riding advice in real time.
It should be noted that the steps 101-108 may not be executed sequentially. In a specific example, referring to the intelligent riding guidance method shown in fig. 4, station passenger flow data, vehicle weighing data and train position information are synchronously acquired.
In an optional implementation manner, the intelligent ride guidance method further includes the following steps:
and step 109, analyzing an reachable path between the position of the riding guidance terminal and the optimal waiting area, and selecting an optimal riding route.
And step 110, displaying a riding route guide identifier according to the optimal riding route.
In an alternative embodiment, the number of waiting areas at the station is equal to the number of train cars arriving at the station. In a specific example, the number of waiting areas of the station and the number of train cars arriving at the station are both 8.
According to the embodiment of the invention, the relevant state data is obtained through the interfaces with the vehicle system, the signal system and the station intelligent video analysis system, and the comprehensive analysis and application of the data are adopted to provide the omnibearing and visual passenger flow state for passengers to take a bus, so that the bus taking guidance function is realized, the difficulty of the station passenger transportation organization can be effectively relieved, the bus taking experience of the passengers is improved, the actual passenger capacity of a train can be effectively improved under the condition of limited transport capacity of the current subway line, and the peak passenger transportation pressure is relieved.
While specific embodiments of the invention have been described above, it will be appreciated by those skilled in the art that these are by way of example only, and that the scope of the invention is defined by the appended claims. Various changes and modifications to these embodiments may be made by those skilled in the art without departing from the spirit and scope of the invention, and these changes and modifications are within the scope of the invention.
Claims (10)
1. An intelligent bus taking guidance device for a subway station is characterized by comprising a data interface unit, an intelligent analysis unit, a network switch and a bus taking guidance terminal, wherein the network switch is electrically connected with the data interface unit, the intelligent analysis unit and the bus taking guidance terminal respectively;
the data interface unit is used for acquiring train position information, train weighing data and station passenger flow density distribution data in real time and sending the train position information, the train weighing data and the station passenger flow density distribution data to the intelligent analysis unit through the network switch;
the intelligent analysis unit is used for matching the arriving train, analyzing and calculating the crowdedness of each carriage of the arriving train and the crowdedness of each waiting area of the station, generating a riding suggestion, and sending the crowdedness of each carriage of the arriving train, the crowdedness of each waiting area of the station and the riding suggestion to the riding guidance terminal through the network switch;
the bus taking guidance terminal is used for displaying the degree of congestion of each carriage of the arriving train, the degree of congestion of each waiting area of the station and the bus taking advice in real time.
2. The intelligent ride induction device of claim 1, wherein the data interface unit comprises a video analysis interface module, a vehicle system interface module, and a signal system interface module;
the video analysis interface module is connected with the station intelligent video analysis system and is used for collecting station passenger flow density distribution data;
the vehicle system interface module is connected with a vehicle system and used for acquiring train group numbers of the train running on the whole line and weighing data of each carriage of the train;
and the signal system interface module is connected with the signal system and is used for acquiring train group numbers and train position information of the train running on the whole line.
3. The intelligent bus taking guidance device according to claim 1, wherein the intelligent analysis unit comprises an arrival train matching module, a congestion degree measuring and calculating module and an optimal waiting area calculating module;
the arrival train matching module is used for matching the arrival train and acquiring the train group number of the arrival train according to the position information of the whole-line running train and the preset station position information;
the congestion degree measuring and calculating module is used for measuring and calculating the congestion degree of each carriage of the arriving train according to the weighing data of each carriage of the arriving train and measuring and calculating the congestion degree of each waiting area of the station according to the passenger flow density data of each waiting area of the station;
the optimal waiting area calculating module is used for calculating the optimal waiting area according to the crowdedness of each carriage of the arriving train and the crowdedness of each waiting area of the station and generating a riding suggestion.
4. The intelligent ride guidance device of claim 1, wherein the ride guidance terminal comprises an optimal waiting route calculation module and a guidance information display module which are electrically connected with each other;
the optimal waiting route calculation module is used for calculating an optimal waiting route and generating a riding route guide identifier;
the guidance information display module is used for displaying the crowdedness, riding suggestions and passenger route guidance marks of each waiting area of the station and each carriage of the arriving train.
5. An intelligent bus taking guidance device as claimed in any one of claims 1 to 4, wherein the bus taking guidance terminal is further configured to display different levels of the degree of congestion of each carriage of the train and the degree of congestion of each waiting area of the station in different colors.
6. An intelligent bus taking induction method for a subway station, which is realized by using the intelligent bus taking induction device as claimed in any one of claims 1-5, and comprises the following steps:
S1acquiring passenger flow density data of each waiting area of a station in real time to generate a comparison relation table of the waiting areas of the station and the passenger flow density data;
S2acquiring the train group number of the whole-line running train and weighing data of each compartment of the corresponding train in real time, and generating a comparison relation table of the train group number and the weighing data of each train;
S3acquiring the train group number of the train running on the whole line and the position information of the corresponding train in real time, and generating a comparison relation table of the train group number and the train position information;
S4analyzing and calculating the matching between the position information of the train running on the whole line and the preset station position information, determining the next train arriving at the station and acquiring the train arriving at the stationThe corresponding train set number of the train;
S5acquiring weighing data of each carriage of the arriving train according to the train set number of the arriving train, and converting the weighing data of each carriage of the arriving train into carriage crowding degree;
S6converting passenger flow density data of each waiting area of the station into crowdedness of each waiting area of the station;
S7generating a riding suggestion according to the degree of congestion of each carriage of the arriving train and the degree of congestion of each waiting area of the station;
S8and displaying the crowdedness of each carriage of the arrival train, the crowdedness of each waiting area of the station and the riding advice in real time.
7. The intelligent ride guidance method of claim 6, wherein the step S7The method specifically comprises the following steps:
S71establishing a corresponding relation between each carriage of the train and each waiting area of the station, and sequentially calculating the arithmetic sum of the congestion degree of each carriage of the train and the congestion degree of each waiting area of the station to obtain the comprehensive congestion degree of each area;
S72and generating a riding suggestion according to the comprehensive congestion degree of each area.
8. The intelligent ride guidance method of claim 7, wherein the step S72The method specifically comprises the following steps:
S721analyzing and calculating an optimal waiting area Z1 based on single area statistics by taking the single area as a statistical object and the comprehensive congestion degree as a statistical index;
S722analyzing and calculating an optimal waiting area Z2 based on the statistics of the two continuous areas by taking the two continuous areas as statistical objects and the sum of the comprehensive congestion degrees of the two continuous areas as a statistical index;
S723and generating a riding suggestion according to the optimal waiting area Z1 and the optimal waiting area Z2.
9. The intelligent ride inducement method of claim 8, wherein the ride recommendations comprise at least one of:
when the optimal waiting area Z1 and the optimal waiting area Z2 are both in the direction of the head of the vehicle, the riding suggestion is 'please wait in the direction of the head of the vehicle';
when the optimal waiting area Z1 is in the direction of the head of the vehicle and the optimal waiting area Z2 is in the direction of the middle of the vehicle, the riding suggestion is 'please wait in the direction of the head of the vehicle';
when the optimal waiting area Z1 is in the direction of the head of the train and the optimal waiting area Z2 is in the direction of the tail of the train, the riding suggestion is 'please wait for the two ends of the train';
when the optimal waiting area Z1 is in the direction of the train, the riding suggestion is 'please wait in the middle of the train';
when the optimal waiting area Z1 is in the tail direction and the optimal waiting area Z2 is in the head direction, the riding suggestion is 'please wait for the two ends of the train';
when the optimal waiting area Z1 is in the direction of the tail of the vehicle and the optimal waiting area Z2 is in the direction of the middle of the vehicle, the riding suggestion is 'please wait in the direction of the tail of the vehicle';
when the optimal waiting area Z1 and the optimal waiting area Z2 are both in the direction of the tail of the vehicle, the riding suggestion is 'please wait in the direction of the tail of the vehicle'.
10. The intelligent ride inducement method of claim 9, further comprising the steps of:
S9and analyzing an reachable path between the position of the riding guidance terminal and the optimal waiting area, and selecting an optimal riding route.
S10And displaying a riding route guide identifier according to the optimal riding route.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113665636A (en) * | 2021-09-02 | 2021-11-19 | 中铁第一勘察设计院集团有限公司 | Subway intelligent passenger guidance system |
| CN113780654A (en) * | 2021-09-08 | 2021-12-10 | 佳都科技集团股份有限公司 | Method, device, equipment and storage medium for guiding passenger walking in subway station |
| CN113946939A (en) * | 2021-09-07 | 2022-01-18 | 卡斯柯信号有限公司 | Method, device, equipment and medium for generating rail transit passenger flow prototype |
| CN114822261A (en) * | 2022-05-10 | 2022-07-29 | 成都唐源智控技术有限责任公司 | Subway passenger waiting guiding method |
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2019
- 2019-10-23 CN CN201911012224.3A patent/CN112700360A/en active Pending
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113665636A (en) * | 2021-09-02 | 2021-11-19 | 中铁第一勘察设计院集团有限公司 | Subway intelligent passenger guidance system |
| CN113946939A (en) * | 2021-09-07 | 2022-01-18 | 卡斯柯信号有限公司 | Method, device, equipment and medium for generating rail transit passenger flow prototype |
| CN113780654A (en) * | 2021-09-08 | 2021-12-10 | 佳都科技集团股份有限公司 | Method, device, equipment and storage medium for guiding passenger walking in subway station |
| CN113780654B (en) * | 2021-09-08 | 2024-04-30 | 佳都科技集团股份有限公司 | Method, device, equipment and storage medium for guiding passengers to walk in subway station |
| CN114822261A (en) * | 2022-05-10 | 2022-07-29 | 成都唐源智控技术有限责任公司 | Subway passenger waiting guiding method |
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