CN117387632B - Intelligent riding guiding system and method for rail transit - Google Patents
Intelligent riding guiding system and method for rail transit Download PDFInfo
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- 238000010276 construction Methods 0.000 claims description 6
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
- G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
Abstract
The invention provides an intelligent riding guiding system and method for rail transit, belonging to the technical field of intelligent guiding, wherein the system comprises: the information acquisition module is used for acquiring the riding number of the riding user, the request time of the riding user for issuing the guiding request and the request position; the first guiding module is used for guiding the first riding to the riding user; the frequency control module is used for controlling the working frequency of the first visual guide assembly related to the first riding guide according to the actual walking information; the guide display module is used for calling the control code of each first visual guide assembly to obtain a guide deviation array of the actual walking information and controlling the second visual guide assembly related to the regression positive rail information to carry out visual guide display; and the second guiding module is used for acquiring the riding seat numbers of the riding users and carrying out second riding guiding by combining the visual guiding display results. The accurate and effective guiding of the user is realized, and the effective riding of the user is ensured.
Description
Technical Field
The invention relates to the technical field of intelligent guidance, in particular to an intelligent riding guidance system and method for rail transit.
Background
Rail traffic refers to a type of transportation means or transportation system in which an operation vehicle needs to travel on a specific rail, and common rail traffic includes conventional railways (common railways, inter-city railways and urban railways), subways, light rails, tramways, and novel rail traffic such as magnetic levitation rail systems and monorail systems, in which no matter what kind of traffic needs passengers to wait for the vehicle to arrive at a station before taking the vehicle, taking a high-speed rail as an example, because some icons are missing or are easily ignored by passengers, the passengers cannot accurately find a taking route, and the guiding fails.
Therefore, the invention provides an intelligent riding guiding system and method for rail transit.
Disclosure of Invention
The invention provides an intelligent riding guiding system and method for rail transit, which are used for carrying out riding guiding based on a guiding end of a user by acquiring riding information and riding requests of the user, further capturing and determining the actual walking information of the user, automatically determining a deviation array to carry out regression orbit guiding, and finally realizing accurate and effective guiding of the user by combining with riding seat numbers, thereby ensuring effective riding of the user.
The invention provides an intelligent riding guiding system for rail traffic, comprising:
the information acquisition module is used for acquiring the riding number of the riding user, the request time of the guiding request issued by the riding user and the request position;
the first guiding module is used for guiding the first riding to the riding user based on the time of the riding number of the riding user and the starting and stopping position of the riding number of the riding user and combining the current walking habit, the request moment and the request position of the riding user;
the frequency control module is used for capturing actual traveling information of the riding user according to the first riding guide and controlling the working frequency of a first visual guide component related to the first riding guide according to the actual traveling information;
the guide display module is used for calling the control code of each first visual guide component to obtain a guide deviation array of the actual walking information, and controlling a second visual guide component related to the regression normal rail information to carry out visual guide display according to the guide deviation array;
and the second guiding module is used for acquiring the riding seat numbers of the riding users and carrying out second riding guiding on the riding users by combining the visual guiding display results.
Preferably, the information acquisition module includes:
the first positioning unit is used for automatically performing first positioning on the riding user based on the guiding end of the riding user after capturing the guiding request issued by the riding user;
the second positioning unit is used for establishing network connection between the guiding end of the riding user and the riding station and automatically performing second positioning on the guiding end;
and the position determining unit is used for determining the request position based on the first positioning result and the second positioning result.
Preferably, the first guiding module includes:
the channel construction unit is used for acquiring all adjacent train numbers and the number of passengers of each adjacent train number in an adjacent time period of the train number time of the train user from the rail transit ticket purchasing system;
the track acquisition unit is used for acquiring daily people stream movement tracks of each adjacent train number, wherein the daily people stream movement tracks comprise different track time points and movement density of each track time point;
the track optimizing unit is used for optimizing the daily people flow moving track according to the number of passengers and predicting to obtain an initial train number channel corresponding to the adjacent train number;
The architecture construction unit is used for constructing a channel influence architecture aiming at the riding user based on all initial train number channels;
the habit determining unit is used for retrieving the historical riding behavior information of the riding user from the user record database, extracting the habit behavior of the historical riding behavior information, and combining the current physical state of the riding user to obtain the current walking habit;
the initial guiding unit is used for carrying out riding planning based on the request time, the request position and the start-stop position to obtain initial riding guiding;
and the first guiding unit is used for adjusting the initial riding guiding based on the riding influence framework and the current walking habit to obtain the first riding guiding.
Preferably, the first guiding unit includes:
the framework analysis subunit is used for carrying out framework analysis on the riding influence framework to obtain a first influence sequence;
habit analysis subunit, configured to perform habit analysis on the current walking habit to obtain a second influence sequence;
a deviation distance determination subunit configured to determine, for the first influence sequence and the second influence sequence, a lateral deviation distance and a longitudinal deviation distance based on each guidance point in the initial riding guidance;
；
Wherein H1 is the lateral deviation distance of the corresponding guide point; rh1 represents the lateral influence distance in the first influence sequence that matches the corresponding guide point; rh2 represents the lateral influence distance in the second influence sequence that matches the corresponding guide point; 0.1 represents a preset precision distance; max represents the maximum value symbol; min represents a minimum symbol;
；
wherein Z1 is the longitudinal offset distance of the corresponding guide point;representing a longitudinal influence distance in the second influence sequence that matches the corresponding guide point; rz2 represents the longitudinal influence distance in the second influence sequence that matches the corresponding guide point;
the point determining subunit is used for constructing a deviation intersection point based on the corresponding guide point based on the transverse deviation distance and the longitudinal deviation distance of each guide point, and drawing a circle based on the first distance between the deviation intersection point and the corresponding guide point as a radius to obtain a first intersection point of the corresponding transverse deviation distance for forward extension and the circle and a second intersection point of the corresponding longitudinal deviation distance for normal extension and the circle;
connecting the first intersection point and the second intersection point, and determining a third intersection point of a rectangular connecting transverse line based on the deviated intersection point and a fourth intersection point of a rectangular connecting longitudinal line;
The range determining subunit is used for determining a center point of the triangle drawn by the third intersection point, the fourth intersection point and the deviation intersection point, and drawing a connecting line segment between the center point and the corresponding deviation intersection point as a diameter to obtain a deviation range;
a line acquisition subunit, configured to acquire a closest point based on a deviation range corresponding to each guide point, two range intersection points perpendicular to a connecting line segment of the corresponding deviation range, and a farthest point;
first connecting the nearest point of each guide point to obtain a first circuit;
performing second connection on the left range intersection point of each guide point to obtain a second line;
thirdly connecting the right range intersection points of each guide point to obtain a third line;
fourth connecting the farthest point of each guide point to obtain a fourth line;
and performing line fitting on the first line, the second line, the third line and the fourth line and combining the guiding lines of the initial riding guidance to obtain a fifth line, and performing the first riding guidance according to the fifth line.
Preferably, the frequency control module includes:
the real-time positioning unit is used for positioning the position coordinates of the riding user for walking according to the first riding guide in real time to obtain actual walking information;
The frequency control unit is used for selecting an initial point and an end point in the actual walking information, screening the position difference between the actual position and the standard position of each first visual guide assembly in the standard walking section from the initial point to the end point from a guide line of the first riding guide preset by a guide end corresponding to the first riding guide, and controlling the working frequency of the corresponding first visual guide assembly.
Preferably, the guide display module includes:
the code matching unit is used for matching corresponding control codes from the result-code mapping table according to the working frequency control result of each first visual guide component;
the comparison unit is used for comparing and analyzing the control code and the standard code to obtain a guide deviation array;
the component mapping unit is used for carrying out component mapping on the guide deviation array according to the regression positive rail information and locking a second visual guide component;
and the guide display unit is used for performing visual guide display according to the second visual guide assembly.
Preferably, the second guiding module includes:
the time prediction unit is used for predicting the first time when the riding user arrives at the start-stop position according to the visual guidance displayed by the guidance display module;
When the first time is higher than the stopping time of the parking lot reaching the starting stopping position, guiding according to the original guiding scheme is continued;
the number determining unit is used for acquiring a riding seat number of the riding user, a first approaching platform number of the riding user based on an original guiding scheme and vehicle interval arrangement information of the parking number when the first time does not precede the parking time when the parking number reaches the initial parking position;
and the second guiding unit is used for carrying out second riding guiding on the riding user based on the priority boarding station number and combining a visual guiding display result.
The invention provides an intelligent riding guiding method for rail transit, which comprises the following steps:
step 1: collecting the riding number of a riding user, the request time of the riding user for issuing a guiding request and the request position;
step 2: based on the time of the number of times of the riding and the starting and stopping position of the number of times of the riding, and combining the current walking habit, the request moment and the request position of the riding user, performing first riding guidance on the riding user;
step 3: capturing actual traveling information of the riding user according to the first riding guide, and controlling the working frequency of a first visual guide assembly related to the first riding guide according to the actual traveling information;
Step 4: the control codes of each first visual guide component are called to obtain a guide deviation array of the actual walking information, and a second visual guide component related to the regression positive rail information is controlled to carry out visual guide display according to the guide deviation array;
and 5, acquiring the riding seat numbers of the riding users, and carrying out second riding guidance on the riding users by combining the visual guiding display results.
Compared with the prior art, the beneficial effects of the application are as follows:
the user riding information and riding request are obtained to conduct riding guidance based on the user's guiding end, the working frequency of the guiding component is further determined by capturing the user's actual walking information, the deviation array is automatically determined to conduct regression orbit correction guidance, and finally, accurate and effective guidance of the user is achieved through combination with riding seat numbers, and effective riding of the user is guaranteed.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a block diagram of an intelligent ride guidance system for rail transit in accordance with an embodiment of the present invention;
FIG. 2 is a flow chart of an intelligent ride guiding method for rail transit according to an embodiment of the present invention;
fig. 3 is a diagram illustrating a process acquisition structure for a first ride-on guide in an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The present invention provides an intelligent ride guide system for rail transit, as shown in fig. 1, comprising:
the information acquisition module is used for acquiring the riding number of the riding user, the request time of the guiding request issued by the riding user and the request position;
the first guiding module is used for guiding the first riding to the riding user based on the time of the riding number of the riding user and the starting and stopping position of the riding number of the riding user and combining the current walking habit, the request moment and the request position of the riding user;
The frequency control module is used for capturing actual traveling information of the riding user according to the first riding guide and controlling the working frequency of a first visual guide component related to the first riding guide according to the actual traveling information;
the guide display module is used for calling the control code of each first visual guide component to obtain a guide deviation array of the actual walking information, and controlling a second visual guide component related to the regression normal rail information to carry out visual guide display according to the guide deviation array;
and the second guiding module is used for acquiring the riding seat numbers of the riding users and carrying out second riding guiding on the riding users by combining the visual guiding display results.
In this embodiment, the number of riding vehicles, for example, the number G016 vehicle number 9 over 12, and the guidance request refers to the current position and the requested position of the corresponding user when the user is in the bus at the station, if the user needs to ride the bus and guidance the route through the guidance terminal (the user mobile phone), the request time at this time is the request time.
In this embodiment, the time of the train number is a specific riding time of the train number G016, for example, 13:00pm.
In this embodiment, the start-stop position refers to a stop platform of the vehicle, which is pre-planned, for example, the high-speed rail stops at the platform 1, and the platform 1 includes a plurality of platform numbers corresponding to the compartments, for example, the platform number of 18 compartments is 18.
In this embodiment, the current walking habit refers to the walking speed of the user, and whether there is a physical defect affecting walking, such as poor mental state, a sprain of the foot, etc., which affects the progress of walking.
In this embodiment, the first riding guidance is a route planning for requesting a position to a starting parking space, and further guidance is performed, and during guidance, similar to the german navigation, for example, route deviation or too fast or too slow speed can be performed in a significant manner, that is, guidance reminding can exist due to route deviation during subsequent actual walking, and guidance reminding is implemented based on a corresponding visual guidance component, for example, deviation exists during a process from a position 1 to a position 2, at this time, a matching component for planning a route from a position 1 to a position 2 is in a significant guidance state, that is, corresponding working frequencies of the matching component are different compared with a state of no reminding, and guidance reminding under different working frequencies is different.
In this embodiment, the control code is determined based on the operating frequency, and the frequency corresponds to the code one by one, mainly for good indication and analysis of the deviation.
In this embodiment, the lead offset array= { component 1 offset alert 01 component 2 offset alert 02.
In this embodiment, returning to the positive track information refers to guiding the user to return to the normal walking route, thereby ensuring that the user is effectively riding.
In this embodiment, the ride seat number refers to a particular seat of the user on the vehicle, such as an 8-car 17C seat.
In this embodiment, the second ride is to ensure that the user can effectively reach the seat, and the first ride is to ensure that the user reaches the docking station as much as possible.
The beneficial effects of the technical scheme are as follows: the user riding information and riding request are obtained to conduct riding guidance based on the user's guiding end, the working frequency of the guiding component is further determined by capturing the user's actual walking information, the deviation array is automatically determined to conduct regression orbit correction guidance, and finally, accurate and effective guidance of the user is achieved through combination with riding seat numbers, and effective riding of the user is guaranteed.
The invention provides an intelligent riding guiding system for rail transit, which comprises an information acquisition module, a control module and a control module, wherein the information acquisition module comprises:
the first positioning unit is used for automatically performing first positioning on the riding user based on the guiding end of the riding user after capturing the guiding request issued by the riding user;
the second positioning unit is used for establishing network connection between the guiding end of the riding user and the riding station and automatically performing second positioning on the guiding end;
and the position determining unit is used for determining the request position based on the first positioning result and the second positioning result.
In this embodiment, the first location is a location performed by a location system carried by the user's handset.
In this embodiment, the second location is a network location, such as wifi location, after the mobile phone makes a network connection with the network system of the boarding station.
The beneficial effects of the technical scheme are as follows: through the self positioning of the guide end and the network positioning after the network connection, the request position can be effectively determined, and an effective basis is provided for the subsequent riding guidance.
The invention provides an intelligent riding guiding system for rail traffic, which comprises a first guiding module, a second guiding module and a third guiding module, wherein the first guiding module comprises:
the channel construction unit is used for acquiring all adjacent train numbers and the number of passengers of each adjacent train number in an adjacent time period of the train number time of the train user from the rail transit ticket purchasing system;
The track acquisition unit is used for acquiring daily people stream movement tracks of each adjacent train number, wherein the daily people stream movement tracks comprise different track time points and movement density of each track time point;
the track optimizing unit is used for optimizing the daily people flow moving track according to the number of passengers and predicting to obtain an initial train number channel corresponding to the adjacent train number;
the architecture construction unit is used for constructing a channel influence architecture aiming at the riding user based on all initial train number channels;
the habit determining unit is used for retrieving the historical riding behavior information of the riding user from the user record database, extracting the habit behavior of the historical riding behavior information, and combining the current physical state of the riding user to obtain the current walking habit;
the initial guiding unit is used for carrying out riding planning based on the request time, the request position and the start-stop position to obtain initial riding guiding;
and the first guiding unit is used for adjusting the initial riding guiding based on the riding influence framework and the current walking habit to obtain the first riding guiding.
In this embodiment, for example, when a high-speed rail station is in a train, different train numbers will exist at adjacent times, and the traffic will be very large at this time, and there will be no doubt a certain obstacle in the effective train taking of the user, so the required data needs to be extracted from the system, for example, the number of adjacent trains, the number of passengers, etc., and the adjacent time period may be within 8 minutes.
In this embodiment, the daily traffic movement track refers to a track of a process from a passenger of each train to a passenger, and the daily traffic movement track of the corresponding train is obtained by counting the track of each passenger.
In this embodiment, the number of passengers is newly acquired, and the corresponding track is further optimized, so that a real track can be obtained conveniently, that is, the current time movement situation is more fitted, and a more traversing basis is provided for the passengers.
In the embodiment, the optimization is based on the number of people, density adjustment is performed on each track point in the corresponding daily people flow moving track, a reliable track is obtained through prediction, and the optimization for each track point is as follows:
；
wherein Y1 is the optimized density; y0 is the original density; m0 is the current flow of people; m1 is the original people flow;and the value range is (0, 1) for the personnel overlapping coefficient of the corresponding track point and the adjacent point.
In this embodiment, the initial train number channel is the track after the original track is optimized.
In this embodiment, the channel influence architecture is obtained by inputting all the optimized track information related to the channel influence architecture into the influence analysis model, and the model is obtained by training the neural network model based on the track information of different combinations and analysis results of influence walking of experts on the track information of the combinations as samples.
In this embodiment, the historical riding behavior information is mainly used to determine the walking habit of the user, for example, the speed is full, the speed is fast, etc., so as to further obtain the influence of the current walking defect of the corresponding user, for example, the foot sprain, etc., on the walking, and further determine the current walking habit.
In this embodiment, the initial ride guidance is adjusted to adjust the initially planned route, for example, from a left aisle to a right aisle, etc., to achieve the first ride guidance.
The beneficial effects of the technical scheme are as follows: by acquiring all train numbers and personnel numbers in adjacent time periods and combining daily people flow tracks, the influence framework is determined, and in combination with behavior habits, the system effectively conducts riding guidance, and provides convenience for effective riding of users.
The invention provides an intelligent riding guiding system for rail traffic, wherein the first guiding unit comprises:
the framework analysis subunit is used for carrying out framework analysis on the channel influence framework to obtain a first influence sequence;
habit analysis subunit, configured to perform habit analysis on the current walking habit to obtain a second influence sequence;
a deviation distance determination subunit configured to determine, for the first influence sequence and the second influence sequence, a lateral deviation distance and a longitudinal deviation distance based on each guidance point in the initial riding guidance;
；
Wherein H1 is the lateral deviation distance of the corresponding guide point; rh1 represents the lateral influence distance in the first influence sequence that matches the corresponding guide point; rh2 represents the lateral influence distance in the second influence sequence that matches the corresponding guide point; 0.1 represents a preset precision distance; max represents the maximum value symbol; min represents a minimum symbol;
；
wherein Z1 is the longitudinal offset distance of the corresponding guide point;representing a longitudinal influence distance in the second influence sequence that matches the corresponding guide point; rz2 represents the longitudinal influence distance in the second influence sequence that matches the corresponding guide point;
the point determining subunit is used for constructing a deviation intersection point based on the corresponding guide point based on the transverse deviation distance and the longitudinal deviation distance of each guide point, and drawing a circle based on the first distance between the deviation intersection point and the corresponding guide point as a radius to obtain a first intersection point of the corresponding transverse deviation distance for forward extension and the circle and a second intersection point of the corresponding longitudinal deviation distance for normal extension and the circle;
connecting the first intersection point and the second intersection point, and determining a third intersection point of a rectangular connecting transverse line based on the deviated intersection point and a fourth intersection point of a rectangular connecting longitudinal line;
The range determining subunit is used for determining a center point of the triangle drawn by the third intersection point, the fourth intersection point and the deviation intersection point, and drawing a connecting line segment between the center point and the corresponding deviation intersection point as a diameter to obtain a deviation range;
a line acquisition subunit, configured to acquire a closest point based on a deviation range corresponding to each guide point, two range intersection points perpendicular to a connecting line segment of the corresponding deviation range, and a farthest point;
first connecting the nearest point of each guide point to obtain a first circuit;
performing second connection on the left range intersection point of each guide point to obtain a second line;
thirdly connecting the right range intersection points of each guide point to obtain a third line;
fourth connecting the farthest point of each guide point to obtain a fourth line;
and performing line fitting on the first line, the second line, the third line and the fourth line and combining the guiding lines of the initial riding guidance to obtain a fifth line, and performing the first riding guidance according to the fifth line.
In this embodiment, the architecture analysis model is used to analyze a channel influence architecture, where the model is obtained by training a neural network model based on different architecture deployments and influence evaluation results of experts on guide channels of different channels in the architecture, so as to obtain a first influence sequence directly, where the first influence sequence= [ the lateral influence distance of the architecture on the guide point 1 and the longitudinal influence distance of the architecture on the guide point 1.
The habit analysis model is used for analyzing the current walking habit, the model is obtained by training a neural network model based on different walking behaviors and evaluation results of the walking behaviors of experts, the second influence sequence is conveniently and directly obtained, and the second influence sequence= [ the lateral influence distance of the behavior habit on the guide point 1 and the longitudinal influence distance of the behavior habit on the guide point 1.
In this embodiment, taking fig. 3 as an example, where D0 is a guide point, L01 is a lateral offset distance, L02 is a longitudinal offset distance, D1 is an offset intersection point, D0 to D1 are first distances, L03 is a result of forward extension based on the lateral offset distance, L04 is a result of forward extension based on the longitudinal offset distance, D2 is a first intersection point, D3 is a second intersection point, L05 is a rectangular connecting transverse line, L06 is a rectangular connecting longitudinal line, D4 is a third intersection point, D5 is a fourth intersection point, and L07 is a connecting line segment based on the three-corner points formed by points D4, D5, and D1.
In this embodiment, the one-range intersection points refer to two-side intersection points of the diameter perpendicular to the connecting line segment and the corresponding range in the deviation range formed by the connecting line segment, the left-side point is the left-side range intersection point, and the right-side point is the right-side range intersection point.
In this embodiment, the corresponding line is obtained by performing a straight line connection based on each point in the connection process.
In this embodiment, the line fitting is performed on the first, second, third, fourth and guiding lines to determine an effective fitting point (non-discrete point) of each position point with consistent transverse coordinates, and then the fitting points are connected to obtain a fifth line.
The beneficial effects of the technical scheme are as follows: the existing distance influence is respectively determined from two aspects of architecture and behavior habit, the transverse influence distance and the longitudinal influence distance are further calculated, the range is conveniently determined, the reliability of range determination is guaranteed through the extension of the distance and the analysis of the intersection point in the range determination process, finally, a line is constructed through the determination of the point, and the rationality of first riding guidance is realized through line fitting, so that the reasonable riding of a user is guaranteed.
The invention provides an intelligent riding guiding system for rail traffic, which comprises a frequency control module, a control module and a control module, wherein the frequency control module comprises:
the real-time positioning unit is used for positioning the position coordinates of the riding user for walking according to the first riding guide in real time to obtain actual walking information;
The frequency control unit is used for selecting an initial point and an end point in the actual walking information, screening the position difference between the actual position and the standard position of each first visual guide assembly in the standard walking section from the initial point to the end point from a guide line of the first riding guide preset by a guide end corresponding to the first riding guide, and controlling the working frequency of the corresponding first visual guide assembly.
In this embodiment, the actual walking information refers to the actual walking position point of the user.
In the embodiment, the initial point and the position point are in the actual walking information, so that the position difference analysis with the standard walking section is convenient.
The beneficial effects of the technical scheme are as follows: the actual walking information is acquired to be compared with the information of the standard walking section to determine the position difference, so that the working frequency of the assembly is controlled, and a data base is provided for the follow-up deviation analysis.
The invention provides an intelligent riding guiding system for rail traffic, which comprises a guiding display module, a guiding display module and a guiding display module, wherein the guiding display module comprises:
the code matching unit is used for matching corresponding control codes from the result-code mapping table according to the working frequency control result of each first visual guide component;
The comparison unit is used for comparing and analyzing the control code and the standard code to obtain a guide deviation array;
the component mapping unit is used for carrying out component mapping on the guide deviation array according to the regression positive rail information and locking a second visual guide component;
and the guide display unit is used for performing visual guide display according to the second visual guide assembly.
In this embodiment, the result-code mapping table includes different frequency control results and codes matched with the results, and is mainly provided for convenience in comparison analysis.
In this embodiment, the purpose of component mapping is to effectively remind the user to walk according to the normal track, so as to realize effective guidance.
The beneficial effects of the technical scheme are as follows: the control codes are matched with the frequency control result, and the guide deviation array is obtained by comparing and analyzing the standard codes, so that the subsequent component mapping is realized, and reasonable visual guide is realized.
The invention provides an intelligent riding guiding system for rail traffic, which comprises a second guiding module, a first guiding module and a second guiding module, wherein the second guiding module comprises:
the time prediction unit is used for predicting the first time when the riding user arrives at the start-stop position according to the visual guidance displayed by the guidance display module;
When the first time is higher than the stopping time of the parking lot reaching the starting stopping position, guiding according to the original guiding scheme is continued;
the number determining unit is used for acquiring a riding seat number of the riding user, a first approaching platform number of the riding user based on an original guiding scheme and vehicle interval arrangement information of the parking number when the first time does not precede the parking time when the parking number reaches the initial parking position;
and the second guiding unit is used for carrying out second riding guiding on the riding user based on the priority boarding station number and combining a visual guiding display result.
In this embodiment, the original guidance scheme refers to a scheme corresponding to the first riding guidance.
In this embodiment, the arrival time, i.e. the first time, is predicted during the route planning.
In this embodiment, the vehicle interval arrangement information refers to a case where there is a different penetration between adjacent cars of the train, and then the user is necessary to get on the train to other cars that can penetrate to his own car.
In this embodiment, for example, the number of the carriage of the user is 10, but 1-8 cars can be penetrated, 9-15 cars can be penetrated, and 8 and 9 cars cannot be penetrated, at this time, the user needs to obtain any carriage of 9-15 for calculation, and then needs to determine the priority to get to the station platform number, because each carriage has its corresponding unique parking number.
The beneficial effects of the technical scheme are as follows: comparing the first time with the stop time, determining the number of the station platform to be preferentially loaded, and further ensuring the effective riding of the user.
The invention provides an intelligent riding guiding method for rail transit, which is shown in fig. 2 and comprises the following steps:
step 1: collecting the riding number of a riding user, the request time of the riding user for issuing a guiding request and the request position;
step 2: based on the time of the number of times of the riding and the starting and stopping position of the number of times of the riding, and combining the current walking habit, the request moment and the request position of the riding user, performing first riding guidance on the riding user;
step 3: capturing actual traveling information of the riding user according to the first riding guide, and controlling the working frequency of a first visual guide assembly related to the first riding guide according to the actual traveling information;
step 4: the control codes of each first visual guide component are called to obtain a guide deviation array of the actual walking information, and a second visual guide component related to the regression positive rail information is controlled to carry out visual guide display according to the guide deviation array;
And 5, acquiring the riding seat numbers of the riding users, and carrying out second riding guidance on the riding users by combining the visual guiding display results.
The beneficial effects of the technical scheme are as follows: the user riding information and riding request are obtained to conduct riding guidance based on the user's guiding end, the working frequency of the guiding component is further determined by capturing the user's actual walking information, the deviation array is automatically determined to conduct regression orbit correction guidance, and finally, accurate and effective guidance of the user is achieved through combination with riding seat numbers, and effective riding of the user is guaranteed.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (6)
1. An intelligent ride guidance system for rail transit, comprising:
the information acquisition module is used for acquiring the riding number of the riding user, the request time of the guiding request issued by the riding user and the request position;
The first guiding module is used for guiding the first riding to the riding user based on the time of the riding number of the riding user and the starting and stopping position of the riding number of the riding user and combining the current walking habit, the request moment and the request position of the riding user;
the frequency control module is used for capturing actual traveling information of the riding user according to the first riding guide and controlling the working frequency of a first visual guide component related to the first riding guide according to the actual traveling information;
the guide display module is used for calling the control code of each first visual guide component to obtain a guide deviation array of the actual walking information, and controlling a second visual guide component related to the regression normal rail information to carry out visual guide display according to the guide deviation array;
the second guiding module is used for acquiring the riding seat numbers of the riding users and carrying out second riding guiding on the riding users by combining the visual guiding display results;
wherein, the first guide module includes:
the channel construction unit is used for acquiring all adjacent train numbers and the number of passengers of each adjacent train number in an adjacent time period of the train number time of the train user from the rail transit ticket purchasing system;
The track acquisition unit is used for acquiring daily people stream movement tracks of each adjacent train number, wherein the daily people stream movement tracks comprise different track time points and movement density of each track time point;
the track optimizing unit is used for optimizing the daily people flow moving track according to the number of passengers and predicting to obtain an initial train number channel corresponding to the adjacent train number;
the architecture construction unit is used for constructing a channel influence architecture aiming at the riding user based on all initial train number channels;
the habit determining unit is used for retrieving the historical riding behavior information of the riding user from the user record database, extracting the habit behavior of the historical riding behavior information, and combining the current physical state of the riding user to obtain the current walking habit;
the initial guiding unit is used for carrying out riding planning based on the request time, the request position and the start-stop position to obtain initial riding guiding;
the first guiding unit is used for adjusting the initial riding guiding based on the riding influence framework and the current walking habit to obtain a first riding guiding;
wherein the first guiding unit includes:
The framework analysis subunit is used for carrying out framework analysis on the riding influence framework to obtain a first influence sequence;
habit analysis subunit, configured to perform habit analysis on the current walking habit to obtain a second influence sequence;
a deviation distance determination subunit configured to determine, for the first influence sequence and the second influence sequence, a lateral deviation distance and a longitudinal deviation distance based on each guidance point in the initial riding guidance;
；
wherein H1 is the lateral deviation distance of the corresponding guide point; rh1 represents the lateral influence distance in the first influence sequence that matches the corresponding guide point; rh2 represents the lateral influence distance in the second influence sequence that matches the corresponding guide point; 0.1 represents a preset precision distance; max represents the maximum value symbol; min represents a minimum symbol;
；
wherein Z1 is the longitudinal offset distance of the corresponding guide point;representing a longitudinal influence distance in the second influence sequence that matches the corresponding guide point; rz2 represents the longitudinal influence distance in the second influence sequence that matches the corresponding guide point;
the point determining subunit is used for constructing a deviation intersection point based on the corresponding guide point based on the transverse deviation distance and the longitudinal deviation distance of each guide point, and drawing a circle based on the first distance between the deviation intersection point and the corresponding guide point as a radius to obtain a first intersection point of the corresponding transverse deviation distance for forward extension and the circle and a second intersection point of the corresponding longitudinal deviation distance for normal extension and the circle;
Connecting the first intersection point and the second intersection point, and determining a third intersection point of a rectangular connecting transverse line based on the deviated intersection point and a fourth intersection point of a rectangular connecting longitudinal line;
the range determining subunit is used for determining a center point of the triangle drawn by the third intersection point, the fourth intersection point and the deviation intersection point, and drawing a connecting line segment between the center point and the corresponding deviation intersection point as a diameter to obtain a deviation range;
a line acquisition subunit, configured to acquire a closest point based on a deviation range corresponding to each guide point, two range intersection points perpendicular to a connecting line segment of the corresponding deviation range, and a farthest point;
first connecting the nearest point of each guide point to obtain a first circuit;
performing second connection on the left range intersection point of each guide point to obtain a second line;
thirdly connecting the right range intersection points of each guide point to obtain a third line;
fourth connecting the farthest point of each guide point to obtain a fourth line;
and performing line fitting on the first line, the second line, the third line and the fourth line and combining the guiding lines of the initial riding guidance to obtain a fifth line, and performing the first riding guidance according to the fifth line.
2. The intelligent ride guidance system for rail transit of claim 1, wherein the information acquisition module comprises:
the first positioning unit is used for automatically performing first positioning on the riding user based on the guiding end of the riding user after capturing the guiding request issued by the riding user;
the second positioning unit is used for establishing network connection between the guiding end of the riding user and the riding station and automatically performing second positioning on the guiding end;
and the position determining unit is used for determining the request position based on the first positioning result and the second positioning result.
3. The intelligent ride guidance system for rail transit of claim 1, wherein the frequency control module comprises:
the real-time positioning unit is used for positioning the position coordinates of the riding user for walking according to the first riding guide in real time to obtain actual walking information;
the frequency control unit is used for selecting an initial point and an end point in the actual walking information, screening the position difference between the actual position and the standard position of each first visual guide assembly in the standard walking section from the initial point to the end point from a guide line of the first riding guide preset by a guide end corresponding to the first riding guide, and controlling the working frequency of the corresponding first visual guide assembly.
4. The intelligent ride guidance system for rail transit of claim 1, wherein the guidance presentation module comprises:
the code matching unit is used for matching corresponding control codes from the result-code mapping table according to the working frequency control result of each first visual guide component;
the comparison unit is used for comparing and analyzing the control code and the standard code to obtain a guide deviation array;
the component mapping unit is used for carrying out component mapping on the guide deviation array according to the regression positive rail information and locking a second visual guide component;
and the guide display unit is used for performing visual guide display according to the second visual guide assembly.
5. The intelligent ride guidance system for rail transit of claim 1, wherein the second guidance module comprises:
the time prediction unit is used for predicting the first time when the riding user arrives at the start-stop position according to the visual guidance displayed by the guidance display module;
when the first time is higher than the stop time of the train number reaching the start stop position, guiding according to the original guiding scheme is continued;
A number determining unit configured to obtain a boarding seat number of the boarding user, a first approach platform number of the boarding user based on an original guidance scheme, and vehicle interval arrangement information of the boarding number when the first time is not prior to a stop time when the boarding number reaches a start stop position;
and the second guiding unit is used for carrying out second riding guiding on the riding user based on the priority boarding station number and combining a visual guiding display result.
6. An intelligent ride guiding method for rail transit, comprising:
step 1: collecting the riding number of a riding user, the request time of the riding user for issuing a guiding request and the request position;
step 2: based on the time of the number of times of the riding and the starting and stopping position of the number of times of the riding, and combining the current walking habit, the request moment and the request position of the riding user, performing first riding guidance on the riding user;
step 3: capturing actual traveling information of the riding user according to the first riding guide, and controlling the working frequency of a first visual guide assembly related to the first riding guide according to the actual traveling information;
Step 4: the control codes of each first visual guide component are called to obtain a guide deviation array of the actual walking information, and a second visual guide component related to the regression positive rail information is controlled to carry out visual guide display according to the guide deviation array;
step 5, obtaining the riding seat numbers of the riding users, and carrying out second riding guidance on the riding users by combining the visual guiding display results;
wherein, step 2 includes:
acquiring all adjacent train numbers and the number of passengers of each adjacent train number in a time period adjacent to the train number time of the train user from a rail transit ticket purchasing system;
acquiring a daily people stream moving track of each adjacent train number, wherein the daily people stream moving track comprises different track time points and moving density of each track time point;
optimizing the daily people flow moving track according to the number of passengers, and predicting to obtain an initial train number channel corresponding to the adjacent train number;
constructing a channel influence framework aiming at the riding user based on all initial train number channels;
the historical riding behavior information of the riding user is called from a user record database, habit behavior extraction is carried out on the historical riding behavior information, and the current walking habit is obtained by combining the current body state of the riding user;
Carrying out riding planning based on the request time, the request position and the start-stop position to obtain initial riding guidance;
adjusting the initial ride guide based on the ride-influencing architecture and current walking habits to obtain a first ride guide, comprising:
performing architecture analysis on the riding influence architecture to obtain a first influence sequence;
habit analysis is carried out on the current walking habit to obtain a second influence sequence;
determining a lateral offset distance and a longitudinal offset distance based on each guide point in the initial ride guide for the first and second influence sequences;
；
wherein H1 is the lateral deviation distance of the corresponding guide point; rh1 represents the lateral influence distance in the first influence sequence that matches the corresponding guide point; rh2 represents the lateral influence distance in the second influence sequence that matches the corresponding guide point; 0.1 represents a preset precision distance; max represents the maximum value symbol; min represents a minimum symbol;
；
wherein Z1 is the longitudinal offset distance of the corresponding guide point;representing a longitudinal influence distance in the second influence sequence that matches the corresponding guide point; rz2 represents the longitudinal influence distance in the second influence sequence that matches the corresponding guide point;
Constructing a deviation intersection point based on the corresponding guide point based on the transverse deviation distance and the longitudinal deviation distance of each guide point, and drawing a circle based on the first distance between the deviation intersection point and the corresponding guide point as a radius to obtain a first intersection point of the corresponding transverse deviation distance for forward extension and the circle and a second intersection point of the corresponding longitudinal deviation distance for normal extension and the circle;
connecting the first intersection point and the second intersection point, and determining a third intersection point of a rectangular connecting transverse line based on the deviated intersection point and a fourth intersection point of a rectangular connecting longitudinal line;
determining a center point of the triangle drawn by the third intersection point, the fourth intersection point and the deviation intersection point, and drawing a connecting line segment between the center point and the corresponding deviation intersection point as a diameter to obtain a deviation range;
acquiring a closest point based on a deviation range corresponding to each guide point, two range intersection points perpendicular to a connecting line segment of the corresponding deviation range and a farthest point;
first connecting the nearest point of each guide point to obtain a first circuit;
performing second connection on the left range intersection point of each guide point to obtain a second line;
Thirdly connecting the right range intersection points of each guide point to obtain a third line;
fourth connecting the farthest point of each guide point to obtain a fourth line;
and performing line fitting on the first line, the second line, the third line and the fourth line and combining the guiding lines of the initial riding guidance to obtain a fifth line, and performing the first riding guidance according to the fifth line.
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