A barrier-free platform service system and method for public transportation

Abstract

The present invention discloses a barrier-free platform service system for public transportation and a method thereof, comprising a waiting system for mutual sensing between people and vehicles, destination route planning and notification of real-time route information of vehicles; a boarding system for sensing the entry of vehicles into the station and conducting voice broadcast to guide passengers to board the vehicle; and a disembarking system for providing voice and vibration reminders of arrival at the station and guiding passengers to disembark. The present invention can increase the convenience of passengers when traveling, and even provides great convenience for the travel of some visually impaired and other disabled people. Monitoring unit 1 can scan and take photos of the passengers' faces and send the photos to the nearest bus driver, so as to promptly help the passengers in need. Monitoring unit 2 can monitor the blind path near the platform to avoid dangerous accidents such as visually impaired people falling down due to obstacles on the blind path, thereby further increasing the safety of visually impaired people's travel.

Description

Technical Field

[0001] The present invention relates to the technical field of public transportation, and in particular to a barrier-free platform service system and method for public transportation. Background Art

[0002] In recent years, with the continuous acceleration of urbanization, the construction of urban public transportation facilities has become increasingly important. The rapidly developing urban public transportation is the first choice and indispensable means of transportation for citizens. It is playing an increasingly irreplaceable role. Urban public transportation is directly related to the city’s economic development and residents’ lives, and has an overall and leading impact on the urban economy. Urban public transportation has become the main body of urban transportation with its convenience, speed and large capacity.

[0003] However, the current bus station facilities are not compatible with the behavioral habits of many disabled people and people with weak normal mobility, which affects their travel and makes travel extremely complicated for disabled people. Summary of the invention

[0004] The object of the present invention is to provide a barrier-free bus station service system and method thereof to solve the problems raised in the above-mentioned background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a barrier-free platform service system for public transportation, comprising

[0006] The waiting system is used for mutual sensing between people and vehicles, destination route planning and notification of real-time route information to vehicles;

[0007] The boarding system is used to sense the vehicle entering the station and provide voice announcements to guide passengers to board the vehicle;

[0008] The getting-off system is used to provide voice and vibration reminders when passengers arrive at the station and to guide passengers to get off the bus.

[0009] As a preferred solution of the present invention: the riding system includes an intelligent terminal, a bus, a platform and a crossing indicator. The intelligent terminal is connected to the bus, the platform and the crossing indicator by signal. A Braille route sign is provided in the platform.

[0010] As a preferred solution of the present invention: the smart terminal is connected to the platform via the global positioning system GPS, the smart terminal is connected to the bus via Bluetooth, the smart terminal is connected to the crossing reminder via radio frequency identification RFID, and the smart terminal includes a smart phone and a smart wearable device.

[0011] As a preferred solution of the present invention: the bus is provided with an on-board guide terminal for the blind, which is used to receive and process signals from various terminal devices, and aggregate, analyze and process the signals and send them to the backend, and transmit them to the driver, passengers and people in need of help through the signal output device;

[0012] The in-vehicle Bluetooth tag communicates with the barrier-free smart tag to identify people who need help getting on the bus and remind the driver and passengers to provide assistance when appropriate;

[0013] The on-board light-emitting diode (LED) screen is used to remind users to get off the bus when necessary, based on the selected route and set destination;

[0014] And the on-board horn is used to receive information from the on-board guide terminal, broadcast the information that needs to be announced, remind passengers to provide necessary help and remind those who need help when they arrive at the station.

[0015] As a preferred solution of the present invention: the waiting system includes a monitoring unit 1 and a monitoring unit 2, the monitoring unit 1 is used to perform facial recognition on passengers who need help, and the monitoring unit 2 is used to monitor whether the blind path in the platform is occupied. Both the monitoring unit 1 and the monitoring unit 2 use cameras for photo monitoring, and the cameras are installed at the platform.

[0016] As a preferred solution of the present invention: the monitoring unit adopts a two-dimensional principal component analysis algorithm 2DPCA algorithm for calculating a pair of face snapshots, specifically:

[0017] The sample set X of face capture images is defined as:

[0018] X={x1,x2,…,x m}

[0019] Where m is the total number of samples of X, and its size is determined by the size of the image pixels. m Define the low-dimensional space dimension input d′ for the data of the mth sample, and center all samples so that the origin of the coordinate is placed at the center of the data sample, find the direction with the largest variance, and make the average value of each feature of the centralized data sample 0, that is, To simplify the algorithm for subsequent covariance matrix calculation, the calculation formula is as follows:

[0020]

[0021] In the formula, x i For the data of the i-th sample in the sample set X, calculate the sample covariance matrix XX T Perform eigendecomposition, find the eigenvalues ​​and eigenvectors, and take the eigenvectors w1, w2, ..., w corresponding to the largest d′ eigenvalues d′, and finally output the projection matrix:

[0022] W = {w1, w2, ..., w d′}

[0023] Wherein, W is the sample set mapped after the sample set X is reduced in dimension d′.

[0024] As a preferred solution of the present invention, the face image quality is screened after the face is captured, and the specific method is as follows: for the captured indicators involving face posture, light intensity, contrast, clarity, etc., the face image that meets the quality requirements is used for subsequent recognition, otherwise it is discarded. First, the external light source, global light intensity, etc. are the key to the face image quality assessment. Assuming that the key points of the face image are H (h0, h1, ..., h j ,…,h n ), the mean and variance calculation results of the facial key points can be obtained as shown below:

[0025]

[0026] In the formula, is the mean of the key points of the face, N is the Nth collected face, Represents the variance of all collected face key points;

[0027] Using the key points of the face image under standard lighting, the lighting quality of the entire face image can be evaluated. The calculation formula is as follows:

[0028] Q illumination = dis(H0,H);

[0029] In the formula, Q illumination represents the illumination quality of the face image, dis(H0,H) is the distance between the key point H0 of the face image and the key point H of the face image;

[0030] In terms of the contrast and clarity quality assessment of face images, the maximum grayscale value I of image I is mainly used. max , minimum gray value I min , complete the contrast evaluation of image pixels, the calculation formula is as shown below:

[0031]

[0032] In the formula, ΔI represents the average difference between the maximum grayscale value and the minimum grayscale value, and C represents the maximum grayscale value I of the face image. max The minimum gray value I of the face image min Calculate the pixel contrast of the face image;

[0033] The quality assessment of facial image clarity mainly measures the image clarity by measuring the proportion of low-frequency and high-frequency information of facial image features. The lack of high-frequency information will cause image blur. The calculation formula is as follows:

[0034] Sharpness=diff(I,lowpass(I))

[0035] Among them, Sharpness represents the clarity of the face image, diff represents the difference in clarity between the face image to be evaluated and the standard face image, lowpass(I) represents the standard face image, and the larger the Sharpness value, the higher the clarity of the detected face image.

[0036] As a preferred solution of the present invention: the monitoring unit 2 detects the blind path and detects the smoothness of the blind path to determine whether the blind path is occupied. When the blind path is smooth, it means that there is no person or object on the blind path, and when the blind path is not smooth, it means that there is a person or object on the blind path. The smoothness detection adopts the edge detection algorithm Canny algorithm for detection, and the detection steps are as follows:

[0037] (1) Smooth the image using a Gaussian filter:

[0038] Use a 5*5 Gaussian filter template, set the standard value of the Gaussian filter to 1, and filter the image. The calculation method is as follows:

[0039] f r (x,y)=f(x,y)*G(x,y);

[0040] In the formula, f r (x, y) represents image data, f(x, y) represents image data, and G(x, y) represents Gaussian function;

[0041] (2) Use the finite difference of the first-order partial derivative to calculate the magnitude and direction of the gradient, using the first-order difference convolution template, the formula is as follows:

[0042]

[0043] In the formula, f x Represents two sets of coordinates in the x direction, f y are two sets of coordinates in the Y direction, is the gradient magnitude in the x direction, is the gradient amplitude in the Y direction;

[0044] Get the amplitude, the formula is as follows:

[0045]

[0046] In the formula, Represents the magnitude of the image gradient point (x, y);

[0047] The formula is as follows:

[0048]

[0049] In the formula, Represents the direction of the image gradient;

[0050] (3) Suppress the non-maximum value of the gradient amplitude, retain the point with the largest local gradient value, suppress other points, and set the non-maximum point to zero;

[0051] (4) Use a dual threshold algorithm to detect and connect edges. Use two thresholds T1 and T2, where T1 = 2T2. According to the two thresholds, two images I1[i, j] and I2[i, j] are obtained. I2[i, j] is used to find each line segment. I1[i, j] is used to extend these line segments in both directions to find the edge breaks and connect these edges.

[0052] (5) Binarize the image to make it more prominent and clear, thereby completing the detection of the blind path.

[0053] A method for using a barrier-free platform service system for public transportation, the specific steps are as follows:

[0054] In the first step, passengers confirm their travel plans in advance through the APP and store them in the barrier-free travel system. Passengers who need help can enter and edit their personal information in advance in the APP.

[0055] In the second step, when the passengers who need help arrive at the barrier-free platform, they can press buttons to find the vehicle arrival information according to the route and voice broadcast the information. The visually impaired can get relevant riding information by touching the Braille route sign in the platform. At the same time, when the crossing indicator detects the position of the disabled, it is automatically or manually pressed to trigger the voice broadcast at the intersection. After helping the disabled to pass and reach the barrier-free platform, the electronic station sign will switch to the corresponding help-related content according to the type of people seeking help, and send the interactive information and the facial recognition picture of the passengers who need help collected by the monitoring unit to the public transportation assistance cloud service system;

[0056] In the third step, the bus assistance cloud service system will synchronize the information to the bus dispatch system. The dispatch system will combine the vehicle GPS and the arrival information to find the nearest bus to the station, send a reminder to the bus to pay attention to the person who needs help, and also send the information of the passengers to the bus driver in a targeted or broadcast manner to help the passengers get on the bus;

[0057] The fourth step is that when the vehicle is about to arrive at the station and the passengers need to get off, the vehicle will use functions such as mobile phone vibration, voice, and screen flashing to remind the passengers. At the same time, the on-board loudspeaker will broadcast the necessary information to remind passengers to provide necessary help and remind those who need help that the station has arrived.

[0058] As a preferred solution of the present invention: the condition for the directional sending is: if the travel plan has been confirmed in advance on the mobile phone APP, a reminder message will be sent to the bus driver who needs to take the route and is closest to the current station; the condition for the broadcast sending is: if the passenger only carries devices with weak interactive functions such as customized transportation cards, smart crutches, etc., relevant reminders will be sent to all bus drivers who will enter the station through broadcasting.

[0059] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0060] The present invention can increase the convenience of passengers when traveling through the coordinated setting of the waiting system, the boarding system and the getting-off system, and even provides great convenience for the travel of some disabled people such as the visually impaired. Through the setting of the monitoring unit one, the facial scan and photo of the passenger can be taken. When the facial image of the passenger who needs help is taken and matches the information input by the passenger in need of help in advance in the mobile phone APP, the public transportation assistance cloud service system will synchronize the information to the public transportation dispatching system, and then send the image to the nearest bus driver, so that the bus driver can promptly help the passenger in need of help when arriving at the station. At the same time, with the setting of the on-board horn, the passenger in need of help can be reminded to get off the bus in time, which further increases the convenience of the passengers getting off the bus. The setting can monitor the blind path near the platform to avoid dangerous accidents such as falls caused by obstacles on the blind path, further increasing the safety of visually impaired people's travel. The whole device not only increases the accessibility of disabled people taking public transportation and increases the safety of disabled people's travel, but also greatly increases the convenience of passengers and disabled people in taking the bus, which is conducive to the commissioning of the device. The setting of the crossing reminder can also automatically trigger the voice broadcast at the intersection when the position of the disabled person is detected, to help the disabled person pass and reach the barrier-free platform. The electronic bus stop sign will switch to the corresponding help-related content according to the type of people seeking help. The setting of Braille route signs can facilitate the visually impaired people to inquire about different bus routes, so that the visually impaired people can find the corresponding routes and buses when traveling. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0062] Figure 1 is a structural diagram of a barrier-free ride service system according to an embodiment of the present invention;

[0063] Figure 2 is a structural diagram of a platform boarding system according to an embodiment of the present invention;

[0064] Figure 3 It is a structural diagram of a directional sending ride system according to an embodiment of the present invention;

[0065] Figure 4 is a structural diagram of a broadcast sending boarding system according to an embodiment of the present invention;

[0066] Figure 5 It is a schematic diagram of the structure of a bus internal terminal signal sending and receiving system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0067] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0068] See also Figure 1-Figure 5 , is an embodiment of the present invention, which provides a barrier-free platform service system for public transportation, including

[0069] The waiting system is used for mutual sensing between people and vehicles, destination route planning and notification of real-time route information to vehicles;

[0070] The boarding system is used to sense the vehicle entering the station and provide voice announcements to guide passengers to board the vehicle;

[0071] The getting-off system is used to provide voice and vibration reminders when passengers arrive at the station and to guide passengers to get off the bus.

[0072] The riding system comprises an intelligent terminal, a bus, a platform and a street crossing indicator. The intelligent terminal is connected with the bus, the platform and the street crossing indicator by signals. A Braille route sign is arranged in the platform.

[0073] In one embodiment, the smart terminal is connected to the platform via the global positioning system GPS, the smart terminal is connected to the bus via Bluetooth, the smart terminal is connected to the crossing indicator via radio frequency identification RFID, and the smart terminal includes a smart phone and a smart wearable device.

[0074] The bus is provided with an on-board guide terminal for the blind, which is used to receive and process signals from various terminal devices, summarize and analyze the signals and send them to the backend, and transmit them to the driver, passengers and people in need of help through the signal output device;

[0075] The in-vehicle Bluetooth tag communicates with the barrier-free smart tag to identify people who need help getting on the bus and remind the driver and passengers to provide assistance when appropriate;

[0076] The on-board light-emitting diode (LED) screen is used to remind users to get off the bus when necessary, based on the selected route and set destination;

[0077] And the on-board horn is used to receive information from the on-board guide terminal, broadcast the information that needs to be announced, remind passengers to provide necessary help and remind those who need help to arrive at the station.

[0078] In one embodiment, the waiting system includes a monitoring unit 1 and a monitoring unit 2, wherein the monitoring unit 1 is used to perform facial recognition on passengers who need help, and the monitoring unit 2 is used to monitor whether the blind path in the platform is occupied. Both the monitoring unit 1 and the monitoring unit 2 use cameras for photo monitoring, and the cameras are installed at the platform.

[0079] The monitoring unit adopts a two-dimensional principal component analysis algorithm 2DPCA algorithm for face capture calculation, specifically:

[0080] The sample set X of face capture images is defined as:

[0081] X={x1,x2,…,x m}

[0082] Where m is the total number of samples of X, and its size is determined by the size of the image pixels. m Define the low-dimensional space dimension input d′ for the data of the mth sample, and center all samples so that the origin of the coordinate is placed at the center of the data sample, find the direction with the largest variance, and make the average value of each feature of the centralized data sample 0, that is, To simplify the algorithm for subsequent covariance matrix calculation, the calculation formula is as follows:

[0083]

[0084] In the formula, x i For the data of the i-th sample in the sample set X, calculate the sample covariance matrix XX T Perform eigendecomposition, find the eigenvalues ​​and eigenvectors, and take the eigenvectors w1, w2, ..., w corresponding to the largest d′ eigenvalues d′ , and finally output the projection matrix:

[0085] W = {w1, w2, ..., w d′}

[0086] Where W is the sample set mapped after the sample set X is reduced to d′ dimension.

[0087] After the face is captured, the face image quality is screened. The specific method is as follows: for the captured indicators involving face posture, light intensity, contrast, clarity, etc., the face image that meets the quality requirements is used for subsequent recognition, otherwise it is discarded. First, the external light source, global light intensity, etc. are the key to the face image quality assessment. Assuming that the key points of the face image are H (h0, h1, ..., h j …,h n ), the mean and variance calculation results of the facial key points can be obtained as shown below:

[0088]

[0089] In the formula, is the mean of the key points of the face, N is the Nth collected face, Represents the variance of all collected face key points;

[0090] Using the key points of the face image under standard lighting, the lighting quality of the entire face image can be evaluated. The calculation formula is as follows:

[0091] Q illumination = dis(H0,H);

[0092] In the formula, Q illumination represents the illumination quality of the face image, dis(H0,H) is the distance between the key point H0 of the face image and the key point H of the face image;

[0093] In terms of the contrast and clarity quality assessment of face images, the maximum grayscale value I of image I is mainly used. max , minimum gray value I min , complete the contrast evaluation of image pixels, the calculation formula is as shown below:

[0094]

[0095] In the formula, ΔI represents the average difference between the maximum grayscale value and the minimum grayscale value, and C represents the maximum grayscale value I of the face image. max The minimum gray value I of the face image min Calculate the pixel contrast of the face image

[0096] The quality assessment of facial image clarity mainly measures the image clarity by measuring the proportion of low-frequency and high-frequency information of facial image features. The lack of high-frequency information will cause image blur. The calculation formula is as follows:

[0097] Sharpness=diff(I,lowpass(I))

[0098] Among them, Sharpness represents the clarity of the face image, diff represents the difference in clarity between the face image to be evaluated and the standard face image, lowpass(I) represents the standard face image, and the larger the Sharpness value, the higher the clarity of the detected face image.

[0099] In one embodiment, the monitoring unit 2 detects the blind path and detects the smoothness of the blind path to determine whether the blind path is occupied. If the blind path is smooth, it means that there is no person or object on the blind path, and if the blind path is not smooth, it means that there is a person or object on the blind path. The smoothness detection uses the edge detection algorithm Canny algorithm for detection, and the detection steps are as follows:

[0100] (1) Smooth the image using a Gaussian filter:

[0101] Use a 5*5 Gaussian filter template, set the standard value of the Gaussian filter to 1, and filter the image. The formula is as follows:

[0102] f r (x,y)=f(x,y)*G(x,y);

[0103] In the formula, f r (x, y) represents image data, f(x, y) represents image data, and G(x, y) represents Gaussian function;

[0104] (2) Use the finite difference of the first-order partial derivative to calculate the magnitude and direction of the gradient, using the first-order difference convolution template, the formula is as follows:

[0105]

[0106] In the formula, f x Represents two sets of coordinates in the x direction, f y are two sets of coordinates in the Y direction, is the gradient magnitude in the x direction, is the gradient amplitude in the Y direction;

[0107] Get the amplitude, the formula is as follows:

[0108]

[0109] In the formula, Represents the magnitude of the image gradient point (x, y);

[0110] The formula is as follows:

[0111]

[0112] (3) Suppress the non-maximum value of the gradient amplitude, retain the point with the largest local gradient value, suppress other points, and set the non-maximum point to zero;

[0113] (4) Use a dual threshold algorithm to detect and connect edges. Use two thresholds T1 and T2, where T1 = 2T2. According to the two thresholds, two images I1[i, j] and I2[i, j] are obtained. I2[i, j] is used to find each line segment. I1[i, j] is used to extend these line segments in both directions to find the edge breaks and connect these edges.

[0114] (5) Binarize the image to make it more prominent and clear, thereby completing the detection of the blind path.

[0115] Another embodiment of the present invention provides a method for using a barrier-free platform service system for public transportation, and the specific steps are as follows:

[0116] In the first step, passengers confirm their travel plans in advance through the APP and store them in the barrier-free travel system. Passengers who need help can enter and edit their personal information in advance in the APP.

[0117] In the second step, when the passengers who need help arrive at the barrier-free platform, they can find the vehicle arrival information according to the route by pressing buttons and voice broadcast the information. The visually impaired can get relevant riding information by touching the Braille route sign in the platform. At the same time, the crossing reminder will automatically (or manually) trigger the voice broadcast at the intersection after detecting the position of the disabled person. After helping the disabled person to pass and reach the barrier-free platform, the electronic station sign will switch to the corresponding help-related content according to the type of people seeking help, and send the interactive information and the facial recognition picture of the passengers who need help collected by the monitoring unit 1 to the public transportation assistance cloud service system;

[0118] In the third step, the bus assistance cloud service system will synchronize the information to the bus dispatch system. The bus dispatch system will combine the vehicle GPS and arrival information to find the nearest bus to the station, send a message reminder (TTS or dispatch instruction) to the bus to pay attention to the person who needs help, and also send the information of the passengers to the bus driver in a targeted or broadcast manner to help the passengers get on the bus;

[0119] The fourth step is that when the vehicle is about to arrive at the station and the passengers need to get off, the vehicle will use functions such as mobile phone vibration, voice, and screen flashing to remind the passengers. At the same time, the on-board loudspeaker will broadcast the necessary information to remind passengers to provide necessary help and remind those who need help that the station has arrived.

[0120] The conditions for targeted sending are: if the travel plan has been confirmed in advance on the mobile phone APP, a reminder message will be sent to the bus driver who needs to take the route and is closest to the current station; the conditions for broadcast sending are: if the passenger only carries devices with weak interactive functions such as customized transportation cards, smart crutches, etc., relevant reminders will be sent through broadcasting to all bus drivers who will enter the station.

[0121] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments, or replace some of the technical features therein with equivalents. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention. All actions to obtain label sets, signals, information or driving data in this application are carried out in compliance with the relevant data protection laws and policies of the place and country, and with the authorization given by the owner of the corresponding device.

Claims

1. A barrier-free platform service system for public transportation, characterized in that: include The waiting system is used for mutual sensing between people and vehicles, destination route planning and notification of real-time route information to vehicles; The boarding system is used to sense the vehicle entering the station and provide voice announcements to guide passengers to board the vehicle; The getting-off system is used to remind passengers of their arrival at the station through voice and vibration, and to guide passengers to get off the bus; The waiting system includes a monitoring unit 1 and a monitoring unit 2. The monitoring unit 1 is used to perform face recognition on passengers who need help, and the monitoring unit 2 is used to monitor whether the blind path in the platform is occupied. Both the monitoring unit 1 and the monitoring unit 2 use cameras for photo monitoring, and the cameras are installed at the platform; The monitoring unit adopts a two-dimensional principal component analysis algorithm 2DPCA algorithm for face capture calculation, specifically: The sample set X of face capture images is defined as: X={x1,x2,…,x m } Where m is the total number of samples of X, and its size is determined by the size of the image pixels. m Define the low-dimensional space dimension input d′ for the data of the mth sample, and center all samples so that the origin of the coordinate is placed at the center of the data sample, find the direction with the largest variance, and make the average value of each feature of the centralized data sample 0, that is, To simplify the algorithm for subsequent covariance matrix calculation, the calculation formula is as follows: In the formula, x i For the data of the i-th sample in the sample set X, calculate the sample covariance matrix XX T Perform eigendecomposition, find the eigenvalues ​​and eigenvectors, and take the eigenvectors w1, w2, ..., w corresponding to the largest d′ eigenvalues d′ , and finally output the projection matrix: W={w1,w2,…,wd ′ } Where W is the sample set mapped after reducing the d′ dimension of the sample set X; The riding system includes an intelligent terminal, a bus, a platform and a street crossing indicator. The intelligent terminal is connected to the bus, the platform and the street crossing indicator by signal. The platform is provided with a Braille route sign. The smart terminal is connected to the platform via the global positioning system GPS, the smart terminal is connected to the bus via Bluetooth, the smart terminal is connected to the street crossing indicator via radio frequency identification RFID, and the smart terminal includes a smart phone and a smart wearable device; The bus is provided with an on-board blind guide terminal, which is used to receive and process signals from various terminal devices, and summarize, analyze and process the signals and send them to the backend; The in-vehicle Bluetooth tag communicates with the barrier-free smart tag to identify people who need help getting on the bus and remind the driver and passengers to provide assistance when appropriate; The on-board light-emitting diode LED screen is used to remind users to get off the vehicle; And the on-board horn is used to receive information from the on-board guide terminal, broadcast the information that needs to be announced, remind passengers to provide necessary help and remind those who need help when they arrive at the station.

2. A barrier-free bus platform service system according to claim 1, characterized in that: After the face is captured, the face image quality is screened. The specific method is as follows: for the captured indicators involving face posture, light intensity, contrast, and clarity, the face image that meets the quality requirements is used for subsequent recognition, otherwise it is discarded. First, the external light source and global light intensity are the key to the face image quality assessment. Assuming that the key points of the face image are H (h0, h1, ..., h j ,…,h n ), the mean and variance calculation results of the facial key points can be obtained as shown below: In the formula, is the mean of the key points of the face, N is the Nth collected face, Represents the variance of all collected face key points; Using the key points of the face image under standard lighting, the lighting quality of the entire face image can be evaluated. The calculation formula is as follows: Q illumination =dis(H0,H); In the formula, Q illumination represents the illumination quality of the face image, dis(H0,H) is the distance between the key point H0 of the face image and the key point H of the face image; In terms of the contrast and clarity quality assessment of face images, the maximum grayscale value I of image I is mainly used. max , minimum gray value I min , complete the contrast evaluation of image pixels, the calculation formula is as shown below: In the formula, ΔI represents the average difference between the maximum grayscale value and the minimum grayscale value, and C represents the maximum grayscale value I of the face image. max The minimum gray value I of the face image min Calculate the pixel contrast of the face image; The quality assessment of facial image clarity mainly measures the image clarity by measuring the proportion of low-frequency and high-frequency information of facial image features. The lack of high-frequency information will cause image blur. The calculation formula is as follows: Sharpness=diff(I,lowpass(I)) Among them, Sharpness represents the clarity of the face image, diff represents the difference in clarity between the face image to be evaluated and the standard face image, lowpass(I) represents the standard face image, and the larger the Sharpness value, the higher the clarity of the detected face image.

3. A barrier-free bus station service system according to claim 2, characterized in that: The monitoring unit 2 detects the blind path and detects the smoothness of the blind path to determine whether the blind path is occupied. The smoothness detection uses the edge detection algorithm Canny algorithm for detection. The detection steps are as follows: (1) Smooth the image using a Gaussian filter: Use a 5*5 Gaussian filter template and set the standard value of the Gaussian filter to 1 to filter the image. The calculation method is as follows: r (x,y)=f(x,y)*G(x,y); In the formula, f r (x, y) represents image data, f(x, y) represents image data, and G(x, y) represents Gaussian function; (2) Use the finite difference of the first-order partial derivative to calculate the magnitude and direction of the gradient, using the first-order difference convolution template, the formula is as follows: In the formula, fx represents two sets of coordinates in the x direction, and fy represents two sets of coordinates in the y direction. is the gradient magnitude in the x direction, is the gradient amplitude in the Y direction; Get the amplitude, the formula is as follows: In the formula, Represents the magnitude of the image gradient point (x, y); The formula is as follows: In the formula, Represents the direction of the image gradient; (3) Suppress the non-maximum value of the gradient amplitude, retain the point with the largest local gradient value, suppress other points, and set the non-maximum point to zero; (4) Use a dual threshold algorithm to detect and connect edges. Use two thresholds T1 and T2, where T1 = 2T2. According to the two thresholds, two images I1[i, j] and I2[i, j] are obtained. I2[i, j] is used to find each line segment. I1[i, j] is used to extend these line segments in both directions to find the edge breaks and connect these edges. (5) Binarize the image to make it more prominent and clear, thereby completing the detection of the blind path.

4. The barrier-free bus station service system according to claim 1, characterized in that: The specific steps are as follows: In the first step, passengers confirm their travel plans in advance through the APP and store them in the barrier-free travel system. Passengers who need help can enter and edit their personal information in advance in the APP. In the second step, when the passengers who need help arrive at the barrier-free platform, they can press buttons to find and voice broadcast the vehicle arrival information according to the route. The visually impaired can obtain relevant riding information by touching the Braille route sign in the platform. At the same time, when the crossing indicator detects the position of the disabled, it is automatically or manually pressed to trigger the voice broadcast at the intersection. After helping the disabled to pass and reach the barrier-free platform, the electronic station sign will switch to the corresponding help content according to the type of people seeking help, and send the interactive information and the facial recognition picture of the passengers who need help collected by the monitoring unit 1 to the public transportation assistance cloud service system; In the third step, the bus assistance cloud service system will synchronize the information to the bus dispatch system. The bus dispatch system will combine the vehicle GPS arrival information to find the nearest bus to the station, send information reminders to the bus for people who need help, and also send the information of the passengers to the bus driver in a targeted or broadcast manner to help the passengers get on the bus; Step 4: When the vehicle is about to arrive at the station and passengers need to get off, the vehicle will use the vibration, voice, and screen flashing functions of the mobile phone to remind passengers. At the same time, the vehicle speakers will broadcast the necessary information to remind passengers to provide necessary assistance and remind those who need help to arrive at the station; The conditions for targeted sending are: if the travel plan has been confirmed in advance on the mobile phone APP, a reminder message will be sent to the bus driver who is closest to the current station and takes the required route; the conditions for broadcast sending are: if the passenger only carries a customized transportation card or a smart cane with weak interactive function, relevant reminders will be sent to all bus drivers who are about to enter the station through broadcasting.

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