TWI824862B - Method for determining degree of crowded compartment, electronic device, and storage medium - Google Patents

Abstract

The present application provides a method for determining degree of crowded compartment, an electronic device, and a storage medium. The method includes: performing an image recognition on an interior overlooking image of a compartment of a vehicle, and determining a remaining carrying space in the compartment based on a result of the image recognition; determining a predicted remaining number of people that can be carried by the compartment according to the remaining carrying space; determining a recommended remaining number of people that the compartment can carry based on a number of passengers in the compartment, the predicted remaining number of people that can be carried and the maximum number of people that the compartment can carry. This application can assist in determining the degree of crowded compartment and effectively realizing passenger diversion, thereby avoiding safety problems caused by excessive concentration of passengers.

Description

Method, electronic equipment and storage medium for determining carriage congestion level

The invention relates to the technical field of public transportation, and in particular, to a method for determining the congestion level of a carriage, electronic equipment and storage media.

When passengers take public transportation (such as a subway), it is usually impossible to know in advance how crowded each car of the arriving vehicle will be. Passengers usually need to choose a certain car to wait in line based on their riding experience. Often, passengers fail to board because the car they are waiting in is too crowded. In this case, passengers need to spend time waiting for the next transport. . This way of riding is too random, which affects travel efficiency.

In view of the above, it is necessary to provide a method, electronic device and storage medium for determining the degree of congestion in a carriage, which can determine the degree of congestion of each carriage of the vehicle, so as to recommend a less crowded carriage to the passengers to save the waiting time of the passengers. Improve travel efficiency.

The method for determining the congestion level of the carriage includes: performing image recognition on the internal top-view image of the carriage, and determining the remaining carrying space in the carriage based on the result of the image recognition; determining the predicted remaining number of people that the carriage can carry based on the remaining carrying space; The number of passengers in the carriage, the predicted remaining number of people and the maximum number of people in the carriage are used to determine the recommended remaining number of people in the carriage; based on the recommended remaining number of people and the maximum number of people, determine The degree of crowding in said carriage.

Optionally, performing image recognition on the internal top view image of the compartment, and determining the remaining load space in the compartment based on the image recognition results includes: using a preset image recognition algorithm to identify targets in the internal top view In the area where the object is located, the area where the target object is located is regarded as an occupied area; the occupied area is updated according to the preset rules to obtain an unoccupied area outside the occupied area; the unoccupied area is divided into stable and the remaining bearing space is determined based on the stable unoccupied area and the unstable unoccupied area.

Optionally, updating the occupied area according to preset rules to obtain an unoccupied area outside the occupied area includes: updating the compartment wall panel in the internal top view image to an occupied area; determining The distance between the compartment wall panel and any other occupied area. If the distance is less than the preset distance threshold, the area between any occupied area corresponding to the distance and the compartment wall panel is updated. is an occupied area; all areas outside the occupied area are regarded as the unoccupied areas.

Optionally, dividing the unoccupied area into a stable unoccupied area and an unstable unoccupied area includes: determining the unoccupied area surrounded by the occupied area as a surrounded area, and treating the surrounded area as The unstable unoccupied area; the area in the unoccupied area other than the unstable unoccupied area is regarded as the stable unoccupied area.

Optionally, determining the remaining bearing space based on the stable unoccupied area and the unstable unoccupied area includes: determining that the unstable unoccupied area is converted into the stable unoccupied area. Conversion rate of the area; calculate the remaining bearing space based on the area of the stable unoccupied area, the area of the unstable unoccupied area and the conversion rate.

Optionally, determining the predicted remaining number of people that the compartment can carry based on the remaining carrying space includes: making the predicted remaining number of people that can be carried be proportional to the remaining carrying space.

Optionally, the method further includes: detecting the number of passengers getting on and off the carriage at each station, and determining the number of passengers in the carriage based on the number of passengers getting on and the number of passengers getting off. Number of guests.

Optionally, the method further includes: displaying the recommended remaining capacity of the carriage to waiting passengers; and using indicator lights of different colors to display the corresponding number of passengers according to the numerical range to which the congestion level belongs. The numerical range indicates the degree of crowding.

The computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by the processor, the method for determining the congestion level of the carriage or the method for determining the congestion level of the carriage is implemented.

The electronic device includes a storage and at least one processor. At least one instruction is stored in the storage. When the at least one instruction is executed by the at least one processor, the method for determining the car congestion level is implemented.

Compared with the prior art, the method for determining the congestion level of a carriage provided by the embodiment of the present application determines the remaining carrying space of the carriage based on the internal top-down image of the carriage, and based on the remaining carrying space, the number of passengers already carried in the carriage and the maximum capacity of the carriage. Determine the number of people to recommend the remaining number of people that can be carried, and determine the congestion level of the carriage. It can determine the congestion level of each carriage of the vehicle, so as to recommend less crowded carriages to passengers to save passengers' waiting time and avoid excessive concentration of passengers. This leads to safety issues and can effectively realize the diversion of rides.

3: Electronic equipment

30: Carriage congestion level determination system

31:Storage

32: Processor

S1~S4: steps

S11~S14: Steps

S121~S123: Steps

In order to more clearly explain the technical solutions in the embodiments of the present application or the conventional technology, the following will briefly introduce the drawings needed to describe the embodiments or the conventional technology. Obviously, the drawings in the following description are only This is an embodiment of the present application. For those of ordinary skill in the art, other drawings can be obtained based on the provided drawings without exerting creative efforts.

Figure 1 is a flow chart of a method for determining the congestion level of a carriage provided by an embodiment of the present application.

Figure 2 is a method for determining the remaining load space in a carriage provided by an embodiment of the present application. flowchart.

FIG. 3 is an example diagram of an occupied area corresponding to a target object provided by an embodiment of the present application.

Figure 4 is a flowchart of determining an unoccupied area provided by an embodiment of the present application.

Figure 5 is a first example diagram of updating an occupied area provided by an embodiment of the present application.

Figure 6 is an example diagram of the distance between the compartment wall panel and the occupied area provided by the embodiment of the present application.

Figure 7 is a second example diagram of updating an occupied area provided by an embodiment of the present application.

Figure 8 is an example diagram of an unstable unoccupied area provided by an embodiment of the present application.

Figure 9 is an architecture diagram of an electronic device provided by an embodiment of the present application.

In order to more clearly understand the above objects, features and advantages of the present application, the present application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, as long as there is no conflict, the embodiments of the present application and the features in the embodiments can be combined with each other.

Many specific details are set forth in the following description to facilitate a full understanding of the present application. The described embodiments are only some, rather than all, of the embodiments of the present application. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of this application.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this application belongs. The terminology used herein in the description of the application is for the purpose of describing specific embodiments only and is not intended to limit the application.

In one embodiment, when passengers take public transportation (such as a subway), it is usually impossible to know in advance the congestion level of each car of the arriving transportation vehicle. Passengers usually need to choose a certain car to wait in line based on their own riding experience. It often happens that passengers are waiting in line. The car in which the passenger is waiting is too crowded and the passenger fails to board. At this time, the passenger needs to spend time waiting for the next transportation.

In order to solve the above problem, an embodiment of the present application provides a method for determining the congestion level of a carriage. The remaining carrying space of the carriage is determined based on the internal top-down image of the carriage. The remaining carrying space, the number of passengers already carried in the carriage and the maximum number of passengers in the carriage are determined. Determine the recommended remaining capacity and determine the level of crowding in the carriage. The method can determine the congestion level of each carriage of the vehicle and recommend less crowded carriages to passengers to save passengers' waiting time, effectively improve travel efficiency and effectively reduce safety hazards caused by overcrowding of passengers.

Refer to Figure 1, which is a flow chart of a method for determining the congestion level of a carriage provided in a preferred embodiment of the present application.

In this embodiment, the method for determining the congestion level of a carriage can be applied to an electronic device (such as the electronic device 3 shown in FIG. 9 ), and the electronic device can be a vehicle-mounted device installed in a vehicle. For vehicles that need to determine the level of compartment congestion, the function of determining the level of compartment congestion provided by the method of the embodiment of the present application can be directly integrated on the electronic device installed in each compartment of the vehicle, or the function of determining the level of compartment congestion provided by the method of the embodiment of the present application can be integrated using a software development kit (Software Development Kit). Development Kit (SDK)) that runs on electronic devices installed on vehicles.

As shown in Figure 1, the method for determining the congestion level of a carriage specifically includes the following steps. According to different needs, the order of the steps in the flow chart can be changed, and some steps can be omitted.

Step S1: Perform image recognition on the internal top-view image of the carriage, and determine the remaining load space in the carriage based on the image recognition results.

In one embodiment, a vehicle (for example, a subway) includes a plurality of carriages, and at least one camera device (for example, a wide-angle camera) is installed in each carriage, and the camera device is used to acquire an internal top-down image of the carriage. For example, at least one camera device can be installed on the top of the carriage to capture an internal top-down image of the interior of the carriage.

In other embodiments, the camera device may further include a depth camera device, and the internal top-view image may include a depth image with a depth value captured by the depth camera device, Specifically, the depth image uses the collected depth values of each point in the carriage as primitive values.

In one embodiment, as shown in Figure 2, a flow chart for determining the remaining load space in a carriage provided by the embodiment of the present application specifically includes the following process:

Step S11: Use a preset image recognition algorithm to identify the area where the target object is located in the internal top view, and regard the area where the target object is located as an occupied area.

In one embodiment, the image recognition algorithm includes an object detection algorithm, including but not limited to R-CNN (Region with Convolutional Neural Network features) algorithm, YOLO (You Only Look Once) algorithm , SSD (Single Short multibox Detector) algorithm.

In one embodiment, the target objects include but are not limited to people and luggage (eg, suitcases). In addition, considering that passengers can carry smaller luggage with them, but larger luggage must be placed on the floor of the carriage and occupy space, an area threshold can be set in advance (for example, 0.5 square meters), and luggage larger than the area threshold will be The area is used as the area where the target object is located. Wherein, the area threshold can also be set based on the ratio of the internal top-view image to the actual area of the compartment, for example, 100 primitive points.

In other embodiments, in addition to the image recognition algorithm, the depth image described in step S1 can also be combined to further identify and filter the area where the target object is located. For example, a depth threshold is preset. (for example, 1.5 meters), and areas smaller than the depth threshold are removed from the area where the target object is located. Wherein, the depth threshold can also be set based on the actual height of the carriage.

After the image recognition algorithm detects the target object, it automatically selects the area where the target object is located to obtain the occupied area. For example, a rectangular frame is used to select the area where the target object is located, and the area within the rectangular frame is regarded as the occupied area. occupied area. For example, as shown in Figure 3, it is an example diagram of the occupied area corresponding to the target object provided by the embodiment of the present application. The entire image represents the internal top-view image, and the surrounding dotted rectangular frame represents the compartment wall panel. The black straight line in the middle represents the carriage door, and the black-filled square area represents the occupied area obtained after selecting the target object. area.

Step S12: Update the occupied area according to preset rules to obtain an unoccupied area outside the occupied area.

In one embodiment, as shown in Figure 4, the flow chart for determining an unoccupied area provided by the embodiment of the present application specifically includes the following process:

Step S121: Update the compartment wall panel in the interior top view image to an occupied area.

In one embodiment, the compartment wall panel is located at the edge of the compartment and belongs to the surrounding closed fixed area. Therefore, the compartment wall panel can be updated to an occupied area, which is equivalent to the area occupied by passengers. In addition, the compartment door is an open area, and passengers need to enter and exit through the compartment door. When a new passenger enters through the compartment door, the passengers who were originally at the compartment door will generally be pushed and automatically move toward the inside of the compartment and away from the compartment door. Therefore, The compartment door can be used as an unoccupied area.

For example, as shown in Figure 5, it is the first example diagram for updating the occupied area provided by the embodiment of the present application. In Figure 5, based on Figure 3, the surrounding compartment wall panels are updated to occupied areas represented by black solid lines. Area, the blank gap of the black solid line on the carriage wall panel indicates the unoccupied area where the carriage door is located. In other embodiments, other fixed facilities in the compartment may also be considered, such as armrests, seats, etc., and the fixed facilities in the compartment may be regarded as occupied areas.

Step S122: Determine the distance between the compartment wall and any other occupied area. If the distance is less than a preset distance threshold, compare any occupied area corresponding to the distance with the compartment wall. The area between is updated as occupied area.

In one embodiment, determining the distance between the compartment wall and any other occupied area includes: establishing a rectangular coordinate system XOY ( For example, Figure 6), take the long side of the internal top-view image as the horizontal axis X of the Cartesian coordinate system, take the short side of the internal top-view image as the vertical axis Y of the Cartesian coordinate system, and take the size of each primitive point as Unit length, based on the Cartesian coordinate system, determines the number of primitive points between the carriage wall panel and any other occupied area as the distance. In one embodiment, as shown in Figure 6, The embodiment of the present application provides an example diagram of the distance between the compartment wall panel and the occupied area. Among them, the rectangular coordinate system XOY established based on the internal top-view image (such as Figure 5) containing the occupied area is shown in Figure 6. The distance between the compartment wall panel and any other occupied area is such as D1, As shown in D2, D3 and D4.

In one embodiment, when a new passenger enters the carriage, the passengers located in the innermost compartment and close to the carriage wall will generally not move again. Therefore, if the distance is less than the preset distance threshold, it means that the passengers in any occupied area corresponding to the distance are already very close to the compartment wall, and any occupied area corresponding to the distance can be compared with the The area between the carriage panels is updated as occupied.

In one embodiment, the distance threshold can be set according to the size of the occupied area corresponding to the human body, and can be set to one-third or half the diameter (or length or width) of the occupied area corresponding to the human body. one. For example, the average side length of the square occupied area in Figure 5 is 30 primitive points, then the distance threshold can be set to 30×1/3, that is, the distance threshold is set to 10 primitive points.

In one embodiment, as shown in FIG. 7 , it is a second example diagram for updating an occupied area provided by the embodiment of the present application. Among them, on the basis of Figure 5, the updated occupied area is shown in the upper left corner and upper right corner of Figure 7.

Step S123: Treat all areas outside the occupied areas as the unoccupied areas.

In one embodiment, as shown in Figure 7, the blank area outside the black occupied area is the unoccupied area.

Step S13: Divide the unoccupied area into a stable unoccupied area and an unstable unoccupied area.

In one embodiment, dividing the unoccupied area into a stable unoccupied area and an unstable unoccupied area includes: determining that the unoccupied area surrounded by the occupied area is a surrounded area, and dividing the surrounded area into area as the unstable unoccupied area; the unoccupied area The area in the area other than the unstable unoccupied area is used as the stable unoccupied area.

In one embodiment, determining that the unoccupied area surrounded by the occupied area is an enclosed area includes: using an image recognition algorithm (such as a contour recognition algorithm) to determine the closure of the unoccupied area composed of the occupied area. Contour, the unoccupied area within the closed contour is regarded as the surrounding area.

In one embodiment, when there is an area surrounded by multiple passengers in the carriage and a new passenger enters the carriage, the following situation will occur: Situation 1: Passengers avoid the newly entering passenger, thereby causing the existing passengers in the carriage to Squeeze and move into the enclosed area, or a new passenger enters the enclosed area. At this time, the enclosed area can be regarded as an unoccupied area; Case 2: If the area surrounded by multiple passengers is smaller (for example, smaller than in step S11 (the area threshold), the passengers may not move or may move together, making it impossible to accommodate new passengers within the enclosed area. At this time, the enclosed area can be regarded as an occupied area.

Based on the above situation, the enclosed area is regarded as the unstable unoccupied area. For example, Figure 8 is an example diagram of an unstable unoccupied area provided by an embodiment of the present application. Among them, the gray area in the upper right corner in Figure 8 represents the unstable unoccupied area. In addition, since other unoccupied areas outside the enclosed area are not closed, existing passengers and newly entering passengers can freely move around in the other unoccupied areas. Therefore, the area in the unoccupied area other than the unstable unoccupied area is regarded as the stable unoccupied area, for example, the blank area shown in FIG. 8 .

Step S14: Determine the remaining bearing space based on the stable unoccupied area and the unstable unoccupied area.

In one embodiment, determining the remaining bearing space based on the stable unoccupied area and the unstable unoccupied area includes: determining that the unstable unoccupied area is converted into the stable unoccupied area. The conversion rate of the unoccupied area; according to the area of the stable unoccupied area, the area of the unstable unoccupied area and the conversion rate, calculate the remaining Carrying space.

In one embodiment, referring to the description in step S13, due to the subjective will of passengers already in the carriage, it is impossible to determine whether the unstable unoccupied areas can all be converted into the stable unoccupied areas. The conversion rate of the unstable unoccupied area into the stable unoccupied area may be determined based on historical data.

Specifically, the historical data is a priori data. For example, the a priori data indicates that the corresponding conversion rates are different when the area of the historical unstable unoccupied area is in different area ranges, and the historical unstable unoccupied area The size of the area is directly proportional to the conversion rate. For example, when the area of the historical unstable unoccupied area is between 300 primitive points and 600 primitive points, the conversion rate is 0.3; when the area of the historical unstable unoccupied area is between 600 primitive points When reaching 900 primitive points, the conversion rate is 0.5 and so on. Then, you can refer to the method of establishing a rectangular coordinate system in step S122 to determine the area of each unstable unoccupied area and the area range to which the area of each unstable unoccupied area belongs, and then determine the said area based on a priori data. The conversion rate of unstable unoccupied areas into said stable unoccupied areas. For example, the area of the unstable unoccupied area A is 800 primitive points, and the area range is 600 primitive points to 900 primitive points. Then the unstable unoccupied area A is converted into the stable unoccupied area. The occupied area has a conversion rate of 0.5.

In one embodiment, calculating the remaining bearing space according to the area of the stable unoccupied area, the area of the unstable unoccupied area and the conversion rate includes: letting the remaining bearing space = the The area of the stable unoccupied area + ∑ The area of any unstable unoccupied area × the conversion rate corresponding to any unstable unoccupied area. Wherein, the area of the stable unoccupied area may be determined with reference to the method of establishing a rectangular coordinate system in step S122. For example, in Figure 8, the area of the stable unoccupied area (blank area) is 14,600 primitive points, the area of the only unstable unoccupied area A is 800 primitive points, and the corresponding conversion rate is 0.5, then the figure The remaining carrying space mentioned in 8 = the area of the stable unoccupied area + the area of the unstable unoccupied area A × the conversion rate corresponding to the unstable unoccupied area A = 14,600 graphic element points +800 primitive points × 0.5 = 15,000 primitive points.

Step S2: Determine the predicted remaining number of people the carriage can carry based on the remaining carrying space.

In one embodiment, determining the predicted remaining number of people that the compartment can carry based on the remaining carrying space includes: making the predicted remaining number of people that can be carried be proportional to the remaining carrying space. Specifically, in step S1, the area S of the remaining bearing space has been determined (for example, 15,000 graphic element points), and the number of standing people p (for example, 5) per square meter can be determined, and then one square meter is determined. The number of corresponding graphic element points in the internal top-view image is N (for example, 1500). Therefore, the N graphic element points in the internal top-view image can carry p people. Then it is predicted that the remaining number of people that can be carried is Pimage=(S ×p)/N (for example, (15000×5)/1500=50).

In other embodiments, in addition to the above method of using the number of pixel points to represent distance and area, the ratio of the length of the internal top-view image to the actual length of the carriage, the width of the internal top-view image and the The proportion of the actual width of the carriage, thereby obtaining the actual distance corresponding to any distance in the internal top-view image and the actual area corresponding to any area in the internal top-view image in proportion.

Step S3: Based on the number of passengers in the carriage, the predicted remaining number of people that can be carried, and the maximum number of people in the carriage, determine the recommended remaining number of people in the carriage.

In one embodiment, the predicted remaining number of people that can be accommodated obtained in step S2 is a value estimated based on the internal overhead image. Since the internal overhead image is processed multiple times in step S1, the predicted remaining number of people that can be accommodated is There are errors and cannot be used as the final recommended remaining capacity. Therefore, step S3 needs to be used to further process the predicted remaining number of people to be accommodated to obtain the final recommended remaining number of people to be accommodated. For example, the final recommended remaining capacity can be obtained through the default proportion. The default proportion can be 50%. Please refer to the example below.

In one embodiment, determining the recommended remaining number of people in the carriage based on the number of passengers in the carriage, the predicted remaining number of people who can carry it, and the maximum number of people in the carriage includes: making the recommended remaining number of people Number of people carrying the vehicle = (maximum number of people carrying the carriage - the number of people carrying the vehicle The number of passengers in the carriage + the predicted remaining number of passengers)/2.

In one embodiment, the method further includes: detecting the number of passengers getting on and off the carriage at each station, and determining the number of passengers in the carriage based on the number of passengers getting on and the number of getting off. .

In one embodiment, each carriage is also equipped with an object movement sensor or a human body sensor for detecting human body. Specifically, the human body sensor may include an infrared sensor, and the infrared sensor may be installed at the door position of the carriage (for example, the surrounding frame of the door) for detecting the movement of the carriage at each station. The number of passengers getting on the bus and the number of passengers getting off the bus are measured, and the number of passengers in the carriage is determined based on the number of passengers getting on the bus and the number of people getting off the bus. Specifically, starting from the originating station of the vehicle, the number of passengers getting on and off the carriage at each station is detected, and at each subsequent station the number of passengers getting on and off is accumulated and subtracted. , get the number of passengers in the carriage (for example, 40).

In one embodiment, the maximum capacity of the carriage is known data and is provided by the manufacturer of the carriage. For example, the maximum capacity of the carriage is 101.

In one embodiment, the maximum capacity of the carriage minus the number of passengers in the carriage is the ideal remaining capacity of the carriage. However, referring to the step of updating the occupied area in step S1, due to various reasons, The carriage cannot continue to accommodate the ideal remaining number of passengers. In other embodiments, in addition to the above method of setting the recommended remaining number of people to be accommodated as the average of the predicted remaining number of people and the ideal remaining number of people, the recommended remaining number of people can also be directly set to the average of the predicted remaining number of people and the ideal remaining number. A certain value in the middle of the remaining number of passengers, which can not only enable the carriage to carry as many people as possible, but also ensure that the carriage will not be overloaded.

In one embodiment, the calculated number of recommended remaining bearers may not be an integer, and in this case, rounding may be performed to obtain an integer value. For example, the recommended remaining number of passengers = (the maximum number of passengers in the carriage - the number of passengers in the carriage + the predicted remaining number of passengers) / 2 = (101-40 + 50) / 2 = 55.5, for 55.5 Rounding down, the recommended remaining number of passengers is 55. exist In other embodiments, rounding up may also be performed, so that the recommended remaining number of bearers is 56.

Step S4: Determine the congestion level of the carriage based on the recommended remaining number of people it can carry and the maximum number of people it can carry.

In one embodiment, determining the congestion level of the carriage based on the recommended remaining number of people and the maximum number of people includes: setting the congestion level = 1 - the recommended remaining number of people/ The maximum number of people that can be accommodated. In one embodiment, the congestion level indicates the degree of crowding of passengers in the carriage. The higher the congestion level, the more passengers there are in the carriage and the fewer new passengers it can accommodate, and the less recommended it is for new passengers to take the carriage. For example, the crowding level=55/110=0.5.

In one embodiment, the method further includes: displaying the recommended remaining capacity of the carriage to waiting passengers; and using indicator lights of different colors to display the recommended remaining capacity of the carriage to the waiting passengers according to the numerical range to which the congestion level belongs. The corresponding numerical range represents the degree of crowding.

In one embodiment, the recommended remaining capacity of each carriage and the congestion level are sent to a terminal platform associated with the vehicle through the network, such as an application software or applet in a mobile phone, Display devices installed within the site, etc. Therefore, the recommended remaining number of people and the congestion level of the carriage can be displayed to the waiting passengers before the vehicle arrives at the station, so that the passengers can know the carrying status of each carriage and choose a carriage with a higher congestion level. Wait in line for the lower carriages to avoid failed rides.

In one embodiment, each carriage may also be equipped with a display device, such as a monitor, for displaying the interior top-down image. Specifically, the display device can be installed outside the door of the carriage, so that waiting passengers can determine the location of the target blank area of the carriage based on the internal top-view image. In addition, the display device may further include an indicator light, using indicator lights of different colors to display the congestion degree represented by a corresponding numerical range to the waiting passengers. For example, when the numerical range of the congestion level is 0.7 to 0.9, a red indicator light is used for indication; when the congestion level is a numerical range of 0.1 to 0.2, a green indicator light is used for indication.

In one embodiment, the method for determining the congestion level of a carriage provided by this application determines the remaining carrying space of the carriage based on the internal top-view image of the carriage. The number of passengers already carried and the maximum capacity of the carriage determine the recommended number of remaining passengers and the congestion level of the carriage. It can determine the congestion level of each carriage of the vehicle and recommend less crowded carriages to passengers to save money. Passenger waiting time.

The above-mentioned Figure 1 introduces in detail the method for determining the congestion level of the carriage of the present application. The following is a description of the functional modules of the software system that implements the method for determining the congestion level of the carriage and the architecture of the hardware device that implements the method for determining the congestion level of the carriage. Make an introduction. It should be understood that the above embodiments are for illustration only, and the scope of the patent application is not limited by this structure.

Refer to FIG. 9 , which is a schematic structural diagram of an electronic device according to a preferred embodiment of the present application.

In the preferred embodiment of the present application, the electronic device 3 includes a storage 31 and at least one processor 32 . Those skilled in the art should understand that the structure of the electronic device shown in Figure 9 does not constitute a limitation of the embodiment of the present application. It can be a bus-type structure or a star-shaped structure. The electronic device 3 can also include a The illustrations illustrate more or less additional hardware or software, or different arrangements of components.

In some embodiments, the electronic device 3 includes a terminal that can automatically perform numerical calculations and/or information processing according to preset or stored instructions. Its hardware includes but is not limited to microprocessors, special integrated circuits, Programmable logic gate arrays, digital signal processors and embedded devices, etc.

It should be noted that the electronic device 3 is only an example. If other existing or possible electronic products that may appear in the future can be adapted to this application, they should also be included in the protection scope of this application and be included here by reference.

In some embodiments, the storage 31 is used to store program codes and various data. For example, the memory 31 can be used to store the car congestion level determination system 30 installed in the electronic device 3, and realize high-speed and automatic access to programs or data during the operation of the electronic device 3. The storage 31 includes a read-only memory (Read-Only Memory, ROM), a programmable read-only memory (PROM), a programmable read-only memory (PROM), and a programmable read-only memory (PROM). Erasable Programmable Read-Only Memory (EPROM), One-time Programmable Read-Only Memory (OTPROM), Electronically Erasable Read-Only Memory Electronically-Erasable Programmable Read-Only Memory (EEPROM), Compact Disc Read-Only Memory (CD-ROM) or other optical disk storage, magnetic disk storage, tape storage, or any other storage device that can be used A computer-readable storage medium that carries or stores data.

In some embodiments, the at least one processor 32 may be composed of an integrated circuit, for example, it may be composed of a single packaged integrated circuit, or it may be composed of multiple integrated circuits packaged with the same function or different functions. , including one or more central processing units (CPUs), microprocessors, digital signal processing chips, graphics processors and a combination of various control chips. The at least one processor 32 is the control core (Control Unit) of the electronic device 3 and uses various interfaces and lines to connect various components of the entire electronic device 3 by running or executing programs stored in the storage 31 or module, and calls the data stored in the storage 31 to perform various functions of the electronic device 3 and process data, such as performing the function of determining the congestion level of the carriage shown in Figure 1 .

In some embodiments, the carriage congestion level determination system 30 runs in the electronic device 3 . The carriage congestion level determination system 30 may include a plurality of functional modules composed of program code segments. The program codes of each program segment in the carriage congestion level determination system 30 can be stored in the memory 31 of the electronic device 3 and executed by at least one processor 32 to implement the carriage congestion level determination shown in Figure 1 Function.

In this embodiment, the carriage congestion level determination system 30 can be divided into multiple functional modules according to the functions it performs. The module referred to in this application refers to a series of computer program segments that can be executed by at least one processor and can complete fixed functions, which are stored in the memory.

Although not shown, the electronic device 3 may also include a power supply (such as a battery) that supplies power to various components. Preferably, the power supply may be connected to the at least one processor through a power management device. The device 32 is logically connected to realize management of charging, discharging, power consumption management and other functions through the power management device. The power supply may also include one or more DC or AC power supplies, recharging devices, power failure test circuits, power converters or inverters, power status indicators and other arbitrary components. The electronic device 3 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described again here.

It should be understood that the above embodiments are for illustration only, and the scope of the patent application is not limited by this structure.

The above-mentioned integrated unit implemented in the form of a software function module can be stored in a computer-readable storage medium. The above-mentioned software function module is stored in a storage medium and includes a number of instructions to cause an electronic device (which can be a server, a personal computer, etc.) or a processor to execute part of the method described in each embodiment of the present application.

Program codes are stored in the memory 31 , and the at least one processor 32 can call the program codes stored in the memory 31 to perform related functions. The program code stored in the memory 31 can be executed by the at least one processor 32 to implement the functions of each module to achieve the purpose of determining the congestion level of the carriage.

In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of modules is only a logical function division, and there may be other division methods in actual implementation.

The modules described as separate components may or may not be physically separated. The components shown as modules may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple networks. on the unit. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional module in various embodiments of the present application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of It is implemented in the form of hardware plus software function modules.

It is obvious to those skilled in the art that the present application is not limited to the details of the above-described exemplary embodiments, and that the present application can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application. Therefore, the embodiments should be regarded as illustrative and non-restrictive from any point of view, and the scope of the present application is defined by the appended claims rather than the above description, and it is therefore intended that those falling within the claims All changes within the meaning and scope of the equivalent elements are included in this application. Any reference designation in a request shall not be construed as limiting the request to which it refers. Furthermore, it is obvious that the word "including" does not exclude other elements or the singular does not exclude the plural. Multiple units or devices stated in the device request may also be implemented by one unit or device through software or hardware. Words such as first and second are used to indicate names and do not indicate any specific order.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application has been described in detail with reference to the above preferred embodiments, those of ordinary skill in the art will understand that the technical solutions of the present application can be modified. The technical solution may be modified or equivalently substituted without departing from the spirit and scope of the technical solution of the present application.

S1~S4: steps

Claims (8)

A method for determining the degree of congestion in a carriage, applied in electronic equipment, wherein the method includes: performing image recognition on an internal top-view image of the carriage, and determining the remaining carrying space in the carriage based on the result of the image recognition; according to the remaining carrying space The spatial determination of the predicted remaining number of people that can be carried in the carriage includes: making the predicted remaining number of people that can be carried in a proportional relationship with the remaining carrying space; based on the number of passengers in the carriage, the predicted remaining number of people that can be carried and the number of people in the carriage The maximum capacity of the carriage is determined by determining the recommended remaining capacity of the compartment, including: making the recommended remaining capacity = (the maximum capacity of the compartment - the number of passengers in the compartment + the predicted remaining capacity) /2; Determine the congestion level of the carriage based on the recommended remaining number of people and the maximum number of people. The method for determining the congestion level of a carriage as described in claim 1, wherein the step of performing image recognition on an overhead image of the interior of the carriage and determining the remaining carrying space in the carriage based on the result of the image recognition includes: using a preset image The recognition algorithm identifies the area where the target object is located in the internal top view, and treats the area where the target object is located as an occupied area; updates the occupied area according to preset rules to obtain unoccupied areas outside the occupied area. area; dividing the unoccupied area into a stable unoccupied area and an unstable unoccupied area, including: determining the unoccupied area surrounded by the occupied area as the surrounded area, and treating the surrounded area as the unoccupied area. Stable unoccupied area; use the area in the unoccupied area except the unstable unoccupied area as the stable unoccupied area; based on the stable unoccupied area and the unstable unoccupied area The occupied area determines the remaining bearing space. The method for determining the congestion level of a carriage as described in claim 2, wherein updating the occupied area according to preset rules to obtain an unoccupied area outside the occupied area includes: The compartment wall panel is updated as an occupied area; the distance between the compartment wall panel and any other occupied area is determined. If the distance is less than the preset distance threshold, any occupied area corresponding to the distance is The area between the compartment wall and the compartment wall is updated as the occupied area; all areas outside the occupied area are regarded as the unoccupied area. The method for determining the congestion level of a carriage according to claim 2, wherein determining the remaining load-carrying space based on the stable unoccupied area and the unstable unoccupied area includes: determining the unstable unoccupied area. The conversion rate of the unoccupied area into the stable unoccupied area; the remaining carrying space is calculated according to the area of the stable unoccupied area, the area of the unstable unoccupied area and the conversion rate. The method for determining the congestion level of a carriage as described in claim 1, wherein the method further includes: detecting the number of passengers getting on and off the carriage at each station, and based on the number of passengers getting on and the number of passengers getting off the carriage, The number of people disembarking determines the number of passengers in the carriage in question. The method for determining the congestion level of a carriage as described in claim 1, wherein the method further includes: displaying the recommended remaining number of people in the carriage to waiting passengers; using different colors according to the numerical range to which the congestion level belongs. The indicator light displays the congestion degree represented by the corresponding numerical range for the waiting passengers. A computer-readable storage medium, wherein the computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, the determination of the carriage congestion level as described in any one of claims 1 to 6 is achieved. method. An electronic device, wherein the electronic device includes a storage and at least one processor The memory stores at least one instruction, and when the at least one instruction is executed by the at least one processor, the method for determining the congestion level of a carriage according to any one of claims 1 to 6 is implemented.

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