Tunnel adaptive regulation and control method and system based on image analysis and storage medium

Abstract

The invention discloses a tunnel adaptive regulation and control method and system based on image analysis and a storage medium, and relates to the technical field of tunnel traffic monitoring, and the method comprises the steps: obtaining the geometric design information of a target tunnel, and determining the distribution condition of illumination equipment of the target tunnel; according to the method, the three-dimensional corridor model of the tunnel is constructed in advance, the tunnel illumination brightness control condition can be observed subsequently, meanwhile, the monitoring points are arranged in the tunnel to monitor the illumination brightness of different areas in the tunnel in real time, and then the tunnel illumination brightness can be monitored according to the illumination brightness condition monitored in real time. And the illumination brightness of the illumination equipment in the target tunnel and the condition outside the target tunnel are combined autonomously to perform self-adaptive hole adjustment, so that the potential safety hazard that a driver enters and leaves the tunnel is reduced, and the driving safety of the driver is ensured. The defect that the driving safety of a driver is easily affected due to the fact that the brightness difference inside and outside the tunnel is too large in the prior art is effectively overcome.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel traffic monitoring, and in particular to a tunnel adaptive control method, system and storage medium based on image analysis. Background Art

[0002] The lighting in tunnels has many effects on driving and drivers, including safety, comfort and visual adaptability. Therefore, the lighting in tunnels must be bright enough to ensure that drivers can clearly see the road, traffic signs and other vehicles to reduce the occurrence of accidents. Especially when drivers enter and exit tunnels, due to the different brightness inside and outside the tunnel, the focus points are more concentrated at the entrance and exit of the tunnel, and more dispersed in the middle section, which is prone to produce "black hole effect" and "white hole effect". When driving at high speed, drivers will experience temporary "blindness" when entering the tunnel due to changes in light intensity, unable to distinguish the situation near the tunnel entrance, which is very likely to cause danger. Summary of the invention

[0003] The purpose of the present invention is to solve the problem in the prior art that the brightness difference between the inside and outside of the tunnel is too large, which easily affects the driving safety of the driver, and to propose a tunnel adaptive control method, system and storage medium based on image analysis.

[0004] In order to achieve the above object, the present invention adopts the following technical solutions:

[0005] In a first aspect, the present invention provides a tunnel adaptive control method based on image analysis, comprising:

[0006] Obtain geometric design information of the target tunnel and determine the distribution of lighting equipment in the target tunnel;

[0007] According to the geometric design information of the target tunnel and the distribution of the lighting equipment of the target tunnel, a three-dimensional corridor model of the target tunnel is constructed;

[0008] A plurality of monitoring points are set in the target tunnel, and the lighting status images of the target tunnel are collected in real time by using the monitoring points to determine the real-time lighting status information of the target tunnel;

[0009] According to the real-time lighting status information of the target tunnel and the distribution of lighting equipment in the target tunnel, simulation writing is performed on the three-dimensional corridor model of the target tunnel to determine the lighting status corridor model of the target tunnel;

[0010] According to tunnel traffic requirements, set the lighting control warning information of the target tunnel;

[0011] The lighting control warning information of the target tunnel is written into the lighting status corridor model of the target tunnel to determine the control information of the lighting equipment in the target tunnel.

[0012] In some feasible solutions, the adaptive control method further includes:

[0013] Divide the three-dimensional corridor model of the target tunnel into regions, and obtain at least two corridor region models of the target tunnel;

[0014] According to each corridor area model of the target tunnel, the control information of the lighting equipment in the target tunnel is determined respectively.

[0015] In some feasible solutions, the method for determining the real-time lighting status information of the target tunnel includes:

[0016] According to the three-dimensional corridor model of the target tunnel, a reference coordinate system of the target tunnel is constructed;

[0017] In the same time sequence, multiple monitoring points are used to collect real-time lighting status images of the target tunnel respectively;

[0018] According to the reference coordinate system, image analysis is performed on the real-time lighting status image of the target tunnel to determine the distribution information of graphic features in each corridor area model of the target tunnel;

[0019] According to the graphic feature distribution information in each corridor area model of the target tunnel, the real-time lighting status information of the target tunnel is determined.

[0020] In some feasible solutions, the method for determining the distribution information of graphic features in each corridor area model of the target tunnel includes:

[0021] According to the distribution of lighting equipment in the target tunnel and in combination with the real-time lighting status image of the target tunnel, the number of lighting equipment in the same average unit area in each corridor area model of the target tunnel is determined respectively;

[0022] According to the distribution of lighting equipment in the target tunnel and in combination with the number of lighting equipment in the same average unit area in each corridor area model, the lighting radiation profile of the lighting equipment in the same average unit area in each corridor area model is determined;

[0023] According to the lighting radiation profile of the lighting equipment in the same average unit area of ​​each corridor area model and in combination with the reference coordinate system, the lighting area of ​​the lighting equipment in the same average unit area of ​​each corridor area model is determined respectively;

[0024] Determine the lighting illuminance in the same average unit area in each corridor area model according to the lighting area of ​​the lighting equipment in the same average unit area in each corridor area model and the number of lighting equipment in the same average unit area in each corridor area model;

[0025] According to the lighting illuminance in the same average unit area in each corridor area model and the lighting area of ​​the lighting equipment in the same average unit area in each corridor area model, the graphic feature distribution information in each corridor area model of the target tunnel is determined.

[0026] In some feasible solutions, the method for determining the distribution information of graphic features in each corridor area model of the target tunnel further includes:

[0027] Assume that there are n lamp groups in the same average unit area in a corridor area model, and assume that the illumination contour of any lamp group in the real-time illumination status image of the target tunnel intersects with the corridor area model at points A, B, C and D. At this time, the illumination area Si of the lamp group is:

[0028] Si=S ΔADC +S ΔABC ,

[0029] In the formula, S ΔADC is the area of ​​the triangle formed by points A, D, and C; S ΔABC is the area of ​​the triangle formed by points A, B, and C;

[0030] Among them, edge AD intersects at edge BC.

[0031] In some feasible solutions, the method for determining the real-time lighting status information of the target tunnel further includes:

[0032] In the same time series, there is a certain corridor area model with the same average illumination per unit area. for:

[0033]

[0034] In the formula, n is the number of light groups arranged under the same average unit area;

[0035] Φ is the luminous flux of each lamp group;

[0036] S i The irradiation area of ​​each lamp group under the same average unit area;

[0037] It is the utilization coefficient, which is related to the size of the illuminated space and the reflective material of the wall.

[0038] In some feasible solutions, the method for determining the control information of the lighting equipment in the target tunnel includes:

[0039] Assume that the target tunnel consists of two corridor area models a1 and a2, then the lighting equipment control quantity of corridor area model a1 is for:

[0040]

[0041] In the formula, is the illumination at the tunnel entrance in the corridor area model a1; is the average illumination outside the target tunnel; is the target tunnel length in the corridor area model a1; K1 is the illumination attenuation compensation coefficient in the corridor area model a1;

[0042] Similarly, the lighting equipment control quantity of corridor area model a2 is for:

[0043]

[0044] In the formula, is the illumination at the tunnel entrance in the corridor area model a2; is the average illumination outside the target tunnel; L a2 is the target tunnel length in the corridor area model a2; K2 is the illumination attenuation compensation coefficient in the corridor area model a2;

[0045] in,

[0046] In a second aspect, the present invention provides a tunnel adaptive control system based on image analysis, which adopts a tunnel adaptive control method based on image analysis as described in any one of the first aspects; the control system further includes:

[0047] An image acquisition module, which is arranged at the monitoring point and is used to acquire an image of the lighting status of the target tunnel in real time;

[0048] A model building module, wherein the model building module is used to build a three-dimensional corridor model of a target tunnel;

[0049] A region division module, wherein the region division module is used to divide the three-dimensional corridor model of the target tunnel into regions to generate a corridor region model of the target tunnel;

[0050] A control module is used to perform lighting control on the lighting device according to the control information of the lighting device.

[0051] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, an image analysis-based tunnel adaptive control method as described in any one of the first aspects is implemented.

[0052] The beneficial effects of the present invention are:

[0053] The present invention pre-constructs a three-dimensional corridor model of the tunnel to facilitate subsequent observation of the tunnel lighting brightness control situation, and sets monitoring points in the tunnel to monitor the lighting brightness of different areas in the tunnel in real time. Then, according to the real-time monitored lighting brightness situation, the lighting brightness of the lighting equipment in the target tunnel is autonomously adjusted in combination with the situation outside the target tunnel to reduce the safety hazards of drivers entering and exiting the tunnel, thereby ensuring the driving safety of the driver. That is, it effectively solves the disadvantage of the prior art that the large brightness difference between the inside and outside of the tunnel easily affects the driving safety of the driver. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 A schematic diagram of the overall process of a tunnel adaptive control method based on image analysis provided in an embodiment of the present invention;

[0055] Figure 2 A partial flow chart of a tunnel adaptive control method based on image analysis provided in an embodiment of the present invention;

[0056] Figure 3 The figure is a schematic diagram of the illumination contour lines of a light group in a tunnel adaptive control method based on image analysis provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0057] 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.

[0058] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0059] In the present invention, unless otherwise clearly specified and limited, the terms "connection", "fixation", etc. should be understood in a broad sense. For example, "fixation" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0060] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the meaning of "and / or" appearing in the full text includes three parallel schemes. Taking "A and / or B" as an example, it includes scheme A, or scheme B, or a scheme that satisfies both A and B. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of ordinary technicians in the field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0061] Reference Figures 1 to 3 As shown, in order to solve the disadvantage of the prior art that the brightness difference between the inside and outside of the tunnel is too large and easily affects the driving safety of the driver, in this embodiment, the present invention provides a tunnel adaptive control method based on image analysis in the first aspect, the adaptive control method pre-constructs a three-dimensional corridor model of the tunnel to facilitate the subsequent observation of the tunnel lighting brightness control situation, and at the same time sets monitoring points in the tunnel to monitor the lighting brightness of different areas in the tunnel in real time, and then according to the real-time monitored lighting brightness situation, autonomously adjusts the lighting brightness of the lighting equipment in the target tunnel in combination with the situation outside the target tunnel to reduce the safety hazards of the driver entering and exiting the tunnel, and ensures the driving safety of the driver. That is, it effectively solves the disadvantage of the prior art that the brightness difference between the inside and outside of the tunnel is too large and easily affects the driving safety of the driver.

[0062] Specifically, a tunnel adaptive control method based on image analysis includes: obtaining geometric design information of the target tunnel and determining the distribution of lighting equipment in the target tunnel; constructing a three-dimensional corridor model of the target tunnel according to the geometric design information of the target tunnel and the distribution of lighting equipment in the target tunnel; that is, determining the three-dimensional corridor model of the target tunnel according to the design of the target tunnel and the layout of lighting equipment in the target tunnel, so as to achieve a clear and intuitive observation of the subsequent lighting control in the target tunnel. Set multiple monitoring points in the target tunnel, use the monitoring points to collect the lighting status image of the target tunnel in real time, and determine the real-time lighting status information of the target tunnel; that is, use different monitoring points to monitor and obtain the lighting conditions in different areas of the target tunnel in real time through wired or wireless methods, and then write the lighting conditions obtained in real time into the three-dimensional corridor model of the target tunnel according to the lighting conditions combined with the distribution of lighting equipment in the target tunnel, so as to determine the lighting status corridor model of the target tunnel, and provide an effective reference basis for the subsequent determination of the lighting conditions of the target tunnel. Then, according to the tunnel traffic requirements, the lighting control warning information of the target tunnel is set; and then the lighting control warning information of the target tunnel is written into the lighting status corridor model of the target tunnel, and then the control information of the lighting equipment in the target tunnel can be determined. That is, in this embodiment, the adaptive control method pre-constructs a three-dimensional corridor model of the tunnel to facilitate the subsequent observation of the tunnel lighting brightness control situation, and at the same time sets monitoring points in the tunnel to monitor the lighting brightness of different areas in the tunnel in real time, and then according to the real-time monitored lighting brightness situation, the lighting brightness of the lighting equipment in the target tunnel is autonomously combined with the situation outside the target tunnel for adaptive adjustment, so as to reduce the safety hazards of drivers entering and exiting the tunnel and ensure the driving safety of the driver. That is, it effectively solves the shortcomings of the prior art that the brightness difference between the inside and outside of the tunnel is too large and easily affects the driving safety of the driver. In a preferred solution, in order to reduce the overall difficulty of tunnel control, the adaptive control method also includes: the three-dimensional corridor model of the target tunnel can be divided into regions, and at least two corridor area models of the target tunnel are obtained; and then according to each corridor area model of the target tunnel, the control information of the lighting equipment in the target tunnel is determined respectively.That is, by dividing the three-dimensional corridor model of the target tunnel into regions, the target tunnel is divided into at least two different corridor area models for brightness lighting control, which can reduce the difficulty of brightness adjustment in long-distance tunnels. At the same time, after adjusting the lighting brightness of one corridor area model, the lighting brightness in other corridor area models can be adjusted according to the lighting brightness of the adjusted corridor area model, avoiding local over-brightness or over-darkness in the target tunnel, and reducing the interference of external brightness changes on the lighting brightness control in the tunnel. Especially in the case of inconsistent brightness at the entrances and exits at both ends of a long-distance tunnel, this adaptive control method can combine the control situation at one end of the target tunnel to control the lighting brightness at the other end, and can also coordinate the control at both ends to meet the tunnel lighting requirements under different circumstances.

[0063] In this embodiment, in order to facilitate understanding of how to determine the real-time lighting status information in the target tunnel, the corridor area model is used as an example. Specifically, the method for determining the real-time lighting status information of the target tunnel includes: constructing a reference coordinate system of the target tunnel according to the three-dimensional corridor model of the target tunnel; then using multiple monitoring points to collect the real-time lighting status image of the target tunnel respectively at the same time sequence; that is, using multiple monitoring points to collect the lighting brightness conditions in different areas of the target tunnel in real time at the same time. Then, according to the reference coordinate system, the real-time lighting status image of the target tunnel can be analyzed to determine the distribution information of the graphic features in each corridor area model of the target tunnel (such as the illumination angle, the illumination area, and the number of illuminated lamp groups, etc.); then, according to the distribution information of the graphic features in each corridor area model of the target tunnel, the real-time lighting status information of the target tunnel is determined. To facilitate understanding of the above content, an example is given here of how to obtain and determine the distribution information of graphic features in each corridor area model of the target tunnel. Specifically, the method for determining the distribution information of graphic features in each corridor area model of the target tunnel includes: according to the distribution of lighting equipment in the target tunnel, and then in combination with the real-time lighting status image of the target tunnel, the number of lighting equipment in the same average unit area in each corridor area model of the target tunnel (that is, the same size unit area in each corridor area model is determined respectively); that is, according to the situation of monitoring point acquisition, the number of lighting lamp groups in the image is determined, and then according to the distribution of lighting equipment in the target tunnel, and in combination with the number of lighting equipment in the same average unit area in each corridor area model, the lighting radiation profile of the lighting equipment in the same average unit area of ​​each corridor area model is determined; that is, the lighting range of each lamp group is determined according to the real-time lighting status image of the target tunnel. Then, according to the lighting radiation profile of the lighting equipment in the same average unit area of ​​each corridor area model, and in combination with the reference coordinate system, the lighting area of ​​the lighting equipment in the same average unit area of ​​each corridor area model can be determined respectively; so as to achieve the ability to determine the lighting illuminance in the same average unit area of ​​each corridor area model according to the lighting area of ​​the lighting equipment in the same average unit area of ​​each corridor area model and the number of lighting equipment in the same average unit area of ​​each corridor area model. At this time, the graphic feature distribution information in each corridor area model of the target tunnel can be determined according to the lighting illuminance in the same average unit area of ​​each corridor area model and the lighting area of ​​the lighting equipment in the same average unit area of ​​each corridor area model.

[0064] Reference Figure 2 and Figure 3More specifically, how to obtain and determine the distribution information of graphic features in a corridor area model is described as follows. Specifically, the method for determining the distribution information of graphic features in each corridor area model of the target tunnel also includes:

[0065] Assume that there are n lamp groups in the same average unit area in a corridor area model, and assume that the illumination contour of any lamp group in the real-time illumination status image of the target tunnel intersects with the corridor area model at points A, B, C and D. At this time, the illumination area Si of the lamp group is:

[0066] Si=S ΔADC +S ΔABC Formula 1;

[0067] In formula 1, S ΔADC is the area of ​​the triangle formed by points A, D, and C; S ΔABC It is the area of ​​the triangle formed by point A, point B, and point C; wherein, side AD intersects at side BC, that is, side AD is the contour line illuminated by one side of the light group, and side BC is the contour line illuminated by the other side of the light group.

[0068] In the above, the S ΔADC and S ΔABC The coordinates of points A, B, C, and D can be determined by combining the reference coordinate system, and then S can be calculated based on the coordinates of the three points of the triangle. ΔADC and S ΔABC area.

[0069] In addition, it should be noted that, in the present embodiment, the illumination area of ​​each lamp group can be determined based on the illumination contour lines on both sides of the lamp group. The intersection points formed by the illumination contour lines on both sides of the lamp group and the target tunnel can be used to determine and divide the lamps into multiple triangles, and then the illumination area of ​​each lamp group can be determined based on the area and number of the triangles.

[0070] In summary, the method for determining the real-time lighting status information of the target tunnel includes:

[0071] Combined with formula 1, under the same time sequence, there is a certain corridor area model with the same average illumination per unit area for:

[0072]

[0073] In formula 2, n is the number of light groups arranged under the same average unit area;

[0074] Φ is the luminous flux of each lamp group;

[0075] S i The irradiation area of ​​each lamp group under the same average unit area;

[0076] It is the utilization coefficient, which is related to the size of the illuminated space and the reflective material of the wall.

[0077] Combining Formula 1 and Formula 2, the method for determining the control information of the lighting equipment in the target tunnel includes:

[0078] Assume that the target tunnel consists of two corridor area models a1 and a2, then the lighting equipment control quantity of corridor area model a1 is for:

[0079]

[0080] In formula 3, is the illumination at the tunnel entrance in the corridor area model a1; is the average illumination outside the target tunnel; is the target tunnel length in the corridor area model a1; K1 is the illumination attenuation compensation coefficient in the corridor area model a1;

[0081] Similarly, the lighting equipment control quantity of corridor area model a2 is for:

[0082]

[0083] In formula 4, is the illumination at the tunnel entrance in the corridor area model a2; is the average illumination outside the target tunnel; L a2 is the target tunnel length in the corridor area model a2; K2 is the illumination attenuation compensation coefficient in the corridor area model a2;

[0084] That is, in Equations 3 and 4, by comparing the brightness inside and outside the target tunnel and the different lengths of the target tunnel, the lighting brightness in the middle of the tunnel can be adjusted in combination with the lighting illumination at the tunnel entrance to ensure that the lighting brightness inside and outside the tunnel meets the tunnel driving requirements and reduce the occurrence of local over-brightness or over-darkness in the target tunnel.

[0085] Among them, since the brightness outside the target tunnel is basically the same, in order to ensure the accurate effect of the control amount, you can set This is to reduce the occurrence of local over-brightness or over-darkness in the target tunnel area.

[0086] In the second aspect, the present invention provides a tunnel adaptive control system based on image analysis, which adopts a tunnel adaptive control method based on image analysis described in any one of the first aspects; the control system also includes: an image acquisition module, a model construction module, a region division module and a control module, the image acquisition module is set at the monitoring point, and the image acquisition module is used to collect the lighting status image of the target tunnel in real time; the image acquisition module can be an imaging acquisition device such as an industrial camera, or a light source detection device. The model construction module is used to construct a three-dimensional corridor model of the target tunnel; the region division module is used to divide the three-dimensional corridor model of the target tunnel into regions to generate a corridor region model of the target tunnel; the control module is used to control the lighting of the lighting equipment according to the control information of the lighting equipment. That is, in this embodiment, the adaptive control system adopts the adaptive control method described above, and the adaptive control system realizes the autonomous adaptive adjustment of the lighting brightness of the lighting equipment in the target tunnel in combination with the situation outside the target tunnel, so as to reduce the safety hazards of the driver entering and exiting the tunnel, and ensure the driving safety of the driver. That is, it effectively solves the shortcomings of the prior art that the brightness difference between the inside and outside of the tunnel is too large and easily affects the driving safety of the driver.

[0087] In some embodiments, the adaptive control system can communicate using any currently known or future developed network protocol such as HTTP (Hyper Text Transfer Protocol), and can be interconnected with any form or medium of digital data communication (e.g., communication network). Examples of communication networks include local area networks ("LAN"), wide area networks ("WAN"), internets (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.

[0088] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chip (SOCs), complex programmable logic devices (CPLDs), etc.

[0089] The third aspect of the present invention provides a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, a method for adaptively controlling a tunnel based on image analysis as described in any one of the first aspects is implemented. The computer-readable medium in this embodiment can be written in one or more programming languages ​​or a combination thereof to write computer program codes for performing the operations of some embodiments of the present disclosure, wherein the programming languages ​​include object-oriented programming languages, such as Java, Small tale, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., using an Internet service provider to connect through the Internet).

[0090] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0091] In particular, according to some embodiments of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, some embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer readable medium, and the computer program includes a program code for executing the method shown in the flowchart.

[0092] The fourth aspect of the present invention provides an electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon; when the one or more programs are executed by the one or more processors, the one or more processors implement a tunnel adaptive control method based on image analysis as described in the first aspect. The above-mentioned computer-readable medium may be included in the above-mentioned electronic device; or it may exist separately, that is, it is not assembled into the electronic device. The above-mentioned computer-readable medium carries one or more programs, and when the above-mentioned one or more programs are executed by the electronic device, the electronic device can implement a tunnel adaptive control method based on image analysis as described in the first aspect.

[0093] A fifth aspect of the present invention provides a computer program product, comprising a computer program, which, when executed by a processor, implements a tunnel adaptive control method based on image analysis as described in the first aspect.

[0094] The above descriptions are only some preferred embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalent features without departing from the above-mentioned inventive concept. For example, the above-mentioned features are replaced with the technical features with similar functions disclosed in the embodiments of the present disclosure (but not limited to) and the technical solutions formed.

Claims

1. A tunnel adaptive control method based on image analysis, characterized in that: include: Obtain geometric design information of the target tunnel and determine the distribution of lighting equipment in the target tunnel; According to the geometric design information of the target tunnel and the distribution of the lighting equipment of the target tunnel, a three-dimensional corridor model of the target tunnel is constructed; A plurality of monitoring points are set in the target tunnel, and the lighting status images of the target tunnel are collected in real time by using the monitoring points to determine the real-time lighting status information of the target tunnel; According to the real-time lighting status information of the target tunnel and the distribution of lighting equipment in the target tunnel, simulation writing is performed on the three-dimensional corridor model of the target tunnel to determine the lighting status corridor model of the target tunnel; According to tunnel traffic requirements, set the lighting control warning information of the target tunnel; The lighting control warning information of the target tunnel is written into the lighting status corridor model of the target tunnel to determine the control information of the lighting equipment in the target tunnel.

2. The tunnel adaptive control method based on image analysis according to claim 1 is characterized in that: The adaptive control method also includes: Divide the three-dimensional corridor model of the target tunnel into regions, and obtain at least two corridor region models of the target tunnel; According to each corridor area model of the target tunnel, the control information of the lighting equipment in the target tunnel is determined respectively.

3. The tunnel adaptive control method based on image analysis according to claim 2 is characterized in that: The method for determining the real-time lighting status information of the target tunnel comprises: According to the three-dimensional corridor model of the target tunnel, a reference coordinate system of the target tunnel is constructed; In the same time sequence, multiple monitoring points are used to collect real-time lighting status images of the target tunnel respectively; According to the reference coordinate system, image analysis is performed on the real-time lighting status image of the target tunnel to determine the distribution information of graphic features in each corridor area model of the target tunnel; According to the graphic feature distribution information in each corridor area model of the target tunnel, the real-time lighting status information of the target tunnel is determined.

4. The tunnel adaptive control method based on image analysis according to claim 3 is characterized in that: The method for determining the distribution information of graphic features in each corridor area model of the target tunnel comprises: According to the distribution of lighting equipment in the target tunnel and in combination with the real-time lighting status image of the target tunnel, the number of lighting equipment in the same average unit area in each corridor area model of the target tunnel is determined respectively; According to the distribution of lighting equipment in the target tunnel and in combination with the number of lighting equipment in the same average unit area in each corridor area model, the lighting radiation profile of the lighting equipment in the same average unit area in each corridor area model is determined; According to the lighting radiation profile of the lighting equipment in the same average unit area of ​​each corridor area model and in combination with the reference coordinate system, the lighting area of ​​the lighting equipment in the same average unit area of ​​each corridor area model is determined respectively; Determine the lighting illuminance in the same average unit area in each corridor area model according to the lighting area of ​​the lighting equipment in the same average unit area in each corridor area model and the number of lighting equipment in the same average unit area in each corridor area model; According to the lighting illuminance in the same average unit area in each corridor area model and the lighting area of ​​the lighting equipment in the same average unit area in each corridor area model, the graphic feature distribution information in each corridor area model of the target tunnel is determined.

5. The tunnel adaptive control method based on image analysis according to claim 4 is characterized in that: The method for determining the distribution information of graphic features in each corridor area model of the target tunnel also includes: Assume that there are n lamp groups in the same average unit area in a corridor area model, and assume that the illumination contour of any lamp group in the real-time illumination status image of the target tunnel intersects with the corridor area model at points A, B, C and D. At this time, the illumination area Si of the lamp group is: Si=S ΔADC +S ΔABC ; In the formula, S ΔADC is the area of ​​the triangle formed by points A, D, and C; S ΔABC is the area of ​​the triangle formed by points A, B, and C; Among them, edge AD intersects at edge BC.

6. The tunnel adaptive control method based on image analysis according to claim 5 is characterized in that: The method for determining the real-time lighting status information of the target tunnel also includes: In the same time series, there is a certain corridor area model with the same average illumination per unit area. for: In the formula, n is the number of light groups arranged under the same average unit area; Φ is the luminous flux of each lamp group; S i The irradiation area of ​​each lamp group under the same average unit area; It is the utilization coefficient, which is related to the size of the illuminated space and the reflective material of the wall.

7. The tunnel adaptive control method based on image analysis according to claim 6 is characterized in that: The method for determining the control information of the lighting equipment in the target tunnel includes: Assume that the target tunnel consists of two corridor area models a1 and a2, then the lighting equipment control quantity of corridor area model a1 is for: In the formula, is the illumination at the tunnel entrance in the corridor area model a1; is the average illumination outside the target tunnel; is the target tunnel length in the corridor area model a1; K1 is the illumination attenuation compensation coefficient in the corridor area model a1; Similarly, the lighting equipment control quantity of corridor area model a2 is for: In the formula, is the illumination at the tunnel entrance in the corridor area model a2; is the average illumination outside the target tunnel; L a2 is the target tunnel length in the corridor area model a2; K2 is the illumination attenuation compensation coefficient in the corridor area model a2; in, 8. A tunnel adaptive control system based on image analysis, characterized in that: A tunnel adaptive control method based on image analysis according to any one of claims 1 to 7 is adopted; the control system further comprises: An image acquisition module, which is arranged at the monitoring point and is used to acquire an image of the lighting status of the target tunnel in real time; A model building module, wherein the model building module is used to build a three-dimensional corridor model of a target tunnel; A region division module, wherein the region division module is used to divide the three-dimensional corridor model of the target tunnel into regions to generate a corridor region model of the target tunnel; A control module is used to perform lighting control on the lighting device according to the control information of the lighting device.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: in, When the program is executed by a processor, an image analysis-based tunnel adaptive control method according to any one of claims 1 to 7 is implemented.

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