Method for measuring and calculating layout position of vehicle detection equipment for tunnel intelligent dimming control system

Abstract

The invention discloses a method for measuring and calculating the layout position of vehicle detection equipment for a tunnel intelligent dimming control system. The method comprises the following steps: acquiring the driving speed of a vehicle approaching and driving into a tunnel from the upstream of the tunnel; determining a first critical safe view distance which is not influenced by the dark environment of the tunnel portal within the view range of the vehicle driver; obtaining response time of the intelligent dimming control system; determining a response distance according to the driving speed and the response time; and determining the layout distance from the vehicle detection equipment to the tunnel portal according to the first critical safe view distance and the response distance. The invention provides a scheme for determining the layout position of the vehicle detection equipment, and the scheme can guide the layout of the vehicle detection equipment to assist the intelligent dimming control of the tunnel, thereby guaranteeing the driving safety and comfort of a driver, avoiding the energy waste, and effectively balancing the energy-saving demand and the safety demand.

Description

Technical Field

[0001] This invention relates to the field of highway tunnel lighting technology, and in particular to a method for calculating the deployment location of vehicle detection equipment for a tunnel intelligent dimming control system. Background Technology

[0002] Currently, in order to achieve energy conservation in tunnel lighting, more and more tunnels are using intelligent dimming control systems. These systems integrate brightness detection equipment, vehicle detection equipment, lighting fixtures with dimming functions, and corresponding control algorithms, and adopt on-demand lighting strategies for tunnel lighting control.

[0003] However, while current technologies have conducted research on the functional requirements and system construction of intelligent dimming control systems, there is a lack of research on the deployment schemes of vehicle detection equipment within these systems. Therefore, there is still room for improvement in this field.

[0004] Currently, existing technologies mainly focus on the research of intelligent dimming control systems or lighting control methods. Chinese patent CN116056275A discloses an intelligent dimming system for undersea tunnels based on 5G transmission, including a monitoring platform, a 5G base station, a 5G signal receiver, a single-lamp controller, and a dimming control box. The 5G signal receiver is installed inside the lighting fixtures and the dimming control box, and the single-lamp controller is installed inside the lighting fixtures. Based on the commands from the dimming control box, the system achieves stepless dimming of the lighting fixtures from 0% to 100%. The dimming control box is connected to the monitoring platform via a 5G signal. The dimming control box contains a controller that collects signals from each terminal device inside the undersea tunnel and uploads the collected signals to the monitoring platform. Chinese patent CN104470139A discloses a closed-loop feedback control method for tunnel lighting, comprising the following steps: S1: collecting brightness information, traffic flow information, vehicle speed information, and vehicle presence information inside and outside the tunnel; S2: calculating the required set brightness values ​​for each road section inside the tunnel based on the data collected in S1 and the highway tunnel lighting design details; S3: acquiring images of the road surface inside the tunnel using a camera, and calculating the actual illuminance values ​​at each point inside the tunnel and the illuminance distribution of the entire road surface based on the image grayscale; S4: performing PID closed-loop feedback adjustment based on the set brightness values ​​and actual illuminance values, determining whether the actual output brightness of the current tunnel lights meets the requirements, and if not, calculating a new brightness value, and converting the output brightness value after PID closed-loop feedback adjustment into brightness control level information for the tunnel lights; S5: using a dimming controller to convert the brightness control level command signal of the lights into a corresponding pulse signal, and adjusting the output brightness value of the tunnel lights through PWM dimming.

[0005] The background description is provided for the purpose of understanding the relevant technologies in this field and is not intended as an admission of prior art. Summary of the Invention

[0006] Therefore, embodiments of the present invention aim to provide a solution that can at least partially solve the problems described above.

[0007] In a first aspect, embodiments of the present invention provide a method for calculating the deployment location of vehicle detection equipment for a tunnel intelligent dimming control system, which may include:

[0008] S110: Obtain the vehicle's speed as it approaches and enters the tunnel from the upstream;

[0009] S120: Determine the first critical safe field of vision distance within the driver's field of vision during driving, unaffected by the dark environment at the tunnel entrance;

[0010] S130: Obtain the response time of the intelligent dimming control system from detecting vehicle information to completing the preset lighting brightness adjustment;

[0011] S140: Determine the response distance traveled by the vehicle within the response time based on the driving speed and the response time; and

[0012] S150: Determine the deployment distance of the vehicle detection equipment from the tunnel entrance based on the first critical safety field of view distance and the response distance.

[0013] In some embodiments, step S120 includes:

[0014] S121: Real-time collection of driving speed at least within the range affected by changes in tunnel brightness;

[0015] S122: Analyze the characteristics of the speed change to determine the first critical position where the speed first decreases; and

[0016] S123: The distance between the first critical position and the tunnel entrance is determined as the first critical safe field of vision distance.

[0017] In some embodiments, step S121 includes: S1211: collecting the driving speed for each of the multiple drivers;

[0018] Step S122 includes:

[0019] S1221: Determine the average driving speed at multiple different acquisition locations, wherein at least some of the acquisition locations are located within the range affected by tunnel brightness changes;

[0020] S1222: Construct a relationship curve between position and driving speed based on the average of the multiple different collection locations and the driving speed;

[0021] S1223: Identify the first critical position where the driving speed first decreases in the relationship curve, wherein the first critical position corresponds to the first critical safe field of vision distance.

[0022] In some embodiments, step S121 includes: S1211: collecting the driving speed for each of the multiple drivers;

[0023] Step S122 includes:

[0024] S1221: Determine the average driving speed at multiple different acquisition locations, wherein at least some of the acquisition locations are located within the range affected by tunnel brightness changes;

[0025] S1222: Construct a relationship curve between position and driving speed based on the average of the multiple different collection locations and the driving speed;

[0026] S1224: Identify the two locations in the relationship curve where the driving speed decreases most significantly;

[0027] S1225: The location farther from the tunnel entrance is determined as the first critical position, and the other is determined as the second critical position. The first critical position corresponds to the first critical safe field of vision distance, and the second critical position corresponds to the second critical safe field of vision distance within the driver's field of vision that is not affected by the sudden change in the brightness of the tunnel entrance lighting.

[0028] In some embodiments, step S120 includes:

[0029] S120': Based on the driving speed, the first critical safe field of vision distance is determined by the relationship model between the first critical safe field of vision distance and the driving speed, wherein the relationship model between the first critical safe field of vision distance and the driving speed characterizes the relationship between the first critical safe field of vision distance and the driving speed at different driving speeds.

[0030] In some embodiments, the relationship between the first critical safe field of vision distance and the driving speed is represented by the following equation:

[0031] L s =av+b

[0032] Among them, L s Let v be the first critical safe field of vision distance, v be the driving speed, and a and b be constants.

[0033] In some embodiments, step S120' includes:

[0034] S121': Collect test driving speeds and corresponding first critical safe field of view distances for multiple different test tunnels; and

[0035] S122': Based on the test driving speeds and corresponding test first critical safe field of vision distances collected from multiple test tunnels, a model of the relationship between the first critical safe field of vision distance and driving speed is constructed through regression analysis;

[0036] S123': The first critical safe field of vision distance is obtained by solving the relational model using the driving speed.

[0037] In some embodiments, step S121' includes: for each of a plurality of initial velocities in each test tunnel,

[0038] S1211': Real-time acquisition of test driving speed at least within the range affected by tunnel brightness changes;

[0039] S1212': Analyze the characteristics of the test driving speed change to determine the first critical position where the test driving speed first decreases; and

[0040] S1213': The distance between the first critical position of the test and the entrance of the test tunnel is determined as the first critical safe field of vision distance of the test.

[0041] In some embodiments, step S1211' includes: collecting test driving speeds for multiple drivers respectively;

[0042] The step S1212' includes:

[0043] S12121': Determine the average test driving speed at multiple different sampling locations, wherein at least some of the sampling locations are located within the range affected by tunnel brightness changes;

[0044] S12122': Based on the average of the multiple different data acquisition locations and the test driving speed, construct a relationship curve between location and test driving speed; and

[0045] S12123': Identify the first critical position in the relationship curve where the test driving speed first decreases, wherein the first critical position corresponds to the first critical safe field of vision distance.

[0046] In some embodiments, step S1211' includes: collecting test driving speeds for multiple drivers respectively;

[0047] The step S1212' includes:

[0048] S12121': Determine the average test driving speed at multiple different sampling locations, wherein at least some of the sampling locations are located within the range affected by tunnel brightness changes;

[0049] S12122': Based on the average of the multiple different data collection locations and the test driving speed, construct a curve showing the relationship between location and test driving speed;

[0050] S12124': Identify the two positions in the relationship curve where the test driving speed decreases most significantly;

[0051] S12125': The location farther from the tunnel entrance is determined as the first critical position for the test, and the other is determined as the second critical position for the test. The first critical position for the test corresponds to the first critical safe field of vision distance, and the second critical position for the test corresponds to the second critical safe field of vision distance within the driver's field of vision that is not affected by the sudden change in the brightness of the tunnel entrance lighting.

[0052] This invention provides a method for calculating the deployment location of vehicle detection equipment in a tunnel intelligent dimming control system. By acquiring the vehicle's speed as it approaches and enters the tunnel from the upstream, the method determines the first critical safe field of vision distance within the driver's field of vision, unaffected by the dark environment at the tunnel entrance. It also acquires the response time of the intelligent dimming control system from detecting vehicle information to completing the preset lighting brightness adjustment. Based on the speed and response time, the method determines the vehicle's response distance within the response time. Finally, it determines the deployment distance of the vehicle detection equipment from the tunnel entrance based on the first critical safe field of vision distance and the response distance. This method determines the minimum safe field of vision distance within which the driver is unaffected by the dark environment at the tunnel entrance during entry, thus guiding the deployment of the vehicle detection equipment. This ensures that the intelligent dimming control system can respond promptly to vehicle entry and complete lighting adjustment, protecting the driver from adverse lighting conditions as they approach the tunnel, maintaining driving safety and comfort. It also avoids premature lighting adjustments that waste energy, effectively balancing energy-saving and driving safety requirements.

[0053] Optional features and other effects of embodiments of the present invention are described in part below, and in part will be apparent from reading this document. Attached Figure Description

[0054] Figure 1 A first exemplary flowchart of a method for calculating the deployment location of a vehicle detection device according to an embodiment of the present invention is shown.

[0055] Figure 2 A second exemplary flowchart of a method for calculating the deployment location of a vehicle detection device according to an embodiment of the present invention is shown;

[0056] Figure 3 A third exemplary flowchart of a method for calculating the deployment location of a vehicle detection device according to an embodiment of the present invention is shown;

[0057] Figure 4A fourth exemplary flowchart of a method for calculating the deployment location of a vehicle detection device according to an embodiment of the present invention is shown;

[0058] Figure 5 A fifth exemplary flowchart of a method for calculating the deployment location of a vehicle detection device according to an embodiment of the present invention is shown;

[0059] Figure 6 A sixth exemplary flowchart of a method for calculating the deployment location of a vehicle detection device according to an embodiment of the present invention is shown;

[0060] Figure 7 A seventh exemplary flowchart of a method for calculating the deployment location of a vehicle detection device according to an embodiment of the present invention is shown;

[0061] Figure 8 An eighth exemplary flowchart of a method for calculating the deployment location of a vehicle detection device according to an embodiment of the present invention is shown;

[0062] Figure 9 A graph showing the relationship between driving speed and distance / position according to a specific embodiment of the present invention is provided.

[0063] Figure 10 A graph showing the relationship between driving speed and distance / position according to a specific embodiment of the present invention is provided.

[0064] Figure 11 A graph showing the relationship between driving speed and distance / position according to a specific embodiment of the present invention is provided.

[0065] Figure 12 A graph showing the relationship between driving speed and distance / position according to a specific embodiment of the present invention is provided.

[0066] Figure 13 A graph showing the relationship between driving speed and distance / position according to a specific embodiment of the present invention is provided.

[0067] Figure 14 A graph showing the relationship between driving speed and distance / position according to a specific embodiment of the present invention is provided.

[0068] Figure 15 A graph showing the relationship between driving speed and distance / position according to a specific embodiment of the present invention is provided.

[0069] Figure 16 A graph showing the relationship between driving speed and distance / position according to a specific embodiment of the present invention is provided.

[0070] Figure 17 A graph showing the relationship between driving speed and distance / position according to a specific embodiment of the present invention is provided.

[0071] Figure 18A graph showing the relationship between driving speed and distance / position according to a specific embodiment of the present invention is provided.

[0072] Figure 19 A schematic diagram showing the layout of a vehicle detection device according to a specific embodiment of the present invention is shown;

[0073] Figure 20 A linear regression diagram showing the relationship between the distance between a vehicle and the tunnel entrance and its speed, according to a specific embodiment of the present invention, is shown. Detailed Implementation

[0074] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings. Here, the illustrative embodiments and descriptions of this invention are used to explain the invention, but are not intended to limit the invention.

[0075] The term "comprising" and its variations as used herein signify an open-ended inclusion, i.e., "including but not limited to". Unless otherwise stated, the term "or" means "and / or". The term "based on" means "at least partially based on". The terms "an example embodiment" and "an embodiment" mean "at least one example embodiment". The term "another embodiment" means "at least one additional embodiment". For ease of understanding of this specification, unless otherwise stated, the sequential terms "first", "second", etc., are used herein to distinguish different elements / articles / objects and do not indicate the order or importance of different elements / articles / objects. In particular, method steps indicated by the terms "first", "second", etc., are not used to indicate the order of method execution; when an embodiment includes elements / articles / objects indicated in a later order, the elements / articles / objects indicated by the terms "first", "second", etc., in the earlier order are not necessarily essential technical features of that embodiment.

[0076] As mentioned earlier, to achieve energy conservation in tunnel lighting, an increasing number of tunnels are employing intelligent dimming control systems. These systems integrate brightness detection equipment, vehicle detection equipment, dimming lighting fixtures, and corresponding control algorithms to achieve on-demand tunnel lighting control centered on "lights on when a vehicle approaches, lights off when a vehicle leaves." In this type of solution, the intelligent dimming control system primarily relies on vehicle detection equipment to detect upstream vehicle information and then determines whether to adjust the lighting brightness at the tunnel entrance, as well as the lighting in the middle and exit sections based on this information.

[0077] However, the inventors of this invention recognized that known solutions typically lack a scientifically sound method for determining the optimal placement of vehicle detection equipment. An unreasonable placement of vehicle detection equipment can lead to several problems: if the placement is too far from the tunnel entrance, the tunnel's normal lighting will be turned on too early, wasting lighting resources and failing to meet current energy conservation and emission reduction requirements; conversely, if the placement is too close to the tunnel entrance, the tunnel's lighting fixtures may not be dimmed in time, resulting in a "black hole effect" or abrupt changes in lighting brightness within the driver's field of vision before entering the tunnel. This reduces the driver's ability to perceive road conditions safely, forcing them to slow down suddenly and increasing driving safety risks. Therefore, how to scientifically and rationally determine the optimal placement distance of vehicle detection equipment from the tunnel entrance to simultaneously meet energy conservation and emission reduction needs and driving safety requirements is a technical problem urgently needing to be solved in this field.

[0078] Therefore, embodiments of the present invention aim to provide a method for calculating the deployment location of vehicle detection equipment in a tunnel intelligent dimming control system. This method can guide the determination of a reasonable deployment location for vehicle detection equipment, especially for determining a reasonable deployment location for vehicle detection equipment near the tunnel entrance (exit). The method for calculating the deployment location of vehicle detection equipment according to embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0079] In an embodiment of the present invention, reference is made to Figure 1 The method for calculating the deployment location of the vehicle detection equipment may include the following steps S110, S120, S130, S140 and S150.

[0080] S110: Obtain the vehicle's speed as it approaches and enters the tunnel from the upstream.

[0081] In this embodiment of the invention, the upstream of the tunnel includes the road area located outside the tunnel entrance when a vehicle travels in the direction of travel towards the tunnel. In some embodiments, the travel speed includes the actual travel speed of the vehicle as it approaches and enters the tunnel from the upstream. In this embodiment, the actual travel speed is obtained, for example, through on-site data collection. In other embodiments, the travel speed may include a preset travel speed of the target tunnel, such as, but not limited to, the design speed of the target tunnel, speed limit, etc., which will be described in detail below.

[0082] In some embodiments, the vehicle's speed as it approaches and enters the tunnel from the upstream can be continuously acquired within a predetermined time period / predetermined travel distance. In some embodiments, the vehicle's speed (data) and corresponding time and location information can be continuously acquired and recorded. In embodiments of the present invention, the methods for acquiring the speed (data) include, but are not limited to: measuring the vehicle speed in real time using a non-contact speedometer, recording the vehicle's location and speed information using a GPS device, etc., and this disclosure does not limit these methods.

[0083] In this embodiment of the invention, the numerical range of the driving speed can be determined according to the actual tunnel conditions. For example, in some specific embodiments, the driving speed can be in the range of 58.4 km / h to 96.8 km / h, which is determined based on actual tunnel test data. However, the invention is not limited to this range and can be adjusted according to the actual conditions of different tunnels.

[0084] S120: Determine the first critical safe field of vision distance within the driver's field of vision during driving, unaffected by the dark environment at the tunnel entrance.

[0085] In this embodiment of the invention, the dark environment at the tunnel entrance includes the visual phenomenon observed by the driver when viewing the tunnel entrance from the bright environment outside the tunnel. As an explanation, when the driver is outside the tunnel approaching it, the human eye has adapted to the high brightness of the external environment, while the lighting inside the tunnel is much lower than the external environment. This significant difference in lighting makes the tunnel entrance area appear dark or a "black hole" effect in the field of vision.

[0086] In this embodiment of the invention, the first critical safe field of vision distance includes the distance between the tunnel entrance and the critical position that ensures the driver is not affected by the dark environment at the tunnel entrance during the approach process. For explanation, when the vehicle is outside this critical position, the driver's field of vision is not yet affected by the dark environment at the tunnel entrance, i.e., the dark environment at the tunnel entrance is not yet clearly perceived, and the driver is in a normal driving state unaffected. When the vehicle enters the critical position, the driver begins to clearly perceive the dark environment of the tunnel entrance, the driver's attention is drawn to the tunnel entrance, and therefore the driver changes their driving strategy, such as reducing driving speed.

[0087] In this embodiment of the invention, the first critical safe field of view distance can be determined by field tests to determine the first critical safe field of view distance of the target tunnel.

[0088] In some embodiments, reference Figure 2 Step S120 may include the following steps S121, S122 and S123.

[0089] S121: Real-time acquisition of driving speed, at least within the range affected by changes in tunnel brightness.

[0090] In this embodiment of the invention, the tunnel brightness change influence range refers to the area (road section range) within which a driver may be affected by the dim lighting environment at the tunnel entrance as the vehicle approaches the tunnel from upstream. In some embodiments, the tunnel brightness change influence range can be set to the entire distance from the starting position to the tunnel entrance. In other embodiments, the tunnel brightness change influence range can also be set to a predetermined distance upstream of the tunnel entrance (e.g., 2000m), depending on the requirements. In other embodiments, the tunnel brightness change influence range can also be set to a predetermined distance plus a certain redundancy, etc., which falls within the protection scope of this invention.

[0091] In some embodiments, real-time data acquisition includes continuously recording the vehicle's speed at certain displacement intervals / time intervals during vehicle movement. In a specific example, the vehicle's speed is collected every 10 meters. In some embodiments, the distance between the vehicle and the tunnel entrance or the vehicle's position coordinates may also be recorded synchronously during the acquisition process to establish a correspondence between speed and distance later.

[0092] S122: Analyze the characteristics of the change in driving speed to determine the first critical position where the driving speed first decreases.

[0093] In this embodiment of the invention, the first decrease in driving speed includes the phenomenon that the driving speed first significantly decreases or abruptly decreases during the process of the vehicle approaching the tunnel from upstream. This decrease in vehicle speed is usually due to the appearance of the tunnel entrance within the driver's field of vision. The lower lighting brightness at the tunnel entrance contrasts sharply with the higher brightness of the surrounding environment, creating a "black hole effect." This affects the driver's continued perception of road conditions ahead, causing the driver to develop a risk-averse mentality and take deceleration measures.

[0094] In this embodiment of the invention, analyzing the characteristics of speed change includes analyzing the process of speed change as the distance between the vehicle and the tunnel entrance. In some embodiments, the first critical position includes the position corresponding to the first significant decrease in speed. In some embodiments, for example, the position corresponding to the speed decrease exceeding a preset threshold (e.g., 5 km / h) can be determined as the first critical position. In some embodiments, the first critical position can also be determined by analyzing the rate of change of speed with distance, which will be described in detail below.

[0095] In this embodiment of the invention, steps S110 and S120 can be performed on the target tunnel to determine the first critical safe field of view distance corresponding to the target tunnel. This can guide the deployment of vehicle detection equipment in the target tunnel to assist in intelligent dimming control of the target tunnel.

[0096] Accordingly, in some embodiments, step S121 may include step S1211 (not shown): collecting driving speeds for multiple drivers respectively.

[0097] In some embodiments, each of the multiple drivers can drive the vehicle from upstream of the tunnel and enter the tunnel, and the driving speed during the entry process can be collected separately. It is understood that in step S1211 above, the environmental conditions can be controlled to be the same or substantially the same, for example, under substantially the same weather, visibility or traffic flow.

[0098] In some embodiments, reference Figure 3 Step S121 may include the following steps S1221, S1222, and S1223.

[0099] S1221: Determine the average driving speed at multiple different data collection locations.

[0100] In this embodiment of the invention, at least some of the acquisition locations are located within the range affected by tunnel brightness variations. The description of the range affected by tunnel brightness variations in this embodiment is as described above and will not be repeated here. In some embodiments, adjacent acquisition locations among multiple different acquisition locations may have a predetermined spacing. In some embodiments, the predetermined spacing can be flexibly set as needed, and this invention does not limit this.

[0101] In this embodiment of the invention, the driving speeds of multiple drivers at each data collection location can be calculated, and then the average driving speed data of the multiple drivers can be calculated. As an explanation, and not a limitation, using the average driving speed of multiple drivers at each data collection location can reduce the impact of individual driver differences and improve the stability and reliability of the data.

[0102] S1222: Construct a curve showing the relationship between location and driving speed based on the average values ​​of multiple different data collection locations and driving speeds.

[0103] In this embodiment of the invention, a curve relating vehicle speed to location distance can be constructed by using each data acquisition location as the abscissa and the average vehicle speed corresponding to each data acquisition location as the ordinate. In some embodiments, methods including but not limited to polynomial fitting, spline interpolation, and least squares fitting can be used to generate a smooth, continuous curve. In this embodiment, the fitted curve can well reflect the overall trend of speed change with location and reduce the impact of fluctuations at individual data points.

[0104] S1223: Identify the first critical position where the driving speed decreases for the first time in the relationship curve.

[0105] In this embodiment of the invention, the first critical position may correspond to the first critical safe field of view distance. A description of the first critical safe field of view distance can be found above and will not be repeated here.

[0106] In some embodiments, the first critical position can be determined by identifying the inflection point in the relationship curve, i.e., the abrupt change in the relationship curve from rising to falling. In some embodiments, the inflection point can be confirmed by manual observation. In other embodiments, the inflection point can also be determined by calculating the derivative or difference of the relationship curve and identifying the position where the derivative first becomes significantly negative. It is understood that the first critical position can be identified by analyzing the relationship curve in various ways, and the present invention does not limit the specific identification method.

[0107] In some embodiments, reference Figure 4 After the step of constructing the relationship curve between the driving speed and the sampling location based on the average of the sampling location and the driving speed, for example after step S122, steps S1224 and S1225 may also be included.

[0108] S1224: Identify the two locations in the relationship curve where the speed decreases most significantly.

[0109] In this embodiment of the invention, the two positions where the driving speed decreases most significantly include the two positions in the relationship curve where the speed decrease is the largest or the speed change rate (deceleration) is the largest.

[0110] S1225: The location farther from the tunnel entrance is determined as the first critical location, and the other is determined as the second critical location.

[0111] In this embodiment of the invention, after identifying the two locations in the relationship curve where the speed decreases most significantly, the location farther from the tunnel entrance can be determined as the first critical location, and the location closer to the tunnel entrance can be determined as the second critical location. In this embodiment, the distance from the tunnel entrance to the first critical location is greater than the distance from the tunnel entrance to the second critical location.

[0112] In this embodiment of the invention, the first critical position corresponds to the first critical safe field of vision distance, and the second critical position corresponds to the second critical safe field of vision distance within the driver's field of vision that is not affected by the abrupt change in tunnel entrance lighting brightness. As an explanation, when the driver first reduces speed (e.g., corresponding to the first critical position), the contrast between light and dark at the tunnel entrance creates a "black hole effect." When the driver reaches the second critical position, their vision has begun to adapt to the darker environment inside the tunnel. At this point, they are primarily affected by the difference between the natural light outside the tunnel and the lighting brightness inside. This light-dark difference affects the driver's visibility distance of road obstacles within the tunnel. The greater the light-dark difference, the smaller the driver's visibility distance of road obstacles, thus affecting driving safety. Therefore, after determining the first critical safe field of vision distance, this invention can further determine the second critical safe field of vision distance, ensuring that the driver can clearly see road obstacles within the tunnel, reducing driving safety risks caused by insufficient visibility, and providing a scientific basis for adjusting tunnel lighting brightness.

[0113] S123: The distance between the first critical position and the tunnel entrance is determined as the first critical safe field of vision distance.

[0114] In this embodiment of the invention, after identifying the first critical position, the distance between that position and the tunnel entrance can be determined, and this distance is the first critical safe field of vision distance. In a specific embodiment, by analyzing the relationship curve, the actual distance between the first critical position and the tunnel entrance is determined to be 820.21m, and the first critical safe field of vision distance corresponding to the tunnel is 820.21m.

[0115] In this embodiment of the invention, by collecting driving speed in real time within the range affected by changes in tunnel brightness, and then analyzing the characteristics of driving speed changes through the constructed relationship curve between position and driving speed, the first critical safe field of view distance reflecting the driver's real driving behavior characteristics in the environment near the tunnel is determined, thereby guiding the deployment position of vehicle detection equipment based on the first critical safe field of view.

[0116] In a further embodiment of the present invention, driving speed data corresponding to the first critical safe field of vision distance in one or more tunnels can be collected and determined to fit the model, thereby it can be widely used for the deployment of vehicle detection equipment in tunnel intelligent dimming control system.

[0117] In this embodiment of the invention, step S120 may include step S120': determining the first critical safe field of vision distance based on the driving speed using a relationship model between the first critical safe field of vision distance and the driving speed.

[0118] In this embodiment of the invention, the relationship model between the first critical safe field of vision distance and the driving speed characterizes the relationship between the first critical safe field of vision distance and the driving speed.

[0119] In some embodiments, the relationship model can be represented as the first critical safe field of view distance L. s A function relative to the speed v.

[0120] In some embodiments, the relationship between the first critical safe field of vision distance and the driving speed is represented by the following equation:

[0121] L s = av + b

[0122] Among them, L s is the first critical safe field of vision distance, in meters; v is the driving speed, in kilometers per hour; a and b are constants that can be determined through regression analysis.

[0123] In one specific embodiment, based on actual tunnel test data, linear regression analysis yielded: a=3.12, b=562.29. The relationship model can then be expressed as:

[0124] L s = 3.12v + 562.29

[0125] In some embodiments, such as Figure 5 As shown, step S120' may include the following steps S121' to S123'.

[0126] S121': Collect test driving speeds and corresponding first critical safety field of vision distances for multiple different test tunnels.

[0127] In embodiments of the present invention, for example, in step S121' above, the test driving speed may include an initial driving speed. In some embodiments, the test driving speed may also include a typical driving speed determined based on the tunnel's design speed, speed limit, historical traffic data, etc. In optional embodiments, the entrance alignment radius of multiple different test tunnels may be greater than a certain threshold (e.g., 1000m) and / or the longitudinal slope may be less than a certain threshold (e.g., 3%). This is to avoid the influence of tunnel entrance alignment conditions on the test driving speed, thereby obtaining more reliable and accurate data.

[0128] In some embodiments, reference Figure 6 The step S121' may include performing the following steps S1211' to S1213' for each initial velocity in each test tunnel.

[0129] S1211': Real-time acquisition of test driving speed at least within the range affected by changes in tunnel brightness.

[0130] S1212': Analyze the characteristics of the change in test driving speed to determine the first critical position of the test when the test driving speed first decreases.

[0131] S1213': The distance between the first critical position of the test and the entrance of the test tunnel is determined as the first critical safe field of vision distance of the test.

[0132] In this embodiment of the invention, the specific description of the above steps S1211', S1212', and S1213' can be found in the description of the aforementioned steps S121, S122, and S123. The difference is that the data collected in the above steps S1211', S1212', and S1213' are multiple test driving speeds in multiple test tunnels.

[0133] In this embodiment of the invention, step S1211' may include the step of collecting test driving speeds for multiple drivers respectively. In this embodiment, for each of the multiple tunnels, each of the multiple drivers may drive the test vehicle from upstream of the tunnel and enter the tunnel, thereby determining the average test driving speed at multiple different collection locations.

[0134] In some embodiments, reference Figure 7 Step S1212' may include steps S12121', S12122' and S12123'.

[0135] S12121': Determine the average test driving speed at multiple different sampling locations.

[0136] In some embodiments, at least some of the acquisition locations are located within the range affected by tunnel brightness variations.

[0137] S12122': Construct a relationship curve between location and test driving speed based on the average of multiple different acquisition locations and the test driving speed.

[0138] S12123': The first critical position of the test when the test driving speed first decreases in the relationship curve.

[0139] In some embodiments, the first critical position of the test corresponds to the first critical safe field of view distance.

[0140] In this embodiment of the invention, the specific descriptions of steps S12121', S12122', and S12123' can be found in the descriptions of steps S1221, S1222, and S1223. The difference lies in that, in steps S12121', S12122', and S12123', the collected data are multiple test driving speeds in multiple test tunnels.

[0141] In some embodiments, reference Figure 8 After the step of constructing the relationship curve between the test driving speed and the collection location based on the average of the collection location and the test driving speed, for example after step S12122', steps S12124' and S12125' may also be included.

[0142] S12124': Identify the two positions in the relationship curve where the test driving speed decreases most significantly.

[0143] S12125': The location farther from the tunnel entrance is determined as the first critical position of the test, and the other is determined as the second critical position of the test.

[0144] In this embodiment of the invention, the first critical position corresponds to the first critical safe field of vision distance, and the second critical position corresponds to the second critical safe field of vision distance within the driver's field of vision that is not affected by the sudden change in the brightness of the lighting at the entrance.

[0145] In this embodiment of the invention, the specific description of steps S12124' and S12125' can be found in the description of steps S1224 and S1225. The difference is that the speeds collected in steps S12124' and S12125' are multiple test driving speeds in multiple test tunnels.

[0146] S122': Based on the test driving speeds and corresponding test first critical safe field of vision distances collected from multiple test tunnels, a relationship model between the first critical safe field of vision distance and the driving speed is constructed through regression analysis.

[0147] In this embodiment of the invention, a relationship model between the test driving speed and the test first critical safe visibility distance can be established using regression analysis based on data pairs obtained from multiple test tunnels. In some embodiments, the regression analysis can employ various methods, such as linear regression, multinomial regression, exponential regression, etc. This invention does not limit the specific regression analysis method, as long as a mathematical model characterizing the relationship between the first critical safe visibility distance and the driving speed can be constructed based on the test data, which falls within the protection scope of this invention.

[0148] S123': The first critical safe field of vision distance is obtained by solving the relational model using the driving speed.

[0149] In this embodiment of the invention, after establishing the relationship model between the first critical safe field of view distance and the driving speed, for a target tunnel where the location of the vehicle detection equipment needs to be determined, the driving speed of the tunnel can be directly substituted into the relationship model for calculation to quickly obtain the corresponding first critical safe field of view distance.

[0150] S130: Obtain the response time of the intelligent dimming control system from detecting vehicle information to completing the preset lighting brightness adjustment.

[0151] In this embodiment of the invention, the response time includes the total time required for the intelligent dimming control system to adjust the tunnel lighting brightness to a preset value from the moment the vehicle detection device detects the vehicle arrival information. For example, this time may include the time consumed by a series of processes such as information transmission, information processing, control command transmission, and lighting device response.

[0152] In some embodiments of the invention, the response time can be obtained by actually measuring the time from vehicle detection to lighting adjustment by the intelligent dimming control system through on-site testing. In other embodiments, it can also be determined by accumulating the response time parameters of each component displayed by the intelligent dimming control system, and the invention does not limit this. In some embodiments, the total response time of the intelligent dimming control system is within a certain range. In this embodiment, the maximum value in the total response time range can be selected as the response time according to the worst-case scenario principle. In a specific embodiment, the total response time of the tunnel lighting intelligent dimming control system is within the range of 100 milliseconds to 2 seconds, and in this case, 2 seconds is taken as the response time.

[0153] S140: Determine the response distance the vehicle travels within the response time based on the driving speed and response time.

[0154] In this embodiment of the invention, the response distance includes the distance traveled by the vehicle continuing to travel at the current speed within the response time of the intelligent dimming control system.

[0155] In some embodiments, the formula for calculating the response distance is:

[0156] L r = v × t

[0157] S150: Determine the deployment distance of the vehicle detection equipment from the tunnel entrance based on the first critical safety field of view distance and response distance.

[0158] In this embodiment of the invention, the deployment distance refers to the distance at which the vehicle detection equipment should be deployed from the tunnel entrance.

[0159] In this embodiment of the invention, the deployment distance includes the sum of the first critical safety field of view distance and the response distance.

[0160] In some embodiments of the present invention, the formula for calculating the deployment distance is as follows:

[0161] L = L s + L r

[0162] Where L is the distance between the vehicle detection equipment and the tunnel entrance, in meters; L s The first critical safe field of view distance, in meters; L r The response distance is in meters (m).

[0163] In some embodiments, the deployment distance can be adjusted appropriately according to actual construction conditions. For example, considering factors such as the accessibility of the equipment installation location and the convenience of maintenance, a certain margin can be appropriately increased or decreased based on the calculation results, which falls within the protection scope of this invention.

[0164] This invention provides a method for calculating the deployment location of vehicle detection equipment in a tunnel intelligent dimming control system. By acquiring the vehicle's speed as it approaches and enters the tunnel from the upstream, the method determines the first critical safe field of vision distance within the driver's field of vision, unaffected by the dark environment at the tunnel entrance. It also acquires the response time of the intelligent dimming control system from detecting vehicle information to completing the preset lighting brightness adjustment. Based on the speed and response time, the method determines the vehicle's response distance within the response time. Finally, it determines the deployment distance of the vehicle detection equipment from the tunnel entrance based on the first critical safe field of vision distance and the response distance. This method determines the minimum safe field of vision distance within which the driver is unaffected by the dark environment at the tunnel entrance during entry, thus guiding the deployment of the vehicle detection equipment. This ensures that the intelligent dimming control system can respond promptly to vehicle entry and complete lighting adjustment, protecting the driver from adverse lighting conditions as they approach the tunnel, maintaining driving safety and comfort. It also avoids premature lighting adjustments that waste energy, effectively balancing energy-saving and driving safety requirements.

[0165] The following describes in detail, with reference to specific embodiments, the method for calculating the deployment location of vehicle detection equipment for a tunnel intelligent dimming control system according to an embodiment of the present invention.

[0166] I. Experimental Design and Preparation

[0167] To determine the minimum safe distance for a driver to remain unaffected by the light environment at the tunnel entrance within their field of vision under different driving speed conditions, this embodiment designed and implemented a field test. The test collected data on the vehicle's speed within the tunnel's affected area, analyzed the characteristics of speed changes, and ultimately determined the minimum safe distance for the driver to remain unaffected by the tunnel's light environment.

[0168] 1.1 Test Road Selection

[0169] In this embodiment, the Rongjiang-Duyun section of the Xiarong Expressway was selected as the test road. To avoid the influence of tunnel entrance alignment conditions on vehicle speed, the selection of the test tunnel followed the following criteria: the tunnel entrance alignment radius was greater than 1000m; the longitudinal slope was less than 3%.

[0170] Based on the above standards, this embodiment selected the tunnels described in Table 1 below as the test tunnels.

[0171] Table 1 Test Tunnel Table

[0172] Tunnel Name direction Tunnel Name direction Gaokan Tunnel Up Gelong Tunnel Downward Changlingpo Tunnel Up Gaosui Tunnel Downward Huangmeng Tunnel Up Huangmeng Tunnel Downward Gaosui Tunnel Up Changlingpo Tunnel Downward Gelong Tunnel Up Gaokan Tunnel Downward

[0173] 1.2 Selection of Test Vehicles and Drivers

[0174] Based on the principle of least favorable visibility, this embodiment selects a passenger car as the test vehicle. This is because, compared to trucks, passenger cars have higher speeds, lower driver eye level, and narrower field of vision, resulting in shorter visibility distances. Therefore, the safety visibility conditions for passenger car drivers are relatively unfavorable, and the test results based on passenger cars offer better safety assurance.

[0175] In this embodiment, 12 healthy drivers were randomly invited to participate in the experiment. The test drivers met the following conditions: they had not consumed alcohol or taken any medication before the experiment, they were well-rested and reacted normally, their uncorrected visual acuity in both eyes was 4.9 or higher on the visual acuity chart, and they had no color blindness, color weakness or other eye diseases.

[0176] 1.3 Preparation of test equipment

[0177] First, a non-contact speedometer was installed on the test vehicle to measure and record its speed in real time. Simultaneously, a GPS positioning device and a time recording device were equipped to record the vehicle's location information and the time it passed through the tunnel entrance.

[0178] 1.4 Experimental Procedure

[0179] The experiment was conducted according to the following steps (1) to (6). During the entire experiment, the experimenter did not intervene or prompt the driving behavior of the test driver.

[0180] (1) Calibrate and test the non-contact speedometer, GPS positioning equipment and other measuring devices installed on the test vehicle.

[0181] (2) Set up the test starting point 2km upstream from the entrance of the first test tunnel, so that the test driver can start from the starting point and drive normally. At the same time, the tester will start recording test data, including vehicle speed, position and time information.

[0182] (3) The test driver drove through all five test tunnels in the uphill direction in sequence (Gaokan Tunnel, Changlingpo Tunnel, Huangmeng Tunnel, Gaosui Tunnel, and Gelong Tunnel), and after exiting the last tunnel in the uphill direction (Gelong Tunnel), made a U-turn at the downstream interchange.

[0183] (4) At a distance of 2km upstream from the entrance of the first test tunnel (Gelong Tunnel) in the downward direction, the tester resumed recording the test data, and the test driver drove through all 5 test tunnels in the downward direction in the same normal driving state.

[0184] (5) The tester marks each tunnel entrance when the vehicle arrives and records the exact time when the vehicle passes through the tunnel entrance so as to determine the relative position of the vehicle and the tunnel entrance.

[0185] (6) Repeat steps 2 to 5 above to complete the test of all 12 test drivers.

[0186] II. Experimental Data Acquisition and Processing

[0187] 2.1 The collected vehicle speed, position and time data are correlated and organized to establish the correspondence between vehicle speed and vehicle position (expressed as distance from the tunnel entrance).

[0188] 2.2 Remove obviously abnormal data points, such as abnormal data caused by interference from other vehicles or equipment failure.

[0189] 2.3 The area from 1000m upstream of the tunnel to 500m inside the tunnel is designated as the key analysis zone, which covers the main areas where drivers may be affected by the tunnel's light environment.

[0190] 2.4 Standardize the location information of all vehicles to the distance relative to the tunnel entrance for comparative analysis.

[0191] III. Analysis of Experimental Results

[0192] By analyzing the compiled test data, the vehicle speeds of all 12 test drivers at different distances were obtained from 1000m upstream of the entrance to 500m inside the tunnels of the 10 test tunnels in both directions.

[0193] For each tunnel, the average vehicle speed of all 12 test drivers was calculated at different distances. Then, based on this data, a curve showing the relationship between vehicle speed and distance was plotted. Figure 9 , Figure 10 , Figure 11 , Figure 12 , Figure 13 , Figure 14 , Figure 15 , Figure 16 , Figure 17 and Figure 18 It displays curves showing the relationship between vehicle speed and position distance in the up and down tunnels of all five test tunnels.

[0194] right Figures 9 to 18 To conduct analysis, in order to Figure 9 Taking the Zhongshanggaokan Tunnel as an example:

[0195] Analysis shows that the vehicle's speed first noticeably decreases approximately 800 meters from the tunnel entrance. At this location, the tunnel entrance begins to appear in the driver's field of vision. The low lighting at the tunnel entrance contrasts sharply with the brighter surrounding environment, creating a "black hole effect." This lighting phenomenon impairs the driver's continuous perception of road conditions ahead. The driver cannot anticipate changes in road alignment, vehicles, and obstacles within the tunnel, leading to anxiety and prompting them to slow down to ensure driving safety.

[0196] Meanwhile, the vehicle slowed down a second time approximately 200 meters from the tunnel entrance. At this point, the driver's focus was already on the tunnel entrance, and the driver began to adapt to the lower light conditions at the tunnel entrance. Simultaneously, the significant difference in brightness between the outside and the tunnel entrance affected the visibility of obstacles on the road surface at the tunnel entrance, causing the driver to reduce speed again to ensure safe entry into the tunnel.

[0197] The same analysis of the test tunnel data for the remaining nine scenarios revealed a similar pattern of speed change, namely, that the vehicle experienced two significant speed reductions as it approached the tunnel.

[0198] IV. Determining the Location of Testing Equipment

[0199] In this embodiment, the driver is already affected by the contrast between light and dark at the tunnel entrance when the vehicle speed is first reduced. Therefore, this embodiment selects the distance from the tunnel entrance corresponding to the first reduction in vehicle speed by the test driver as the first critical safe field of vision distance. In this embodiment, if the sudden change in lighting brightness at the tunnel entrance section is superimposed within the driver's field of vision, it will further affect the driver's visual comfort and driving load, increasing the risk to driving safety. Therefore, this embodiment can also select the distance from the tunnel entrance corresponding to the second reduction in vehicle speed by the test driver as the second critical safe field of vision distance.

[0200] For the uphill high-ridge tunnel, from Figure 9The speed-position curve shown indicates that the location where the vehicle speed first significantly decreases is approximately 820.21m from the tunnel entrance, corresponding to an average vehicle speed of 77.3km / h. Therefore, the first critical safe field of vision distance L for this tunnel is... s = 820.21m. The intelligent dimming control system used in this tunnel has a response time of 2 seconds. Therefore, the distance L that the vehicle travels within this response time is... r =77.3 × 2 / 3.6 = 42.9m. Therefore, refer to... Figure 19 The distance between the vehicle detection equipment deployment points in the uphill high-slope tunnel is L=L s +L r =820.21 + 42.9 = 863m. That is, the vehicle detection equipment in Gaokan Tunnel should be installed at a location approximately 863m upstream of the tunnel entrance.

[0201] Similarly, the deployment locations of vehicle detection equipment were determined for each of the other test tunnels, resulting in the following: Figures 10 to 18 The velocity-position relationship curve shown.

[0202] V. Summary and Analysis of Experimental Data

[0203] This embodiment summarizes and organizes the test data from five test tunnels (both directions). The vehicle speed and distance from the tunnel entrance when the test driver first reduced the vehicle speed in the five tunnels are shown in the table below:

[0204] Table 2 Summary of vehicle distance and speed from tunnel entrance

[0205] Tunnel Name direction Distance from tunnel entrance (m) Driving speed (km / h) Gaokan Tunnel Up 820.21 77.3 Changlingpo Tunnel Up 765.02 72.5 Huangmeng Tunnel Up 719.42 58.4 Gaosui Tunnel Up 805.53 87.5 Gelong Tunnel Up 798.85 66.5 Gelong Tunnel Downward 747.65 61.7 Gaosui Tunnel Downward 781.11 73.8 Huangmeng Tunnel Downward 837.68 82.6 Changlingpo Tunnel Downward 870.86 96.8 Gaokan Tunnel Downward 794.73 65.3

[0206] VI. Establish a model relating the first critical safe field of vision distance to driving speed.

[0207] Based on the data on the distance between the vehicle and the tunnel entrance and the driving speed obtained above, this embodiment further establishes a relationship model between the two to enable rapid prediction of the first critical safe field of vision distance based on the vehicle's speed. As shown in Table 2 above, the distance between the driver and the tunnel entrance (i.e., the first critical safe field of vision distance) varies under different tunnel conditions and driving speeds. However, the overall trend is that the higher the vehicle speed, the greater the corresponding first critical safe field of vision distance. This phenomenon is because the safe distance for the driver is closely related to the driving speed: as the vehicle speed increases, the driver's gaze point shifts forward to look at the distance, expanding the field of vision. Therefore, the driver will see the tunnel entrance earlier and correspondingly reduce the vehicle speed earlier.

[0208] Here, a scatter plot is drawn between vehicle speed and the first critical safe field of vision distance (see [link]). Figure 20 ).from Figure 20 As can be seen, the first critical safe field of vision distance increases with increasing vehicle speed, and the two show a roughly linear relationship. A Pearson correlation coefficient test (r=0.86) indicates a strong positive linear correlation between the two.

[0209] Subsequently, this embodiment uses linear regression analysis to establish the first critical safe field of view distance L. s A linear relationship model relative to the travel speed v is used to quantitatively describe the above relationship:

[0210] L s =av+b

[0211] Among them, L s is the first critical safe field of vision distance, in meters; v is the vehicle speed, 58.4 < v < 96.8 km / h; a and b are undetermined constants.

[0212] Here, Figure 20 The following relationship model was obtained after fitting the data using linear regression:

[0213] L s =3.12v + 562.29

[0214] The determination coefficient r was further calculated for this model. 2 =0.74, indicating that the linear regression model has a good fit. For new tunnels where the placement of vehicle detection equipment needs to be adjusted, the relational model can be used to quickly determine the placement of the equipment in the new tunnel without having to conduct on-site tests for each new tunnel. This achieves the goal of ensuring driver safety and visual comfort while avoiding premature lighting activation and energy waste caused by excessively long placement distances. It enables the tunnel intelligent dimming control system to truly achieve on-demand lighting, while simultaneously meeting energy conservation and emission reduction requirements as well as driving safety requirements.

[0215] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. For those skilled in the art, the present invention can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the present invention should be included within the scope of protection of the present invention.

[0216] Under the teachings of this invention, features of the method embodiments can be combined in a non-contradictory manner to obtain new embodiments, which fall within the scope of this invention.

[0217] Unless explicitly stated otherwise, the actions or steps of the methods and procedures described in the embodiments of the present invention do not necessarily have to be performed in a specific order and can still achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0218] This document describes several embodiments of the present invention; however, for the sake of brevity, the descriptions of the embodiments are not exhaustive, and identical or similar features or parts between the embodiments may be omitted. In this document, "one embodiment," "some embodiments," "example," "specific example," or "some examples" refers to embodiments applicable to at least one, but not all, of the present invention. The above terms do not necessarily refer to the same embodiments or examples. Without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described herein, as well as the features of the different embodiments or examples.

[0219] The exemplary systems and methods of the present invention have been specifically shown and described with reference to the foregoing embodiments, and are merely examples of preferred modes of implementation of the systems and methods. Those skilled in the art will understand that various changes can be made to the embodiments of the systems and methods described herein without departing from the spirit and scope of the invention as defined in the appended claims when implementing the systems and / or methods.

Claims

1. A method for calculating the deployment location of vehicle detection equipment for a tunnel intelligent dimming control system, characterized in that, include: S110: Obtain the vehicle's speed as it approaches and enters the tunnel from the upstream; S120: Determine the first critical safe field of vision distance within the driver's field of vision during driving, unaffected by the dark environment at the tunnel entrance; S130: Obtain the response time of the intelligent dimming control system from detecting vehicle information to completing the preset lighting brightness adjustment; S140: Determine the response distance traveled by the vehicle within the response time based on the driving speed and the response time; as well as S150: Determine the deployment distance of the vehicle detection equipment from the tunnel entrance based on the first critical safety field of view distance and the response distance.

2. The calculation method according to claim 1, characterized in that, Step S120 includes: S121: Real-time collection of driving speed at least within the range affected by changes in tunnel brightness; S122: Analyze the characteristics of the speed change to determine the first critical position where the speed first decreases; and S123: The distance between the first critical position and the tunnel entrance is determined as the first critical safe field of vision distance.

3. The calculation method according to claim 2, characterized in that, Step S121 includes: S1211: Collecting the driving speed for each of the multiple drivers; Step S122 includes: S1221: Determine the average driving speed at multiple different acquisition locations, wherein at least some of the acquisition locations are located within the range affected by tunnel brightness changes; S1222: Construct a relationship curve between position and driving speed based on the average of the multiple different collection locations and the driving speed; S1223: Identify the first critical position where the driving speed first decreases in the relationship curve, wherein the first critical position corresponds to the first critical safe field of vision distance.

4. The calculation method according to claim 2, characterized in that, Step S121 includes: S1211: Collecting the driving speed for each of the multiple drivers; Step S122 includes: S1221: Determine the average driving speed at multiple different acquisition locations, wherein at least some of the acquisition locations are located within the range affected by tunnel brightness changes; S1222: Construct a relationship curve between position and driving speed based on the average of the multiple different collection locations and the driving speed; S1224: Identify the two locations in the relationship curve where the driving speed decreases most significantly; S1225: The location farther from the tunnel entrance is determined as the first critical position, and the other is determined as the second critical position. The first critical position corresponds to the first critical safe field of vision distance, and the second critical position corresponds to the second critical safe field of vision distance within the driver's field of vision that is not affected by the sudden change in the brightness of the tunnel entrance lighting.

5. The calculation method according to claim 1, characterized in that, Step S120 includes: S120': Based on the driving speed, the first critical safe field of vision distance is determined by the relationship model between the first critical safe field of vision distance and the driving speed, wherein the relationship model between the first critical safe field of vision distance and the driving speed characterizes the relationship between the first critical safe field of vision distance and the driving speed at different driving speeds.

6. The calculation method according to claim 5, characterized in that, The relationship between the first critical safe field of vision distance and driving speed is represented by the following formula: L s =of+b Among them, L s Let v be the first critical safe field of vision distance, v be the driving speed, and a and b be constants.

7. The calculation method according to claim 5 or 6, characterized in that, Step S120' includes: S121': Collect test driving speeds and corresponding first critical safe field of view distances for multiple different test tunnels; and S122': Based on the test driving speeds and corresponding test first critical safe field of vision distances collected from multiple test tunnels, a model of the relationship between the first critical safe field of vision distance and driving speed is constructed through regression analysis; S123': The first critical safe field of vision distance is obtained by solving the relational model using the driving speed.

8. The calculation method according to claim 7, characterized in that, Step S121' includes: for each of the plurality of initial velocities in each test tunnel. S1211': Real-time acquisition of test driving speed at least within the range affected by tunnel brightness changes; S1212': Analyze the characteristics of the test driving speed change to determine the first critical position where the test driving speed first decreases; and S1213': The distance between the first critical position of the test and the entrance of the test tunnel is determined as the first critical safe field of vision distance of the test.

9. The calculation method according to claim 8, characterized in that, The step S1211' includes: collecting test driving speeds for multiple drivers respectively; The step S1212' includes: S12121': Determine the average test driving speed at multiple different sampling locations, wherein at least some of the sampling locations are located within the range affected by tunnel brightness changes; S12122': Based on the average of the multiple different data acquisition locations and the test driving speed, construct a relationship curve between location and test driving speed; and S12123': Identify the first critical position in the relationship curve where the test driving speed first decreases, wherein the first critical position corresponds to the first critical safe field of vision distance.

10. The calculation method according to claim 8, characterized in that, Step S1211' includes: collecting test driving speeds for multiple drivers respectively; The step S1212' includes: S12121': Determine the average test driving speed at multiple different sampling locations, wherein at least some of the sampling locations are located within the range affected by tunnel brightness changes; S12122': Based on the average of the multiple different data collection locations and the test driving speed, construct a curve showing the relationship between location and test driving speed; S12124': Identify the two positions in the relationship curve where the test driving speed decreases most significantly; S12125': The location farther from the tunnel entrance is determined as the first critical position for the test, and the other is determined as the second critical position for the test. The first critical position for the test corresponds to the first critical safe field of vision distance, and the second critical position for the test corresponds to the second critical safe field of vision distance within the driver's field of vision that is not affected by the sudden change in the brightness of the tunnel entrance lighting.

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