A high beam linkage lighting device and method for a bidirectional two-lane ordinary highway tunnel

Abstract

The present invention belongs to the field of active automotive safety technology and discloses a high-beam linkage lighting device and method for a bidirectional, two-lane conventional highway tunnel. The device and method comprise a dynamic high-beam recognition system, a delayed tunnel lighting adjustment system, and a wireless communication module. The dynamic high-beam recognition system calculates the speed, average speed, and volume of vehicles at each sampling point in the tunnel, determines whether a vehicle's high beams are on, and marks the light intensity of vehicles with high beams on. The delayed tunnel lighting adjustment system then generates lighting control information to adjust the light intensity and color temperature of the tunnel lighting device. This device and method achieve dynamic delayed lighting in the tunnel that reduces the negative effects of high beams. The entire adjustment process is smooth, helping drivers adapt to light changes and reducing the irritation and discomfort caused by changes in the lighting device's light intensity and color temperature.

Description

Technical Field

[0001] The present invention belongs to the technical field of active automobile safety, and relates to a high-beam linkage lighting device and method for a bidirectional two-lane ordinary highway tunnel. Background Art

[0002] Tunnels are common infrastructure in the transportation field. In ordinary two-way, two-lane highway tunnels, when a vehicle turns on its high beam, it may have a serious impact on the vision of oncoming drivers, causing almost loss of visual perception and increasing the risk of traffic accidents.

[0003] However, existing technologies can only detect vehicles with high beams on and penalize their behavior, but there is no corresponding device or method for real-time adjustment of the light intensity and color temperature of tunnel lighting devices. When vehicles in tunnels turn on their high beams, many traffic accidents still occur, and driving safety is poor.

[0004] In view of this, the present invention is proposed. Summary of the Invention

[0005] The purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art and propose a high-beam linkage lighting device and method for a bidirectional, two-lane ordinary highway tunnel. Through a dynamic high-beam recognition system, vehicles with high beams on are identified in real time, and a delayed tunnel lighting adjustment system is used. Drivers of affected oncoming vehicles will receive smooth adjustments to the lighting device in the tunnel in advance before encountering vehicles with high beams on, thereby helping drivers adapt to light changes, reducing the irritation and discomfort caused by changes in the light intensity of the lighting device, and improving driving safety.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A high-beam linkage lighting device for a bidirectional, two-lane ordinary highway tunnel includes a dynamic high-beam recognition system, a delayed tunnel lighting adjustment system, and a wireless communication module, wherein the dynamic high-beam recognition system, the delayed tunnel lighting adjustment system, and the wireless communication module are connected via a wired or wireless connection.

[0008] The dynamic high beam recognition system is used to identify vehicles with high beams on in real time and calculate the traffic volume passing through each sampling point in the tunnel, the speed of each vehicle and the average speed of all vehicles;

[0009] The delayed tunnel lighting adjustment system is used to receive data information sent by the dynamic high beam recognition system, generate lighting control information, and adjust the light intensity and color temperature of each sampling point in the tunnel in real time according to the generated lighting control information;

[0010] The wireless communication module is used to realize data transmission between the dynamic high beam recognition system and the delayed tunnel lighting adjustment system.

[0011] Furthermore, the dynamic high beam recognition system includes an image acquisition module, a light intensity monitoring module and a data preprocessing unit.

[0012] The image acquisition module includes multiple cameras installed at the tunnel entrance and inside the tunnel, and the multiple cameras are arranged at equal intervals in the direction of incoming and outgoing vehicles. The cameras are used to collect image information of vehicles in the tunnel in real time;

[0013] The light intensity monitoring module includes an optical sensor that records changes in vehicle light intensity, and the optical sensor is used to monitor the light intensity of vehicles in the tunnel in real time;

[0014] The data pre-processing unit is used to receive data from the camera and optical sensor in real time, and calculate the traffic flow at each sampling point in the tunnel, the speed of each vehicle and the average speed of all vehicles in real time, as well as determine whether the vehicles in the tunnel have turned on their high beams and mark the high beam intensity of vehicles that have turned on their high beams;

[0015] The delayed tunnel lighting adjustment system includes a lighting device capable of adjusting light intensity and color temperature, a data processing unit and a lighting control device;

[0016] The lighting devices are installed on the top and sides of the tunnel;

[0017] The data processing unit is used to receive the output information of the data pre-processing unit in real time and generate lighting control information;

[0018] The lighting control system adjusts the light intensity and color temperature of the lighting device in real time according to the lighting control information.

[0019] In addition, the present invention also provides a lighting method for a high-beam linkage lighting device in a bidirectional two-lane ordinary highway tunnel, comprising the following steps:

[0020] Step 1: The dynamic high-beam recognition system identifies vehicles with high-beams on and their intensity in real time. It also calculates the traffic volume at each sampling point in the tunnel, the speed of each vehicle, and the average speed of all vehicles. This data is then sent to the delayed tunnel lighting adjustment system via a wireless communication module.

[0021] Step 2: The delayed tunnel lighting adjustment system receives data information from the dynamic high beam recognition system in real time, generates lighting control information, and adjusts the light intensity and color temperature of the lighting devices in the tunnel in real time according to the lighting control information.

[0022] Furthermore, the specific steps of step 1 are as follows:

[0023] Step 1.1 Use the camera installed in the tunnel to collect image information in real time;

[0024] Step 1.2. Use an optical sensor to monitor the light intensity of vehicles in the tunnel in real time and record the changes in light intensity.

[0025] Step 1.3. The data preprocessing unit identifies vehicles with high beams on and their light intensity based on the image information collected by the camera and the light intensity information from the optical sensor, and calculates the speed, average speed, and traffic volume of each vehicle at each sampling point in the tunnel.

[0026] Furthermore, the specific steps of step 2 are:

[0027] Step 2.1 When a sampling point detects a vehicle with high beams on, determine its light intensity a. Calculate the time difference |Tc| between the moment the high beam vehicle is detected at that sampling point and the moment the oncoming vehicle at the adjacent sampling point encounters the high beam vehicle, starting from the sampling point itself and proceeding in descending order. Terminate the calculation when |Tc| exceeds 60 seconds or the number of intervals from that sampling point exceeds 10.

[0028] Step 2.2 Calculate the vehicle lighting coefficient Ka of the corresponding sampling point based on the time difference |Tc|;

[0029] Step 2.3: Update the target lighting coefficient Km and state Bm of the sampling point in real time according to the single vehicle lighting coefficient Ka of the sampling point;

[0030] Step 2.4 updates the lighting control coefficient Kz of the lighting device in real time according to the target lighting coefficient Km and its state Bm of the sampling point;

[0031] Step 2.5: updating the light intensity and color temperature of the lighting device in real time according to the lighting control coefficient Kz of the lighting device;

[0032] Step 2.6: The lighting control system adjusts the light intensity and color temperature of the lighting device in real time based on the light intensity and color temperature information of the lighting device obtained in step 2.5.

[0033] Furthermore, in step 2.1, |Tc| is calculated as follows:

[0034] |Tc|=max(Ty[n],Td[m])+Te

[0035] Wherein, Ty[n] represents the time when the vehicle with high beams on reaches the nth sampling point in the direction of the oncoming vehicle, with the sampling point of the vehicle with high beams on as the origin and the direction of the oncoming vehicle as the sampling axis. Td[m] represents the time when the oncoming vehicle reaches the mth sampling point in the direction of the vehicle with high beams on.

[0036] Te represents the time difference from the moment when the vehicle with high beam lights arrives later and the sampling point closest to the road section where the vehicle with high beam lights meets the oncoming vehicle to the moment when the two vehicles meet;

[0037] The specific calculation method of Te is: compare the time it takes for the vehicle with high beams on to reach the sampling point closest to the encounter point with the oncoming vehicle. Assuming that the vehicle with high beams on arrives first, its average speed is v1, the lead time is T, the average speed of the oncoming vehicle is v2, and the distance between two adjacent sampling points is S, then Te = (S-v1×T) / (v1+v2).

[0038] Furthermore, in step 2.2, the calculation formula of the bicycle lighting coefficient Ka is:

[0039] Ka=a×f1(|Tc|)

[0040] Where f1 is a cubic linear function with a maximum value of 1 and a minimum value of 0, and a is the light intensity of a vehicle with high beam turned on.

[0041] Furthermore, in step 2.3, the target illumination coefficient Km is updated as follows:

[0042] (1) When a vehicle with high beams on appears and a new single vehicle lighting coefficient Ka appears at the sampling point closest to the encounter position of the oncoming vehicle in the direction of travel, the single vehicle lighting coefficient Ka is compared with its target lighting coefficient Km, and the maximum value is taken as the updated target lighting coefficient Km. If the single vehicle lighting coefficient Ka is greater than the target lighting coefficient Km, the update state Bm of the target lighting coefficient Km is set to 1, indicating that it is being updated.

[0043] (2) When a vehicle with high beams turned on does not leave the camera field of view at the sampling point, the high beam status of the vehicle is continuously judged, and when the high beams are turned on, the new single vehicle lighting coefficient Ka is continuously calculated and the target lighting coefficient Km is updated.

[0044] Furthermore, in step 2.4, the target illumination coefficient Kz is updated as follows:

[0045] (1) When the target lighting coefficient Km of a sampling point is different from the lighting control coefficient Kz and the update state Bm corresponding to the target lighting coefficient Km is 1, the lighting control coefficient Kz gradually changes to the target lighting coefficient Km;

[0046] (2) When the lighting control coefficient Kz is consistent with the target lighting coefficient Km, set the target lighting coefficient Km and the update state Bm to 0, and keep the lighting control coefficient Kz unchanged for 10 seconds, and then gradually reduce it to 0;

[0047] (3) When the target lighting coefficient Km is updated, the above process (2) is interrupted and the lighting control coefficient Kz is gradually changed to the target lighting coefficient Km.

[0048] Furthermore, the step 2.5 is specifically as follows:

[0049] Ilight=Ibase+k*max(0,(Kz-Ts))

[0050] Where Ilight is the adjusted lighting intensity, Ibase is the basic lighting intensity, k is the light intensity control coefficient, Kz is the lighting control coefficient, and Ts is the minimum threshold for light intensity adjustment;

[0051] Clight=Cbase+m*max(0,(Kz-Ta))

[0052] Among them, Clight is the adjusted color temperature, Cbase is the base color temperature, m is the color temperature adjustment coefficient, Kz is the lighting control coefficient, and Ta is the minimum threshold for color temperature adjustment.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] The present invention provides a high-beam linkage lighting device and method for a bidirectional, two-lane, ordinary highway tunnel. This device utilizes a dynamic high-beam recognition system and a delayed tunnel lighting adjustment system to implement dynamic delayed lighting within the tunnel, mitigating the negative effects of high-beam lighting. When drivers of oncoming vehicles encounter high-beam lighting, they will experience a gradual adjustment of the tunnel lighting before encountering a high-beam vehicle. Prior to meeting the vehicle, the tunnel lighting intensity steadily increases, making it easier for drivers of oncoming vehicles to adapt to the high-beam lighting and reducing the irritation caused by rapid changes in the tunnel lighting intensity. After the meeting, the lighting intensity also gradually decreases to normal lighting, helping drivers adapt to the light changes and reducing the irritation and discomfort caused by the subsequent changes in the lighting intensity. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] The accompanying drawings are incorporated in and constitute a part of this specification and, together with the description, serve to explain the principles of the invention.

[0056] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0057] Figure 1 This is an overall flow chart of a method for a high-beam linkage lighting device for a bidirectional, two-lane ordinary highway tunnel provided by the present invention;

[0058] Figure 2 A flow chart of a dynamic high beam recognition system in a lighting method for a high beam linkage lighting device for a bidirectional, two-lane ordinary highway tunnel provided by the present invention;

[0059] Figure 3 This is a flow chart of a delayed tunnel lighting adjustment system in a lighting method for a high-beam linkage lighting device in a bidirectional, two-lane ordinary highway tunnel provided by the present invention. DETAILED DESCRIPTION

[0060] Here, exemplary embodiments will be described in detail, and the embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are only examples of devices consistent with some aspects of the present invention as detailed in the appended claims.

[0061] Please refer to Figure 1 This embodiment provides a bidirectional, two-lane ordinary highway tunnel high-beam linkage lighting device, including a dynamic high-beam recognition system, a delayed tunnel lighting adjustment system, a wireless communication module, a power management system, and a monitoring and feedback system. The dynamic high-beam recognition system, the delayed tunnel lighting adjustment system, the wireless communication module, and the power management system are connected to the monitoring and feedback system via wired or wireless means.

[0062] In the entire device, the sampling point is the location where the image acquisition module and the light intensity monitoring module are installed.

[0063] The dynamic high beam recognition system is used to identify vehicles with high beams on in real time, mark the light intensity of vehicles with high beams on, and calculate the traffic flow passing through each sampling point in the tunnel, the speed of each vehicle and the average speed of all vehicles.

[0064] The dynamic high-beam recognition system includes an image acquisition module, a light intensity monitoring module, and a data preprocessing unit. The image acquisition module consists of multiple cameras installed at the tunnel entrance and inside the tunnel, evenly spaced from both oncoming and outgoing traffic. To ensure coverage of all lanes, the cameras shoot at a standard angle of -15 to -30 degrees. High-resolution cameras with excellent low-light performance (such as CMOS or CCD cameras) are used to capture real-time images of vehicles in the tunnel.

[0065] The light intensity monitoring module includes a high-sensitivity photoelectric sensor, which is synchronized with the camera's position and shooting angle to ensure that the vehicle's light source can be captured. It then cooperates with the camera to monitor the light intensity of vehicles in the tunnel in real time and record changes in light intensity.

[0066] The data preprocessing unit includes a high-performance microprocessor or embedded system, which is used to receive data from cameras and optical sensors in real time, and calculate the traffic flow at each sampling point in the tunnel, the speed of each vehicle and the average speed of all vehicles in real time, as well as determine whether the vehicles in the tunnel have turned on their high beams and mark the high beam intensity of vehicles that have turned on their high beams.

[0067] The delayed tunnel lighting adjustment system receives data from the dynamic high-beam recognition system, generates lighting control information, and adjusts the light intensity and color temperature of the tunnel lighting devices in real time based on the generated lighting control information. Specifically, the delayed tunnel lighting adjustment system includes lighting devices capable of adjusting light intensity and color temperature, a data processing unit, and a lighting control system.

[0068] Specifically, the lighting device is a high-intensity dimmable LED lamp that supports adjustment of light intensity and color temperature. It is evenly distributed along the top and sides of the tunnel to ensure that the lighting covers the entire lane.

[0069] The data processing unit is used to receive the output information of the data pre-processing unit in real time and generate lighting control information.

[0070] The lighting control system remotely controls and automatically adjusts the lighting device according to the lighting control information, realizing real-time adjustment of the light intensity and color temperature of the lighting device.

[0071] The wireless communication module is used to enable data transmission between the dynamic high-beam recognition system and the delayed tunnel lighting adjustment system, ensuring real-time data sharing and processing. Specifically, the wireless communication module can be Wi-Fi, Zigbee, or LoRa.

[0072] The monitoring and feedback system is a visual interface for operators to view the system status and adjust parameters in the entire device. It is used to monitor the system operation status in real time, record data and provide feedback.

[0073] The power management system provides stable power to all devices to ensure the normal operation of the entire device. It has overload protection and voltage regulation functions to improve the reliability of the entire device.

[0074] In addition, this embodiment also provides a lighting method for a high-beam linkage lighting device in a bidirectional two-lane ordinary highway tunnel, comprising the following steps:

[0075] Step 1: Please refer to Figure 1 and Figure 2 The dynamic high beam recognition system identifies vehicles with high beams on and their light intensity in real time, calculates the traffic volume at each sampling point in the tunnel, the speed of each vehicle and the average speed of all vehicles, and sends this data information to the delayed tunnel lighting adjustment system through the wireless communication module.

[0076] Step 1.1 Use the camera installed in the tunnel to collect image information in real time;

[0077] Step 1.2. Use an optical sensor to monitor the light intensity of vehicles in the tunnel in real time and record the changes in light intensity.

[0078] Step 1.3. The data preprocessing unit identifies vehicles with high beams on and their light intensity based on the image information collected by the camera and the light intensity information from the optical sensor, and calculates the speed, average speed, and traffic volume of each vehicle at each sampling point in the tunnel.

[0079] The video captured by the camera uses the YOLO algorithm and deepsort algorithm to perform vehicle recognition, obtain vehicle trajectory generation and average speed.

[0080] In step 1.3, the speed of each vehicle at each sampling point is calculated by using the deepsort algorithm to obtain the trajectory of each vehicle passing through each sampling point. The distance between the vehicle and the sampling point is calculated using a pre-marked scale to further calculate the vehicle speed. The average speed at each sampling point is calculated as: the sum of the average speeds of all vehicles at that sampling point / the number of vehicles at that sampling point.

[0081] The light intensity information collected by the photoelectric sensor is used to determine whether the high beam is on and record the high beam intensity of the vehicle. The vehicle's high beam is determined based on whether the vehicle's light intensity exceeds the maximum light intensity threshold. This threshold is a parameter that can be adjusted based on actual usage.

[0082] Specifically, in step 1.3, the specific method for identifying the high beam is as follows: set L 最大光强阈值 , the light intensity value L collected by the photoelectric sensor 光强 With L 最大光强阈值 In comparison, if L 光强 >L 最大光强阈值 , confirm that the high beam is on, use the YOLO algorithm to identify the vehicle with the high beam on in the video captured by the camera, and output the result as all the detected vehicles with the high beam on, and mark them as the high beam on state, and set their light intensity L 光强 =Photoelectric sensor reading.

[0083] Step 2: Please refer to Figure 1 and Figure 3 The delayed tunnel lighting adjustment system receives the data information sent by the dynamic high beam recognition system in real time, generates lighting control information, and adjusts the light intensity and color temperature of the lighting devices in the tunnel in real time according to the lighting control information.

[0084] The delayed dynamic lighting of the delayed tunnel lighting adjustment system is based on the time difference |Tc| between the moment a high-beam vehicle is detected and the moment an oncoming vehicle encounters the high-beam vehicle. The lighting device is adjusted most strongly when the vehicle encounters the high-beam vehicle. The adjustment gradually increases from the default value before the encounter and gradually returns to the default value after the encounter, allowing the oncoming vehicle to gradually adapt to the high-intensity lighting. The lighting is gradually restored after the encounter ends. The details are as follows:

[0085] Step 2.1 When the high beam of a vehicle is detected at a certain sampling point, determine its light intensity a. Calculate the time difference |Tc| between the moment when the oncoming vehicle meets the high beam vehicle and the moment when the high beam vehicle is detected, in order of proximity to the sampling point where the high beam vehicle is detected. Finally, obtain the time series |Tc[n]| with this sampling point as the origin and adjacent sampling points as axes. Since the meeting of the oncoming vehicle and the high beam vehicle may not occur in the future, the absolute value is used to represent the time intervals of vehicles approaching and leaving the high beam vehicle simultaneously. Stop the calculation when |Tc| > 60s or the number of intervals from this sampling point exceeds n, where n is defaulted to 10 and can be adjusted according to the actual distance between sampling points, etc.

[0086] The specific calculation method of the time |Tc| is as follows:

[0087] Taking the sampling point where the high beam vehicle is located as the origin, calculate the time Ty[1] from the sampling point where the high beam vehicle is located to the first sampling point in the direction of the oncoming vehicle. At the same time, calculate the time Td[1] from the sampling point of the oncoming vehicle to the first sampling point in the direction of the high beam vehicle. Compare the magnitudes of Ty[1] and Td[1], and the one with less time moves forward again to calculate the time required to reach the next sampling point. Calculate successively until the sampling points calculated by both coincide. At this time, compare the magnitudes of the times Ty[n] and Td[m] calculated by both, and the one with more time retreats one sampling point. Assume Ty[n] < Td[m], then the sampling point in the direction of the oncoming vehicle towards the high beam vehicle retreats one point backward to the (m - 1)-th sampling point in the direction of the high beam vehicle, and the time for retreat is Td[m - 1]. At this time, due to the recursive relationship, Td[m - 1] < Ty[n] < Td[m] is satisfied. At this time, the high beam vehicle reaches the n-th sampling point in the direction of the oncoming vehicle, and the time used is Ty[n]. The oncoming vehicle reaches the (m - 1)-th sampling point in the direction of the high beam vehicle, and the time used is Td[m - 1]. Finally, calculate the time Te from when the high beam vehicle reaches the n-th sampling point to when the two vehicles meet. The specific calculation method of the time |Tc| is:

[0088] |Tc| = max(Ty[n], Td[m]) + Te

[0089] Ty[n] represents the time it takes for the high-beam vehicle to reach the nth sampling point in that direction, with the sampling point of the high-beam vehicle as the origin and the direction of the oncoming vehicle as the sampling axis. Since oncoming vehicles are both in front of and behind the high-beam vehicle, the sampling axis is the direction of the oncoming vehicle. Td[m] represents the time it takes for the oncoming vehicle to reach the mth sampling point in that direction, with the sampling point of the oncoming vehicle as the origin and the sampling axis from the oncoming vehicle's sampling point to the high-beam vehicle.

[0090] Te represents the time difference from the moment when the vehicle arriving later with the high beam lights reaches the sampling point closest to the position where the oncoming vehicle meets to the moment when the two vehicles meet.

[0091] The time Ty[n] when a vehicle with its high beam on arrives at a certain sampling point in its travel direction is calculated based on its real-time speed and the traffic flow and average speed of the first n sampling points in its travel direction.

[0092] Ty[n] is calculated as follows: A GRU model is trained and used, with the input being the current speed of vehicles with high beams on at the sampling point, the average speed and volume of vehicles at the sampling point with high beams on, and the volume and average speed of the previous n sampling points in the direction of travel. The GRU network parameters are set to two layers, with 64 and 32 nodes respectively. The tanh activation function is used, and the mean square error (MSE) is used as the loss function. The final output is a single node representing the average speed of vehicles with high beams on at the nth sampling point. The arrival time Ty[n] is calculated as the distance between the n sampling points divided by the average speed at the nth sampling point.

[0093] The time Td[n] is calculated as the sum of the time it takes for oncoming vehicles to pass each two adjacent sampling points. The time it takes for oncoming vehicles to pass each two adjacent sampling points is calculated based on the distance between the two sampling points, the average speed, and the traffic volume. Specifically, the distance between the two sampling points is divided by the calculated average speed. The average speed is calculated by multiplying the average speed of the two sampling points, the absolute value of the average speed difference, and the traffic volume by a fifth-order eigenvector. This eigenvector is used as a training and learning parameter for the network, and the Mean Sequential Equation (MSE) is used as the loss function.

[0094] The specific calculation method for the time Te required from the vehicle with high beams on reaching the nth sampling point to the encounter of the two vehicles is: compare the time it takes for the vehicle with high beams on to reach the sampling point closest to the encounter position with the oncoming vehicle. Assuming that the vehicle with high beams on arrives first, its average speed is v1, the lead time is T, the average speed of the oncoming vehicle is v2, and the distance between two adjacent sampling points is S, then Te = (S-v1×T) / (v1+v2).

[0095] Step 2.2 calculates the vehicle lighting coefficient Ka of the adjacent sampling points in step 2.1 according to the time difference |Tc|.

[0096] The calculation formula of bicycle lighting coefficient Ka is:

[0097] Ka=a×f1(|Tc|)

[0098] Where f1 is a cubic linear function with a maximum value of 1 and a minimum value of 0, and a is the light intensity of a vehicle with high beam turned on.

[0099] Specifically, f1 = -(t-60)(t+60) / 3600, the peak is 1 at 0 and 0 at ±60.

[0100] Step 2.3: Update the target lighting coefficient Km and state Bm of the sampling point in real time according to the single vehicle lighting coefficient Ka of the sampling point;

[0101] The target lighting coefficient Km is updated as follows:

[0102] (1) When a vehicle with high beams on appears and a new single vehicle lighting coefficient Ka appears at the sampling point closest to the encounter position of the oncoming vehicle in the direction of travel, the single vehicle lighting coefficient Ka is compared with its target lighting coefficient Km, and the maximum value is taken as the updated target lighting coefficient Km. If the single vehicle lighting coefficient Ka is greater than its target lighting coefficient Km, the update state Bm of the target lighting coefficient Km is set to 1, indicating that it is being updated;

[0103] (2) When a vehicle with high beams turned on does not leave the camera field of view at the sampling point, the high beam status of the vehicle with high beams turned on is continuously judged, and the new single vehicle lighting coefficient Ka is continuously calculated when the high beams are turned on, and the target lighting coefficient Km is updated.

[0104] Step 2.4 updates the target lighting coefficient Km and state Bm of the lighting device in real time according to the single vehicle lighting coefficient Ka at the sampling point;

[0105] The lighting control coefficient Kz actually controls the illumination of the lighting device and is affected by the target lighting coefficient Km. The target lighting coefficient Km is the target of the lighting control coefficient adjustment. The target lighting coefficient Kz is updated as follows:

[0106] (1) When the target lighting coefficient Km of a sampling point is different from the lighting control coefficient Kz and the update state Bm corresponding to its target lighting coefficient Km is 1, the lighting control coefficient Kz gradually changes to the target lighting coefficient Km;

[0107] During this process, the default change speed of the lighting control coefficient Kz is: V 变 =-(t-10)(t+10) / 100, where t is the adjustment time.

[0108] The coefficients of this formula can be adjusted in advance through subjective experiments in the deployment tunnel to achieve a better transition of lighting changes.

[0109] The lighting control coefficient Kz gradually changes to the target lighting coefficient Km within 10 seconds;

[0110] (2) When the lighting control coefficient Kz is consistent with the target lighting coefficient Km, set the target lighting coefficient Km and the update state Bm to 0, and keep the lighting control coefficient Kz unchanged for 10 seconds, and then gradually reduce it to 0;

[0111] In this process, the formula for returning the lighting control coefficient Kz to zero is a cubic linear function, with 0 as the 0 point, the original value of Kz as 1 point, and the change speed of the lighting control coefficient Kz V 变 Defaults to

[0112] V 变 =-(t-30)(t+30) / 900, where t is the adjustment time.

[0113] The coefficients of this formula can be adjusted in advance through subjective experiments in the deployment tunnel to achieve a better transition of lighting changes.

[0114] (3) When the target lighting coefficient Km is updated, the above process (2) is interrupted, and the lighting control coefficient Kz gradually changes to the target lighting coefficient Km; the change speed formula is a cubic linear function with a maximum value of 1 and a minimum value of 0.

[0115] In this process, the changing speed of the lighting control coefficient Kz is the same as that in step (1) by default.

[0116] After the lighting control coefficient Kz of each sampling point is confirmed, the actual lighting control coefficient of the lighting device between the sampling points is calculated by linear difference.

[0117] Step 2.5 updates the light intensity and color temperature of the lighting device according to the lighting control coefficient Kz of the lighting device.

[0118] After determining the lighting control coefficient Kz for the lighting device, the lighting control system updates the lighting device's light intensity and color in real time. Before meeting other vehicles, to reduce visual interference caused by high beams, the lighting device's light intensity is gradually increased to ensure a clear field of vision and protect driving safety. Furthermore, to reduce visual irritation caused by high brightness, the color temperature is adjusted from cool white light (e.g., 6000K) to warm white light (e.g., 3000K) to reduce visual fatigue and discomfort. After the meeting, the lighting device's light intensity is gradually reduced to normal lighting to help the driver adapt to the light change and reduce irritation and discomfort caused by the subsequent change in lighting intensity.

[0119] The specific calculation method of the light intensity and color temperature of the lighting device is as follows:

[0120] Light intensity calculation formula:

[0121] Ilight=Ibase+k*max(0,(Kz-Ts))

[0122] Among them, Ilight is the adjusted lighting intensity, Ibase is the basic lighting intensity, k is the light intensity control coefficient, Kz is the lighting control coefficient, and Ts is the minimum threshold for light intensity adjustment. k and Ts are parameters that can be adjusted according to the actual use effect.

[0123] Color temperature adjustment formula:

[0124] Clight=Cbase+m*max(0,(Kz-Ta))

[0125] Among them, Clight is the adjusted color temperature, Cbase is the basic color temperature, m is the color temperature adjustment coefficient, Kz is the lighting control coefficient, Ta is the minimum threshold for color temperature adjustment. m and Ta are parameters that can be adjusted according to the actual use effect.

[0126] In step 2.6, the lighting control system adjusts the intensity and color temperature of the lighting device in real time based on the intensity and color temperature information obtained in step 2.5, to implement dynamic delayed lighting in the tunnel to reduce the negative impact of high beams. Drivers of oncoming vehicles will receive advance tunnel lighting adjustments before encountering vehicles with high beams on, allowing for a more stable increase in the intensity of the lighting device. This reduces the irritation caused by rapid changes in the intensity of the lighting device, making it easier to adapt to the effects of high beams and improving driving safety. After the meeting, the intensity of the lighting device is also gradually reduced to normal lighting to help drivers adapt to the light changes and reduce the irritation and discomfort caused by the change in the intensity of the lighting device.

[0127] The above are only specific embodiments of the present invention to enable those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention.

[0128] It should be understood that the present invention is not limited to the above description and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for high-beam linkage lighting in a bidirectional, two-lane ordinary highway tunnel, characterized in that: The following steps are involved: Step 1: The dynamic high-beam recognition system identifies vehicles with high-beams on and their intensity in real time. It also calculates the traffic volume at each sampling point in the tunnel, the speed of each vehicle, and the average speed of all vehicles. This data is then sent to the delayed tunnel lighting adjustment system via a wireless communication module. Step 2: The delayed tunnel lighting adjustment system receives data from the dynamic high beam recognition system in real time and generates lighting control information. Based on the lighting control information, the system adjusts the light intensity and color temperature of the lighting devices in the tunnel in real time. The specific steps of step 2 are as follows: Step 2.1 When a sampling point detects a vehicle with high beams on, determine its light intensity a. Calculate the time difference |Tc| between the moment the high beam vehicle is detected at that sampling point and the moment the oncoming vehicle at the adjacent sampling point encounters the high beam vehicle, starting from the sampling point itself and proceeding in descending order. Terminate the calculation when |Tc| exceeds 60 seconds or the number of intervals from that sampling point exceeds 10. In step 2.1, |Tc| is calculated as follows: Among them, Ty[n] represents the time when the vehicle with high beam lights on reaches the nth sampling point in the direction with the sampling point where the vehicle with high beam lights on is located as the origin and the direction of the oncoming vehicle is the sampling axis. Indicates the direction from the sampling point of the oncoming vehicle to the vehicle with the high beam turned on. The time of each sampling point; It represents the time difference from the moment when the vehicle with high beam lights arrives later and the sampling point closest to the road section where the vehicle with high beam lights meets the oncoming vehicle to the moment when the two vehicles meet; described The specific calculation method is: compare the time it takes for the vehicle with high beam lights on to reach the sampling point closest to the encounter position with the oncoming vehicle. Assuming that the vehicle with high beam lights on arrives first, its average speed is v1, the leading time is T, the average speed of the oncoming vehicle is v2, and the distance between two adjacent sampling points is S, then =(S-v1×T) / (v1+v2); Step 2.2 Calculate the vehicle lighting coefficient Ka of the corresponding sampling point based on the time difference |Tc|; In step 2.2, the calculation formula of the vehicle lighting coefficient Ka is: Ka=a×f1(|Tc|) Where f1 is a cubic linear function with a maximum value of 1 and a minimum value of 0, and a is the light intensity of the vehicle with high beam turned on; Step 2.3: Update the target lighting coefficient Km and state Bm of the sampling point in real time according to the single vehicle lighting coefficient Ka of the sampling point; In step 2.3, the target illumination coefficient Km is updated as follows: (1) When a vehicle with high beams on appears and a new single vehicle lighting coefficient Ka appears at the sampling point closest to the encounter position of the oncoming vehicle in the direction of travel, the single vehicle lighting coefficient Ka is compared with its target lighting coefficient Km, and the maximum value is taken as the updated target lighting coefficient Km. If the single vehicle lighting coefficient Ka is greater than the target lighting coefficient Km, the update status Bm of the target lighting coefficient Km is set to 1, indicating that it is being updated; (2) When a vehicle with high beams turned on does not leave the camera field of view at the sampling point, the high beam status of the vehicle is continuously judged, and when the high beams are turned on, the new single vehicle lighting coefficient Ka is continuously calculated and the target lighting coefficient Km is updated; Step 2.4 Update the lighting control coefficient Kz of the lighting device in real time according to the target lighting coefficient Km and its state Bm of the sampling point; In step 2.4, the lighting control coefficient Kz is updated as follows: (1) When the target lighting coefficient Km of a sampling point is different from the lighting control coefficient Kz and the update state Bm corresponding to the target lighting coefficient Km is 1, the lighting control coefficient Kz gradually changes to the target lighting coefficient Km; (2) When the lighting control coefficient Kz is consistent with the target lighting coefficient Km, set the target lighting coefficient Km and the update state Bm to 0, and keep the lighting control coefficient Kz unchanged for 10 seconds, and then gradually reduce it to 0; (3) When the target lighting coefficient Km is updated, the above process (2) is interrupted and the lighting control coefficient Kz is gradually changed to the target lighting coefficient Km; Step 2.5: Update the light intensity and color temperature of the lighting device in real time according to the lighting control coefficient Kz of the lighting device; The step 2.5 is specifically as follows: Ilight=Ibase+k*max(0,(Kz-Ts)) Where Ilight is the adjusted lighting intensity, Ibase is the basic lighting intensity, k is the light intensity control coefficient, Kz is the lighting control coefficient, and Ts is the minimum threshold for light intensity adjustment; Clight=Cbase+m*max(0,(Kz-Ta)) Where Clight is the adjusted color temperature, Cbase is the base color temperature, m is the color temperature adjustment coefficient, Kz is the lighting control coefficient, and Ta is the minimum threshold for color temperature adjustment. Step 2.6 The lighting control system adjusts the light intensity and color temperature of the lighting device in real time based on the light intensity and color temperature information of the lighting device obtained in step 2.

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2. The method for high beam linkage lighting in a bidirectional two-lane ordinary highway tunnel according to claim 1, characterized in that: The specific steps of step 1 are as follows: Step 1.1 Use the camera installed in the tunnel to collect image information in real time; Step 1.

2. Use an optical sensor to monitor the light intensity of vehicles in the tunnel in real time and record the changes in light intensity. Step 1.

3. The data preprocessing unit identifies vehicles with high beams on and their light intensity based on the image information collected by the camera and the light intensity information from the optical sensor, and calculates the speed, average speed, and traffic volume of each vehicle at each sampling point in the tunnel.

3. A lighting device for realizing the high beam linkage lighting method for a bidirectional two-lane ordinary highway tunnel as claimed in claim 1 or 2, characterized in that: It includes a dynamic high beam recognition system, a delayed tunnel lighting adjustment system and a wireless communication module, wherein the dynamic high beam recognition system, the delayed tunnel lighting adjustment system and the wireless communication module are connected via a wired or wireless manner; The dynamic high beam recognition system is used to identify vehicles with high beams on in real time and calculate the traffic volume passing through each sampling point in the tunnel, the speed of each vehicle and the average speed of all vehicles; The delayed tunnel lighting adjustment system is used to receive data information sent by the dynamic high beam recognition system, generate lighting control information, and adjust the light intensity and color temperature of each sampling point in the tunnel in real time according to the generated lighting control information; The wireless communication module is used to realize data transmission between the dynamic high beam recognition system and the delayed tunnel lighting adjustment system.

4. The lighting device according to claim 3, characterized in that The dynamic high beam recognition system includes an image acquisition module, a light intensity monitoring module and a data preprocessing unit. The image acquisition module includes multiple cameras installed at the tunnel entrance and inside the tunnel, and the multiple cameras are arranged at equal intervals in the direction of incoming and outgoing vehicles. The cameras are used to collect image information of vehicles in the tunnel in real time; The light intensity monitoring module includes an optical sensor that records changes in vehicle light intensity, and the optical sensor is used to monitor the light intensity of vehicles in the tunnel in real time; The data pre-processing unit is used to receive data from the camera and optical sensor in real time, and calculate the traffic flow at each sampling point in the tunnel, the speed of each vehicle and the average speed of all vehicles in real time, as well as determine whether the vehicles in the tunnel have turned on their high beams and mark the light intensity of vehicles with their high beams turned on; The delayed tunnel lighting adjustment system includes a lighting device capable of adjusting light intensity and color temperature, a data processing unit and a lighting control system; The lighting devices are installed on the top and sides of the tunnel; The data processing unit is used to receive the output information of the data pre-processing unit in real time and generate lighting control information; The lighting control system adjusts the light intensity and color temperature of the lighting device in real time according to the lighting control information.

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