Driving load identification and regulation method based on tunnel entrance and exit

Abstract

The invention relates to the technical field of intelligent traffic and vehicle safe driving, in particular to the field of driver driving load identification and intelligent regulation and control. Comprising the following steps: step 1, data acquisition, including vehicle real-time speed V, driver age information A, continuous driving duration T, tunnel external illumination L < external > and tunnel internal illumination L < internal >; 2, determining the illumination L < outside > outside the tunnel and the illumination L < inside > inside the tunnel, and calculating the influence intensity E of the black hole effect or the white hole effect; 3, the heart rate growth rate H is calculated; 4, the driving load condition of the driver is judged according to the heart rate growth rate H of the driver, and the sound-touch dual-mode sensing intelligent cabin and the three-dimensional annular lamp strip set are regulated and controlled according to the load condition. According to the driving load identification and regulation and control method based on the tunnel entrance and exit, the driving load can be accurately identified, the driving pressure of a driver at the tunnel entrance and exit is relieved, the driving safety is guaranteed, and the driving comfort is improved.

Description

Technical Field

[0001] This invention relates to the fields of intelligent transportation and safe driving technology, specifically to the field of driver load identification and intelligent control. Background Technology

[0002] Driving in tunnels presents drivers with a complex array of challenges that seriously threaten driving safety and comfort. Lighting is paramount, with the "black hole effect" and "white hole effect" posing significant challenges at tunnel entrances and exits. When a vehicle enters a dimly lit tunnel from bright light, the "black hole effect" occurs, momentarily impairing the driver's vision and making it difficult to see road conditions, signs, and other vehicles, drastically increasing driving risk. Conversely, when exiting a tunnel, the sudden influx of bright natural light triggers the "white hole effect," causing temporary visual "white blindness" and hindering the driver's ability to accurately assess the external environment. This rapid change in light not only increases the difficulty of visual adaptation but also easily leads to visual fatigue, significantly distracting the driver and potentially causing traffic accidents.

[0003] Fatigue from prolonged driving cannot be ignored. The relatively enclosed environment of a tunnel, lacking rich external visual stimulation, easily induces drowsiness in drivers. In the event of an emergency, a fatigued driver is less likely to react correctly in time, leading to accidents. Furthermore, driver age is a significant factor affecting driving safety: younger drivers typically have stronger visual adaptation abilities, while older drivers experience a decline in visual and physical functions, making them less adaptable to changes in light. They require more time to adjust their vision when driving in a tunnel, undoubtedly increasing driving risks. The varying perception and response capabilities of drivers of different age groups to changes in light and driving load further complicate tunnel driving.

[0004] In conclusion, these factors are intertwined and seriously affect the safety and comfort of driving in tunnels. Summary of the Invention

[0005] The present invention aims to provide a method for identifying and controlling driving load based on tunnel entrances and exits, so as to accurately identify driving load, alleviate driving pressure faced by drivers at tunnel entrances and exits, ensure driving safety, and improve driving comfort.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a method for identifying and controlling driver load based on tunnel entrances and exits, comprising the following steps: Step 1: Data acquisition. The data includes the vehicle's real-time speed V, driver's age information A, continuous driving duration T, and tunnel external illuminance L. 外 Illumination L inside the tunnel内 ; Step 2: Determine the external illuminance L of the tunnel. 外 Illumination L inside the tunnel 内 Calculate the intensity E of the "black hole effect" or "white hole effect"; Step 3: Calculate the heart rate growth rate H using the following formula:

[0007]

[0008] In the above formula, H 进 With H 出 V represents the driver's heart rate growth rate when entering and exiting the tunnel. 进 With V 出 These are the vehicle speeds collected before the vehicle enters and exits the tunnel, E 进 For the "black hole effect", E 出 The intensity of the "white hole effect"; Step 4: Determine the driver's driving load based on the driver's heart rate growth rate H, and adjust the "sound-touch" dual-modal sensing intelligent cockpit and three-dimensional ring light strip group according to the load status.

[0009] The beneficial effects of this plan are: 1. Precise Assessment Based on Multi-Factor Integration: This invention constructs a comprehensive and scientific driving load assessment system by comprehensively collecting data from multiple aspects, including illuminance inside and outside the tunnel, vehicle speed, driver age, and fatigue level. When calculating the heart rate growth rate, the formula comprehensively considers factors such as vehicle speed and illuminance. The quadratic and cubic terms of speed in the heart rate growth rate formula reflect the impact of vehicle speed on the driver's psychological and physiological state, while the illuminance-related and logarithmic terms meticulously depict the effect of changes in the lighting environment on the driver's heart rate. Simultaneously, visual adaptation coefficients are assigned to different intervals based on the driver's age, and fatigue level coefficients are determined based on fatigue status. Furthermore, the intensity of the "black hole effect" or "white hole effect" is calculated by combining illuminance differences, comprehensively and accurately assessing driving load from multiple dimensions, making the assessment of driving load more accurate.

[0010] 2. Real-time dynamic control: This invention has the ability to control in real time. It collects various data in real time during the process of vehicles entering and exiting tunnels. Once the driving load level changes, it can immediately trigger corresponding control measures, allowing the driver to quickly become alert and adjust the driving state, effectively ensuring driving safety.

[0011] 3. Multi-dimensional coordinated control: The control system of this invention includes a three-dimensional ring light strip group and a "sound-touch" dual-modal sensing intelligent cockpit, realizing multi-dimensional coordinated control and multi-sensory coordinated stimulation, allowing the driver to quickly adapt to changes in driving load and ensuring driving safety.

[0012] 4. Wide range of applications and practical advantages. This invention has a wide range of applications and practicality. Regardless of tunnel length or traffic volume, as long as vehicles are traveling at tunnel entrances and exits, this invention can function effectively. Under different weather conditions, even with factors affecting driving such as rain, the system can operate normally by simply referencing changes in illumination inside and outside the tunnel and vehicle driving conditions. For drivers of different ages, the system can accurately assess and adjust driving load based on their individual characteristics.

[0013] Furthermore, the formula for calculating the intensity E of the "black hole effect" or "white hole effect" is as follows:

[0014] In the formula, E represents the intensity of the "black hole effect" or "white hole effect," and L... 内 L represents the illumination level inside the tunnel. 外 For the external illuminance of the tunnel, T i A is the fatigue coefficient. i This is the visual adaptation coefficient.

[0015] The beneficial effects of this solution are as follows: By integrating the difference in illumination inside and outside the tunnel, driver fatigue levels, and visual adaptability, this solution can accurately quantify the impact of illumination changes on driver vision through multi-factor fusion, providing reliable data support for driving load assessment. This dynamic control based on accurate calculation effectively alleviates driver visual stress, reduces accident risks, and improves tunnel driving safety. Regardless of changes in illumination such as day and night, seasonal changes, or drivers of different ages and fatigue levels, the E-value calculation results can be dynamically adjusted according to individual circumstances, ensuring the stable and accurate operation of the driving load identification and control system in complex scenarios. This provides adaptability for various types of drivers, improving the system's versatility and practicality. Furthermore, the fatigue coefficient T i Classified according to continuous driving time T: Continuous driving time The fatigue level is defined as the driver being not fatigued, with a fatigue coefficient T1 of 1.0. Continuous driving time This is defined as mild driver fatigue, with a fatigue coefficient T2 of 1.2. Continuous driving time The fatigue level is defined as severe or above fatigue of the driver, with a fatigue coefficient T3 of 1.5.

[0016] The beneficial effects of this solution are as follows: The quantification method of this invention avoids the ambiguity of subjective judgment, providing reliable basic data for the accurate calculation of subsequent driving load, making driving load assessment more scientific and accurate. In actual driving, using the impact of continuous driving time on driver fatigue levels for classification is simple, intuitive, and easy to apply. It can accurately capture the trend of driver fatigue changes, enabling the driving load identification and control system to respond to different levels of fatigue in real time and effectively, enhancing the system's practicality and adaptability in real-world environments. At a macro level, by collecting and analyzing fatigue level coefficient data from different drivers, the distribution of fatigued driving can be understood. Relevant management departments can then specifically set up fatigued driving warning signs, construct rest areas and other infrastructure, and formulate more reasonable traffic management policies to effectively reduce fatigued driving behavior and improve road traffic safety.

[0017] Furthermore, the visual adaptation coefficient A i Classified by driver's age: Drivers aged 18-30 are defined as young drivers, and the visual adaptation coefficient... ; Drivers aged 30-40 are defined as young and middle-aged drivers, and the visual adaptation coefficient... ; Drivers aged 40-50 are defined as middle-aged drivers, and the visual adaptation coefficient... ; Drivers aged 50-65 are defined as middle-aged and elderly drivers, and the visual adaptation coefficient... ; Drivers aged 65 and above are defined as elderly drivers, and the visual adaptation coefficient... .

[0018] The beneficial effects of this solution are as follows: This invention fully considers the physiological differences in visual adaptation ability among people of different ages. This segmentation method can accurately reflect the differences in visual adaptation ability of drivers of different ages, making driving load assessment more in line with individual actual conditions, improving the accuracy of assessment, and at the same time reflecting the care of the transportation system for different groups of people, promoting the humanized development of the transportation system.

[0019] At the same time, it not only takes into account the actual physiological differences of drivers during the driving process, but also uses technical means to provide suitable driving environments and safety guarantees for drivers of different ages, making the transportation system more inclusive and friendly, which helps to improve the acceptance and trust of all drivers in intelligent transportation systems and promote the widespread application and development of intelligent transportation technology.

[0020] Furthermore, the driver's workload is divided into low load, medium load, and high load, with the following criteria: When the driver's heart rate growth rate H is ≤5%, the driver's driving load is defined as low load; When the driver's heart rate growth rate H is in the range of 5%-10%, the driver's driving load is defined as medium load; When the driver's heart rate growth rate H is ≥10%, the driver's driving load is defined as high load.

[0021] The beneficial effects of this solution are as follows: by using the heart rate growth rate (H) as a quantitative standard to classify driving load levels, the real-time driving status of the driver at tunnel entrances and exits can be accurately determined. The heart rate growth rate data used to classify driving load levels provides data support for the control of the three-dimensional ring light strip and the "sound-touch" dual-modal sensing intelligent cockpit.

[0022] Meanwhile, traffic management departments can collect driving load data, analyze the distribution of driving load in different time periods and different tunnels, and then optimize the tunnel system. This standardized classification also facilitates the subsequent expansion and upgrading of technologies. Researchers can further optimize control strategies based on this, develop more functional modules adapted to different scenarios, promote the development of intelligent driving in tunnels, and improve the intelligence level of the transportation system.

[0023] Furthermore, the control of the three-dimensional ring light strip group includes the following steps: Multiple three-dimensional ring light strips are installed on the side walls at the tunnel entrance and tunnel exit, and these three-dimensional ring light strips extend along the length of the tunnel. Each three-dimensional ring light strip includes a side-facing reflective area and a side-rear illumination area. The side-rear illumination areas of all three-dimensional ring light strips form a warning area. Multiple color warning positions are set in the warning area along the length of the tunnel. The distance between adjacent color warning positions is the working spacing. The specific working states of the color warning positions and working spacing under different driving loads are as follows. When the driver's driving load level is low, the color of the color indicator is the first indicator color, and the working distance is 120-180m; When the driver's driving load level is medium load, the color of the color indicator is the second indicator color, and the working distance is 80-120m; When the driver's driving load level is high, the color of the indicator is the third indicator color, and the working distance is 40-80m. The monitoring area is defined as the location inside the tunnel and near the tunnel exit, and the location outside the tunnel and near the tunnel entrance. When the number of vehicles in any monitoring area is greater than 1, the working status of the corresponding monitoring area's color indicator and working distance is executed according to the highest driving load level among all drivers.

[0024] The beneficial effects of this plan are: 1. A three-dimensional ring-shaped light strip is installed at key sections of the tunnel entrance and exit. The side and back lighting areas use different colors and spacing to indicate the driving load level, providing drivers with a direct visual warning. The first warning color (low load) uses a milder color, indicating a relatively relaxed driving environment where the driver can maintain a normal driving state. The second warning color (medium load) uses a more intense color than the first, reminding the driver to increase attention and drive cautiously. The third warning color (high load) uses an even more intense color than the second, strongly warning the driver that the current driving load is high and requires high vigilance and appropriate measures, such as slowing down and adjusting their driving state. This intuitive warning method helps drivers quickly understand their driving load status, react appropriately in a timely manner, and ensure driving safety.

[0025] 2. When the number of vehicles is greater than one, the side and rear lighting area operates according to the highest driving load level among all drivers. This mechanism effectively addresses multi-vehicle traffic scenarios. When multiple vehicles are traveling at the tunnel entrance and exit, even if some vehicles are at different driving load levels, the side and rear lighting area can still be uniformly controlled according to the highest level, ensuring that all drivers receive the safest warning information. This avoids confusion and misunderstanding caused by different control standards, improves overall control efficiency and safety, and safeguards traffic order at the tunnel entrance and exit.

[0026] Furthermore, the three-dimensional ring light strip also includes a roofed road surface lighting area, and the brightness of the roofed road surface lighting area of ​​all three-dimensional ring light strips gradually increases from near the tunnel entrance to near the tunnel interior.

[0027] The beneficial effects of this solution are as follows: The use of gradual brightness adjustment technology in the overhead road lighting area effectively alleviates the visual stress on drivers caused by the "black hole effect" and "white hole effect." At the tunnel entrance, the brightness of the overhead road lighting area gradually decreases from being similar to natural light, while the brightness changes in the opposite direction at the exit. This simulates the natural visual adaptation process of the human eye, allowing drivers' eyes to gradually adapt to changes in light, reducing the risk of visual fatigue and momentary blindness, thereby significantly improving driving safety and reducing the incidence of traffic accidents caused by visual problems.

[0028] Furthermore, the illuminance difference between the overhead road lighting areas of adjacent three-dimensional ring light strips The calculation formula is as follows:

[0029] In the formula, L represents the illuminance difference between adjacent three-dimensional ring light strips and the road surface lighting area above. 外 L represents the external illuminance of the tunnel. 内 denoted as illuminance inside the tunnel, and n as the number of working three-dimensional ring light strips.

[0030] The beneficial effects of this plan are: Furthermore, the intelligent cockpit control in step 4 includes acoustic and tactile dimensions. At least one of the acoustic and tactile dimensions is activated when the vehicle approaches the tunnel entrance / exit. The acoustic dimension control includes: When the driver's driving load level is low, play alpha wave sound with a frequency of 8-13Hz and a volume of 40dB. When the driver's driving load level is medium load, play a low-frequency rhythmic sound with a frequency of 50-200Hz and a volume of 50dB. When the driver's driving load level is high, at least one of the following will be triggered: alarm and warning voice. The alarm starts at 200Hz and rapidly increases in frequency at a rate of 90-110Hz per second, reaching 500Hz and 60dB within 2-3 seconds; the warning voice is used to alert the driver that the load is high. Control of the tactile dimension includes: When the driver's driving load level is medium, air is sprayed onto the driver's hands at a wind speed of 2.5-3.5 m / s; When the driver's driving load level is high, air is sprayed onto the driver's hands at a wind speed of 4.5-5.5 m / s.

[0031] The beneficial effects of this plan are: 1. The "sound-touch" dual-modal perception intelligent cockpit enhances driving safety through the coordinated control of acoustic and tactile dimensions and the use of multi-sensory stimulation. The simultaneous action of multiple stimuli can quickly awaken the driver's stress response and prompt them to take the correct driving actions.

[0032] 2. Provides targeted acoustic and haptic feedback based on different driving load levels, precisely matching the driver's needs in different states and optimizing the driving experience. The intelligent cockpit can adjust acoustic and haptic feedback in real time according to dynamic changes in driving load levels, exhibiting strong adaptability.

[0033] Furthermore, a driving load identification system based on tunnel entrances and exits is designed, including a data acquisition module, an intelligent computing module, and a load control module. The data acquisition module is used to collect data from step 1, the intelligent computing module is used to calculate the heart rate growth rate, and the load control module is used to control the load in step 4.

[0034] The beneficial effects of this solution are as follows: the three modules of the system work closely together, data acquisition provides information for intelligent computing, and the results of intelligent computing guide load regulation. This collaborative operation across the entire process and multiple modules constructs a comprehensive driving load identification and regulation system, effectively reducing driving risks and ensuring driving safety in tunnels. It integrates multiple sensor technologies, intelligent computing algorithms, and multimodal regulation methods to provide intelligent solutions for tunnel driving scenarios. It can be integrated with other intelligent transportation systems to improve the overall intelligence level of the transportation system. Attached Figure Description

[0035] Figure 1 This is a flowchart of the identification system according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the installation location of the tunnel entrance / exit according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the layout of the three-dimensional ring-shaped light strip assembly according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of the three-dimensional ring-shaped light strip in Embodiment 2 of the present invention; Figure 5 This is a schematic diagram of the "sound-touch" dual-modal sensing smart cockpit of Embodiment 2 of the present invention. Detailed Implementation

[0036] The following detailed description illustrates the specific implementation method: The reference numerals in the accompanying drawings include: roadside unit 1, calculation unit 2, lighting control unit 3, three-dimensional ring light strip group 4, illuminance sensor 5, side frontal reflective area 6, side rear lighting area 7, roof road lighting area 8, in-vehicle acoustic regulator 9, in-vehicle tactile regulator 10.

[0037] Example This invention discloses a method for identifying and controlling driver load based on tunnel entrances and exits, comprising the following steps: Step 1: Data acquisition. The data includes the vehicle's real-time speed V, driver's age information A, continuous driving duration T, and tunnel external illuminance L. 外 Illumination L inside the tunnel 内 ; Step 2: Determine the external illuminance L of the tunnel. 外 Illumination L inside the tunnel 内 The intensity E of the "black hole effect" or "white hole effect" is calculated using the following formula:

[0038] In the formula, E represents the intensity of the "black hole effect" or "white hole effect," and L... 内 L represents the illumination level inside the tunnel. 外For the external illuminance of the tunnel, T i A is the fatigue coefficient. i Visual adaptation coefficient; Step 3: Calculate the heart rate growth rate H using the following formula:

[0039]

[0040] In the above formula, H 进 With H 出 V represents the driver's heart rate growth rate when entering and exiting the tunnel. 进 With V 出 These are the vehicle speeds collected before the vehicle enters and exits the tunnel, E 进 For the "black hole effect", E 出 The intensity of the "white hole effect"; Based on the calculation formula for the influence intensity E of the "black hole effect" or "white hole effect", the calculation formula for the heart rate growth rate H in this embodiment is as follows:

[0041]

[0042] Among them, the fatigue coefficient T i Classified according to continuous driving time T: Continuous driving time The fatigue level is defined as the driver being not fatigued, with a fatigue coefficient T1 of 1.0. Continuous driving time This is defined as mild driver fatigue, with a fatigue coefficient T2 of 1.2. Continuous driving time The fatigue level is defined as severe or above fatigue of the driver, with a fatigue coefficient T3 of 1.5. Visual adaptation coefficient A i Classified by driver's age: Drivers aged 18-30 are defined as young drivers, and the visual adaptation coefficient... ; Drivers aged 30-40 are defined as young and middle-aged drivers, and the visual adaptation coefficient... ; Drivers aged 40-50 are defined as middle-aged drivers, and the visual adaptation coefficient... ; Drivers aged 50-65 are defined as middle-aged and elderly drivers, and the visual adaptation coefficient... ; Drivers aged 65 and above are defined as elderly drivers, and the visual adaptation coefficient... ; Step 4: Determine the driver's driving load based on the driver's heart rate growth rate (H). When the vehicle enters the tunnel, the system activates as the vehicle approaches the tunnel entrance. When the vehicle leaves the tunnel, the system activates again when the vehicle is inside the tunnel and 300-500m from the tunnel exit, lasting 3-8 seconds. The system adjusts the "sound-touch" dual-modal sensing intelligent cockpit and 3D ring light strip group according to the driver's load. During adjustment, the driver's driving load is divided into low, medium, and high loads. When the driver's driving load is low, only the 3D ring light strip group is activated for adjustment. The driver's driving load classification criteria are as follows: When the driver's heart rate growth rate H is ≤5%, the driver's driving load is defined as low load; When the driver's heart rate growth rate H is in the range of 5%-10%, the driver's driving load is defined as medium load; When the driver's heart rate growth rate H is ≥10%, the driver's driving load is defined as high load; The control of the three-dimensional ring light strip group includes the following steps: Multiple three-dimensional ring-shaped light strips are installed on the sidewalls at the tunnel entrance and exit, extending along the length of the tunnel. In this embodiment, six three-dimensional ring-shaped light strips are installed, with a spacing of 50m between adjacent strips. Each three-dimensional ring light strip includes a side-facing reflective area, a side-rear illumination area, and a top road surface illumination area; the side-rear illumination areas of all three-dimensional ring light strips form a warning area, and multiple color warning positions are set in the warning area along the tunnel length direction. The distance between adjacent color warning positions is the working spacing. The specific working states of color warning positions and working spacing under different driving loads are as follows. When the driver's driving load level is low, the color of the color indicator is the first indicator color, and the working distance is 150m. When the driver's driving load level is medium load, the color of the color indicator is the second indicator color, and the working distance is 100m; When the driver's driving load level is high, the color of the color indicator is the third indicator color, and the working distance is 50m. The monitoring areas are defined as both the area inside the tunnel and near the tunnel exit, and the area outside the tunnel and near the tunnel entrance. When the number of vehicles in any monitoring area is greater than 1, the working status of the color indicator and working distance of the corresponding monitoring area is executed according to the highest driving load level among all drivers. Specifically, in this embodiment, the area located inside the tunnel and less than or equal to 300m from the tunnel exit is defined as the monitoring area leaving the tunnel, and the area located outside the tunnel and less than or equal to 50m from the tunnel entrance is defined as the monitoring area entering the tunnel. Meanwhile, the side-facing reflective area serves to provide visual guidance; in this embodiment, a high-reflectivity glass microsphere reflective film material is used to reflect light into the driver's field of vision. The overhead road lighting area illuminates the road surface; the brightness of the overhead road lighting area of ​​adjacent three-dimensional ring light strips gradually changes, with the illuminance gradually decreasing when entering the tunnel and gradually increasing when leaving the tunnel. Illuminance difference between adjacent three-dimensional ring light strips and the overhead road lighting area The calculation formula is as follows:

[0043] In the formula, L represents the illuminance difference between adjacent three-dimensional ring light strips and the road surface lighting area above. 外 L represents the external illuminance of the tunnel. 内 denoted as the illuminance inside the tunnel, and n as the number of working three-dimensional ring light strips; Intelligent cockpit control includes acoustic and tactile dimensions. Acoustic control includes: When the driver's driving load level is low, play alpha wave music with a sound frequency of 8-13Hz and a volume of 40dB. When the driver's driving load level is medium load, play music with low frequency rhythm and melody, with a sound frequency of 50-200Hz and 50dB. When the driver's driving load level is high, an alarm and warning voice are triggered. The alarm starts at 200Hz and rapidly increases in frequency at a rate of 100Hz per second, reaching 500Hz and 60dB within 3 seconds. The warning voice is used to remind the driver that the load is high. In this embodiment, "Caution: Dazzling" is used as the warning voice. Control of the tactile dimension includes: When the driver's driving load level is medium load, air is blown onto the driver's hands at a wind speed of 3 m / s. When the driver's driving load level is high, air is sprayed onto the driver's hands at a wind speed of 5 m / s.

[0044] The present invention also designs a driver load identification system based on tunnel entrances and exits, including a data acquisition module, an intelligent calculation module and a load control module. The data acquisition module is used to collect data in step 1, the intelligent calculation module is used to calculate the heart rate growth rate, and the load control module is used to control in step 4, so as to realize the above identification and control methods.

[0045] This invention specifically collects data from tunnel entrances and exits for practical verification. The illuminance data collected by the illuminance sensor 5 in this embodiment are set as follows: illuminance inside the tunnel is... The external illuminance of the tunnel is .

[0046] (1) Assuming the vehicle speed collected by the roadside unit , ,age Continuous driving time Therefore, the driver's visual adaptation coefficient Fatigue level coefficient .

[0047] The influence intensity E of the "black hole effect" or "white hole effect" is calculated using the formula, resulting in E=4398.13. heart rate growth rate The calculation formula is used to calculate

[0048] Similarly, heart rate growth rate for:

[0049] Driver's heart rate increase when entering the tunnel The driver's heart rate growth rate when exiting the tunnel Based on the degree of driving load, the driver's heart rate load level when entering the tunnel is medium load, and the heart rate load level when exiting the tunnel is low load. Load is adjusted according to the corresponding level when entering and exiting the tunnel to ensure that the driver's load is effectively controlled and to ensure safe driving.

[0050] (2) Assuming the vehicle speed collected by the roadside unit , ,age Continuous driving time Therefore, the driver's visual adaptation coefficient Fatigue level coefficient .

[0051] The influence intensity E of the "black hole effect" or "white hole effect" is calculated using the formula: E = 6108.52. heart rate growth rate The calculation formula is used to calculate

[0052] Similarly, heart rate growth rate for:

[0053] Driver's heart rate increase when entering the tunnel The driver's heart rate growth rate when exiting the tunnel Based on the degree of driving load, the driver's heart rate load level is high when entering the tunnel and low when exiting the tunnel. Load is adjusted according to the corresponding level when entering and exiting the tunnel to ensure that the driver's load is effectively controlled and to ensure safe driving.

[0054] When the aforementioned driving load recognition system based on tunnel entrances and exits is working, the data acquisition module collects data on illumination inside and outside the tunnel, vehicle speed entering and exiting the tunnel, and driver data. The intelligent computing module calculates the visual adaptation coefficient, fatigue coefficient, black / white hole effect intensity, heart rate growth rate, and driving load level based on the collected data. The load control module includes a three-dimensional ring light strip and a dual-modal "sound-touch" sensing intelligent cockpit. The three-dimensional ring light strip serves as the visual control device for tunnel entrances and exits; the dual-modal "sound-touch" sensing intelligent cockpit provides the driver with acoustic and tactile information inside the vehicle to help the driver adjust their driving load.

[0055] Specifically, in combination Figure 2 and Figure 3 As shown, in the driver load recognition system based on tunnel entrances and exits, the data acquisition module is located 300m before the tunnel entrance. Roadside unit 1 accurately collects the real-time speed V of the vehicle. The acquisition principle utilizes radar speed measurement technology, calculating the vehicle speed based on the Doppler effect by transmitting and receiving electromagnetic waves. Regarding driver data collection, the system obtains the driver's age information A and continuous driving duration T through the in-vehicle information acquisition module. This collected data, along with the illuminance collected by illuminance sensor 5, is rapidly transmitted to the calculation unit 2 at the tunnel entrance for analysis and processing. The results are then quickly transmitted to the lighting control unit 3. A three-dimensional ring-shaped light strip is installed along the sidewall of the driving lane 300m before the tunnel entrance and 300m after the tunnel exit, maximizing the visual guidance effect on the driver. The relationship between its operating status and the driver's driving load is as follows: The function of having a side-facing reflective area is to provide visual guidance by reflecting light into the driver's field of vision.

[0056] The function of the side and rear lighting area is to provide driving load warning. The specific working states of the side and rear lighting areas of the adjacent three-dimensional ring light strips under different driving loads are as follows: When the driver's driving load level is low, the color of the area with side and rear lighting is white, and the working distance is 150m; When the driver's driving load level is medium load, the color of the area with side and rear lighting is yellow, and the working distance is 100m; When the driver's driving load level is high, the color of the area with side and rear lighting is red, and the working distance is 50m.

[0057] When the number of vehicles is greater than 1, the side and back lighting area of ​​the three-dimensional ring light strip is operated according to the highest driving load level among all drivers.

[0058] The function of the overhead road lighting area is to illuminate the road surface. The illuminance difference between the overhead road lighting areas of adjacent three-dimensional ring light strips is... The calculation formula is as follows:

[0059] In the formula, L represents the illuminance difference between adjacent three-dimensional ring light strips and the road surface lighting area above. 外 L represents the external illuminance of the tunnel. 内 denoted as illuminance inside the tunnel, and n as the number of working three-dimensional ring light strips.

[0060] The three-dimensional ring light strip can provide visual guidance, warn drivers of the intensity of their load, and help the driver's eyes gradually adapt to changes in light, reducing the visual impact of the "black hole effect" and "white hole effect".

[0061] Combination Figure 2 and Figure 5 As shown, the results of the analysis and processing of the input data by the computing unit 2 are quickly transmitted to the vehicle. The "sound-touch" dual-modal perception intelligent cockpit in the vehicle enhances driving safety through the coordinated control of acoustic and tactile dimensions and the use of multi-sensory stimulation. The "sound-touch" dual-modal perception intelligent cockpit mainly consists of two parts: the in-vehicle acoustic modulator 6 and the in-vehicle tactile modulator 7.

[0062] When the calculation unit 2 determines that the driver is in a low-load state, the in-vehicle acoustic regulator 6 starts working. It plays alpha wave music (8-13Hz, 40dB). At the same time, the in-vehicle tactile regulator 7 is inactive to avoid unnecessary interference to the driver. Once the calculation unit 2 determines that the driver's load state has changed to medium load, the in-vehicle acoustic regulator 6 will switch to playing music with low-frequency rhythm and melody (50-200Hz, 50dB). The in-vehicle tactile regulator 7 is also activated at this time, starting to spray air onto the driver's hands at a speed of 3m / s. If the calculation unit 2 detects that the driver has entered a high-load state, the in-vehicle acoustic regulator 6 will immediately trigger an alarm (starting at 200Hz, rapidly increasing the frequency at a rate of approximately 100Hz per second, reaching 500Hz, 60dB within 2-3 seconds) and play an emergency voice message (240 words / minute). At the same time, the in-vehicle tactile regulator 7 controls the airflow speed to 5m / s.

[0063] Based on case (1) of Example 1, the driver's heart rate growth rate when entering the tunnel. The driver's heart rate growth rate when exiting the tunnel Based on the level of driving load, the driver's heart rate load level is classified as medium load when entering the tunnel and low load when exiting the tunnel. Therefore, the three-dimensional ring light strip group appears yellow at the tunnel entrance and operates at a spacing of 100m; it appears white at the tunnel exit and operates at a spacing of 150m. The "sound-touch" dual-modal sensing intelligent cockpit in the vehicle triggers low-frequency rhythm and melody music (50-200Hz, 50dB) in the acoustic regulator when entering the tunnel, and controls the air jet speed to 3m / s in the tactile regulator; when exiting the tunnel, the acoustic regulator plays alpha wave music (8-13Hz, 40dB), and the tactile regulator is inactive.

[0064] Based on case (2) of Example 1, the driver's heart rate growth rate when entering the tunnel. The driver's heart rate growth rate when exiting the tunnel Based on the level of driving load, the driver's heart rate load level is high when entering the tunnel and low when exiting the tunnel. Therefore, the three-dimensional ring light strip group is red at the tunnel entrance and operates at a spacing of 50m; it is white at the tunnel exit and operates at a spacing of 150m. The "sound-touch" dual-modal sensing intelligent cockpit in the vehicle triggers an alarm (starting at 200Hz, rapidly increasing the frequency at a rate of about 100Hz per second, reaching 500Hz within 2-3 seconds) and plays an emergency voice message (240 words / minute) when entering the tunnel, while the in-vehicle tactile sensor controls the airflow speed to 5m / s; when exiting the tunnel, the in-vehicle acoustic sensor plays alpha wave music (8-13Hz, 40dB), and the in-vehicle tactile sensor is inactive.

[0065] The aforementioned real-time dynamic control allows the system to continuously collect various data during vehicle entry and exit from tunnels. This data is then rapidly analyzed and processed by the intelligent computing unit. Once the driving load level changes, corresponding control measures are immediately triggered. The three-dimensional ring light strip adjusts the brightness of the overhead road lighting area based on the illuminance difference between inside and outside the tunnel. It also adjusts the working spacing and color of the side and rear lighting areas according to the driving load level, helping the driver to anticipate changes in driving load and adapt to the lighting environment. The "sound-touch" dual-modal sensing intelligent cockpit also adjusts synchronously. When the driving load is high, it plays emergency voice prompts and triggers alarms acoustically, while the tactile system sprays air onto the driver's hands. Through multi-sensory stimulation, the driver quickly becomes alert and adjusts their driving state, effectively ensuring driving safety.

[0066] The above descriptions are merely embodiments of the present invention, and common knowledge such as specific technical solutions and / or characteristics are not described in detail here. It should be noted that those skilled in the art can make various modifications and improvements without departing from the technical solutions of the present invention, and these should also be considered within the scope of protection of the present invention. These modifications and improvements will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A method for identifying and controlling driving load based on tunnel entrances and exits, characterized in that: Includes the following steps: Step 1: Data acquisition. The data includes the vehicle's real-time speed V, driver's age information A, continuous driving duration T, and tunnel external illuminance L. 外 Illumination L inside the tunnel 内 ; Step 2: Determine the external illuminance L of the tunnel. 外 Illumination L inside the tunnel 内 Calculate the intensity E of the "black hole effect" or "white hole effect"; Step 3: Calculate the heart rate growth rate H using the following formula: In the above formula, H 进 With H 出 V represents the driver's heart rate growth rate when entering and exiting the tunnel. 进 With V 出 These are the vehicle speeds collected before the vehicle enters and exits the tunnel, E 进 For the "black hole effect", E 出 The intensity of the "white hole effect"; Step 4: Determine the driver's driving load based on the driver's heart rate growth rate H, and adjust the "sound-touch" dual-modal sensing intelligent cockpit and three-dimensional ring light strip group according to the load status.

2. The method for identifying and controlling driving load based on tunnel entrances and exits according to claim 1, characterized in that: The formula for calculating the intensity E of the "black hole effect" or "white hole effect" is: In the formula, E represents the intensity of the "black hole effect" or "white hole effect," and L... 内 L represents the illumination level inside the tunnel. 外 For the external illuminance of the tunnel, T i A is the fatigue coefficient. i This is the visual adaptation coefficient.

3. The method for identifying and controlling driving load based on tunnel entrances and exits according to claim 2, characterized in that: The fatigue level coefficient T i Classified according to continuous driving time T: Continuous driving time The fatigue level is defined as the driver being not fatigued, with a fatigue coefficient T1 of 1.

0. Continuous driving time This is defined as mild driver fatigue, with a fatigue coefficient T2 of 1.

2. Continuous driving time The fatigue level is defined as severe or above fatigue of the driver, with a fatigue coefficient T3 of 1.

5.

4. The method for identifying and controlling driving load based on tunnel entrances and exits according to claim 2, characterized in that: Visual adaptation coefficient A i Classified by driver's age: Drivers aged 18-30 are defined as young drivers, and the visual adaptation coefficient... ; Drivers aged 30-40 are defined as young and middle-aged drivers, and the visual adaptation coefficient... ; Drivers aged 40-50 are defined as middle-aged drivers, and the visual adaptation coefficient... ; Drivers aged 50-65 are defined as middle-aged and elderly drivers, and the visual adaptation coefficient... ; Drivers aged 65 and above are defined as elderly drivers, and the visual adaptation coefficient... .

5. A method for identifying and controlling driving load based on tunnel entrances and exits according to any one of claims 1 to 4, characterized in that: Driver workload is categorized into low, medium, and high loads, based on the following criteria: When the driver's heart rate growth rate H is ≤5%, the driver's driving load is defined as low load; When the driver's heart rate increase rate H is within the range of 5%-10%, the driver's driving load is defined as medium load; When a driver's heart rate growth rate H is ≥10%, the driver's driving load is defined as high load.

6. The method for identifying and controlling driving load based on tunnel entrances and exits according to claim 5, characterized in that: The control of the three-dimensional ring light strip group includes the following steps: Multiple three-dimensional ring light strips are installed on the side walls at the tunnel entrance and tunnel exit, and these three-dimensional ring light strips extend along the length of the tunnel. Each three-dimensional ring light strip includes a side-facing reflective area and a side-rear illumination area. The side-rear illumination areas of all three-dimensional ring light strips form a warning area. Multiple color warning positions are set in the warning area along the length of the tunnel. The distance between adjacent color warning positions is the working spacing. The specific working states of the color warning positions and working spacing under different driving loads are as follows. When the driver's driving load level is low, the color of the color indicator is the first indicator color, and the working distance is 120-180m; When the driver's driving load level is medium load, the color of the color indicator is the second indicator color, and the working distance is 80-120m; When the driver's driving load level is high, the color of the color indicator is the third indicator color, and the working distance is 40-80m. The monitoring areas are defined as the locations inside the tunnel and near the tunnel exit, and the locations outside the tunnel and near the tunnel entrance. When the number of vehicles in any monitoring area is greater than 1, the working status of the corresponding monitoring area's color indicator and working distance will be executed according to the highest driving load level among all drivers.

7. The method for identifying and controlling driving load based on tunnel entrances and exits according to claim 6, characterized in that: The three-dimensional ring light strip also includes a roofed road surface lighting area, and the brightness of the roofed road surface lighting area of ​​all three-dimensional ring light strips gradually increases from near the tunnel entrance to near the tunnel interior.

8. The method for identifying and controlling driving load based on tunnel entrances and exits according to claim 6, characterized in that: Illuminance difference between adjacent three-dimensional ring light strips and the overhead road lighting area The calculation formula is as follows: In the formula, L represents the illuminance difference between adjacent three-dimensional ring light strips and the road surface lighting area above. 外 L represents the external illuminance of the tunnel. 内 denoted as illuminance inside the tunnel, and n as the number of working three-dimensional ring light strips.

9. The method for identifying and controlling driving load based on tunnel entrances and exits according to claim 5, characterized in that: Step 4, the intelligent cockpit control, includes acoustic and tactile dimensions. At least one of the acoustic and tactile dimensions is activated when the vehicle approaches the tunnel entrance / exit. The acoustic dimension control includes: When the driver's driving load level is low, play alpha wave sound with a frequency of 8-13Hz and a volume of 40dB. When the driver's driving load level is medium load, play a low-frequency rhythmic sound with a frequency of 50-200Hz and a volume of 50dB. When the driver's driving load level is high, at least one of the following will be triggered: alarm and warning voice. The alarm starts at 200Hz and rapidly increases in frequency at a rate of 90-110Hz per second, reaching 500Hz and 60dB within 2-3 seconds; the warning voice is used to alert the driver that the load is high. Control of the tactile dimension includes: When the driver's driving load level is medium, air is sprayed onto the driver's hands at a wind speed of 2.5-3.5 m / s; When the driver's driving load level is high, air is sprayed onto the driver's hands at a wind speed of 4.5-5.5 m / s.

10. The method for identifying and controlling driving load based on tunnel entrances and exits according to claim 5, characterized in that: Design a driver load identification system based on tunnel entrances and exits, including a data acquisition module, an intelligent computing module, and a load control module. The data acquisition module is used to collect data in step 1, the intelligent computing module is used to calculate the heart rate growth rate, and the load control module is used to control the load in step 4.

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