A dynamic light distribution road lighting system for vehicle-road cooperative scenarios

Abstract

This application relates to the field of novel lighting technology, specifically to a dynamic light distribution road lighting system in a vehicle-road cooperative scenario. The system includes: a road data acquisition module for collecting road data; a road spatial feature analysis module for determining the illumination overlap length of luminaires in each road segment at each moment; obtaining the illumination conflict index of each road segment at each moment; a traffic flow time-varying feature analysis module for determining the traffic flow matching degree of each road segment at each moment; a vehicle mixed traffic feature analysis module for determining the mixed traffic distribution characteristics of each road segment at each moment; and a road lighting control module for obtaining the control factor of each road segment at each moment based on the illumination conflict index, traffic flow matching degree, and mixed traffic distribution characteristics of each road segment, and obtaining the pitch angle deviation and brightness adjustment amount of the luminaires in each road segment at each moment through a mapping function. This application aims to solve the dimming failure problem caused by illumination overlap interference at grade-separated intersections.

Description

Technical Field

[0001] This application relates to the field of new lighting technology, specifically to a dynamic light distribution road lighting system in a vehicle-road cooperative scenario. Background Technology

[0002] Road lighting systems provide nighttime illumination to roads through infrastructure such as lamps and control equipment. Their core functions are to ensure driving safety, improve traffic efficiency, and create a suitable nighttime traffic environment. In intelligent scenarios involving vehicle-road cooperation, sensors collect real-time data on vehicle location, speed, and ambient light intensity. Combined with intelligent algorithms, the brightness, illumination range, and lighting periods of energy-efficient lighting equipment are dynamically adjusted. This achieves on-demand lighting and dynamic light distribution, significantly improving energy efficiency while ensuring safety. It is a key technology for the integration of intelligent transportation and green lighting.

[0003] Traditional energy-saving lighting equipment typically employs a fixed segmented dimming strategy when dynamically distributing light. This relies on a single sensor to collect vehicle location or ambient light data, adjusting brightness according to preset lighting segment division rules. For example, it might increase the brightness of a section of road when a vehicle enters and then dim it again after the vehicle leaves. However, this method fails to adequately consider the overlapping interference of light from grade-separated intersections in complex road networks. This can lead to situations where vehicles on higher levels accidentally trigger the lighting on lower levels, such as at ramps and interchanges. This results in wasted light resources, limited energy-saving effects, or overcompensation. Summary of the Invention

[0004] In view of the above, it is necessary to provide a dynamic light distribution road lighting system for vehicle-road cooperative scenarios to solve the above problems.

[0005] One embodiment of this application provides a dynamic light distribution road lighting system for a vehicle-road cooperative scenario, the system comprising:

[0006] The road data acquisition module is used to collect the number of grade-separated intersections and the total length of each road segment, the installation height of the lights in each road segment, the half-peak angle of the light distribution, and the pitch angle at each moment; to collect the traffic flow of the road network at each moment; and to collect the number of various types of vehicles in the road network at each moment and within the previously preset traffic flow analysis period.

[0007] The road space feature analysis module is used to determine the illumination overlap length of the lamps in each road segment at each moment based on the installation height, half-peak angle, and pitch angle of the lamps in each road segment, combined with the distance between adjacent streetlights; it analyzes the distribution characteristics of the number of grade-separated intersections in the overall road segment, the proportion of illumination overlap length in the total length of the road segment, and, combined with the angle distribution between intersecting roads in each road segment, obtains the illumination conflict index of each road segment at each moment;

[0008] The traffic flow time-varying feature analysis module is used to preset the first time period and the second time period; divide the second time period into multiple time periods; analyze the distribution characteristics of all traffic flow in the same time period in the first time period where each time point is located; use a timer to record the duration; and combine the numerical characteristics of traffic flow to determine the traffic flow matching degree of each road segment at each time point.

[0009] The vehicle mixed traffic feature analysis module is used to analyze the traffic flow characteristics of vehicles in each road segment during a preset traffic flow analysis period. Combined with the distribution characteristics of the number of vehicles of various types, it determines the mixed traffic distribution characteristics of each road segment at each time.

[0010] The road lighting control module is used to obtain the control factor of each road segment at each time based on the illumination conflict index, traffic flow matching degree and mixed traffic distribution characteristics of each road segment at each time. Through the mapping function, the pitch angle deviation and brightness adjustment amount of the lamps of each road segment at each time are obtained.

[0011] The specific formula for determining the illumination overlap length of the luminaires in each road segment at each moment is: L0=2H×[tan(ε+δ)-tan(ε-δ)]-D; where L0 represents the illumination overlap length of the luminaires in each road segment at each moment; H represents the installation height of the luminaires in each road segment; ε represents the pitch angle of the luminaires in each road segment at each moment; δ represents the half-peak angle of the light distribution of the luminaires in each road segment; tan() represents the tangent trigonometric function; and D represents the distance between adjacent luminaires in each road segment.

[0012] The specific process for obtaining the illumination conflict index of each road segment at each moment is as follows:

[0013] Obtain the maximum number of grade-separated intersection levels among all road segments, and denote it as the maximum number of grade-separated intersection levels. Denote the ratio of each road segment to the maximum number of grade-separated intersection levels as the first ratio.

[0014] Calculate the ratio of the illumination overlap length of the lamps in each road segment at each moment to the total length of each road segment, and record it as the second ratio;

[0015] Obtain the cosine trigonometric function value of the minimum angle between all intersecting roads in each road segment;

[0016] The first ratio, the second ratio, and the cosine trigonometric function value are each assigned a preset weight, and the weighted sum is used to obtain the illumination conflict index of each road segment at each time.

[0017] The first time period includes a preset number of second time periods.

[0018] Specifically, the use of a timer to record the duration refers to:

[0019] From the beginning of the first time period to the present time, calculate the average traffic flow of all times in the same time period as the traffic flow threshold for the current time.

[0020] If the difference between the current traffic flow and the corresponding traffic flow threshold is greater than the maximum traffic flow multiple of the preset value, a timer is started to record the duration until the deviation is less than the threshold, at which point the timer is reset.

[0021] The process of determining the traffic flow matching degree of each road segment at each time point is as follows:

[0022] The maximum traffic flow is defined as the maximum traffic flow from the start of the first time period to each time period.

[0023] Calculate the difference between the traffic flow at each moment and the corresponding traffic flow threshold, divide it by the maximum traffic flow, and record the resulting value as the third ratio.

[0024] Periodic analysis of historical traffic flow is performed to obtain the periodic coefficient;

[0025] Obtain the ratio of the duration of the most recent timer record at each time point to the period coefficient, and denote it as the fourth ratio;

[0026] The result of positively fusing the third ratio and the fourth ratio is used as the traffic flow matching degree of each road segment at each time.

[0027] Specifically, the period coefficient is obtained by performing a Fourier transform on historical traffic flow data and using the time length corresponding to the maximum period as the period coefficient.

[0028] Specifically, determining the mixed traffic distribution characteristics of each road segment at each time point involves:

[0029] Instantaneous speed is calculated by the displacement of vehicles in adjacent frames. The average instantaneous speed of each vehicle at each moment and within the previously preset traffic flow analysis time is calculated to obtain the average speed of each vehicle at each moment. The average speed and standard deviation of the average speed of all vehicles at each moment are calculated to obtain the average vehicle speed and the standard deviation of traffic flow speed.

[0030] Vehicles with a body length greater than a preset value are classified as large vehicles, and the rest as small vehicles; the proportion of large vehicles is calculated based on the number of large vehicles and small vehicles at each moment and within the previous preset traffic flow analysis period.

[0031] Calculate the ratio of the standard deviation of traffic flow speed to the average speed at each time point, and denote it as the fifth ratio.

[0032] The proportion of large vehicles and the fifth ratio are positively fused to obtain the mixed traffic distribution characteristics of each road segment at each time.

[0033] The formula for the pitch angle deviation is as follows: In the formula, Δθ represents the pitch angle deviation of the lights in each road segment at each time, CF represents the control factor of each road segment at each time, and θ min θ mid and θ max These represent the preset minimum, median, and maximum pitch angles of the lighting fixture, respectively.

[0034] The formula for the brightness adjustment amount is as follows: In the formula, ΔL represents the brightness adjustment of the lights in each road segment at each moment, L min L mid and L max These represent the preset minimum, median, and maximum brightness values ​​of the lighting fixtures, respectively. CF represents the control factor for each road segment at each moment, sin() represents the sine trigonometric function, and π represents pi.

[0035] This application has at least the following beneficial effects:

[0036] The road data acquisition module of this application is responsible for collecting spatial characteristics and traffic flow data of the road network, providing basic input data for subsequent analysis. The road spatial characteristic analysis module determines the length of the illumination overlap area of ​​lamps in each road segment by analyzing the spatial parameters of the lamps and the distance between adjacent lamps. Simultaneously, it calculates and obtains the illumination conflict index of each road segment at each moment, used to measure the degree of excessive or insufficient overlap in the lamp illumination range. The traffic flow time-varying characteristic analysis module analyzes traffic flow changes over different time periods. By dividing the time period, it analyzes the distribution characteristics of traffic flow within each time period, obtaining the duration and numerical characteristics of traffic flow, and thus determining the traffic flow matching degree of each road segment at each moment, i.e., the degree of matching between current traffic flow and lighting demand. The vehicle mixed traffic characteristic analysis module analyzes the vehicle driving characteristics of each road segment over a time period, especially the distribution characteristics of large and small vehicles under mixed traffic conditions. It can identify and determine the mixed traffic distribution characteristics, i.e., the distribution status of different types of vehicles on the road segment, thereby affecting lighting control. Based on the data analyzed above, the road lighting control module calculates the control factor for each road segment by combining the illumination conflict index, traffic flow matching degree, and mixed traffic distribution characteristics at each time point. Through a pre-calibrated mapping function, it obtains the pitch angle deviation and brightness adjustment of the luminaires in each road segment at each time point, achieving dynamic adjustment of street lighting to optimize lighting effects and reduce glare or excessive illumination. This application solves the dimming failure problem caused by overlapping illumination interference at grade-separated intersections and achieves on-demand lighting, significantly reducing energy consumption while ensuring driving safety and improving lighting uniformity, thus balancing the real-time nature of traffic flow with the energy-saving nature of green lighting. Attached Figure Description

[0037] Figure 1 A block diagram of a dynamic light distribution road lighting system in a vehicle-road cooperative scenario is provided in this application;

[0038] Figure 2 A flowchart detailing the pitch angle deviation and brightness adjustment of each road segment luminaire provided in this application at each moment. Detailed Implementation

[0039] In the description of the embodiments in this application, the words "exemplary," "or," and "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplary," "or," and "for example" is intended to present the relevant concepts in a specific manner.

[0040] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in this application's specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.

[0041] It should also be noted that the terms "first" and "second" in this application and its accompanying drawings are used to distinguish similar objects, rather than to describe a specific order or sequence. The methods disclosed in the embodiments of this application or the methods shown in the flowcharts include one or more steps for implementing the method. Without departing from the scope of protection of this application, the execution order of multiple steps can be interchanged, and some steps can also be deleted.

[0042] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0043] The following description, in conjunction with the accompanying drawings, details a specific scheme for a dynamic light distribution road lighting system in a vehicle-road cooperative scenario provided in this application.

[0044] Please see Figure 1 The diagram illustrates a block diagram of a dynamic light distribution road lighting system in a vehicle-road cooperative scenario according to an embodiment of this application. The system includes: a road data acquisition module, a road spatial feature analysis module, a traffic flow time-varying feature analysis module, a vehicle mixed traffic feature analysis module, and a road lighting control module.

[0045] This application first proposes a dynamic light distribution road lighting system for a vehicle-road cooperative scenario, applied in the field of novel lighting technology. The system includes:

[0046] Road data acquisition module: Collects the number of grade-separated intersections and the total length of each road segment, the installation height of the lights in each road segment, the half-peak angle of the light distribution, and the pitch angle at each moment; collects the traffic flow of the road network at each moment; and collects the number of vehicles of various types in the road network at each moment and within the previously preset traffic flow analysis period.

[0047] This application primarily addresses the problem of dimming strategy failure and energy waste caused by overlapping and intersecting light from grade-separated roads in complex road networks using traditional energy-saving lighting equipment. Therefore, it first collects spatial characteristic values ​​for each road segment, including: the number of grade-separated intersections and the total length of the road segment. In this application, each L... t The road is divided into sections, and the three-dimensional hierarchical attributes of the road section are read from the urban road BIM model to obtain the number of three-dimensional intersection layers.

[0048] The system collects time-varying characteristics of road network traffic flow, including traffic volume. Specifically, a three-axis geomagnetic sensor is installed at the entrance of each lane to sense changes in magnetic flux as vehicles pass by, outputting pulse signals. Edge computing nodes count the pulse frequency using timer modules and combine this with a vehicle length calibration algorithm to calculate real-time traffic flow.

[0049] The characteristics of mixed traffic of vehicles are obtained, including the number of large vehicles and the number of small vehicles. Specifically, based on the video stream from existing road surveillance cameras, a lightweight convolutional neural network is used to perform real-time target detection on the video frames. In this embodiment, YOLO-Lite is used, and vehicles with a length greater than 6m are defined as large vehicles. The number of large vehicles and small vehicles passing through each road segment within a preset traffic flow analysis time is counted. In this embodiment, the preset traffic flow analysis time is 1 hour.

[0050] Road spatial feature analysis module: Based on the installation height, half-peak angle and pitch angle of the lamps in each road segment, and the distance between adjacent streetlights, determine the illumination overlap length of the lamps in each road segment at each moment; analyze the distribution characteristics of the number of grade-separated intersections in the overall road segment, the proportion of illumination overlap length in the total length of the road segment, and combine the angle distribution between intersecting roads in each road segment to obtain the illumination conflict index of each road segment at each moment.

[0051] In three-dimensional road network scenarios, multi-level road intersections can lead to overlapping projections of lighting areas at different road heights. Simultaneously, changes in road angles can cause light reflection interference. Traditional fixed light distribution patterns often result in both over-lit areas and blind spots. By quantifying the degree of interference of the three-dimensional road network structure on light distribution—that is, extracting characteristic parameters such as the number of intersection layers, light overlap length, and road angle—the geometric complexity of the road network is transformed into a calculable conflict index. This provides a quantitative basis for dynamic dimming, resolving the technical contradiction between wasted light resources and insufficient lighting uniformity in multi-level road networks, and achieving a balanced optimization of energy consumption and lighting effect.

[0052] In this application, the maximum number of grade separation levels in all road segments is recorded as the maximum number of grade separation levels; the spatial direction vectors of intersecting roads in each road segment are read from the BIM model, and the angle between the horizontal projection planes is calculated using the vector dot product formula. The minimum angle in the current road is taken as the road angle corresponding to each road segment.

[0053] Based on the installation height H and the half-peak angle δ of the luminaire, the projected coverage length d0 of a single luminaire on the road surface is calculated as 2H × tanδ. The overlapping part of the coverage area of ​​adjacent luminaires, i.e., the illumination overlap length d = 4H × tanδ - D, where D represents the distance between two adjacent streetlights. When the luminaire dynamically adjusts its pitch angle via a motor, it is updated in real time, and the formula is: L0 = 2H × [tan(ε+δ) - tan(ε-δ)] - D; where L0 represents the illumination overlap length of the luminaire in each road segment at each moment; H represents the installation height of the luminaire in each road segment; ε represents the pitch angle of the luminaire in each road segment at each moment; δ represents the half-peak angle of the luminaire in each road segment; tan() represents the tangent trigonometric function; and D represents the distance between adjacent luminaires in each road segment.

[0054] The light conflict index (SCI) for each road segment at each time point is denoted as SCI, and its formula is as follows: In the formula, N r This indicates the number of grade-separated intersection levels for each road segment; L0 represents the maximum number of grade separation levels across all road segments; L0 represents the illumination overlap length of the lights in each road segment at each moment; L t θ represents the total length of each road segment; θ represents the road angle corresponding to each road segment; cos() represents the cosine function; α, β, and γ all represent preset weighting coefficients, i.e., the proportion of influence of each dimension feature on illumination conflict, with values ​​ranging from 0 to 1. In this embodiment, the values ​​are 0.3, 0.4, and 0.3 respectively. Implementers can choose their own values ​​according to actual conditions, and this application does not impose any restrictions on this. Let this be the first ratio, and... This is denoted as the second ratio.

[0055] It should be understood that the number of grade-separated intersection layers represents the complexity of the road network in the vertical dimension, i.e., the number of grade-separated intersection layers involved in the current road segment. The larger the value, the more likely road segments at different heights are to have vertical overlap in the illuminated area, meaning that the lights from the upper road may project onto the lower road surface, causing excessive lighting and reflected glare. By using the maximum number of layers in the road network design, these effects can be mapped to dimensionless values ​​between 0 and 1.

[0056] The illumination overlap length characterizes the horizontal overlap projection length of adjacent lighting areas, that is, the overlapping part of the illumination areas of adjacent lamps. The ratio of this overlap to the total length of the road segment reflects the redundancy of illumination resources. The higher the ratio, the more serious the waste of horizontal illumination overlap.

[0057] The road angle represents the angle between two intersecting roads in a plane. It is usually calculated as an acute angle. The smaller the value, the more likely the illuminated areas are to overlap along the road's extension direction. Conversely, the larger the angle difference between the intersecting projections of the lights, the lower the probability of overlap. The angle is converted into a conflict factor through a cosine function.

[0058] The higher the light conflict index, the more serious the light overlap and waste in the three-dimensional road network. In this case, it is more necessary to prioritize reducing the light intensity in the overlapping areas and optimizing the projection direction to reduce energy waste and visual interference. Conversely, the lower the index, the lower the level of interference of the road network structure on the light distribution. The light uniformity and utilization rate are good, and the lighting mode can be maintained to maximize energy efficiency while ensuring the safety of road illumination.

[0059] Traffic flow time-varying characteristic analysis module: preset a first time period and a second time period; divide the second time period into multiple time periods, analyze the distribution characteristics of all traffic flow in the same time period within the first time period at each time point, use a timer to record the duration, and combine the numerical characteristics of traffic flow to determine the traffic flow matching degree of each road segment at each time point.

[0060] The illumination conflict index primarily addresses spatial illumination conflicts caused by static road network structures, but it cannot cope with the dynamic changes in traffic flow over time. In tidal flow lane scenarios, traffic direction and volume migrate periodically with morning and evening peak hours. If fixed lighting zones or light distribution strategies are used, insufficient illumination in densely trafficked sections and energy waste in sparsely trafficked sections will result. Traffic flow matching degree, by quantifying the dynamic matching degree between real-time traffic flow and preset traffic flow models, provides a flexible adjustment basis for the lighting system in the time dimension, filling the adjustment gap of the illumination conflict index in dynamic traffic flow scenarios.

[0061] The maximum traffic flow is defined as the maximum traffic flow from the start of the first time period to the current time. In this embodiment, the length of the first time period is one week.

[0062] The second time period is divided into multiple time periods. In this embodiment, the length of the second time period is one day, specifically divided into: morning peak 6:00-10:00, afternoon off-peak 10:00-16:00, evening peak 16:00-22:00, and nighttime 22:00-6:00. The implementer can divide it according to the actual situation. The average traffic flow from the start time of the first time period to the current time is used as the traffic flow threshold for the corresponding time period. When the deviation between the real-time traffic flow and the traffic flow threshold is greater than the maximum traffic flow of a preset multiple, a timer is started to record the duration until the deviation is less than the threshold, at which point the timer is reset. In this embodiment, the preset multiple is 0.2. Fourier transform is performed on the traffic flow data of the past three months to identify periodic components, and the time length of the maximum period is extracted as the period coefficient. The identification of periodic components through Fourier transform is a well-known existing technology, and this application will not elaborate on it.

[0063] The traffic flow matching degree of each road segment at each time point is denoted as TD, and its formula is: In the formula, F tF represents the traffic flow at each moment. p This represents the traffic threshold at each moment. T represents the maximum traffic flow at each moment, Δt represents the duration recorded by the most recent timer, and T represents the maximum traffic flow at each moment. c This represents the period coefficient. It should be noted that if the current time is the moment the timer is currently recording, since the recording may not be complete yet, the duration of the most recent complete timer recording should be considered. Let this be the third ratio. This is denoted as the fourth ratio.

[0064] It should be understood that by calculating the relative deviation between real-time flow and flow threshold, the larger the deviation, the further the current flow deviates from the normal level, and the more urgent the lighting adjustment needs to be. By dividing by the maximum flow, the absolute flow deviation is converted into a relative value in the range of 0 to 1, so that the flow fluctuations of road sections with different flow rates are comparable.

[0065] Traffic flow often experiences sudden, instantaneous changes due to unforeseen events. Adjusting lighting solely based on instantaneous deviations would lead to frequent system starts and stops, increasing energy consumption and shortening equipment lifespan. Therefore, introducing the duration of traffic flow deviation captures these persistent trends, preventing ineffective adjustments triggered by short-term traffic fluctuations. This approach only applies to persistently abnormal tidal flow patterns. By dividing by the period coefficient, the duration of traffic flow deviation is converted into a relative value within the range of 0 to 1, making the cumulative effects over time comparable across different road sections.

[0066] The smaller the traffic flow matching value, the smaller the current traffic flow deviation or the shorter the duration, and the better the current traffic flow matches the preset lighting strategy, and the less adjustment is needed; conversely, the larger the traffic flow deviation and the longer the duration, the more necessary it is to dynamically redistribute the lighting power to achieve energy-saving light distribution.

[0067] Vehicle Mixed Traffic Feature Analysis Module: Analyzes the traffic flow characteristics of vehicles on each road segment during the preset traffic flow analysis time, and determines the mixed traffic distribution characteristics of each road segment at each time moment by combining the distribution characteristics of the number of vehicles of various types.

[0068] The illumination conflict index and traffic flow matching degree are triggered based on the lighting needs of road network structure and traffic flow, but they have not yet solved the lighting conflict problem caused by vehicle type mixing and differences in driving conditions in real traffic. In mixed traffic environments, different types of vehicles have significantly different lighting needs. Large vehicles require a wider high beam illumination range, while small vehicles are more sensitive to glare. At the same time, bus stops and lane changes by private cars can lead to increased speed fluctuations and instability. In this situation, the traditional uniform dimming mode is prone to conflict between insufficient lighting for large vehicles and glare interference from small vehicles. Therefore, it is necessary to quantify the vehicle type ratio and speed fluctuation characteristics in mixed traffic using a mixed traffic conflict coefficient to provide a basis for vehicle type-specific dimming and dynamic brightness compensation.

[0069] Using the multi-frame difference method of the camera, the instantaneous speed of the vehicle is calculated by the displacement of the vehicle in adjacent frames. The average of all instantaneous speeds of each vehicle at each moment and within the previously preset traffic flow analysis time is calculated to obtain the average speed of each vehicle at each moment. The average and standard deviation of the average speeds of all vehicles at each moment are calculated to obtain the average vehicle speed and the standard deviation of traffic flow speed.

[0070] Furthermore, the mixed-traffic conflict coefficient for each road segment at each time point is denoted as MCC, and its formula is as follows: In the formula, n l n s σ represents the number of large vehicles and small vehicles counted at each time point and within the previous preset traffic flow analysis period, respectively; v This represents the standard deviation of traffic flow speed at each moment and within the previous preset traffic flow analysis period; v avg This represents the average vehicle speed at each moment and within the previous preset traffic flow analysis period; This is denoted as the fifth ratio.

[0071] It should be understood that the ratio of large vehicles to the total number of vehicles represents the mixed traffic ratio. The higher this value, the greater the demand for long-distance strong light coverage, while when the proportion of small vehicles increases, the focus should be on close-range uniform lighting. The ratio of standard traffic speed to average vehicle speed quantifies traffic flow stability. The higher this value, the more significant the speed difference between different vehicle types, requiring dynamic adjustment of lighting duration and distance. Faster vehicles need to activate streetlights further ahead in advance, while slower vehicles need to increase the brightness of the current road segment.

[0072] The higher the value of the mixed-traffic conflict coefficient, the more significant the combined conflict between the degree of vehicle type mixing and the dispersion of traffic flow speed in the current road segment. In this case, it is more necessary to increase the brightness of high beams and extend the lighting coverage distance in lanes with a high proportion of large vehicles, and reduce the light intensity of glare areas in areas with dense small vehicles. Conversely, it indicates that the vehicle type composition of the road segment is uniform and the traffic flow speed is stable.

[0073] Road lighting control module: Based on the illumination conflict index, traffic flow matching degree and mixed traffic distribution characteristics of each road segment at each time, the control factor of each road segment at each time is obtained. Through the mapping function, the pitch angle deviation and brightness adjustment amount of the lamps of each road segment at each time are obtained.

[0074] The angle and brightness of LED lights can be adjusted by quantifying static road network structure, time-based traffic flow changes, and mixed traffic characteristics. However, these single-dimensional indicators are prone to conflict and are difficult to directly translate into specific adjustment actions for the lights. It is necessary to unify the measurement of the requirements of each dimension to solve the contradictions or overcompensation that may occur when adjusting a single indicator. This will ensure that the lights can accurately guide reasonable pitch and brightness adjustments under different road sections and traffic conditions, thereby taking into account both road lighting safety and energy efficiency optimization.

[0075] The illumination conflict index obtained for each road segment, as well as the traffic flow matching degree and mixed traffic conflict coefficient obtained for each road segment at each time, are normalized to eliminate the difference in dimensions, and then summed to obtain the control factor. The lamps are adjusted according to the normalized control factor. The normalization function used in this embodiment is the sigmoid function.

[0076] By using a pre-calibrated mapping function, the control factor is mapped to the corresponding pitch angle deviation Δθ and brightness adjustment amount ΔL. Finally, Δθ and ΔL are converted into motor drive pulses and PWM dimming commands, which are then sent to each street light through a low-power communication module to achieve closed-loop control.

[0077] To achieve differentiated control of the tilt angle and brightness of LED lights, different mapping methods are selected, among which the tilt angle mapping formula is: CF represents the control factor for each road segment at each time step, θ min θ mid and θ max Let θ represent the minimum, median, and maximum pitch angles of the luminaire, respectively. mid Based on the reference, when CF = 0.5, the angle remains unchanged. When CF > 0.5 or CF < 0.5, θ shifts linearly and symmetrically to both sides at the same rate, responding to the need to adjust downwards for low conflict and upwards for high conflict. In this embodiment, the minimum and maximum values ​​of the pitch angle of the lamp are -15° and 30°, respectively.

[0078] The formula for mapping brightness is: In the formula, L min L mid and L max These represent the preset minimum, median, and maximum brightness values ​​of the lamp, respectively. The brightness is mapped using a sine function, with L... midAs a baseline, as the CF (Cyclic Fibre) shifts towards 0 or 1, the brightness curve first fluctuates slowly and then rapidly approaches extreme values ​​at both ends, forming a non-linear increase / decrease effect that is stable in the middle and sensitive at both ends. This is particularly suitable for maintaining stable energy-saving output in low or medium conflict scenarios, while rapidly adjusting to minimum or maximum brightness in extremely low or extremely high conflict situations to achieve a rapid response to safe illumination requirements. The combination of these two forms enables the system to be highly energy-efficient under normal conditions and provide sufficient visibility protection in abnormal or critical moments. In this embodiment, the minimum and maximum values ​​of the luminaire brightness are 5 lux and 50 lux, respectively.

[0079] It should be noted that the minimum and maximum values ​​for pitch angle and brightness are fixed values ​​set based on actual conditions, and actual adjustments should be limited to these ranges. The specific flowcharts for the pitch angle deviation and brightness adjustment of each road segment's lights at each moment are shown below. Figure 2 As shown.

[0080] The obtained Δθ and ΔL are converted into motor drive pulses and PWM dimming commands. These commands are then sent to each street light via a low-power communication module. The LED lights, as the core execution components, utilize built-in stepper motors and PWM dimming circuits to respond to control commands from the edge computing node. Upon receiving a motor drive pulse, the stepper motor drives the light fixture body to make fine-tuned angle adjustments via a gear transmission mechanism, with the adjustment range limited to θ. min to θ max Within the designated area, the direction of light projection is ensured to align with the calculated optimal illumination range, effectively avoiding overlapping illumination areas at grade-separated intersections. Simultaneously, the PWM dimming circuit dynamically adjusts the duty cycle of the output pulse based on the brightness adjustment value, ensuring the luminous intensity of the LED light source remains within L... min To L max The lighting adjustments are designed to meet the high-intensity beam requirements of large vehicles while avoiding glare interference for smaller vehicles. This creates a real-time closed loop between hardware execution and software decision-making, ensuring the accuracy and timeliness of lighting adjustments in complex road networks and dynamic traffic scenarios.

[0081] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description; sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0082] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A dynamic light distribution road lighting system for vehicle-road cooperative scenarios, characterized in that, The system includes: The road data acquisition module is used to collect the number of grade-separated intersections and the total length of each road segment, the installation height of the lights in each road segment, the half-peak angle of the light distribution, and the pitch angle at each moment; to collect the traffic flow of the road network at each moment; and to collect the number of various types of vehicles in the road network at each moment and within the previously preset traffic flow analysis period. The road spatial feature analysis module is used to determine the illumination overlap length of the lamps in each road segment at each moment based on the installation height, half-peak angle, and pitch angle of the lamps in each road segment, combined with the distance between adjacent streetlights; obtain the maximum value of the number of grade separation layers in all road segments, denoted as the maximum number of grade separation layers, and record the ratio of the number of grade separation layers in each road segment to the maximum number of grade separation layers as the first ratio; calculate the ratio of the illumination overlap length of the lamps in each road segment at each moment to the total length of each road segment, denoted as the second ratio; obtain the cosine trigonometric function value of the minimum included angle between all intersecting roads in each road segment; assign preset weights to the first ratio, the second ratio, and the cosine trigonometric function value respectively, and obtain the illumination conflict index of each road segment at each moment by weighted summation; The traffic flow time-varying feature analysis module is used to preset a first time period and a second time period, wherein the first time period contains a preset number of second time periods; the second time period is divided into multiple time periods, and the distribution characteristics of all traffic flow from the start time of the first time period to each time period are analyzed. The duration is recorded by a timer, and combined with the numerical characteristics of traffic flow, the traffic flow matching degree of each road segment at each time period is determined. The use of a timer to record the duration is specifically as follows: Obtain the time period from the start of the first time period to the corresponding time period of each time, and use the average traffic flow of all times within the time period as the traffic flow threshold for each time. If the difference between the current traffic flow and the corresponding traffic flow threshold is greater than the maximum traffic flow of a preset multiple, a timer is started to record the duration until the deviation is less than the traffic flow threshold, at which point the timer is reset. The determination of the traffic flow matching degree for each road segment at each time moment is specifically as follows: The maximum traffic flow is defined as the maximum traffic flow from the start of the first time period to each time period. Calculate the difference between the traffic flow at each moment and the corresponding traffic flow threshold, divide it by the maximum traffic flow, and record the resulting value as the third ratio. Periodic analysis of historical traffic flow is performed to obtain the periodic coefficient; Obtain the ratio of the duration of the most recent timer record at each time point to the period coefficient, and denote it as the fourth ratio; The result of positively fusing the third ratio and the fourth ratio is used as the traffic flow matching degree of each road segment at each time. The vehicle mixed traffic feature analysis module is used to calculate the instantaneous speed of vehicles by their displacement in adjacent frames, calculate the average of all instantaneous speeds of each vehicle at each moment and within the previous preset traffic flow analysis period, obtain the average speed of each vehicle at each moment, calculate the average and standard deviation of the average speeds of all vehicles at each moment, obtain the average vehicle speed and the standard deviation of traffic flow speed; vehicles with a body length greater than a preset value are classified as large vehicles, and the rest are classified as small vehicles; based on the number of large vehicles and the number of small vehicles within each moment and within the previous preset traffic flow analysis period, the proportion of large vehicles is calculated; the ratio of the standard deviation of traffic flow speed to the average vehicle speed at each moment is calculated and recorded as the fifth ratio; the proportion of large vehicles and the fifth ratio are positively fused to obtain the mixed traffic distribution characteristics of each road segment at each moment; The road lighting control module is used to obtain the control factor of each road segment at each time based on the illumination conflict index, traffic flow matching degree and mixed traffic distribution characteristics of each road segment at each time. Through the mapping function, the pitch angle deviation and brightness adjustment amount of the lamps of each road segment at each time are obtained.

2. The dynamic light distribution road lighting system in a vehicle-road cooperative scenario as described in claim 1, characterized in that, The specific formula for determining the illumination overlap length of the lamps in each road segment at each moment is as follows: In the formula, This indicates the length of overlap of illumination from the lights in each road segment at each moment; This indicates the installation height of the lights in each road section; This indicates the pitch angle of the lights in each road segment at each moment; This indicates the half-peak angle of the light distribution of the luminaires in each road segment; Represents the tangent trigonometric function; This indicates the distance between adjacent lights in each road segment.

3. The dynamic light distribution road lighting system in a vehicle-road cooperative scenario as described in claim 1, characterized in that, The period coefficient is obtained by performing a Fourier transform on historical traffic flow data and using the time length corresponding to the maximum period as the period coefficient.

4. A dynamic light distribution road lighting system for a vehicle-road cooperative scenario as described in claim 1, characterized in that, The formula for the pitch angle deviation is as follows: In the formula, This indicates the pitch angle deviation of the lights in each road segment at each moment. This represents the control factor for each road segment at each time point. , and These represent the preset minimum, median, and maximum pitch angles of the lighting fixture, respectively.

5. A dynamic light distribution road lighting system for a vehicle-road cooperative scenario as described in claim 1, characterized in that, The formula for the brightness adjustment amount is as follows: In the formula, This indicates the amount of brightness adjustment of the lights in each road section at each moment. , and These represent the preset minimum, median, and maximum brightness values ​​of the lighting fixture, respectively. This represents the control factor for each road segment at each time point. Represents the trigonometric functions of sine. It represents pi (π).

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