Automatic lighting system of vehicle
By designing an automatic vehicle lighting system that integrates data collection, road condition analysis, network monitoring and adaptive control, it solves the problem that it is difficult for the existing system to comprehensively consider multiple information data, improves the accuracy and sensitivity of lighting adjustment, and enhances Improve driver’s driving safety.
Patent Information
- Application Number
- CN202411496278.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-25
- Publication Date
- 2025-01-21
AI Technical Summary
The existing automatic vehicle lighting system is difficult to comprehensively consider road congestion data, surrounding vehicle position data and road condition information data, resulting in low accuracy of lighting adjustment judgments, and it is difficult to consider the system's network delay, affecting the sensitivity of high beam turning on.
The automatic lighting system including the vehicle control end and the cloud data processing platform is designed to collect road congestion, vehicle location and road conditions information data through data collection modules, road conditions information analysis module analysis of road congestion impact coefficients and road conditions impact coefficients, vehicle communication networks The monitoring module monitor the data transmission speed in real time and calculate the weighted preset value of the light signal communication. The adaptive control module calculates the necessity of the high beam based on these data and adjusts the brightness of the light.
By comprehensively analyzing a variety of information data, the accuracy and sensitivity of light adjustment are improved, the driver's driving safety is enhanced, and the driving needs under different road conditions can be responded to in a timely manner.
Smart Images
Figure CN119329399A_ABST
Abstract
Description
Technical Field
[0001] The invention belongs to the field of vehicle lighting control, in particular to an automatic lighting system for a vehicle. Background Art
[0002] With the continuous development of science and technology and the application of intelligent technology, the automotive industry is also constantly innovating. As an important part of the field of automotive intelligence, the automatic lighting system aims to improve the visibility and comfort of drivers when driving at night and reduce the risk of traffic accidents caused by improper lighting settings. The traditional manual lighting control method has problems such as inconvenient operation and easy to ignore the adjustment, while the automatic lighting system can actively adjust the lighting mode according to the real-time environmental conditions, making driving safer and more convenient. Therefore, more and more automakers have begun to introduce automatic lighting systems into their automotive products, and they have gradually become an indispensable part of modern automotive equipment.
[0003] The existing vehicle automatic lighting system is difficult to comprehensively consider the current road congestion data, surrounding vehicle location data, and road condition information data. It is not convenient to comprehensively consider multiple information, which affects the accuracy of lighting adjustment judgment. It is difficult to take the system's network delay conditions into account in the subsequent analysis of the necessity of turning on the high beam, resulting in the system's low sensitivity in adjusting the lights. Summary of the invention
[0004] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes an automatic lighting system for a vehicle, which is used to solve the technical problems that it is difficult to comprehensively consider multiple information, affecting the accuracy of lighting adjustment judgment, and it is difficult to consider the system's network delay status in the subsequent analysis of the necessity of turning on the high beam, resulting in low sensitivity of the system in adjusting the lighting.
[0005] To solve the above problems, a first aspect of the present invention provides an automatic lighting system for a vehicle, comprising: a vehicle control terminal and a cloud data processing platform; Vehicle control terminal, including: Data collection module: used to collect the vehicle's current road congestion data, surrounding vehicle location data, and road condition information data through the Beidou satellite positioning platform, and transmit the collected data to the cloud data processing platform; Light sensing module: used to detect the ambient brightness around the vehicle. When the ambient brightness is lower than the threshold, the vehicle's high beam lights are automatically turned on and the collected data is transmitted to the cloud data processing platform. Cloud data processing platform, including: Road condition information analysis module: used to analyze the road congestion impact coefficient and the road condition impact coefficient according to the road congestion data and road condition information data of the data acquisition module; Vehicle communication network monitoring module: used to collect the data transmission speed between the vehicle control terminal and the cloud data processing platform in real time, as well as the data transmission speed of the data collected by the data acquisition module through the Beidou satellite positioning platform, and calculate the preset value of the light signal communication weight according to the collected data transmission speed; Adaptive control module: Calculates the necessity of turning on the vehicle's high beam based on the surrounding vehicle position data, as well as the road congestion impact coefficient and the road condition impact coefficient. Based on the necessity of turning on the vehicle's high beam, sends a high beam or low beam turn-on signal to the vehicle control end, and calculates the brightness setting value of the high beam or low beam sent by the vehicle control end in combination with the light signal communication weighted preset value.
[0006] As a further solution of the present invention: the data acquisition module collects the current road congestion data of the vehicle, the position data of surrounding vehicles, and the road condition information data through the Beidou satellite positioning platform, including the following steps: The data acquisition module obtains the map data of the area where the vehicle is located and the position data of surrounding vehicles according to the current position of the vehicle through the Beidou satellite positioning platform; According to the map data of the area where the vehicle is located, the road vehicle saturation is counted, and according to the road vehicle saturation, the congestion state of the road where the vehicle is located and the duration of the congestion state at the current position of the vehicle are determined as the current road congestion data of the vehicle; According to the map data of the area where the vehicle is located and the position data of surrounding vehicles, the number of vehicles within 50m around the vehicle is obtained, and the light intensity data of surrounding vehicles is collected through the front and rear cameras of the current vehicle as the position data of surrounding vehicles; Through the map data of the area where the vehicle is located, the road sign data, the number of traffic lights, the number of pedestrians within 100m in front of the vehicle, and the weather data of the current vehicle location are identified as road condition information data.
[0007] As a further solution of the present invention, according to the map data of the area where the vehicle is located, the road vehicle saturation is counted, and according to the road vehicle saturation, the congestion state of the road position where the vehicle is located and the duration of the congestion state at the current position of the vehicle are determined, including the following steps: The road where the vehicle is located is divided into a detection section every 50 meters, and the vehicle saturation of each detection section on the road is counted; If the road vehicle saturation is ≤0.4, the corresponding road section is a non-congested road section; if 0.4<road vehicle saturation≤0.75, the corresponding road section is a light to moderately congested road section; if the road vehicle saturation is>0.85, the corresponding road section is a heavily congested road section; The congestion status of the road where the vehicle is located is determined based on the vehicle position data and the congestion status data of the road section, and the duration of the congestion status at the current position of the vehicle is determined.
[0008] As a further solution of the present invention: the road condition information analysis module analyzes the road congestion impact coefficient and the road condition impact coefficient according to the road congestion data and the road condition information data of the data acquisition module, comprising the following steps: According to the road congestion data collected by the data collection module, the road where the vehicle is located in the past 24 hours is analyzed, the road congestion data is screened every hour, and the corresponding congestion status and the duration of the congestion status are counted; According to the congestion state and the duration of the congestion state corresponding to the filtered data, the average duration of the congestion state corresponding to the congestion state is calculated as the average duration of the congestion state on the road where the vehicle is located in the past 24 hours, and the road congestion impact coefficient is analyzed; , the vehicle location congestion status is no congestion , the vehicle location congestion status is light congestion , the vehicle location congestion status is severe congestion Among them, α is the road congestion impact coefficient, Ka1 is the duration of the current congestion state of the road where the vehicle is located, Ka0 is the average duration of the congestion state of the road where the vehicle is located in the past 24 hours, and L is the total length of the road where the vehicle is located; Analyze the road condition impact coefficient according to the road condition information data collected by the data collection module; , there is a warning road sign within 100m ahead of the vehicle; , there is no warning road sign within 100m ahead of the vehicle; Among them, Kb1 is the number of traffic lights in the road condition information data, Kb0 is the preset maximum number of traffic lights, Kc1 is the number of pedestrians in the road condition information data, Kc0 is the preset maximum number of pedestrians; r is the weather influence of the current vehicle location, when the weather at the current vehicle location is not rainy, the value of r is 0.1, when the weather at the current vehicle location is rainy, the value of r is 0.15, ε is the preset warning road sign influence, and ε is a constant 0.2.
[0009] As a further solution of the present invention: the vehicle communication network monitoring module collects the data transmission speed between the vehicle control terminal and the cloud data processing platform in real time, and the data transmission speed of the data collection module collecting data through the Beidou satellite positioning platform, and calculates the preset value of the light signal communication weight according to the collected data transmission speed, including the following steps: Real-time data transmission speed between the vehicle control terminal and the cloud data processing platform, as well as the data transmission speed of the data acquisition module collected through the Beidou satellite positioning platform. If the collected data is less than the preset threshold, a manual control light signal is sent to the vehicle control terminal; Otherwise, the light signal communication weighted preset value is calculated according to the collected data transmission speed.
[0010] As a further solution of the present invention: calculating the preset value of the light signal communication weight according to the collected data transmission speed includes the following steps: Create a test data transmission channel between the vehicle control terminal and the Beidou satellite positioning platform, and calculate the data transmission rate between the vehicle control terminal and the Beidou satellite positioning platform; Create a test data transmission channel between the vehicle control terminal and the cloud data processing platform to calculate the data transmission rate between the vehicle control terminal and the cloud data processing platform; The light signal communication weighted preset value X is calculated according to the following formula: Among them, V1 s is the maximum data transmission rate between the vehicle control terminal and the Beidou satellite positioning platform, V1 is the data transmission rate between the vehicle control terminal and the Beidou satellite positioning platform, and V2 is the data transmission rate between the vehicle control terminal and the Beidou satellite positioning platform. s is the maximum data transmission rate between the vehicle control terminal and the cloud data processing platform, and V2 is the data transmission rate between the vehicle control terminal and the cloud data processing platform.
[0011] As a further solution of the present invention: the adaptive control module calculates the necessity of turning on the vehicle high beam according to the surrounding vehicle position data, the road congestion influence coefficient and the road condition influence coefficient, including the following steps: Through the data of the light sensing module, detect whether the vehicle automatically turns on the vehicle high beam; If the vehicle's high beam is not automatically turned on, the necessity of turning on the vehicle's high beam is evaluated based on the number of vehicles within 50 meters around the vehicle, the light intensity data of surrounding vehicles collected by the front and rear cameras of the vehicle, the road congestion impact coefficient and the road condition impact coefficient; If the vehicle's high beams are already switched on automatically, no assessment of the necessity of switching on the vehicle's high beams is performed.
[0012] As a further solution of the present invention: according to the vehicle quantity data within 50m around the vehicle, the surrounding vehicle light intensity data collected by the front and rear cameras of the vehicle, the road congestion influence coefficient and the road condition influence coefficient, the necessity of turning on the vehicle high beam is evaluated, including the following steps: Based on the vehicle quantity data within 50m around the vehicle, and the surrounding vehicle light intensity data collected by the front and rear cameras of the vehicle; Filter the surrounding vehicle light intensity data collected by the front and rear cameras of the vehicle within the last five minutes, and use image recognition technology to calculate the number of vehicles with high beams turned on in the surrounding vehicle light intensity data, and the number of vehicles with low beams turned on in the surrounding vehicle light intensity data; The necessity of turning on the vehicle's high beam is evaluated using the following formula: Among them, R is the evaluation value of the necessity of turning on the vehicle's high beam, S1 is the number of vehicles with high beams turned on in the surrounding vehicle light intensity data, and S2 is the number of vehicles with low beams turned on in the surrounding vehicle light intensity data.
[0013] As a further solution of the present invention, according to the necessity of turning on the high beam of the vehicle, sending a high beam or low beam turning on signal to the vehicle control terminal includes the following steps: According to the evaluation value R of the necessity of turning on the high beam of the vehicle, if the evaluation value R of the necessity of turning on the high beam of the vehicle is greater than 0.5, it is determined that the high beam is turned on, and a high beam turn-on to base value signal is sent to the vehicle control end; If the evaluation value R of the necessity of turning on the vehicle's high beam is less than or equal to 0.5 and greater than 0.2, it is determined that the high beam is turned on, and a low beam on-base value signal is sent to the vehicle control end.
[0014] As a further solution of the present invention: the adaptive control module calculates the brightness setting value of the high beam or low beam sent by the vehicle control terminal, including the following steps: According to the evaluation value of the necessity of turning on the vehicle's high beam and the preset value of the light signal communication weight, the basic brightness adjustment value of the high beam or low beam is calculated by the following formula: , the adaptive control module determines to turn on the high beam; , the adaptive control module determines to turn on the low beam; Where E is the basic brightness adjustment value of the high beam or low beam, in cd; If the adaptive control module determines to turn on the high beam, when R*(1-X) is greater than or equal to 0.6, the basic value of the high beam plus the corresponding basic brightness adjustment value is calculated as the brightness setting value of the high beam; when R*(1-X) is less than or equal to 0.2, the basic value of the high beam is used as the brightness setting value of the high beam; when R*(1-X) is greater than 0.2 and less than 0.6, the brightness setting value of the high beam is not calculated, and the current brightness of the high beam is maintained; If the adaptive control module determines to turn on the low beam, When it is greater than or equal to 0.6, the basic value of the low beam plus the corresponding basic brightness adjustment value is calculated as the brightness setting value of the low beam. When it is less than or equal to 0.2, the base value of the low beam is used as the brightness setting value of the low beam. When it is greater than 0.2 and less than 0.6, the brightness setting value of the low beam is not calculated and the current brightness of the low beam is maintained.
[0015] Compared with the prior art, the present invention has the following beneficial effects: The present invention uses the road condition information analysis module of the cloud data processing platform to analyze the road congestion influence coefficient and the road condition influence coefficient based on the road congestion data and road condition information data of the data acquisition module; through comprehensive analysis of the real-time road congestion data and road condition information data collected by the data acquisition module, it is convenient to more accurately evaluate the actual situation of the road and improve the reliability of the data. The latest road congestion and road condition information is received in real time, and the analysis results are updated in time. Based on the analysis of the road congestion influence coefficient and the road condition influence coefficient, it helps the system to make a more intelligent decision to turn on the high beam in the future, thereby improving the driving safety of the driver.
[0016] The present invention collects the data transmission speed between the vehicle control terminal and the cloud data processing platform in real time through the vehicle communication network monitoring module of the cloud data processing platform, as well as the data transmission speed of the data collected by the data collection module through the Beidou satellite positioning platform, and calculates the light signal communication weighted preset value according to the collected data transmission speed; by monitoring the data transmission speed between the vehicle control terminal and the cloud data processing platform and the data transmission speed of the Beidou satellite positioning platform, it is convenient to understand the network delay status of the system in real time, and calculate the light signal communication weighted preset value through the collected data transmission speed, so as to take the system network delay status into consideration in the subsequent analysis of the necessity of turning on the high beam, which helps to improve the sensitivity of the system in adjusting the light. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0018] Figure 1 Schematic diagram of the system framework of the present invention. DETAILED DESCRIPTION
[0019] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0020] See also Figure 1 ,This embodiment provides an automatic lighting system for a vehicle, including: a vehicle control terminal and a cloud data processing platform; Vehicle control terminal, including: Data collection module: used to collect the vehicle's current road congestion data, surrounding vehicle location data, and road condition information data through the Beidou satellite positioning platform, and transmit the collected data to the cloud data processing platform; Light sensing module: used to detect the ambient brightness around the vehicle. When the ambient brightness is lower than the threshold, the vehicle's high beam lights are automatically turned on and the collected data is transmitted to the cloud data processing platform. Cloud data processing platform, including: Road condition information analysis module: used to analyze the road congestion impact coefficient and the road condition impact coefficient according to the road congestion data and road condition information data of the data acquisition module; Vehicle communication network monitoring module: used to collect the data transmission speed between the vehicle control terminal and the cloud data processing platform in real time, as well as the data transmission speed of the data collection module through the Beidou satellite positioning platform, and calculate the preset value of the light signal communication weight according to the collected data transmission speed; in this embodiment, a GNSS receiver is selected as the Beidou positioning module of the Beidou satellite positioning platform, and it is connected to the data collection device to determine the number of bytes of each data packet, and the time required to send and receive data is recorded by a high-precision timer; and the data transmission speed can be calculated by the following formula: transmission speed (bps) = data packet size (bytes) × 8 / transmission time (seconds).
[0021] Adaptive control module: Calculates the necessity of turning on the vehicle's high beam based on the surrounding vehicle position data, as well as the road congestion impact coefficient and the road condition impact coefficient. Based on the necessity of turning on the vehicle's high beam, sends a high beam or low beam turn-on signal to the vehicle control end, and calculates the brightness setting value of the high beam or low beam sent by the vehicle control end in combination with the light signal communication weighted preset value.
[0022] Specifically, in this embodiment, a data acquisition module is set to collect the vehicle's current road congestion data, surrounding vehicle position data, and road condition information data through the Beidou satellite positioning platform, and transmit the collected data to the cloud data processing platform; the light sensing module detects the ambient brightness around the vehicle, and when the ambient brightness is lower than a threshold, the vehicle's high beam is automatically turned on, and the collected data is transmitted to the cloud data processing platform; by collecting a variety of information about the current vehicle, through the collection of road congestion data, surrounding vehicle position data, and road condition information data, it is convenient to better control the vehicle lights in the future.
[0023] The road condition information analysis module of the cloud data processing platform analyzes the road congestion impact coefficient and the road condition impact coefficient based on the road congestion data and road condition information data of the data collection module; through comprehensive analysis of the real-time road congestion data and road condition information data collected by the data collection module, the actual situation of the road can be evaluated more accurately, improving the reliability of the data. The latest road congestion and road condition information is received in real time, and the analysis results are updated in a timely manner. Based on the analysis of the road congestion impact coefficient and the road condition impact coefficient, the system can make a more intelligent decision to turn on the high beam in the future, improving the driving safety of the driver.
[0024] The vehicle communication network monitoring module of the cloud data processing platform collects in real time the data transmission speed between the vehicle control terminal and the cloud data processing platform, as well as the data transmission speed of the data collected by the data collection module through the Beidou satellite positioning platform, and calculates the light signal communication weighted preset value based on the collected data transmission speed; by monitoring the data transmission speed between the vehicle control terminal and the cloud data processing platform and the data transmission speed of the Beidou satellite positioning platform, it is convenient to understand the network delay status of the system in real time, and calculate the light signal communication weighted preset value based on the collected data transmission speed, so as to take the system's network delay status into consideration in the subsequent analysis of the necessity of turning on the high beam, which helps to improve the system's sensitivity in adjusting the light.
[0025] The adaptive control module of the cloud data processing platform calculates the necessity of turning on the vehicle's high beam according to the surrounding vehicle position data, the road congestion influence coefficient and the road condition influence coefficient. According to the necessity of turning on the vehicle's high beam, a high beam or low beam turn-on signal is sent to the vehicle control end, and the brightness setting value of the high beam or low beam sent by the vehicle control end is calculated in combination with the light signal communication weighted preset value. Based on the analysis of the road congestion influence coefficient and the road condition influence coefficient, as well as the surrounding vehicle position data, road congestion and road condition information, the necessity of turning on the vehicle's high beam is calculated, which facilitates the intelligent decision to turn on the high beam, thereby improving the driving safety of the driver. According to the real-time collected data, the calculation and sending of the light turn-on signal can timely adjust the vehicle's light brightness to adapt to driving needs in different environments. At the same time, the brightness setting value is calculated in combination with the light signal communication weighted preset value, and the system's network delay condition is taken into account in the subsequent high beam turn-on necessity analysis process, which helps to improve the system's sensitivity in adjusting the light and helps to improve the system's stability and reliability in various complex situations.
[0026] Furthermore, the data acquisition module collects the vehicle's current road congestion data, surrounding vehicle location data, and road condition information data through the Beidou satellite positioning platform, including the following steps: The data acquisition module obtains the map data of the area where the vehicle is located and the position data of surrounding vehicles according to the current position of the vehicle through the Beidou satellite positioning platform; According to the map data of the area where the vehicle is located, the road vehicle saturation is counted, and according to the road vehicle saturation, the congestion state of the road where the vehicle is located and the duration of the congestion state at the current position of the vehicle are determined as the current road congestion data of the vehicle; According to the map data of the area where the vehicle is located and the position data of surrounding vehicles, the number of vehicles within 50m around the vehicle is obtained, and the light intensity data of surrounding vehicles is collected through the front and rear cameras of the current vehicle as the position data of surrounding vehicles; Through the map data of the area where the vehicle is located, the road sign data, the number of traffic lights, the number of pedestrians within 100m in front of the vehicle, and the weather data of the current vehicle location are identified as road condition information data.
[0027] In this embodiment, the map data of the area where the vehicle is located and the location data of surrounding vehicles are obtained, and accurate longitude and latitude information is obtained through the Beidou GNSS receiver of the vehicle; the existing software is used to process the GNSS signal and extract the longitude and latitude coordinates of the current vehicle. Use the API that provides high-precision road data such as Open Street Map, Baidu Map, and Amap. According to the obtained longitude and latitude, request map data of the relevant area through the API. Obtain a high-precision map containing road signs and traffic light information. At the same time, ensure that the map data is in a machine-readable format, such as GeoJSON, Shapefile, etc., and usually need to specify a range, such as a radius of 100 meters.
[0028] Upload all authenticated vehicle positions to a central server, and then obtain information about surrounding vehicles from the server. This method is common in most intelligent transportation systems.
[0029] Using Post GIS spatial query technology, all road signs and traffic lights within 100 meters of the vehicle's current location are retrieved from the database.
[0030] High-definition cameras deployed around the vehicle can monitor and count the number of people in the area ahead in real time.
[0031] Use Open Weather Map and Weather API to obtain real-time weather information for your current location. When sending a request, use the current longitude and latitude as parameters.
[0032] On the basis of the above embodiment, in this embodiment, according to the map data of the area where the vehicle is located, the road vehicle saturation is counted, and according to the road vehicle saturation, the congestion state of the road position where the vehicle is located and the duration of the congestion state at the current position of the vehicle are determined, including the following steps: The road where the vehicle is located is divided into a detection section every 50 meters, and the vehicle saturation of each detection section on the road is counted; If the road vehicle saturation is ≤0.4, the corresponding road section is a non-congested road section; if 0.4<road vehicle saturation≤0.75, the corresponding road section is a light to moderately congested road section; if the road vehicle saturation is>0.85, the corresponding road section is a heavily congested road section; The congestion status of the road where the vehicle is located is determined based on the vehicle position data and the congestion status data of the road section, and the duration of the congestion status at the current position of the vehicle is determined.
[0033] On the basis of the above embodiment, in this embodiment, the vehicle communication network monitoring module collects the data transmission speed between the vehicle control terminal and the cloud data processing platform in real time, and the data transmission speed of the data collection module collecting data through the Beidou satellite positioning platform, and calculates the preset value of the light signal communication weight according to the collected data transmission speed, including the following steps: Real-time data transmission speed between the vehicle control terminal and the cloud data processing platform, as well as the data transmission speed of the data acquisition module collected through the Beidou satellite positioning platform. If the collected data is less than the preset threshold, a manual control light signal is sent to the vehicle control terminal; Otherwise, the light signal communication weighted preset value is calculated according to the collected data transmission speed.
[0034] Further, calculating the preset value of the light signal communication weight according to the collected data transmission speed includes the following steps: Create a test data transmission channel between the vehicle control terminal and the Beidou satellite positioning platform, and calculate the data transmission rate between the vehicle control terminal and the Beidou satellite positioning platform; Create a test data transmission channel between the vehicle control terminal and the cloud data processing platform to calculate the data transmission rate between the vehicle control terminal and the cloud data processing platform; The light signal communication weighted preset value X is calculated according to the following formula: Among them, V1 s is the maximum data transmission rate between the vehicle control terminal and the Beidou satellite positioning platform, V1 is the data transmission rate between the vehicle control terminal and the Beidou satellite positioning platform, and V2 is the data transmission rate between the vehicle control terminal and the Beidou satellite positioning platform. s is the maximum data transmission rate between the vehicle control terminal and the cloud data processing platform, and V2 is the data transmission rate between the vehicle control terminal and the cloud data processing platform.
[0035] Specifically, in this embodiment, a test data transmission channel is created between the vehicle control terminal and the Beidou satellite positioning platform, and the data transmission rate between the vehicle control terminal and the Beidou satellite positioning platform is calculated, including the following steps: The vehicle control end sends test data to the Beidou satellite positioning platform through the test data transmission channel at preset intervals, and starts the data transmission speed timer while sending the data; After receiving the test data sent by the vehicle control terminal, the Beidou satellite positioning platform transmits the test data back to the vehicle control terminal; When the time recorded by the data transmission speed timer reaches the preset test unit time, the vehicle control terminal stops sending the test data; The vehicle control end calculates the data transmission rate between the vehicle control end and the Beidou satellite positioning platform by dividing the amount of data transmitted within the preset test unit time by the preset test unit time.
[0036] On the basis of the above embodiment, in this embodiment, the road condition information analysis module analyzes the road congestion impact coefficient and the road condition impact coefficient according to the road congestion data and the road condition information data of the data acquisition module, including the following steps: According to the road congestion data collected by the data collection module, the road where the vehicle is located in the past 24 hours is analyzed, the road congestion data is screened every hour, and the corresponding congestion status and the duration of the congestion status are counted; According to the congestion state and the duration of the congestion state corresponding to the filtered data, the average duration of the congestion state corresponding to the congestion state is calculated as the average duration of the congestion state on the road where the vehicle is located in the past 24 hours, and the road congestion impact coefficient is analyzed; , the vehicle location congestion status is no congestion , the vehicle location congestion status is light congestion , the vehicle location congestion status is severe congestion Among them, α is the road congestion impact coefficient, Ka1 is the duration of the current congestion state of the road where the vehicle is located, Ka0 is the average duration of the congestion state of the road where the vehicle is located in the past 24 hours, and L is the total length of the road where the vehicle is located; Analyze the road condition impact coefficient according to the road condition information data collected by the data collection module; , there is a warning road sign within 100m ahead of the vehicle; , there is no warning road sign within 100m ahead of the vehicle; Among them, Kb1 is the number of traffic lights in the road condition information data, Kb0 is the preset maximum number of traffic lights, Kc1 is the number of pedestrians in the road condition information data, Kc0 is the preset maximum number of pedestrians; r is the weather influence of the current vehicle location, when the weather at the current vehicle location is not rainy, the value of r is 0.1, when the weather at the current vehicle location is rainy, the value of r is 0.15, ε is the preset warning road sign influence, and ε is a constant 0.2.
[0037] Furthermore, the adaptive control module calculates the necessity of turning on the vehicle's high beam according to the surrounding vehicle position data, the road congestion influence coefficient and the road condition influence coefficient, including the following steps: Through the data of the light sensing module, detect whether the vehicle automatically turns on the vehicle high beam; If the vehicle's high beam is not automatically turned on, the necessity of turning on the vehicle's high beam is evaluated based on the number of vehicles within 50 meters around the vehicle, the light intensity data of surrounding vehicles collected by the front and rear cameras of the vehicle, the road congestion impact coefficient and the road condition impact coefficient; If the vehicle's high beams are already switched on automatically, no assessment of the necessity of switching on the vehicle's high beams is performed.
[0038] Furthermore, based on the vehicle quantity data within 50m around the vehicle, the surrounding vehicle light intensity data collected by the front and rear cameras of the vehicle, the road congestion impact coefficient and the road condition impact coefficient, the necessity of turning on the vehicle high beam is evaluated, including the following steps: Based on the vehicle quantity data within 50m around the vehicle, and the surrounding vehicle light intensity data collected by the front and rear cameras of the vehicle; Filter the surrounding vehicle light intensity data collected by the front and rear cameras of the vehicle within the last five minutes, and use image recognition technology to calculate the number of vehicles with high beams turned on in the surrounding vehicle light intensity data, and the number of vehicles with low beams turned on in the surrounding vehicle light intensity data; The necessity of turning on the vehicle's high beam is evaluated using the following formula: Among them, R is the evaluation value of the necessity of turning on the vehicle's high beam, S1 is the number of vehicles with high beams turned on in the surrounding vehicle light intensity data, and S2 is the number of vehicles with low beams turned on in the surrounding vehicle light intensity data.
[0039] Further, according to the necessity of turning on the high beam of the vehicle, sending a high beam or low beam turning on signal to the vehicle control end includes the following steps: According to the evaluation value R of the necessity of turning on the high beam of the vehicle, if the evaluation value R of the necessity of turning on the high beam of the vehicle is greater than 0.5, it is determined that the high beam is turned on, and a high beam turn-on to base value signal is sent to the vehicle control end; If the evaluation value R of the necessity of turning on the vehicle's high beam is less than or equal to 0.5 and greater than 0.2, it is determined that the high beam is turned on, and a low beam on-base value signal is sent to the vehicle control end.
[0040] Furthermore, the adaptive control module calculates the brightness setting value of the high beam or low beam sent by the vehicle control terminal, including the following steps: According to the evaluation value of the necessity of turning on the vehicle's high beam and the preset value of the light signal communication weight, the basic brightness adjustment value of the high beam or low beam is calculated by the following formula: , the adaptive control module determines to turn on the high beam; , the adaptive control module determines to turn on the low beam; Where E is the basic brightness adjustment value of the high beam or low beam, in cd; If the adaptive control module determines to turn on the high beam, when R*(1-X) is greater than or equal to 0.6, the basic value of the high beam plus the corresponding basic brightness adjustment value is calculated as the brightness setting value of the high beam; when R*(1-X) is less than or equal to 0.2, the basic value of the high beam is used as the brightness setting value of the high beam; when R*(1-X) is greater than 0.2 and less than 0.6, the brightness setting value of the high beam is not calculated, and the current brightness of the high beam is maintained; If the adaptive control module determines to turn on the low beam, When it is greater than or equal to 0.6, the basic value of the low beam plus the corresponding basic brightness adjustment value is calculated as the brightness setting value of the low beam. When it is less than or equal to 0.2, the base value of the low beam is used as the brightness setting value of the low beam. When it is greater than 0.2 and less than 0.6, the brightness setting value of the low beam is not calculated and the current brightness of the low beam is maintained.
[0041] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.
Claims
1. An intelligent vehicle light control method, characterized in that: include: Step S1: using a high-definition camera to collect image data of the external environment of the vehicle headlight; Step S2: Eliminate interference light sources from the collected image data of the vehicle headlight's external environment; Step S3: analyzing the road condition of the processed vehicle headlight external environment image data; Step S4: Analyze the analyzed road curvature index and the vehicle wheelbase to obtain a headlight deflection angle, and transmit the headlight deflection angle to the controller; Step S5: Calculate the headlight brightness according to the driving speed and the ambient light brightness of the vehicle when it is driving; Step S6: The controller receives the headlight deflection angle and the road type, and performs intelligent control of the headlight.
2. The intelligent vehicle light control method according to claim 1, characterized in that: In step S1, the high-definition camera selects a camera with 4K high resolution, 30fps frame rate and excellent low-light performance, and installs the high-definition camera in the center of the front of the vehicle, and connects the high-definition camera to the A1 user interface; the camera's field of view covers the main area in front of the headlights, including lanes, road markings and traffic signs.
3. The intelligent vehicle light control method according to claim 1, characterized in that: In step S2, any lane in the collected vehicle headlight environment image data is divided into m parts, and the lane line element set on the left side of the lane area in the ath lane section of this lane is represented as , the right lane line element set is represented as ; The calculation method for fitting the left element set is as follows: ,in, is represented as the left-side fitted value, It is expressed as the fitted slope of the right lane of the a-th lane. It is represented as the slope of the left lane line in the left lane element set, Indicates the starting position of the left lane; The calculation method for fitting the right element set is as follows: ,in, is represented as the right-hand side fitted value, It is represented as the slope of the right lane line in the right lane element set, It is expressed as the fitted slope of the right lane of the a-th lane. Indicates the starting position of the right lane; According to the fitting formula and The data of the headlight sources that are not in the same lane as the target headlight source are eliminated.
4. The intelligent vehicle light control method according to claim 3, characterized in that: The calculation method of the fitting slope of the right lane of lane a is as follows: ,in, It is represented as the fitted slope of the right lane of the a-th lane, and n is represented as the number of elements. It is represented as the slope of the left lane line in the left lane element set, It is represented as the left lane width in the left lane element set; The calculation method of the fitting slope of the right lane of lane a is as follows: ,in, It is represented as the fitted slope of the right lane of the a-th lane, and n is represented as the number of elements. It is represented as the slope of the right lane line in the right lane element set, Represented as the width of the right lane in the right lane element set.
5. The intelligent vehicle light control method according to claim 1, characterized in that: In step S3, the vehicle headlight external environment image data excluding the vehicle lights not in the same lane is subjected to road condition analysis. The road conditions are divided into straight roads and turning roads. The specific method for calculating the road conditions of the vehicle is as follows: , where E represents the road curvature index, Represents the starting position of the left lane, Indicates the starting position of the right lane, It is represented by the width of the left lane in the left lane element set, It is represented as the slope of the left lane line in the left lane element set, It is expressed as the fitted slope of the right lane of the a-th lane. It is expressed as the fitted slope of the right lane of lane segment a; The calculated road curvature index is compared with the preset road curvature index threshold. If the calculated road curvature index is greater than the preset road curvature index threshold, the road condition is a curved road; if the calculated road curvature index is less than the preset road curvature index threshold, the road condition is a straight road.
6. The intelligent vehicle light control method according to claim 1, characterized in that: In step S4, the method for calculating the vehicle deflection angle is specifically as follows: Among them, P represents the vehicle's deflection angle, F represents the vehicle's wheelbase, and g represents the vehicle's mass. is the rear wheel cornering stiffness, is the front wheel cornering stiffness, It is expressed as the distance from the center of the vehicle to the rear wheel. It is expressed as the distance from the center of the vehicle to the front wheel. It is expressed as the front wheel turning radius and E is expressed as the road curvature index.
7. The intelligent vehicle light control method according to claim 1, characterized in that: In step S5, the method for calculating the vehicle light illumination value is specifically as follows: Among them, H represents the illumination value of the car lights, T represents the ambient light index when the car is driving, and V represents the vehicle speed. , , It is expressed as the factor affecting the brightness of the headlights; in, , , are three factors that affect the illumination value of the headlights. Expressed as the headlight power, It is expressed as the beam angle of the headlight; the beam angle of the headlight is the shape and direction of the light beam emitted by the headlight; It is expressed as a weather index. When it is foggy, the weather index is 0; when it is rainy, the weather index is 1; when there is no rain or fog, the weather index is 2.
8. The intelligent vehicle light control method according to claim 7, characterized in that: The specific calculation method of vehicle speed is: , where V represents the vehicle speed, N represents the number of pulses generated by the sensor per unit time, R represents the wheel radius, K represents the pulse sampling period, Y represents the number of signal teeth, and U represents the main transmission ratio.
9. The intelligent vehicle light control method according to claim 1, characterized in that: In step S6, the vehicle light control system includes: a vehicle light controller, a photosensitive sensor, a Hall speed sensor, and a direction sensor; The controller includes one or more microprocessors that can quickly process data and send precise control signals to the headlight adjustment mechanism; the headlight adjustment mechanism includes a servo motor or a stepper motor that can precisely control the rotation angle of the headlight; when the vehicle is traveling on a straight road, the headlight usually maintains a standard illumination direction to ensure a sufficient lighting range; when turning, the headlight will turn outward at a certain angle according to the turning angle and the speed of the vehicle to illuminate the curved road section that the vehicle is about to enter; The controller receives the headlight deflection angle data and the road type from step S4, which provide the controller with detailed information about the current vehicle driving condition and external environment; the controller performs a comprehensive analysis based on the data.
10. An intelligent vehicle light control system, using an intelligent vehicle light control method as claimed in any one of claims 1 to 9, characterized in that: Image data acquisition module: used to collect image data of the external environment of vehicle headlights using a high-definition camera; Image data processing module: used to remove interfering light sources from the collected image data of the external environment of vehicle headlights; Road condition analysis module: used to analyze the road condition of the processed vehicle headlight external environment image data; Headlight deflection angle analysis module: used to analyze the analyzed road curvature index and vehicle wheelbase to obtain the headlight deflection angle, and transmit the headlight deflection angle to the controller; Headlight brightness calculation module: used to calculate the headlight brightness based on the driving speed and the ambient light brightness when the vehicle is driving; Intelligent control module: used for the controller to receive the deflection angle of the headlights and the road type, and to perform intelligent control of the headlights.