CN-120957281-B - Smart city street lamp illumination adjusting method and system

Abstract

The application relates to the technical field of street lamp illumination, and discloses a method and a system for regulating intelligent city street lamp illumination, wherein the method comprises the steps of obtaining a road image through an image sensor on a street lamp, extracting vehicle characteristic images such as vehicle lamp, glass distribution and the like, calculating and judging a real vehicle by combining a multi-dimensional matching value, and determining a driving direction; and calculating the characteristic speed through the characteristic image displacement and the time stamp, and if the characteristic speed exceeds the set speed, calculating a speed comparison value, and controlling the brightness interval change of the street lamp within the set distance in front of the vehicle. When in adjustment, the brightness is inversely related to the distance between the street lamp and the vehicle, and the brightness fluctuation amplitude is inversely related to the speed comparison value. The application can dynamically adapt to the running state of the vehicle, avoid invalid illumination, and reduce energy waste while ensuring running safety and visual comfort.

Inventors

• TANG ZHONGYI
• LIU QING

Assignees

• 长沙霞意光电科技有限公司

Dates

Publication Date

20260512

Application Date

20251014

Claims (10)

1. 1. The intelligent city street lamp illumination adjusting method is characterized by comprising the following steps: acquiring a road image based on an image sensor arranged on a street lamp, and extracting a first vehicle characteristic image and a second vehicle characteristic image from the road image, wherein the first vehicle characteristic image is a lamp image, and the second vehicle characteristic image is a glass image; Calculating a first image matching value according to the first vehicle characteristic image and a preset first characteristic template, and calculating a second image matching value according to the second vehicle characteristic image and a preset second characteristic template; calculating a characteristic interval matching value according to the first vehicle characteristic image and the second vehicle characteristic image, wherein the pixel interval and the angle deviation of the first vehicle characteristic image and the second vehicle characteristic image in the road image are calculated, and the characteristic interval matching value is output; Calculating a vehicle matching value according to the first image matching value, the second image matching value and the inter-feature matching value, and if the vehicle matching value is larger than a preset matching value, calculating a vehicle direction according to the first vehicle feature image and the second vehicle image, and acquiring a first continuous time stamp of the first vehicle feature image and a second continuous time stamp of the second vehicle feature image; Calculating a first speed according to the displacement of the first vehicle characteristic image on the road image and a first continuous time stamp, calculating a second speed according to the displacement of the second vehicle characteristic image on the road image and a second continuous time stamp, calculating a characteristic speed according to the first speed and the second speed, and if the characteristic speed is larger than a preset set speed, calculating a speed comparison value according to the characteristic speed and the set speed, and controlling the brightness interval change of the street lamp positioned in the set distance in front of the current vehicle: The brightness of the street lamp is regulated according to the street lamp distance between the street lamp and the current vehicle in an opposite phase, wherein the farther the street lamp distance is, the lower the street lamp brightness is; and adjusting the brightness fluctuation amplitude of the brightness interval change according to the negative correlation of the speed comparison value, wherein the larger the speed comparison value is, the smaller the brightness fluctuation amplitude is, and the smaller the speed comparison value is, the larger the brightness fluctuation amplitude is.
2. 2. The smart city street lighting adjustment method of claim 1, further comprising the steps of: calculating a vehicle characteristic dimension parameter according to the first vehicle characteristic image and the second vehicle characteristic image; matching the vehicle size according to the vehicle characteristic size parameter; calculating a size reference value according to the size of the vehicle and a preset set size; The set distance is adjusted according to positive correlation of the dimension reference value, and the larger the dimension reference value is, the longer the set distance is, the smaller the dimension reference value is, and the shorter the set distance is.
3. 3. The smart city street lighting adjustment method of claim 1, further comprising the steps of: Extracting a shadow image and a pavement image from the road image; Calculating shadow pixel values of the shadow image and calculating pavement pixel values of the pavement image; Calculating a shadow reference value according to a preset algorithm according to the shadow pixel value and the pavement pixel value, wherein the shadow reference value= ((pavement pixel value-shadow pixel value)/pixel value dynamic range) multiplied by a reference value scaling factor, and the pixel value dynamic range is the difference between the theoretical maximum value and the minimum value of the pixel value output by the image sensor; and regulating the brightness basic value of the street lamp according to the positive correlation of the shadow reference value, wherein the larger the shadow reference value is, the higher the brightness basic value of the street lamp is, the smaller the shadow reference value is, and the lower the brightness basic value of the street lamp is.
4. 4. The smart city street lighting adjustment method of claim 1, further comprising the steps of: calculating the change speed of the speed comparison value in the set period; And adjusting the minimum unit of brightness fluctuation amplitude according to the negative correlation of the change speed, wherein the faster the change speed is, the larger the minimum unit is, the slower the change speed is, and the smaller the minimum unit is.
5. 5. The smart city street lighting adjustment method of claim 1, further comprising the steps of: calculating a change trend value of the speed comparison value, wherein the change trend value is the change rate or the change amount of the speed comparison value in a continuous time interval, and adjusting the color temperature of the street lamp according to the change trend value; If the change trend value is larger than a value in a preset trend value range, the color temperature of the street lamp is a preset low color temperature value; If the change trend value is in the preset trend value range, the color temperature of the street lamp is a preset medium color temperature value; if the change trend value is smaller than the value in the preset trend value range, the color temperature of the street lamp is a preset high color temperature value.
6. 6. The smart city street lighting adjustment method of claim 1, further comprising the steps of: Calculating a change trend value of the speed control value, wherein the change trend value is the change rate or the change amount of the speed control value in a continuous time interval; calculating a change trend calculated value according to the change trend value and a preset reference trend value; and adjusting the color temperature of the street lamp according to the inverse relation of the calculated value of the variation trend, wherein the smaller the calculated value of the variation trend is, the brighter the color temperature of the street lamp is, and the larger the calculated value of the variation trend is, the darker the color temperature of the street lamp is.
7. 7. The smart city street lighting adjustment method of claim 1, further comprising the steps of: acquiring a laser sensing image formed by laser radar scanning light of a vehicle; calculating the size of a coverage area according to the laser-induced image; And adjusting the number of street lamps at each interval in the brightness interval change according to the positive correlation of the coverage area, wherein the larger the coverage area is, the more the number of street lamps at each interval is, and the smaller the coverage area is, the fewer the number of street lamps at each interval is.
8. 8. The smart city street lighting adjustment method of claim 7, further comprising the steps of: acquiring scanning light resolution of a laser sensing image; And adjusting the brightness increment of brightness according to the positive correlation of the scanning light resolution, wherein the higher the scanning light resolution is, the larger the brightness increment of brightness is, and the lower the scanning light resolution is, the smaller the brightness increment of brightness is.
9. 9. The smart city street lighting adjustment method of claim 7, further comprising the steps of: acquiring scanning light frequency of a laser induction image; And according to the positive correlation of the scanning light frequency, adjusting the brightness decrement of the brightness dimming, wherein the higher the scanning light frequency is, the larger the brightness decrement of the brightness dimming is, and the lower the scanning light frequency is, the smaller the brightness decrement of the brightness dimming is.
10. 10. A smart city street lamp lighting adjustment system comprising a processor, wherein the steps of the smart city street lamp lighting adjustment method as claimed in any one of claims 1-9 are performed in the processor.

Description

Smart city street lamp illumination adjusting method and system Technical Field The application relates to the technical field of street lamp illumination, in particular to a method and a system for adjusting street lamp illumination in a smart city. Background Urban street lamp illumination is a core component of urban infrastructure, and plays a key role in guaranteeing night traffic safety and improving security level of public areas. The technical system is subject to multi-generation evolution, is gradually upgraded from the light sources of traditional incandescent lamps, high-pressure sodium lamps and the like to an efficient light source system taking LEDs as cores, and forms a basic framework comprising a power supply module, a control unit and a circuit network in a matched mode. With the advancement of smart city construction, urban street lamp lighting technology is developing toward energy conservation. The intelligent system is characterized by introducing a control center technology, determining different illumination time based on different sunlight conditions, realizing remote monitoring and centralized management of the state of the street lamp, and focusing on optimizing energy consumption by combining environmental data and responding to urban construction requirements. In the current urban street lamp lighting systems, most of the urban street lamp lighting systems still adopt a constant lighting mode, namely, the running is maintained by presetting fixed power or brightness parameters, and the system has a simple adjusting function based on time or environment light intensity, but lacks a fine adjusting method for adapting to real-time change of road conditions. In an actual scene, the road condition dynamic difference is obvious, the illumination mode is constant, and the fine management requirement of the smart city is difficult to match. Disclosure of Invention The application provides a smart city street lamp illumination adjusting method and system for improving the urban street lamp illumination to be suitable for the fine adjustment of road conditions. In a first aspect, the application provides a method for adjusting illumination of a smart city street lamp, which adopts the following technical scheme: a method for regulating illumination of a smart city street lamp comprises the following steps: Acquiring a road image based on an image sensor arranged on a street lamp, and extracting a first vehicle characteristic image and a second vehicle characteristic image from the road image; Calculating a first image matching value according to the first vehicle characteristic image and a preset first characteristic template, and calculating a second image matching value according to the second vehicle characteristic image and a preset second characteristic template; Calculating a vehicle matching value according to the first image matching value, the second image matching value and the inter-feature matching value, and if the vehicle matching value is larger than a preset matching value, calculating a vehicle direction according to the first vehicle feature image and the second vehicle image, and acquiring a first continuous time stamp of the first vehicle feature image and a second continuous time stamp of the second vehicle feature image; Calculating a first speed according to the displacement of the first vehicle characteristic image on the road image and a first continuous time stamp, calculating a second speed according to the displacement of the second vehicle characteristic image on the road image and a second continuous time stamp, calculating a characteristic speed according to the first speed and the second speed, and if the characteristic speed is larger than a preset set speed, calculating a speed comparison value according to the characteristic speed and the set speed, and controlling the brightness interval change of the street lamp positioned in the set distance in front of the current vehicle: The brightness of the street lamp is regulated according to the street lamp distance between the street lamp and the current vehicle in an opposite phase, wherein the farther the street lamp distance is, the lower the street lamp brightness is; and adjusting the brightness fluctuation amplitude of the brightness interval change according to the negative correlation of the speed comparison value, wherein the larger the speed comparison value is, the smaller the brightness fluctuation amplitude is, and the smaller the speed comparison value is, the larger the brightness fluctuation amplitude is. By adopting the technical scheme, the vehicle can be accurately identified, the vehicle matching value is calculated by extracting the double characteristics of the vehicle lamp distribution and the glass distribution and combining the image matching value and the characteristic interval matching value, the single characteristic misjudgment is avoided, the real vehicle is ensured to be trigg